Näljane Wal-Mart tahab ka smiley alla kugistada / Erik Aru
Aru, Erik
2006-01-01
USA jaekaubanduskett Wal-Mart tahab oma kaubamärgina registreerida smiley' - kollase naerunäo kujutise. Smiley' leiutajaks peab end Suurbritannias asuva ühemehefirma SmileyWorld omanik Franklin Loufrani. Lisa: Wal-Mart üritab jõukamaid kundesid meelitada. Tabel: Wal-Mart
Voisin, Mathew R; Witiw, Christopher D; Deorajh, Ryan; Guha, Daipayan; Oremakinde, Adetunji; Wang, Shelly; Yang, Victor
2018-01-01
Multilevel spondylolysis is a rare cause of progressive lower back pain, and patients who fail conservative management are treated surgically. Direct repair methods can maintain mobility and lead to decreased morbidity compared with spinal fusion in single-level spondylolysis. In this paper, we present a patient with nonadjacent multilevel spondylolysis who underwent the "smiley face" technique of direct multilevel repair without fusion using 3-dimensional intraoperative spinal navigation. Bilateral spondylolysis at L3 and L5 with associated spondylolisthesis in a 50-year-old male was repaired using the "smiley face" technique. Patient-reported outcomes, including the Oswestry Disability Index (ODI) and visual analog scale scores for back and leg pain, were assessed preoperatively along with 6 weeks and 4 months postoperatively. Postoperative computed tomography imaging showed precise screw insertion and rod placement along with stable hardware alignment in follow-up imaging. The patient's ODI and lower back visual analog scale scores decreased from 25 to 8 and 7.5 to 4, respectively, correlating to an excellent outcome on ODI. Direct repair and avoidance of fusion is possible and can provide good functional outcomes in patients with nonadjacent multilevel spondylolysis and associated spondylolisthesis. Copyright © 2017 Elsevier Inc. All rights reserved.
Osipov, Gennady
2013-04-01
We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode
Designing for Learning and Play - The Smiley Model as Framework
DEFF Research Database (Denmark)
Weitze, Charlotte Lærke
2016-01-01
digital games. The Smiley Model inspired and provided a scaffold or a heuristic for the overall gamified learning design –- as well as for the students’ learning game design processes when creating small games turning the learning situation into an engaging experience. The audience for the experiments......This paper presents a framework for designing engaging learning experiences in games – the Smiley Model. In this Design-Based Research project, student-game-designers were learning inside a gamified learning design - while designing and implementing learning goals from curriculum into the small...... was adult upper secondary general students as well as 7th grade primary school students. The intention with this article is to inspire future learning designers that would like to experiment with integrating learning and play....
Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS
Davis, Philip A.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA
Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS
Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As
Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As
Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products
Davis, Philip A.; Cagney, Laura E.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA
Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As
Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such
Davis, Philip A.; Cagney, Laura E.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from
Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the
Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products
Davis, Philip A.; Cagney, Laura E.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such
Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products
Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such
Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the
Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS
Davis, Philip A.
2014-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that
Davis, Philip A.; Cagney, Laura E.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As
Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be
Davis, Philip A.; Cagney, Laura E.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As
Davis, Philip A.; Cagney, Laura E.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match
Satellite image collection optimization
Martin, William
2002-09-01
Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.
Davis, Philip A.; Cagney, Laura E.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such
Davis, Philip A.; Cagney, Laura E.
2012-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such
Davis, Philip A.
2014-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such
Davis, Philip A.
2014-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image
Infektion beim Menschen und beim Hund mit der Milbe Cheyletiella yasguri Smiley
DEFF Research Database (Denmark)
Brandrup, F; Andersen, Klaus Ejner; Kristensen, S
1979-01-01
The infection with the mite Cheyletiella yasguri Smiley in 3 dogs and 5 out of 6 persons exposed to infestation is reported. Two of the dogs appeared to have been infected during a stay in a kennel. The dogs presented with moderate itching and slight to massive floury squamation on the back. In t...
Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such
Concept Model For Designing Engaging And Motivating Games For Learning - The Smiley-Model
DEFF Research Database (Denmark)
Weitze, Charlotte Lærke; Ørngreen, Rikke
2012-01-01
The desire to use learning games in education is increasing, but the development of games for learning is still a growing field. Research shows that it remains difficult to develop learning games that are both instructive and engaging, although it is precisely the presence of these two elements...... that is believed to be an advantage when using learning games in education. In this paper the Smiley-model is presented (figure 1). The model describes which parameters and elements are important when designing a learning game. The present research is a result of a case-based action research study for designing...... a music learning game that teaches children to play piano using sheet music, and at the same time is fun and engaging. Although the model was originally developed for and through music, it has a more generic nature, and may be relevant for other fields as well. The Smiley-model is a condensed version...
Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As
Davis, Philip A.; Cagney, Laura E.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from
Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS
Davis, Philip A.; Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ahankashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008, 2009, 2010),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this
Davis, Philip A.; Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Bamyan mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such
Davis, Philip A.; Davis, Philip A.
2013-01-01
The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that
Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.
2018-05-01
The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image
Directory of Open Access Journals (Sweden)
Anica Veronika Fietz
2017-11-01
Full Text Available Abstract Our paper explores how participants of voluntary transparency systems react to the cancellation of such programmes. We concern ourselves with participants of the voluntary transparency scheme known as the “North Rhine-Westphalia Smiley”. The Smiley system, which awarded the compliant behavior of businesses that joined it, was established in 2007 but cancelled in 2013 due to lack of participants. In our survey, the vast majority of the respondents express regret at the cancellation of the scheme. The goals of this paper are to (i econometrically explain how socio-demographic, monetary, and non-monetary determinants influence participants’ willingness to continue with the voluntary transparency system and (ii find reasons for the inconsistency between the lack of participants and the expression of regret within our survey. We find evidence that the non-monetary variables “revenue” and “award” and the monetary variable “revenue” influence participants’ regret. We speculate that status quo bias and loss aversion are the reasons why businesses favour maintaining the Smiley scheme once they have experienced it.
Shadow imaging of geosynchronous satellites
Douglas, Dennis Michael
Geosynchronous (GEO) satellites are essential for modern communication networks. If communication to a GEO satellite is lost and a malfunction occurs upon orbit insertion such as a solar panel not deploying there is no direct way to observe it from Earth. Due to the GEO orbit distance of ~36,000 km from Earth's surface, the Rayleigh criteria dictates that a 14 m telescope is required to conventionally image a satellite with spatial resolution down to 1 m using visible light. Furthermore, a telescope larger than 30 m is required under ideal conditions to obtain spatial resolution down to 0.4 m. This dissertation evaluates a method for obtaining high spatial resolution images of GEO satellites from an Earth based system by measuring the irradiance distribution on the ground resulting from the occultation of the satellite passing in front of a star. The representative size of a GEO satellite combined with the orbital distance results in the ground shadow being consistent with a Fresnel diffraction pattern when observed at visible wavelengths. A measurement of the ground shadow irradiance is used as an amplitude constraint in a Gerchberg-Saxton phase retrieval algorithm that produces a reconstruction of the satellite's 2D transmission function which is analogous to a reverse contrast image of the satellite. The advantage of shadow imaging is that a terrestrial based redundant set of linearly distributed inexpensive small telescopes, each coupled to high speed detectors, is a more effective resolved imaging system for GEO satellites than a very large telescope under ideal conditions. Modeling and simulation efforts indicate sub-meter spatial resolution can be readily achieved using collection apertures of less than 1 meter in diameter. A mathematical basis is established for the treatment of the physical phenomena involved in the shadow imaging process. This includes the source star brightness and angular extent, and the diffraction of starlight from the satellite
SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES
Directory of Open Access Journals (Sweden)
A. Sharma
2015-03-01
Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.
Smoothing of Fused Spectral Consistent Satellite Images
DEFF Research Database (Denmark)
Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli
2006-01-01
on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. (2005) proposed a method of fusion of satellite images that is based on the properties of imaging physics...
Applying satellite technology to energy and mineral exploration
Carter, William D.; Rowan, Lawrence C.
1978-01-01
IGCP Project 143 ("Remote Sensing and Mineral Exploration"), is a worldwide research project designed to make satellite data an operational geological tool along with the geologic pick, hand lens, topographic map, aerial photo and geophysical instruments and data that comprise the exploration package. While remote sensing data will not replace field exploration and mapping, careful study of such data prior to field work should make the effort more efficient.
International Nuclear Information System (INIS)
Budge, T.K.
1980-09-01
This project was a demonstration of the capabilities of Landsat satellite image processing applied to the monitoring of mining activity in New Mexico. Study areas included the Navajo coal surface mine, the Jackpile uranium surface mine, and the potash mining district near Carlsbad, New Mexico. Computer classifications of a number of land use categories in these mines were presented and discussed. A literature review of a number of case studies concerning the use of Landsat image processing in mineral exploration and related activities was prepared. Included in this review is a discussion of the Landsat satellite system and the basics of computer image processing. Topics such as destriping, contrast stretches, atmospheric corrections, ratioing, and classification techniques are addressed. Summaries of the STANSORT II and ELAS software packages and the Technology Application Center's Digital Image Processing System (TDIPS) are presented
Image processing of airborne geophysical data: a potential exploration tool for atomic minerals
International Nuclear Information System (INIS)
Shanti Kumar, C.; Bhairam, C.L.; Kak, S.N.; Achar, K.K.
1993-01-01
Data sets obtained from airborne gamma-ray spectrometric (AGRS) and aeromagnetic (AM) surveys, after necessary correction, are usually presented as profiles or as contour maps for interpretation in mineral exploration and geological analysis. Currently, imaging of the geophysical data sets have been extensively used as they have many advantages in their usage compared to conventional techniques. For the application of image processing techniques to the AGRS and AM data, software programs were customized for converting the digital data compatible to the satellite image processing system (SIPS). The geophysical data has been imaged and rectified to a poly conic projection, using cubic convolution resampling technique. While imaging, the radioelemental concentration values are rescaled to 256 grey levels. Software for the statistical information of radioelements and printing of coloured paper image have also been developed. Some of the image processing techniques used include, generation of colour composite images for preparing radioelemental (eU,eTh, and K) images and radioelemental colour composite images (K,eTh, eU) enabling display of a combined radioelemental distribution. Aeromagnetic data on the other hand are displayed in grey tone, pseudo-colours, and shaded relief images. Many other image enhancement techniques used for improving the display for further interpretation comprise, band ratioing, band combinations, filtering, look up table manipulation, and other similar functions. Advanced image processing techniques such as the principal component analysis (PCA) for understanding the geochemical and geological phenomena and the hue saturation and intensity (HSI) transformation for integration of radioelemental data with its corresponding satellite images facilitated display of radioelemental images draped over the satellite image. Statistics of radioelement and inter-elemental relationship has been obtained. The paper deals with the methodology adopted in the
Egypt satellite images for land surface characterization
DEFF Research Database (Denmark)
Hasager, Charlotte Bay
images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...
Video retrieval by still-image analysis with ImageMiner
Kreyss, Jutta; Roeper, M.; Alshuth, Peter; Hermes, Thorsten; Herzog, Otthein
1997-01-01
The large amount of available multimedia information (e.g. videos, audio, images) requires efficient and effective annotation and retrieval methods. As videos start playing a more important role in the frame of multimedia, we want to make these available for content-based retrieval. The ImageMiner-System, which was developed at the University of Bremen in the AI group, is designed for content-based retrieval of single images by a new combination of techniques and methods from computer vision and artificial intelligence. In our approach to make videos available for retrieval in a large database of videos and images there are two necessary steps: First, the detection and extraction of shots from a video, which is done by a histogram based method and second, the construction of the separate frames in a shot to one still single images. This is performed by a mosaicing-technique. The resulting mosaiced image gives a one image visualization of the shot and can be analyzed by the ImageMiner-System. ImageMiner has been tested on several domains, (e.g. landscape images, technical drawings), which cover a wide range of applications.
Satellite images to aircraft in flight. [GEOS image transmission feasibility analysis
Camp, D.; Luers, J. K.; Kadlec, P. W.
1977-01-01
A study has been initiated to evaluate the feasibility of transmitting selected GOES images to aircraft in flight. Pertinent observations that could be made from satellite images on board aircraft include jet stream activity, cloud/wind motion, cloud temperatures, tropical storm activity, and location of severe weather. The basic features of the Satellite Aircraft Flight Environment System (SAFES) are described. This system uses East GOES and West GOES satellite images, which are interpreted, enhanced, and then retransmitted to designated aircraft.
Virtual Satellite Construction and Application for Image Classification
International Nuclear Information System (INIS)
Su, W G; Su, F Z; Zhou, C H
2014-01-01
Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively
Directory of Open Access Journals (Sweden)
A. H. Ahrari
2017-09-01
Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.
Spectrally Consistent Satellite Image Fusion with Improved Image Priors
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.
2006-01-01
Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....
Northern Everglades, Florida, satellite image map
Thomas, Jean-Claude; Jones, John W.
2002-01-01
These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.
ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES
Directory of Open Access Journals (Sweden)
H. Kim
2012-07-01
Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.
Use of the high-resolution satellite images for detection of fractures related to the ore deposits
Cruz-Mondaca, M.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.
2012-12-01
The Aster and GeoEye satellite high-resolution images were used to detect the structures related to the fracturing of the upper crust in the North of Chile. In particular, lineament analysis has been applied to detect the presence of epithermal fluids of low sulfurization associated with the Paleozoic ore deposits. These results have been compared with the location of the minerals altered by the presence of geothermal fluids detected using the spectral libraries. Later, the presence of fractures has been corroborated during recognition of fractures in situ and the geochemical analysis of samples of minerals altered by the presence of fluids. It was shown that the results obtained are relevant for the gold vein detection.
Medical image transmission via communication satellite: evaluation of ultrasonographic images.
Suzuki, H; Horikoshi, H; Shiba, H; Shimamoto, S
1996-01-01
As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment.
Velocity estimation of an airplane through a single satellite image
Institute of Scientific and Technical Information of China (English)
Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li
2012-01-01
The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.
Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining
Directory of Open Access Journals (Sweden)
Yo-Ping Huang
2008-02-01
Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.
South Florida Everglades: satellite image map
Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.
2001-01-01
These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.
The best printing methods to print satellite images
Directory of Open Access Journals (Sweden)
G.A. Yousif
2011-12-01
In this paper different printing systems were used to print an image of SPOT-4 satellite, caver part of Sharm Elshekh area, Sinai, Egypt, on the same type of paper as much as possible, especially in the photography. This step is followed by measuring the experimental data, and analyzed colors to determine the best printing systems for satellite image printing data. The laser system is the more printing system where produce a wider range of color and highest densities of ink and access much color detail. Followed by the offset system which it recorded the best dot gain. Moreover, the study shows that it can use the advantages of each method according to the satellite image color and quantity to be produced.
Entropy-Based Block Processing for Satellite Image Registration
Directory of Open Access Journals (Sweden)
Ikhyun Lee
2012-11-01
Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.
The best printing methods to print satellite images
G.A. Yousif; R.Sh. Mohamed
2011-01-01
Printing systems operate in general as a system of color its color scale is limited as compared with the system color satellite images. Satellite image is building from very small cell named pixel, which represents the picture element and the unity of color when the image is displayed on the screen, this unit becomes lesser in size and called screen point. This unit posseses different size and shape from the method of printing to another, depending on the output resolution, tools and material...
ASTER 2002-2003 Kansas Satellite Image Database (KSID)
Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...
MODIS 2002-2003 Kansas Satellite Image Database (KSID)
Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...
Classification of high resolution satellite images
Karlsson, Anders
2003-01-01
In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.
Directory of Open Access Journals (Sweden)
Xiao Ling
2016-08-01
Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.
Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection
DEFF Research Database (Denmark)
Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli
2007-01-01
based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...
Satellite-generated radar images of the earth
International Nuclear Information System (INIS)
Schanda, E.
1980-01-01
The Synthetic Aperture Radar (SAR) on board of SEASAT was the first non-military satellite-borne radar producing high-resolution images of the earth. Several examples of European scenes are discussed to demonstrate the properties of presently available optically processes images. (orig.)
Model-based satellite image fusion
DEFF Research Database (Denmark)
Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg
2008-01-01
A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....
Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations
Jorgensen, A.; Schmitt, H.; Mozurkewich, D.; Armstrong, J.; Restaino, S.; Hindsley, R.
2011-09-01
Geostationary satellites are generally too small to image at high resolution with conventional single-dish telescopes. Obtaining many resolution elements across a typical geostationary satellite body requires a single-dish telescope with a diameter of 10’s of m or more, with a good adaptive optics system. An alternative is to use an optical/infrared interferometer consisting of multiple smaller telescopes in an array configuration. In this paper and companion papers1, 2 we discuss the performance of a common-mount 30-element interferometer. The instrument design is presented by Mozurkewich et al.,1 and imaging performance is presented by Schmitt et al.2 In this paper we discuss signal-to-noise ratio for both fringe-tracking and imaging. We conclude that the common-mount interferometer is sufficiently sensitive to track fringes on the majority of geostationary satellites. We also find that high-fidelity images can be obtained after a short integration time of a few minutes to a few tens of minutes.
International Nuclear Information System (INIS)
Xuan Yanxiu; Zhang Jielin
2010-01-01
Based on the spectrum characteristics analysis of uranium mineralization alteration rocks and minerals, and using satellite multi-spectral remote sensing image data as the main information sources, multiple remote sensing data processing techniques and methods such as color compound, band ratio, principal component analysis and image color segmentation, are synthetically applied to extract uranium mineralization and alteration information from the remote sensing image. The results of this study provided basic data for analysis of uranium ore-formation conditions in the area. (authors)
Image Positioning Accuracy Analysis for Super Low Altitude Remote Sensing Satellites
Directory of Open Access Journals (Sweden)
Ming Xu
2012-10-01
Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line-of-sight rebuilding of each detection element and this direction precisely intersecting with the Earth's elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.
Fundamental Limitations for Imaging GEO Satellites
2015-10-18
Fundamental limitations for imaging GEO satellites D. Mozurkewich Seabrook Engineering , Seabrook, MD 20706 USA H. R. Schmitt, J. T. Armstrong Naval...higher spatial frequency. Send correspondence to David Mozurkewich, Seabrook Engineering , 9310 Dubarry Ave., Seabrook MD 20706 E-mail: dave
Medical image transmission via communication satellite. Evaluation of bone scintigraphy
International Nuclear Information System (INIS)
Suzuki, Hideki; Inoue, Tomio; Endo, Keigo; Shimamoto, Shigeru.
1995-01-01
As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT 1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical imagings by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6±2.6% via satellite, and 93.2±2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes. (author)
[Medical image transmission via communication satellite: evaluation of bone scintigraphy].
Suzuki, H; Inoue, T; Endo, K; Shimamoto, S
1995-10-01
As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical images by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6 +/- 2.6% via satellite, and 93.2 +/- 2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes.
Kansas Satellite Image Database (KSID) 2004-2005
Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...
Mapping soil heterogeneity using RapidEye satellite images
Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane
2016-04-01
In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.
Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm
Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan
2017-12-01
Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.
Remote Sensing Analysis of Mineralized Alteration in the Ramand Area (Qazvin Province
Directory of Open Access Journals (Sweden)
Seyed Abolfazl Ezzati
2016-07-01
Full Text Available Introduction The Ramand area, southwest of Buin- Zahra, about 60 kilometers from Qazvin, lies in the igneous belt of the Urmieh-Dokhtar region, the main structural zone of north-central Iran. Rhyodacite and rhyolite lava flows are the principal host rocks of mineralization and alteration of the area, most of which occurs in faulted and brecciated zones alongmaj or northwest-trending fault systems (such as Kour-Cheshmeh, Hassan Abad and their branches. Clay minerals determined from satellite images indicated principally argillic hydrothermal alteration before laboratory mineralogical analysis. According to instrumental analyses, mineralized alteration with greater amounts of argillic halos and lesser amounts of sericitic-propylitic minerals contains quartz veinlets in the vertical and lateral sections. Initially, alteration in the Ramand area was revealed in ETM images by using the SPCA technique of Crosta and Moore, 1990 (Selective Principle Component Analysis. Compared with other techniques, SPCA results have reliable spectral signatures for identifying argillic minerals and Fe-oxides as the main mineralogical association in hydrothermal environments. Subsequently, multispectral images (ASTER were analyzed using band ratios.The results indicated silicification alteration along the faulted regions in the Ramand area. Later, areas of silicification alteration were prospected for precious and base metal mineralization.Sampling results suggested that the altered areas have some potential for epithermal mineralization, according to instrumental analyses and micrographic evidence. Materials and methods 1- Collecting satellite images, geological evidence and related documents 2- Image processing to reveal and identify the mineralized alteration. 3- Sampling of the mineralized zones indicated by the remote sensing. 4- Thin- and polished section microscopic studies. 5- X-ray diffraction analysis (XRD (19 samples, inductively coupled plasma mass
International Nuclear Information System (INIS)
Fouad, M. K.; Mielik, M. L.; Gharieb, A. N.
2004-01-01
The present study aims essentially at proving that the application of the integrated airborne gamma spectrometric and satellite image data is capable of refining the mapped surface geology, and identification of anomalous zones of radioelement content that could provide favorable exploration targets for radioactive mineralizations.The application of the appropriate statistical technique to correlate between satellite image data and gamma-spectrometric data is of great significance in this respect. Experience shows that Landsat T M data in 7 spectral bands are successfully used in such studies rather than MSS. Multivariate statistical analysis techniques are applied to airborne spectrometric and different spectral Landsat T M data. Reduction of the data from n-dimensionality, both qualitatively as color composite image, and quantitatively, as principal component analysis, is performed using some statistical control parameters. This technique shows distinct efficiency in defining areas where different lit ho facies occur. An area located at the north of the Eastern Desert of Egypt, north of Hurgada town, was chosen to test the proposed technique of integrated interpretation of data of different physical nature. The reduced data are represented and interpreted both qualitatively and quantitatively. The advantages and limitations of applying such technique to the different airborne spectrometric, and Landsat T M data are identified. (authors)
Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee
2018-04-01
In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.
Quantitative image of bone mineral content
International Nuclear Information System (INIS)
Katoh, Tsuguhisa
1990-01-01
A dual energy subtraction system was constructed on an experimental basis for the quantitative image of bone mineral content. The system consists of a radiographing system and an image processor. Two radiograms were taken with dual x-ray energy in a single exposure using an x-ray beam dichromized by a tin filter. In this system, a film cassette was used where a low speed film-screen system, a copper filter and a high speed film-screen system were layered on top of each other. The images were read by a microdensitometer and processed by a personal computer. The image processing included the corrections of the film characteristics and heterogeneity in the x-ray field, and the dual energy subtraction in which the effect of the high energy component of the dichromized beam on the tube side image was corrected. In order to determine the accuracy of the system, experiments using wedge phantoms made of mixtures of epoxy resin and bone mineral-equivalent materials in various fractions were performed for various tube potentials and film processing conditions. The results indicated that the relative precision of the system was within ±4% and that the propagation of the film noise was within ±11 mg/cm 2 for the 0.2 mm pixels. The results also indicated that the system response was independent of the tube potential and the film processing condition. The bone mineral weight in each phalanx of the freshly dissected hand of a rhesus monkey was measured by this system and compared with the ash weight. The results showed an error of ±10%, slightly larger than that of phantom experiments, which is probably due to the effect of fat and the variation of focus-object distance. The air kerma in free air at the object was approximately 0.5 mGy for one exposure. The results indicate that this system is applicable to clinical use and provides useful information for evaluating a time-course of localized bone disease. (author)
Principles of image processing in machine vision systems for the color analysis of minerals
Petukhova, Daria B.; Gorbunova, Elena V.; Chertov, Aleksandr N.; Korotaev, Valery V.
2014-09-01
At the moment color sorting method is one of promising methods of mineral raw materials enrichment. This method is based on registration of color differences between images of analyzed objects. As is generally known the problem with delimitation of close color tints when sorting low-contrast minerals is one of the main disadvantages of color sorting method. It is can be related with wrong choice of a color model and incomplete image processing in machine vision system for realizing color sorting algorithm. Another problem is a necessity of image processing features reconfiguration when changing the type of analyzed minerals. This is due to the fact that optical properties of mineral samples vary from one mineral deposit to another. Therefore searching for values of image processing features is non-trivial task. And this task doesn't always have an acceptable solution. In addition there are no uniform guidelines for determining criteria of mineral samples separation. It is assumed that the process of image processing features reconfiguration had to be made by machine learning. But in practice it's carried out by adjusting the operating parameters which are satisfactory for one specific enrichment task. This approach usually leads to the fact that machine vision system unable to estimate rapidly the concentration rate of analyzed mineral ore by using color sorting method. This paper presents the results of research aimed at addressing mentioned shortcomings in image processing organization for machine vision systems which are used to color sorting of mineral samples. The principles of color analysis for low-contrast minerals by using machine vision systems are also studied. In addition, a special processing algorithm for color images of mineral samples is developed. Mentioned algorithm allows you to determine automatically the criteria of mineral samples separation based on an analysis of representative mineral samples. Experimental studies of the proposed algorithm
Nanoscale X-Ray Microscopic Imaging of Mammalian Mineralized Tissue
Andrews, Joy C.; Almeida, Eduardo; van der Meulen, Marjolein C.H.; Alwood, Joshua S.; Lee, Chialing; Liu, Yijin; Chen, Jie; Meirer, Florian; Feser, Michael; Gelb, Jeff; Rudati, Juana; Tkachuk, Andrei; Yun, Wenbing; Pianetta, Piero
2010-01-01
A novel hard transmission X-ray microscope (TXM) at the Stanford Synchrotron Radiation Light-source operating from 5 to 15 keV X-ray energy with 14 to 30 µm2 field of view has been used for high-resolution (30–40 nm) imaging and density quantification of mineralized tissue. TXM is uniquely suited for imaging of internal cellular structures and networks in mammalian mineralized tissues using relatively thick (50 µm), untreated samples that preserve tissue micro- and nanostructure. To test this...
The SUMO Ship Detector Algorithm for Satellite Radar Images
Directory of Open Access Journals (Sweden)
Harm Greidanus
2017-03-01
Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU
Benavides-Rivas, C. L.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.
2014-12-01
Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT 8 satellite have been used to delineate the geological structures related to the potential geothermal reservoirs located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique, using the ADALGEO software, developed by [Soto et al., 2013]. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields. A lineament is generally defined as a straight or slightly curved feature in the landscape visible satellite image as an aligned sequence of pixel intensity contrast compared to the background. The system features extracted from satellite images is not identical to the geological lineaments that are generally determined by ground surveys, however, generally reflects the structure of faults and fractures in the crust. A temporal sequence of eight Landsat multispectral images of Central Andes geothermal field, located in VI region de Chile, was used to study changes in the configuration of the lineaments during 2011. The presence of minerals with silicification, epidotization, and albitization, which are typical for geothrmal reservoirs, was also identified, using their spectral characteristics, and subsequently corroborated in the field. Both lineament analysis and spectral analysis gave similar location of the reservoir, which increases reliability of the results.
AN APPROACH FOR STITCHING SATELLITE IMAGES IN A BIGDATA MAPREDUCE FRAMEWORK
Directory of Open Access Journals (Sweden)
H. Sarı
2017-11-01
Full Text Available In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper and then String formats in the forms of 255s and 0s (second mapper, and finally, find the best possible matching position of the images by a reduce function.
An Approach for Stitching Satellite Images in a Bigdata Mapreduce Framework
Sarı, H.; Eken, S.; Sayar, A.
2017-11-01
In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper) and then String formats in the forms of 255s and 0s (second mapper), and finally, find the best possible matching position of the images by a reduce function.
Detecting aircrafts from satellite images using saliency and conical ...
Indian Academy of Sciences (India)
Samik Banerjee
automatically detect all kinds of interesting targets in satellite images. .... which is used for text and image categorization, has been also introduced for object ...... 3.4 GHz processor, 32 GB RAM and Windows 7 (64 bit). Operating System. 6.
LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES
Directory of Open Access Journals (Sweden)
M. Tom
2018-05-01
Full Text Available Monitoring and analyzing the (decreasing trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m–1000 m satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal. Only the cloud-free (clean pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM. We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.
Lake Ice Detection in Low-Resolution Optical Satellite Images
Tom, M.; Kälin, U.; Sütterlin, M.; Baltsavias, E.; Schindler, K.
2018-05-01
Monitoring and analyzing the (decreasing) trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m-1000 m) satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM) lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen) semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal). Only the cloud-free (clean) pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM). We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.
Directory of Open Access Journals (Sweden)
Taek Seo Jung
2006-03-01
Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.
The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation
Directory of Open Access Journals (Sweden)
Xiao-fang Xie
2007-05-01
Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.
Geometric calibration of ERS satellite SAR images
DEFF Research Database (Denmark)
Mohr, Johan Jacob; Madsen, Søren Nørvang
2001-01-01
Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...
Ice Sheet Change Detection by Satellite Image Differencing
Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.
2010-01-01
Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.
Directory of Open Access Journals (Sweden)
L. Pompilio
2006-06-01
Full Text Available Problems related to airborne hyperspectral image data are reviewed and the requirements for data analysis applied to mineralogical (rocks and soils interpretation are discussed. The variability of mineral spectral features, including absorption position, shape and depth is considered and interpreted as due to chemical composition, grain size effects and mineral association. It is also shown how this variability can be related to well defined geologic processes. The influence of sensor noise and diffuse atmospheric radiance in classification accuracy is also analyzed.
Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID)
Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...
RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES
Directory of Open Access Journals (Sweden)
K. Gong
2017-05-01
Full Text Available High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.
MINER - A Mobile Imager of Neutrons for Emergency Responders
Energy Technology Data Exchange (ETDEWEB)
Goldsmith, John E. M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brennan, James S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gerling, Mark D [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kiff, Scott D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mascarenhas, Nicholas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Van De Vreugde, James L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-10-01
We have developed a mobile fast neutron imaging platform to enhance the capabilities of emergency responders in the localization and characterization of special nuclear material. This mobile imager of neutrons for emergency responders (MINER) is based on the Neutron Scatter Camera, a large segmented imaging system that was optimized for large-area search applications. Due to the reduced size and power requirements of a man-portable system, MINER has been engineered to fit a much smaller form factor, and to be operated from either a battery or AC power. We chose a design that enabled omnidirectional (4π) imaging, with only a ~twofold decrease in sensitivity compared to the much larger neutron scatter cameras. The system was designed to optimize its performance for neutron imaging and spectroscopy, but it does also function as a Compton camera for gamma imaging. This document outlines the project activities, broadly characterized as system development, laboratory measurements, and deployments, and presents sample results in these areas. Additional information can be found in the documents that reside in WebPMIS.
Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images
Directory of Open Access Journals (Sweden)
Biao Wang
2017-08-01
Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.
Mineral Precipitation in Fractures: Multiscale Imaging and Geochemical Modeling
Hajirezaie, S.; Peters, C. A.; Swift, A.; Sheets, J. M.; Cole, D. R.; Crandall, D.; Cheshire, M.; Stack, A. G.; Anovitz, L. M.
2017-12-01
For subsurface energy technologies such as geologic carbon sequestration, fractures are potential pathways for fluid migration from target formations. Highly permeable fractures may become sealed by mineral precipitation. In this study, we examined shale specimens with existing cemented fractures as natural analogues, using an array of imaging methods to characterize mineralogy and porosity at several spatial scales. In addition, we used reactive transport modeling to investigate geochemical conditions that can lead to extensive mineral precipitation and to simulate the impacts on fracture hydraulic properties. The naturally-cemented fractured rock specimens were from the Upper Wolfcamp formation in Texas, at 10,000 ft depth. The specimens were scanned using x-ray computed tomography (xCT) at resolution of 13 microns. The xCT images revealed an original fracture aperture of 1.9 mm filled with several distinct mineral phases and vuggy void regions, and the mineral phase volumes and surface areas were quantified and mapped in 3D. Specimens were thin-sectioned and examined at micron- and submicron-scales using petrographic microscopy (PM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and small angle X-ray scattering (SAXS). Collectively these methods revealed crystals of dolomite as large as 900 microns in length overlain with a heterogeneous mixture of carbonate minerals including calcite, dolomite, and Fe-rich dolomite, interspersed at spatial scales as small as 5 microns. In addition, secondary precipitation of SiO2 was found to fill some of the void space. This multiscale imaging was used to inform the reactive transport modeling employed to examine the conditions that can cause the observed mineral precipitation in fractures at a larger scale. Two brines containing solutions that when mixed would lead to precipitation of various carbonate minerals were simulated as injectants into a fracture domain. In particular, the competing
Accuracy assessment of topographic mapping using UAV image integrated with satellite images
International Nuclear Information System (INIS)
Azmi, S M; Ahmad, Baharin; Ahmad, Anuar
2014-01-01
Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps
Recurrent Neural Networks to Correct Satellite Image Classification Maps
Maggiori, Emmanuel; Charpiat, Guillaume; Tarabalka, Yuliya; Alliez, Pierre
2017-09-01
While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.
Images of war: using satellite images for human rights monitoring in Turkish Kurdistan.
de Vos, Hugo; Jongerden, Joost; van Etten, Jacob
2008-09-01
In areas of war and armed conflict it is difficult to get trustworthy and coherent information. Civil society and human rights groups often face problems of dealing with fragmented witness reports, disinformation of war propaganda, and difficult direct access to these areas. Turkish Kurdistan was used as a case study of armed conflict to evaluate the potential use of satellite images for verification of witness reports collected by human rights groups. The Turkish army was reported to be burning forests, fields and villages as a strategy in the conflict against guerrilla uprising. This paper concludes that satellite images are useful to validate witness reports of forest fires. Even though the use of this technology for human rights groups will depend on some feasibility factors such as prices, access and expertise, the images proved to be key for analysis of spatial aspects of conflict and valuable for reconstructing a more trustworthy picture.
Improving Eastern Bluebird nest box performance using computer analysis of satellite images
Directory of Open Access Journals (Sweden)
Sarah Svatora
2012-06-01
Full Text Available Bird conservationists have been introducing man-made boxes in an effort to increase the bluebird population. In this study we use computer analysis of satellite images to show that the performance of the boxes used by Eastern Bluebirds (Sialia sialis in Michigan can be improved by about 48%. The analysis is based on a strongcorrelation found between the edge directionality measured in the satellite image of the area around the box, and the preferences of the birds when selecting their nesting site. The method is based on satellite images taken from Google Earth, and can be used by conservationists to select a box placement strategy that will optimize the efficacy of the boxes deployed in a given area.
Directory of Open Access Journals (Sweden)
He Yongming
2016-10-01
Full Text Available Satellite hardware has reached a level of development that enables imaging satellites to realize applications in the area of meteorology and environmental monitoring. As the requirements in terms of feasibility and the actual profit achieved by satellite applications increase, we need to comprehensively consider the actual status, constraints, unpredictable information, and complicated requirements. The management of this complex information and the allocation of satellite resources to realize image acquisition have become essential for enhancing the efficiency of satellite instrumentation. In view of this, we designed a satellite auto mission planning system, which includes two sub-systems: the imaging satellite itself and the ground base, and these systems would then collaborate to process complicated missions: the satellite mainly focuses on mission planning and functions according to actual parameters, whereas the ground base provides auxiliary information, management, and control. Based on the requirements analysis, we have devised the application scenarios, main module, and key techniques. Comparison of the simulation results of the system, confirmed the feasibility and optimization efficiency of the system framework, which also stimulates new thinking for the method of monitoring environment and design of mission planning systems.
Goetz, Alexander F. H.
1986-01-01
The application of remote sensing techniques to mineral exploration involves the use of both spatial (morphological) as well as spectral information. This paper is directed toward a discussion of the uses of spectral image information and emphasizes the newest airborne and spaceborne sensor developments involving imaging spectrometers.
Convolutional neural network features based change detection in satellite images
Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong
2016-07-01
With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.
FFT-enhanced IHS transform method for fusing high-resolution satellite images
Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.
2007-01-01
Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).
Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.
2017-09-01
The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.
Spatial Data Exploring by Satellite Image Distributed Processing
Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.
2012-04-01
Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands
Very high resolution satellite data: New challenges in image analysis
Digital Repository Service at National Institute of Oceanography (India)
Sathe, P.V.; Muraleedharan, P.M.
with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...
Landsat TM and ETM+ Kansas Satellite Image Database (KSID)
Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...
International Nuclear Information System (INIS)
Yang Guofang; Lin Ziyu
2014-01-01
Remote sensing technology and high resolution satellite image were used to interprete the geologic information in Janchivlan, Mongolia. Mineralization condition information related uranium such as rocks and strata, faults, hydrothermal alteration were studied. By information extraction and target recognition from ALOS and ETM image, Devonian was found to be composed of two lithological units. The double token-ring structures in the midwest of study area were closely related to uranium metalization period of magmatic activity. According to the relationship of the comprehensive information and uranium mineralization, favorable metallogenic target was predicted in the study area, which was useful to uranium prospecting in the study area. (authors)
In-situ nanoscale imaging of clay minerals with atomic force microscopy
International Nuclear Information System (INIS)
Bosbach, D.
2010-01-01
Document available in extended abstract form only. Clay minerals play a key role in many concepts for high-level nuclear waste repository systems in deep geological formations. Various aspects related to the long-term safety of nuclear disposal are linked to their fundamental physical-chemical properties, in particular with respect to their reactivity in aqueous environments. Atomic Force Microscopy (AFM) allows high resolution imaging of clay minerals in-situ while they are exposed to an aqueous solution. The presentation is intended to provide an overview of examples of AFM studies on clay minerals: 1. AFM is an ideal tool to visualize the shape of individual clay particles down to molecular scales including a quantitative description of for example their aspect ratio. Furthermore, the particle size can be easily extracted from AFM data for individual particles as well as particle size distribution. 2. Surface area of clay minerals is a key issue when discussing heterogeneous reactions such as dissolution, adsorption or (surface) precipitation - total surface area, BET surface area, reactive surface area need to be distinguished. In particular reactive surface area is linked to specific reactive surface sites. AFM is of course able to identify such sites and consequently AFM data allow to characterize and to quantify reactive surface area. 3. The reactivity of clay mineral surfaces in aqueous environments controls the behaviour of clay minerals under repository conditions and also affects the migration/retention of radionuclides. It could be shown that the dissolution of smectite particles under acidic conditions at room temperature primarily occurs at (hk0) particle edges, whereas the reactivity of the (001) basal surfaces is very limited. The heterogeneous (surface) precipitation of secondary iron (hydr)oxides phase could be unraveled by AFM observations. Surface precipitation occurs preferentially at (hk0) edges surfaces. Ignoring the surface site specific
Directory of Open Access Journals (Sweden)
Peter Berglez
2018-01-01
Full Text Available The purpose of the article is to contribute a critical theoretical understanding of cross-professional relations on social media, focusing on politicians, journalists and PR practitioners. It is well known that these professional groups establish personal and close relations in offline contexts, but more attention needs to be paid to the role of social media. Here, it is argued that, in the context of digital media use, semi-private chatting, humour, and mutual acknowledgement, including the use of likes, smileys, heart symbols, etc. are evidence of a 'neoliberalization' of cross-professional relations. The underlying idea is that the common practice of self-branding undermines representations of professional belonging and exacerbates the blurring of professional boundaries. The critical conceptualization of such 'transboundary' interaction between politicians, journalists and PR practitioners, which is guided by a cultural materialist approach, includes the presentation of examples deriving from the Swedish Twittersphere, and suggestions for empirical research.
a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images
Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei
2018-04-01
Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.
Detection of jet contrails from satellite images
Meinert, Dieter
1994-02-01
In order to investigate the influence of modern technology on the world climate it is important to have automatic detection methods for man-induced parameters. In this case the influence of jet contrails on the greenhouse effect shall be investigated by means of images from polar orbiting satellites. Current methods of line recognition and amplification cannot distinguish between contrails and rather sharp edges of natural cirrus or noise. They still rely on human control. Through the combination of different methods from cloud physics, image comparison, pattern recognition, and artificial intelligence we try to overcome this handicap. Here we will present the basic methods applied to each image frame, and list preliminary results derived this way.
GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES
Directory of Open Access Journals (Sweden)
Catherine Mering
2011-05-01
Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.
METEOROLOGICAL SATELLITE IMAGES IN GEOGRAPHY CLASSES: a didactic possibility
Directory of Open Access Journals (Sweden)
Diego Correia Maia
2016-01-01
Full Text Available ABSTRACT: The satellite images are still largely unexplored as didactic resource in geography classes, particularly about meteorology. This article aims to contribute to the development of new methodologies of interpretation and understanding, beyond the construction of pedagogical practices involving meteorological satellite images, concepts and issues related to climate issues. The aim of this paper is to present possibilities for the use of meteorological satellite images in the Teaching of Geography, aiming the promoting and the understanding of contents of air masses and fronts and climatic factors. RESUMO: As imagens de satélite ainda são pouco exploradas como recurso didático nas aulas de Geografia, principalmente aquelas relativas à meteorologia. Este artigo visa contribuir com o desenvolvimento de novas metodologias de interpretação e compreensão, além da construção de práticas pedagógicas envolvendo imagens de satélite meteorológico, conceitos e temas ligados às questões climáticas. Seu objetivo é apresentar possibilidades de utilização das imagens de satélite meteorológico no Ensino de Geografia, visando à promoção e ao entendimento dos conteúdos de massas de ar e frentes e de elementos climáticos. Palavras chave
Spatial mapping of mineralization with manganese-enhanced magnetic resonance imaging
Chesnick, I.E.; Centeno, J.A.; Todorov, T.I.; Koenig, A.E.; Potter, K.
2011-01-01
Paramagnetic manganese can be employed as a calcium surrogate to sensitize the magnetic resonance imaging (MRI) technique to the processing of calcium during the bone formation process. At low doses, after just 48h of exposure, osteoblasts take up sufficient quantities of manganese to cause marked reductions in the water proton T1 values compared with untreated cells. After just 24h of exposure, 25??M MnCl2 had no significant effect on cell viability. However, for mineralization studies 100??M MnCl2 was used to avoid issues of manganese depletion in calvarial organ cultures and a post-treatment delay of 48h was implemented to ensure that manganese ions taken up by osteoblasts is deposited as mineral. All specimens were identified by their days in vitro (DIV). Using inductively coupled plasma optical emission spectroscopy (ICP-OES), we confirmed that Mn-treated calvariae continued to deposit mineral in culture and that the mineral composition was similar to that of age-matched controls. Notably there was a significant decrease in the manganese content of DIV18 compared with DIV11 specimens, possibly relating to less manganese sequestration as a result of mineral maturation. More importantly, quantitative T1 maps of Mn-treated calvariae showed localized reductions in T1 values over the calvarial surface, indicative of local variations in the surface manganese content. This result was verified with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). We also found that ??R1 values, calculated by subtracting the relaxation rate of Mn-treated specimens from the relaxation rate of age-matched controls, were proportional to the surface manganese content and thus mineralizing activity. From this analysis, we established that mineralization of DIV4 and DIV11 specimens occurred in all tissue zones, but was reduced for DIV18 specimens because of mineral maturation with less manganese sequestration. In DIV25 specimens, active mineralization was observed for
Directory of Open Access Journals (Sweden)
Y. Balkanski
2007-01-01
Full Text Available Modelling studies and satellite retrievals do not agree on the amplitude and/or sign of the direct radiative perturbation from dust. Modelling studies have systematically overpredicted mineral dust absorption compared to estimates based upon satellite retrievals. In this paper we first point out the source of this discrepancy, which originates from the shortwave refractive index of dust used in models. The imaginary part of the refractive index retrieved from AERONET over the range 300 to 700 nm is 3 to 6 times smaller than that used previously to model dust. We attempt to constrain these refractive indices using a mineralogical database and varying the abundances of iron oxides (the main absorber in the visible. We first consider the optically active mineral constituents of dust and compute the refractive indices from internal and external mixtures of minerals with relative amounts encountered in parent soils. We then compute the radiative perturbation due to mineral aerosols for internally and externally mixed minerals for 3 different hematite contents, 0.9%, 1.5% and 2.7% by volume. These constant amounts of hematite allow bracketing the influence of dust aerosol when it is respectively an inefficient, standard and a very efficient absorber. These values represent low, central and high content of iron oxides in dust determined from the mineralogical database. Linke et al. (2006 determined independently that iron-oxides represent 1.0 to 2.5% by volume using x-Ray fluorescence on 4 different samples collected over Morocco and Egypt. Based upon values of the refractive index retrieved from AERONET, we show that the best agreement between 440 and 1020 nm occurs for mineral dust internally mixed with 1.5% volume weighted hematite. This representation of mineral dust allows us to compute, using a general circulation model, a new global estimate of mineral dust perturbation between –0.47 and –0.24 Wm−2 at the top of the atmosphere, and between
Geostationary Satellite (GOES) Images
National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...
Autonomous Planetary 3-D Reconstruction From Satellite Images
DEFF Research Database (Denmark)
Denver, Troelz
1999-01-01
is discussed.Based on such features, 3-D representations may be compiled from two or more 2-D satellite images. The main purposes of such a mapping system are extraction of landing sites, objects of scientific interest and general planetary surveying. All data processing is performed autonomously onboard...
Directory of Open Access Journals (Sweden)
N. Champion
2012-08-01
Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.
Identification of mineral deposits in the brain on radiological images: a systematic review
International Nuclear Information System (INIS)
DelValdes Hernandez, Maria; Maconick, Lucy C.; Tan, Elizabeth M.J.; Wardlaw, Joanna M.
2012-01-01
MRI has allowed the study of mineral deposition in the brain throughout life and in disease. However, studies differ in their reporting of minerals on MRI for reasons that are unclear. We conducted a systematic review from 1985 to July 2011 to determine the appearance of iron, calcium, copper and manganese on MRI and CT and their reliability. We assessed which imaging investigations provided the most consistent results compared with histology. Of 325 papers on minerals imaging, we included 46 studies that confirmed findings either directly or indirectly using a non-imaging method such as histology. Within this group, there was inconsistency in the identification of iron probably because of changes in its paramagnetic properties during its degradation. Iron appeared consistently hypointense only on T2*-weighted MRI, and along with calcified areas, hyperattenuated on CT. Appearance of copper, calcium and manganese, although consistently reported as hyperintense on T1-weighted MRI, was confirmed histologically in few studies. On T2-weighted imaging, calcified areas were always reported as hypointense, while the appearance of iron depended on the concentration, location and degradation stage. More work is required to improve the reliability of imaging methods to detect and differentiate brain mineral deposition accurately. (orig.)
Geomorphology of coastal environments from satellite images
International Nuclear Information System (INIS)
Da Rocha Ribeiro, R.; Velho, L.; Schossler, V.
2010-01-01
This study aims at recognizing coastal environments supported by data from the Landsat Thematic Mapper (TM) satellite. The digital processing of images, System Information Geographic (SIG) techniques and field observation in one section of the “Província Costeira do Rio Grande do Sul” between the Rio Grande and the São Gonçalo channels - resulted in a geomorphologic profile and mapping
Multi sensor satellite imagers for commercial remote sensing
Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.
2005-10-01
This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.
Influence of Water and Mineral Oil on the Leaks in Satellite Motor Commutation Unit Clearances
Directory of Open Access Journals (Sweden)
Śliwiński Paweł
2017-09-01
Full Text Available The article describes the flow rates of mineral oil and water flowing, as working media, through the commutation unit of a hydraulic satellite motor. It is demonstrated that geometrical dimensions of commutation unit clearances change as a function of the machine shaft rotation angle. Methods for measuring the rate of this flow and the pressure in the working chamber are presented. The results of pressure measurements in the working chamber during the transition from the filling cycle to the emptying cycle are included. The pressure in the motor’s working chamber changes linearly as a function of the shaft rotation angle, which has a significant effect on the leakage in the commutation unit clearances. The paper presents new mathematical formulas in the form: Q=f(Δpγ to calculate the flow rate of water and mineral oil in the commutation unit clearances. The γ factor is described as a function of fluid viscosity and clearance length (the motor shaft rotation angle. The coefficients used in these formulas were determined based on the results of laboratory tests of a motor supplied with water and mineral oil.
Directory of Open Access Journals (Sweden)
Sankaran Rajendran
2015-02-01
Full Text Available The present study demonstrates the capability of a multispectral sensor for the detection of the minerals in the rocks surrounding the Rusayl and Al Jafnayn regions, Sultanate of Oman. The study of spectral absorptions of rocks and minerals in the visible and near infrared (VNIR and short wavelength infrared (SWIR spectral bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER using the Spectral Angle Mapper (SAM supervised image classification technique has provided information on the occurrence of minerals in the rock types of the regions. The study shows the occurrence of carbonate minerals in the limestone formations and of poorly altered silicate minerals in the basic dyke rocks of the study regions. The analysis of minerals over the ancient terraces and recent alluvial deposits show that the deposit materials are derived from the dykes and foliated gabbro source rocks. The image interpretation is compared to the geological map, verified in the field and confirmed through laboratory analyses. The satellite data and the image processing techniques used have potential in the recognition of minerals in the rocks of the study region and could be used in similar arid regions elsewhere in the world.
Nakajima, I; Inokuchi, S; Tajima, T; Takahashi, T
1985-04-01
An experiment to transmit ultrasonic tomographic section images required for remote medical diagnosis and care was conducted using the mobile telecommunication satellite OSCAR-10. The images received showed the intestinal condition of a patient incapable of verbal communication, however the image screen had a fairly coarse particle structure. On the basis of these experiments, were considered as the transmission of ultrasonic tomographic images extremely effective in remote diagnosis.
Directory of Open Access Journals (Sweden)
MADANI Mohammed
2017-10-01
Full Text Available In this paper, a new satellite image encryption algorithm based on the combination of multiple chaotic systems and a random cyclic rotation technique is proposed. Our contribution consists in implementing three different chaotic maps (logistic, sine, and standard combined to improve the security of satellite images. Besides enhancing the encryption, the proposed algorithm also focuses on advanced efficiency of the ciphered images. Compared with classical encryption schemes based on multiple chaotic maps and the Rubik's cube rotation, our approach has not only the same merits of chaos systems like high sensitivity to initial values, unpredictability, and pseudo-randomness, but also other advantages like a higher number of permutations, better performances in Peak Signal to Noise Ratio (PSNR and a Maximum Deviation (MD.
An Investigation on Water Quality of Darlik Dam Drinking Water using Satellite Images
Directory of Open Access Journals (Sweden)
Erhan Alparslan
2010-01-01
Full Text Available Darlik Dam supplies 15% of the water demand of Istanbul Metropolitan City of Turkey. Water quality (WQ in the Darlik Dam was investigated from Landsat 5 TM satellite images of the years 2004, 2005, and 2006 in order to determine land use/land cover changes in the watershed of the dam that may deteriorate its WQ. The images were geometrically and atmospherically corrected for WQ analysis. Next, an investigation was made by multiple regression analysis between the unitless planetary reflectance values of the first four bands of the June 2005 Landsat TM image of the dam and WQ parameters, such as chlorophyll-a, total dissolved matter, turbidity, total phosphorous, and total nitrogen, measured at satellite image acquisition time at seven stations in the dam. Finally, WQ in the dam was studied from satellite images of the years 2004, 2005, and 2006 by pattern recognition techniques in order to determine possible water pollution in the dam. This study was compared to a previous study done by the authors in the Küçükçekmece water reservoir, also in Istanbul City.
Automatic Registration Method for Fusion of ZY-1-02C Satellite Images
Directory of Open Access Journals (Sweden)
Qi Chen
2013-12-01
Full Text Available Automatic image registration (AIR has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system.
Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series
Champion, Nicolas
2016-06-01
Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl
AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES
Directory of Open Access Journals (Sweden)
N. Champion
2016-06-01
Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8
Global Solar Radiation in Spain from Satellite Images
International Nuclear Information System (INIS)
Ramirez, L.; Mora, L.; Sidrach de Cardona, M.; Navarro, A. A.; Varela, M.; Cruz, M. de la
2003-01-01
In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been reevaluated to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar, impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyrano metric measures in a concrete locality, but it provides a very valid indicator in places in which it is not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs
AUTOMATED CONSTRUCTION OF COVERAGE CATALOGUES OF ASTER SATELLITE IMAGE FOR URBAN AREAS OF THE WORLD
Directory of Open Access Journals (Sweden)
H. Miyazaki
2012-07-01
Full Text Available We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST, Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel-based cloud assessment and pixel value correction over seasonal variations.
International Nuclear Information System (INIS)
Yang Xu; Liu Dechang; Zhang Jielin
2008-01-01
In this study, the signification and content of prospecting information of uranium deposit are expounded. Quickbird high spatial resolution satellite data are used to extract the prospecting information of uranium deposit in Bashibulake area in the north of Tarim Basin. By using the pertinent methods of image processing, the information of ore-bearing bed, ore-control structure and mineralized alteration have been extracted. The results show a high consistency with the field survey. The aim of this study is to explore practicability of high spatial resolution satellite data for prospecting minerals, and to broaden the thinking of prospectation at similar area. (authors)
New and Emerging Satellite Imaging Capabilities in Support of Safeguards
International Nuclear Information System (INIS)
Johnson, M.; Paquette, J.P.; Spyropoulos, N.; Rainville, L.; Schichor, P.; Hong, M.
2015-01-01
This abstract is focused on new and emerging commercial satellite imagery (CSI) capabilities. For more than a decade, experienced imagery analysts have been exploiting and analyzing CSI in support of the Department of Safeguards. As the remote sensing industry continues to evolve, additional CSI imagery types are becoming available that could enhance our ability to evaluate and verify States' declarations and to investigate the possible presence of undeclared activities. A newly available and promising CSI capability that may have a Safeguards application is Full Motion Video (FMV) imagery collection from satellites. For quite some time, FMV imagery has been collected from airborne platforms, but now FMV sensors are being deployed into space. Like its airborne counterpart, satellite FMV imagery could provide analysts with a great deal of information, including insight into the operational status of facilities and patterns of activity. From a Safeguards perspective, FMV imagery could help the Agency in the evaluation and verification of States' declared facilities and activities. There are advantages of FMV imaging capabilities that cannot be duplicated with other CSI capabilities, including the ability to loiter over areas of interest and the potential to revisit sites multiple times per day. Additional sensor capabilities applicable to the Safeguards mission include, but are not limited to, the following sensors: · Thermal Infrared imaging sensors will be launched in late 2014 to monitor operational status, e.g., heat from a transformer. · High resolution ShortWave Infrared sensors able to characterize materials that could support verification of Additional Protocol declarations under Article 2.a(v). · Unmanned Aerial Vehicles with individual sensors or specific sensor combinations. The Safeguards Symposium provides a forum to showcase and demonstrate safeguards applications for these emerging satellite imaging capabilities. (author)
V-SIPAL - A VIRTUAL LABORATORY FOR SATELLITE IMAGE PROCESSING AND ANALYSIS
Directory of Open Access Journals (Sweden)
K. M. Buddhiraju
2012-09-01
Full Text Available In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.
Prospects of application of survey satellite image for meteorology
Kapochkina, A. B.; Kapochkin, B. B.; Kucherenko, N. V.
The maximal interest is represented with the information from geostationary satellites. These satellites repeat shootings the chosen territories, allowing to study dynamics of images. Most interesting shootings in IR a range. Studying of survey image is applied to studying linear elements of clouds (LEC). It is established, that "LEC " arise only above breaks of an earth's crust. In research results of the complex analysis of the satellite data, hydrometeorological supervision, seismicity, supervision over deformations of a surface of the Earth are used. It is established that before formation "LEC " in a ground layer arise anomalies of temperature and humidity. The situation above Europe 16 May, 2001 is considered. "LEC " in Europe block carry of air weights from the west to the east. Synoptic conditions above the Great Britain July, 7-10, 2000 is considered. Moving "LEC" trace distribution of deformation waves to an earth's crust. Satellite shootings Europe before earthquake in Greece 14.08.2003 are considered. These days ground supervision were conducted and the data of the geostationary satellite were analyzed. During moving "LEC " occur failures (destruction houses & of gas mains), earthquake. The situation above Iberian peninsula 12-16.11.2001 is considered. "LEC" arose before flooding in Europe. The situation before flooding in Germany June, 6-8, 2002 and flooding on the river Kuban June, 16-23, 2002 is considered. In case of occurrence of tectonic compression of an earth's crust there are "LEC ", tracer intensive movements of air upwards and downwards above negative and positive anomalies of the form of a terrestrial surface, accordingly. Such meteorological situations are dangerous to flights of aircraft, the fast gravitational anomalies influencing into orbits of movement of satellites trace. The situation above equatorial Atlantic 26.03.2003 years is considered. At tectonic compression of continental scale overcast covers the whole continents for more
Satellite image time series simulation for environmental monitoring
Guo, Tao
2014-11-01
The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of
Directory of Open Access Journals (Sweden)
Elizabeth J. Botha
2016-05-01
Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.
Moving object detection in video satellite image based on deep learning
Zhang, Xueyang; Xiang, Junhua
2017-11-01
Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.
Directory of Open Access Journals (Sweden)
N. M. S. M. Kadhim
2015-03-01
Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates
Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.
2015-03-01
Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of
IoSiS: a radar system for imaging of satellites in space
Jirousek, M.; Anger, S.; Dill, S.; Schreiber, E.; Peichl, M.
2017-05-01
Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolution radar images are helpful in analyzing a possible damage. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi-purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a highpower traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1 m RX antenna mounted on a common steerable positioner. High-resolution radar images are obtained by using Inverse Synthetic Aperture Radar (ISAR) techniques. The guided tracking of known objects during overpass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system including the basic setup of the antenna, the radar instrument with the RF error correction, and the measurement strategy. Also a short description about a simulation tool for the whole instrument and expected images is shown.
Discovering significant evolution patterns from satellite image time series.
Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain
2011-12-01
Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.
Foodstuff Survey Around a Major Nuclear Facility with Test of Satellite Image Application
International Nuclear Information System (INIS)
Fledderman, P.D.
1999-01-01
'A foodstuff survey was performed around the Savannah River Site, Aiken SC. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of SRS center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined in two ways: by the usual process of assuming uniform crop distribution in each county on the basis of agricultural statistics reported by state agencies, and by analysis of two LANDSAT TM images obtained in May and September. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the Site and by 16-km distance intervals from 16 km to 80 km. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption. For four food crops, the amounts per section based on county agricultural statistics prorated by area were compared with the amounts per section based on satellite image analysis. The median ratios of the former to the latter were 0.6 - 0.7, suggesting that the two approaches are comparable but that satellite image analysis gave consistently higher amounts. Use of satellite image analysis is recommended on the basis of these findings to obtain site-specific, as compared to area-averaged, information on crop locations in conjunction with radionuclide pathway modelling. Some improvements in technique are suggested for satellite image application to characterize additional crops.'
Polar-Orbiting Satellite (POES) Images
National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...
3D reconstruction from multi-view VHR-satellite images in MicMac
Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur
2018-05-01
This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.
Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging
Nag, S.; Li, A.
2016-12-01
Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall
Lineament systems indentification in Banten site using Spot 5 satellite image
International Nuclear Information System (INIS)
Yuliastuti; Heni Susiati; Yunus Daud; A-Sarwiyana Sastratenaya
2013-01-01
Lineament systems identification in Banten site using SPOT 5 satellite image has been performed. Based on regional site survey in Java Island, Banten is one of the potential candidate sites. The objective of this study was to determine direction and chronology of regional lineament morphology which was consider as fault or faulting in Banten site. The methodology used this study covered satellite image cropping, band selection, edge enhancement filtering, lineament extraction and lineament analysis. Result of the study showed that there were three dominant lineament groups, namely N-S, NW-SE, and E-W. Based on the forming chronology of the lineament, N-S group was the oldest one, followed by E-W group and NW-SE as the youngest group. These lineament groups have been confirmed as a manifestation of fault system structure. (author)
Surface mineral maps of Afghanistan derived from HyMap imaging spectrometer data, version 2
Kokaly, Raymond F.; King, Trude V.V.; Hoefen, Todd M.
2013-01-01
This report presents a new version of surface mineral maps derived from HyMap imaging spectrometer data collected over Afghanistan in the fall of 2007. This report also describes the processing steps applied to the imaging spectrometer data. The 218 individual flight lines composing the Afghanistan dataset, covering more than 438,000 square kilometers, were georeferenced to a mosaic of orthorectified Landsat images. The HyMap data were converted from radiance to reflectance using a radiative transfer program in combination with ground-calibration sites and a network of cross-cutting calibration flight lines. The U.S. Geological Survey Material Identification and Characterization Algorithm (MICA) was used to generate two thematic maps of surface minerals: a map of iron-bearing minerals and other materials, which have their primary absorption features at the shorter wavelengths of the reflected solar wavelength range, and a map of carbonates, phyllosilicates, sulfates, altered minerals, and other materials, which have their primary absorption features at the longer wavelengths of the reflected solar wavelength range. In contrast to the original version, version 2 of these maps is provided at full resolution of 23-meter pixel size. The thematic maps, MICA summary images, and the material fit and depth images are distributed in digital files linked to this report, in a format readable by remote sensing software and Geographic Information Systems (GIS). The digital files can be downloaded from http://pubs.usgs.gov/ds/787/downloads/.
Directory of Open Access Journals (Sweden)
Nina Merkle
2017-06-01
Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.
International Nuclear Information System (INIS)
Luo Fusheng; Cui Zhenkui; Fang Maolong; Wang Guojuan; Yao Hua
1998-12-01
The key of mineral exploration by remote sensing method is the extraction and identification of mineralization-related geologic information from remote sensing data under the guidance of mineralization theory. Remote sensing research of deposits is combined with the analysis of regional geology setting, so as to give full play to the advantage of remote sensing technology. According to the geologic features of the covered area, different kinds of satellite data are, at first, selected and processed with different methods and therefore mineralization-related geologic information is effectively extracted. Then regional geologic setting is discussed and main mineralization-controlled factors, such as uranium-occurred volcanic basins, mineralization-controlled faults and granite bodies, Mesozoic volcanic rock series, volcanic framework, are identified. On the basis of the former study, the remote sensing image models of different kinds of deposits have been established. Finally, multi-source information integration technique has been applied to the assessment of favorable mineralization areas. This research shows that it is feasible to extract and identify mineralization-related information from remote sensing images in complicated and covered areas, and that the study area is favorable for uranium and polymetal deposit explorations because of its favorable geologic setting and mineralization conditions
Solar resources estimation combining digital terrain models and satellite images techniques
Energy Technology Data Exchange (ETDEWEB)
Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)
2010-12-15
One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)
AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION
Directory of Open Access Journals (Sweden)
P. Kupidura
2016-06-01
Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the
NEAR REAL-TIME AUTOMATIC MARINE VESSEL DETECTION ON OPTICAL SATELLITE IMAGES
Directory of Open Access Journals (Sweden)
G. Máttyus
2013-05-01
Full Text Available Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation. Optical satellite images (OSI can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.
Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images
Máttyus, G.
2013-05-01
Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.
Directory of Open Access Journals (Sweden)
ONȚEL IRINA
2014-03-01
Full Text Available Satellite images are an important source of information to identify and analyse some hazardous climatic phenomena such as the dryness and drought. These phenomena are characterized by scarce rainfall, increased evapotranspiration and high soil moisture deficit. The soil water reserve depletes to the wilting coefficient, soon followed by the pedological drought which has negative effects on vegetation and agricultural productivity. The MODIS satellite images (Moderate Resolution Imaging Spectroradiometer allow the monitoring of the vegetation throughout the entire vegetative period, with a frequency of 1-2 days and with a spatial resolution of 250 m, 500 m and 1 km away. Another useful source of information is the LANDSAT satellite images, with a spatial resolution of 30 m. Based on MODIS and Landsat satellite images, were calculated moisture monitoring index such as SIWSI (Shortwave Infrared Water Stress Index. Consequently, some years with low moisture such as 2000, 2002, 2007 and 2012 could be identified. Spatially, the areas with moisture deficit varied from one year to another all over the whole analised period (2000-2012. The remote sensing results was corelated with Standard Precipitation Anomaly, which gives a measure of the severity of a wet or dry event.
Energy Technology Data Exchange (ETDEWEB)
Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL
2010-10-21
The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.
Ronald E. McRoberts
2010-01-01
Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...
Accuracy comparison of Pléiades satellite ortho-images using GPS ...
African Journals Online (AJOL)
resolution satellite ortho-image when different types of ground control are used. This required the execution of two orthorectification tests where only the type of GCPs differed. The results of these tests were interesting since it highlighted the ...
Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang
2017-08-01
According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.
A fast and automatic mosaic method for high-resolution satellite images
Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing
2015-12-01
We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.
Directory of Open Access Journals (Sweden)
Shaodan Li
2017-11-01
Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.
Use of high resolution satellite images for monitoring of earthquakes and volcano activity.
Arellano-Baeza, Alonso A.
Our studies have shown that the strain energy accumulation deep in the Earth's crust that precedes a strong earthquake can be detected by applying a lineament extraction technique to the high-resolution multispectral satellite images. A lineament is a straight or a somewhat curved feature in a satellite image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. We analyzed tens of earthquakes occurred in the Pacific coast of the South America with the Richter scale magnitude ˜4.5, using ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changed significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth's crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion. The results obtained made it possible to include this research as a part of scientific program of Chilean Remote Sensing Satellite mission to be launched in 2010.
Chagas disease study using satellite image processing: A Bolivian case
Vargas-Cuentas, Natalia I.; Roman-Gonzalez, Avid; Mantari, Alicia Alva; Muñoz, Luis AnthonyAucapuma
2018-03-01
Remote sensing is the technology that has enabled us to obtain information about the Earth's surface without directly contacting it. For this reason, currently, the Bolivian state has considered a list of interesting applications of remote sensing in the country, including the following: biodiversity and environment monitoring, mining and geology, epidemiology, agriculture, water resources and land use planning. The use of satellite images has become a great tool for epidemiology because with this technological advance we can determine the environment in which transmission occurs, the distribution of the disease and its evolution over time. In that context, one of the important diseases related to public health in Bolivia is Chagas disease, also known as South American Trypanosomiasis. Chagas is caused by a blood-sucking bug or Vinchuca, which causes serious intestinal and heart long term problems and affects 33.4% of the Bolivian population. This disease affects mostly humble people, so the Bolivian state invests millions of dollars to acquire medicine and distribute it for free. Due to the above reasons, the present research aims to analyze some areas of Bolivia using satellite images for developing an epidemiology study. The primary objective is to understand the environment in which the transmission of the disease happens, and the climatic conditions under which occurs, observe the behavior of the blood-sucking bug, identify in which months occur higher outbreaks, in which months the bug leaves its eggs, and under which weather conditions this happens. All this information would be contrasted with information extracted from the satellite images and data from the Ministry of Health, and the Institute of Meteorology in Bolivia. All this data will allow us to have a more integrated understanding of this disease and promote new possibilities to prevent and control it.
Image analysis of seafloor photographs for estimation of deep-sea minerals
Digital Repository Service at National Institute of Oceanography (India)
Sharma, R.; Jaisankar, S.; Samanta, S.; Sardar, A.A.; Gracias, D.G.
of these minerals, necessitating the involvement of a user input. A method has been developed whereby spectral signatures of different features are identified using a software ‘trained’ by a user, and the images are digitized for coverage estimation of nodules...
Wang, N.; Yang, R.
2018-04-01
Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.
Three-dimensional information extraction from GaoFen-1 satellite images for landslide monitoring
Wang, Shixin; Yang, Baolin; Zhou, Yi; Wang, Futao; Zhang, Rui; Zhao, Qing
2018-05-01
To more efficiently use GaoFen-1 (GF-1) satellite images for landslide emergency monitoring, a Digital Surface Model (DSM) can be generated from GF-1 across-track stereo image pairs to build a terrain dataset. This study proposes a landslide 3D information extraction method based on the terrain changes of slope objects. The slope objects are mergences of segmented image objects which have similar aspects; and the terrain changes are calculated from the post-disaster Digital Elevation Model (DEM) from GF-1 and the pre-disaster DEM from GDEM V2. A high mountain landslide that occurred in Wenchuan County, Sichuan Province is used to conduct a 3D information extraction test. The extracted total area of the landslide is 22.58 ha; the displaced earth volume is 652,100 m3; and the average sliding direction is 263.83°. The accuracies of them are 0.89, 0.87 and 0.95, respectively. Thus, the proposed method expands the application of GF-1 satellite images to the field of landslide emergency monitoring.
A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing.
Udelhoven, Thomas; Schlerf, Martin; Segl, Karl; Mallick, Kaniska; Bossung, Christian; Retzlaff, Rebecca; Rock, Gilles; Fischer, Peter; Müller, Andreas; Storch, Tobias; Eisele, Andreas; Weise, Dennis; Hupfer, Werner; Knigge, Thiemo
2017-07-01
This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1-5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2-12.5 µm (instrument NEDT 0.05 K-0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0-10.25 µm and 10.25-12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1-3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval.
A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing
Directory of Open Access Journals (Sweden)
Thomas Udelhoven
2017-07-01
Full Text Available This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping. The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1–5 days at off-nadir. At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month. To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1 a hyperspectral TIR system with ~75 bands at 7.2–12.5 µm (instrument NEDT 0.05 K–0.1 K and a ground sampling distance (GSD of 60 m, and (2 a panchromatic high-resolution TIR-imager with two channels (8.0–10.25 µm and 10.25–12.5 µm and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1–3 days to combine data from the visible and near infrared (VNIR, the shortwave infrared (SWIR and TIR spectral regions and to refine parameter retrieval.
Deep learning for the detection of barchan dunes in satellite images
Azzaoui, A. M.; Adnani, M.; Elbelrhiti, H.; Chaouki, B. E. K.; Masmoudi, L.
2017-12-01
Barchan dunes are known to be the fastest moving sand dunes in deserts as they form under unidirectional winds and limited sand supply over a firm coherent basement (Elbelrhiti and Hargitai,2015). They were studied in the context of natural hazard monitoring as they could be a threat to human activities and infrastructures. Also, they were studied as a natural phenomenon occurring in other planetary landforms such as Mars or Venus (Bourke et al., 2010). Our region of interest was located in a desert region in the south of Morocco, in a barchan dunes corridor next to the town of Tarfaya. This region which is part of the Sahara desert contained thousands of barchans; which limits the number of dunes that could be studied during field missions. Therefore, we chose to monitor barchan dunes with satellite imagery, which can be seen as a complementary approach to field missions. We collected data from the Sentinel platform (https://scihub.copernicus.eu/dhus/); we used a machine learning method as a basis for the detection of barchan dunes positions in the satellite image. We trained a deep learning model on a mid-sized dataset that contained blocks representing images of barchan dunes, and images of other desert features, that we collected by cropping and annotating the source image. During testing, we browsed the satellite image with a gliding window that evaluated each block, and then produced a probability map. Finally, a threshold on the latter map exposed the location of barchan dunes. We used a subsample of data to train the model and we gradually incremented the size of the training set to get finer results and avoid over fitting. The positions of barchan dunes were successfully detected and deep learning was an effective method for this application. Sentinel-2 images were chosen for their availability and good temporal resolution, which will allow the tracking of barchan dunes in future work. While Sentinel images had sufficient spatial resolution for the
Wind Statistics Offshore based on Satellite Images
DEFF Research Database (Denmark)
Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete
2009-01-01
-based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters......Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy...
Use of satellite images for the monitoring of water systems
Hillebrand, Gudrun; Winterscheid, Axel; Baschek, Björn; Wolf, Thomas
2015-04-01
Satellite images are a proven source of information for monitoring ecological indicators in coastal waters and inland river systems. This potential of remote sensing products was demonstrated by recent research projects (e.g. EU-funded project Freshmon - www.freshmon.eu) and other activities by national institutions. Among indicators for water quality, a particular focus was set on the temporal and spatial dynamics of suspended particulate matter (SPM) and Chlorophyll-a (Chl-a). The German Federal Institute of Hydrology (BfG) was using the Weser and Elbe estuaries as test cases to compare in-situ measurements with results obtained from a temporal series of automatically generated maps of SPM distributions based on remote sensing data. Maps of SPM and Chl-a distributions in European inland rivers and alpine lakes were generated by the Freshmon Project. Earth observation based products are a valuable source for additional data that can well supplement in-situ monitoring. For 2015, the BfG and the Institute for Lake Research of the State Institute for the Environment, Measurements and Nature Conservation of Baden-Wuerttemberg, Germany (LUBW) are in the process to start implementing an operational service for monitoring SPM and Chl-a based on satellite images (Landsat 7 & 8, Sentinel 2, and if required other systems with higher spatial resolution, e.g. Rapid Eye). In this 2-years project, which is part of the European Copernicus Programme, the operational service will be set up for - the inland rivers of Rhine and Elbe - the North Sea estuaries of Elbe, Weser and Ems. Furthermore - Lake Constance and other lakes located within the Federal State of Baden-Wuerttemberg. In future, the service can be implemented for other rivers and lakes as well. Key feature of the project is a data base that holds the stock of geo-referenced maps of SPM and Chl-a distributions. Via web-based portals (e.g. GGInA - geo-portal of the BfG; UIS - environmental information system of the
Weiner, A. M.; Gundy, J.; Brown-Bertold, B.; Yates, H.; Dobler, J. T.
2017-12-01
Since their introduction, geostationary weather satellites have enabled us to track hurricane life-cycle movement from development to dissipation. During the 2017 hurricane season, the new GOES-16 geostationary satellite demonstrated just how far we have progressed technologically in geostationary satellite imaging, with hurricane imagery showing never-before-seen detail of the hurricane eye and eyewall structure and life cycle. In addition, new ground system technology, leveraging high-performance computing, delivered imagery and data to forecasters with unprecedented speed—and with updates as often as every 30 seconds. As additional satellites and new products become operational, forecasters will be able to track hurricanes with even greater accuracy and assist in aftermath evaluations. This presentation will present glimpses into the past, a look at the present, and a prediction for the future utilization of geostationary satellites with respect to all facets of hurricane support.
Liang, Yu-Li
Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory
Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction
Su, X.
2017-12-01
A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.
International Nuclear Information System (INIS)
Batchelar, Deidre L.; Davidson, Melanie T.M.; Dabrowski, Waldemar; Cunningham, Ian A.
2006-01-01
Quantitative analysis of bone composition is necessary for the accurate diagnosis and monitoring of metabolic bone diseases. Accurate assessment of the bone mineralization state is the first requirement for a comprehensive analysis. In diagnostic imaging, x-ray coherent scatter depends upon the molecular structure of tissues. Coherent-scatter computed tomography (CSCT) exploits this feature to identify tissue types in composite biological specimens. We have used CSCT to map the distributions of tissues relevant to bone disease (fat, soft tissue, collagen, and mineral) within bone-tissue phantoms and an excised cadaveric bone sample. Using a purpose-built scanner, we have measured hydroxyapatite (bone mineral) concentrations based on coherent-scatter patterns from a series of samples with varying hydroxyapatite content. The measured scatter intensity is proportional to mineral density in true g/cm 3 . Repeated measurements of the hydroxyapatite concentration in each sample were within, at most, 2% of each other, revealing an excellent precision in determining hydroxyapatite concentration. All measurements were also found to be accurate to within 3% of the known values. Phantoms simulating normal, over-, and under-mineralized bone were created by mixing known masses of pure collagen and hydroxyapatite. An analysis of the composite scatter patterns gave the density of each material. For each composite, the densities were within 2% of the known values. Collagen and hydroxyapatite concentrations were also examined in a bone-mimicking phantom, incorporating other bone constituents (fat, soft tissue). Tomographic maps of the coherent-scatter properties of each specimen were reconstructed, from which material-specific images were generated. Each tissue was clearly distinguished and the collagen-mineral ratio determined from this phantom was also within 2% of the known value. Existing bone analysis techniques cannot determine the collagen-mineral ratio in intact specimens
INTEGRATION OF PALSAR AND ASTER SATELLITE DATA FOR GEOLOGICAL MAPPING IN TROPICS
Directory of Open Access Journals (Sweden)
A. Beiranvand Pour
2015-10-01
Full Text Available This research investigates the integration of the Phased Array type L-band Synthetic Aperture Radar (PALSAR and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER satellite data for geological mapping applications in tropical environments. The eastern part of the central belt of peninsular Malaysia has been investigated to identify structural features and mineral mapping using PALSAR and ASTER data. Adaptive local sigma and directional filters were applied to PALSAR data for detecting geological structure elements in the study area. The vegetation, mineralogic and lithologic indices for ASTER bands were tested in tropical climate. Lineaments (fault and fractures and curvilinear (anticline or syncline were detected using PALSAR fused image of directional filters (N-S, NE-SW, and NW-SE.Vegetation index image map show vegetation cover by fusing ASTER VNIR bands. High concentration of clay minerals zone was detected using fused image map derived from ASTER SWIR bands. Fusion of ASTER TIR bands produced image map of the lithological units. Results indicate that data integration and data fusion from PALSAR and ASTER sources enhanced information extraction for geological mapping in tropical environments.
Solar irradiance assessment in insular areas using Himawari-8 satellite images
Liandrat, O.; Cros, S.; Turpin, M.; Pineau, J. F.
2016-12-01
The high amount of surface solar irradiance (SSI) in the tropics is an advantage for a profitable PV production. It will allow many tropical islands to pursue their economic growth with a clean, affordable and locally produced energy. However, the local meteorological conditions induce a very high variability which is problematic for a safe and gainful injection into the power grid. This issue is even more critical in non-interconnected territories where network stability is an absolute necessity. Therefore, the injection of PV power is legally limited in some European oversea territories. In this context, intraday irradiance forecasting (several hours ahead) is particularly useful to mitigate the production variability by reducing the cost of power storage management. At this time scale, cloud cover evolves with a stochastic behaviour not properly represented in numerical weather prediction (NWP) models. Analysing cloud motion using images from geostationary meteorological satellites is a well-known alternative to forecasting SSI up to 6 hours ahead with a better accuracy than NWP models. In this study, we present and apply our satellite-based solar irradiance forecasting methods over two measurement sites located in the field of view of the satellite Himawari-8: Cocos (Keeling) Islands (Australia) and New Caledonia (France). In particular, we converted 4 months of images from Himawari-8 visible channel into cloud index maps. Then, we applied an algorithm computing a cloud motion vector field from a short sequence of consecutive images. Comparisons between forecasted SSI at 1 hour of time horizon and collocated pyranometric measurements show a relative RMSE between 20 and 27%. Error sources related to the tropic insular context (coastal area heterogeneity, sub-pixel scale orographic cloud appearance, convective situation…) are discussed at every implementation step for the different methods.
King, Trude V.V.; Berger, Byron R.; Johnson, Michaela R.
2014-01-01
As part of the U.S. Geological Survey and Department of Defense Task Force for Business and Stability Operations natural resources revitalization activities in Afghanistan, four permissive areas for mineralization, Bamyan 1, Farah 1, Ghazni 1, and Ghazni 2, have been identified using imaging spectroscopy data. To support economic development, the areas of potential mineralization were selected on the occurrence of selected mineral assemblages mapped using the HyMap™ data (kaolinite, jarosite, hydrated silica, chlorite, epidote, iron-bearing carbonate, buddingtonite, dickite, and alunite) that may be indicative of past mineralization processes in areas with limited or no previous mineral resource studies. Approximately 30 sites were initially determined to be candidates for areas of potential mineralization. Additional criteria and material used to refine the selection and prioritization process included existing geologic maps, Landsat Thematic Mapper data, and published literature. The HyMapTM data were interpreted in the context of the regional geologic and tectonic setting and used the presence of alteration mineral assemblages to identify areas with the potential for undiscovered mineral resources. Further field-sampling, mapping, and supporting geochemical analyses are necessary to fully substantiate and verify the specific deposit types in the four areas of potential mineralization.
Automatic Matching of Multi-Source Satellite Images: A Case Study on ZY-1-02C and ETM+
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Bo Wang
2017-10-01
Full Text Available The ever-growing number of applications for satellites is being compromised by their poor direct positioning precision. Existing orthoimages, such as enhanced thematic mapper (ETM+ orthoimages, can provide georeferences or improve the geo-referencing accuracy of satellite images, such ZY-1-02C images that have unsatisfactory positioning precision, thus enhancing their processing efficiency and application. In this paper, a feasible image matching approach using multi-source satellite images is proposed on the basis of an experiment carried out with ZY-1-02C Level 1 images and ETM+ orthoimages. The proposed approach overcame differences in rotation angle, scale, and translation between images. The rotation and scale variances were evaluated on the basis of rational polynomial coefficients. The translation vectors were generated after blocking the overall phase correlation. Then, normalized cross-correlation and least-squares matching were applied for matching. Finally, the gross errors of the corresponding points were eliminated by local statistic vectors in a TIN structure. Experimental results showed a matching precision of less than two pixels (root-mean-square error, and comparison results indicated that the proposed method outperforms Scale-Invariant Feature Transform (SIFT, Speeded Up Robust Features (SURF, and Affine-Scale Invariant Feature Transform (A-SIFT in terms of reliability and efficiency.
An anti-image interference quadrature IF architecture for satellite receivers
Directory of Open Access Journals (Sweden)
He Weidong
2014-08-01
Full Text Available Since Global Navigation Satellite System (GNSS signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF receivers, image aliasing due to in-phase and quadrature (I/Q channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in analog-to-digital converters (ADC. As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is proposed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.
Marlow, W. A.; Cahoy, K.; Males, J.; Carlton, A.; Yoon, H.
2015-12-01
Real-time observation and monitoring of geostationary (GEO) satellites with ground-based imaging systems would be an attractive alternative to fielding high cost, long lead, space-based imagers, but ground-based observations are inherently limited by atmospheric turbulence. Adaptive optics (AO) systems are used to help ground telescopes achieve diffraction-limited seeing. AO systems have historically relied on the use of bright natural guide stars or laser guide stars projected on a layer of the upper atmosphere by ground laser systems. There are several challenges with this approach such as the sidereal motion of GEO objects relative to natural guide stars and limitations of ground-based laser guide stars; they cannot be used to correct tip-tilt, they are not point sources, and have finite angular sizes when detected at the receiver. There is a difference between the wavefront error measured using the guide star compared with the target due to cone effect, which also makes it difficult to use a distributed aperture system with a larger baseline to improve resolution. Inspired by previous concepts proposed by A.H. Greenaway, we present using a space-based laser guide starprojected from a satellite orbiting the Earth. We show that a nanosatellite-based guide star system meets the needs for imaging GEO objects using a low power laser even from 36,000 km altitude. Satellite guide star (SGS) systemswould be well above atmospheric turbulence and could provide a small angular size reference source. CubeSatsoffer inexpensive, frequent access to space at a fraction of the cost of traditional systems, and are now being deployed to geostationary orbits and on interplanetary trajectories. The fundamental CubeSat bus unit of 10 cm cubed can be combined in multiple units and offers a common form factor allowing for easy integration as secondary payloads on traditional launches and rapid testing of new technologies on-orbit. We describe a 6U CubeSat SGS measuring 10 cm x 20 cm x
Synchronous atmospheric radiation correction of GF-2 satellite multispectral image
Bian, Fuqiang; Fan, Dongdong; Zhang, Yan; Wang, Dandan
2018-02-01
GF-2 remote sensing products have been widely used in many fields for its high-quality information, which provides technical support for the the macroeconomic decisions. Atmospheric correction is the necessary part in the data preprocessing of the quantitative high resolution remote sensing, which can eliminate the signal interference in the radiation path caused by atmospheric scattering and absorption, and reducting apparent reflectance into real reflectance of the surface targets. Aiming at the problem that current research lack of atmospheric date which are synchronization and region matching of the surface observation image, this research utilize the MODIS Level 1B synchronous data to simulate synchronized atmospheric condition, and write programs to implementation process of aerosol retrieval and atmospheric correction, then generate a lookup table of the remote sensing image based on the radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum) to correct the atmospheric effect of multispectral image from GF-2 satellite PMS-1 payload. According to the correction results, this paper analyzes the pixel histogram of the reflectance spectrum of the 4 spectral bands of PMS-1, and evaluates the correction results of different spectral bands. Then conducted a comparison experiment on the same GF-2 image based on the QUAC. According to the different targets respectively statistics the average value of NDVI, implement a comparative study of NDVI from two different results. The degree of influence was discussed by whether to adopt synchronous atmospheric date. The study shows that the result of the synchronous atmospheric parameters have significantly improved the quantitative application of the GF-2 remote sensing data.
Hoffer, R. M. (Principal Investigator)
1974-01-01
The author has identified the following significant results. One capability which has been recognized by many geologists working with space photography is the ability to see linear features and alinements which were previously not apparent. To the exploration geologist, major lineaments seen on satellite images are of particular interest. A portion of ERTS-1 frame 1407-17193 (3 Sept. 1973) was used for mapping lineaments and producing an iso-lineament intersection map. Skylab photography over the area of prime area was not useable due to snow cover. Once the lineaments were mapped, a grid with 2.5 km spacing was overlayed on the map and the lineament intersections occurring within each grid square were counted and the number plotted in the center of the grid square. These numbers were then contoured producing a contour map of equal lineament intersection. It is believed that the areas of high intersection concentration would be the most favorable area for ore mineralization if favorable host rocks are also present. These highly fractured areas would act as conduits for carrying the ore forming solutions to the site of deposition in a favorable host rock. Two of the six areas of high intersection concentration are over areas of present or past mining camps and small claims are known to exist near the others. These would be prime target areas for future mineral exploration.
Helmke, Peer; Baschek, Björn; Hunsänger, Thomas; Kranz, Susanne
2014-10-01
For detecting accidental and illegal pollution by mineral oil, the German exclusive economic zone and surrounding waters have been monitored by aircraft operationally for more than 25 years. Aircraft surveillance uses predominantly Side-Looking-Airborne-Radar for visualization of the effect of oil to smoothen capillary waves. A set of near range sensors complements the remote sensing data available for the human operator to classify the detected features as "mineral oil", "natural phenomenon", "other substance" or "unknown" pollution. Today, as an add-on to aerial surveillance, the German Central Command of Maritime Emergencies uses the operational satellite service "CleanSeaNet" provided by the European Maritime Safety Agency: Radar satellite data is analyzed in near real time and alerts of potential pollution are sent out. Shortly after receiving the results, aircraft surveillance flights are started by the 3rd Naval Air Wing and the locations of the satellite alerts are checked. Thus, a combined system of satellite and aerial surveillance is in place. The German Federal Institute of Hydrology, BfG, has access to the data of the pollution events detected during these flights and the corresponding meta-data of flights and satellite images. In this work, a period of two years of this data is analyzed. The probability to detect pollutions is evaluated for (A) flight missions associated with satellite scenes, and (B) additional flights performed independently from satellite scenes. Thus, the influence of satellite alerts on the efficiency of aircraft monitoring is investigated. Coverage and coordination of the monitoring by aircraft and satellite are assessed and implications for the operational monitoring are discussed.
Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk
2017-10-01
Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.
Band co-registration modeling of LAPAN-A3/IPB multispectral imager based on satellite attitude
Hakim, P. R.; Syafrudin, A. H.; Utama, S.; Jayani, A. P. S.
2018-05-01
One of significant geometric distortion on images of LAPAN-A3/IPB multispectral imager is co-registration error between each color channel detector. Band co-registration distortion usually can be corrected by using several approaches, which are manual method, image matching algorithm, or sensor modeling and calibration approach. This paper develops another approach to minimize band co-registration distortion on LAPAN-A3/IPB multispectral image by using supervised modeling of image matching with respect to satellite attitude. Modeling results show that band co-registration error in across-track axis is strongly influenced by yaw angle, while error in along-track axis is fairly influenced by both pitch and roll angle. Accuracy of the models obtained is pretty good, which lies between 1-3 pixels error for each axis of each pair of band co-registration. This mean that the model can be used to correct the distorted images without the need of slower image matching algorithm, nor the laborious effort needed in manual approach and sensor calibration. Since the calculation can be executed in order of seconds, this approach can be used in real time quick-look image processing in ground station or even in satellite on-board image processing.
Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming
2017-10-01
Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.
DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES
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M. A. Azzaoui
2016-06-01
Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.
Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran
2018-03-01
This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).
PROBLEMS AND LIMITATIONS OF SATELLITE IMAGE ORIENTATION FOR DETERMINATION OF HEIGHT MODELS
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K. Jacobsen
2017-05-01
Full Text Available The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC. The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3, WorldView-2 (WV2, Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs. The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the
Problems and Limitations of Satellite Image Orientation for Determination of Height Models
Jacobsen, K.
2017-05-01
The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height
Thematic mapping from satellite imagery
Denègre, J
2013-01-01
Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre
Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.
2016-12-01
Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and
Dindar, Serdar; Kaewunruen, Sakdirat; Osman, Mohd H.
2017-10-01
One of the emerging significant advances in engineering, satellite imaging (SI) is becoming very common in any kind of civil engineering projects e.g., bridge, canal, dam, earthworks, power plant, water works etc., to provide an accurate, economical and expeditious means of acquiring a rapid assessment. Satellite imaging services in general utilise combinations of high quality satellite imagery, image processing and interpretation to obtain specific required information, e.g. surface movement analysis. To extract, manipulate and provide such a precise knowledge, several systems, including geographic information systems (GIS) and global positioning system (GPS), are generally used for orthorectification. Although such systems are useful for mitigating risk from projects, their productiveness is arguable and operational risk after application is open to discussion. As the applicability of any novel application to the railway industry is often measured in terms of whether or not it has gained in-depth knowledge and to what degree, as a result of errors during its operation, this novel application generates risk in ongoing projects. This study reviews what can be achievable for risk management of railway turnouts thorough satellite imaging. The methodology is established on the basis of other published articles in this area and the results of applications to understand how applicable such imagining process is on railway turnouts, and how sub-systems in turnouts can be effectively traced/operated with less risk than at present. As a result of this review study, it is aimed that the railway sector better understands risk mitigation in particular applications.
Ore minerals textural characterization by hyperspectral imaging
Bonifazi, Giuseppe; Picone, Nicoletta; Serranti, Silvia
2013-02-01
The utilization of hyperspectral detection devices, for natural resources mapping/exploitation through remote sensing techniques, dates back to the early 1970s. From the first devices utilizing a one-dimensional profile spectrometer, HyperSpectral Imaging (HSI) devices have been developed. Thus, from specific-customized devices, originally developed by Governmental Agencies (e.g. NASA, specialized research labs, etc.), a lot of HSI based equipment are today available at commercial level. Parallel to this huge increase of hyperspectral systems development/manufacturing, addressed to airborne application, a strong increase also occurred in developing HSI based devices for "ground" utilization that is sensing units able to play inside a laboratory, a processing plant and/or in an open field. Thanks to this diffusion more and more applications have been developed and tested in this last years also in the materials sectors. Such an approach, when successful, is quite challenging being usually reliable, robust and characterised by lower costs if compared with those usually associated to commonly applied analytical off- and/or on-line analytical approaches. In this paper such an approach is presented with reference to ore minerals characterization. According to the different phases and stages of ore minerals and products characterization, and starting from the analyses of the detected hyperspectral firms, it is possible to derive useful information about mineral flow stream properties and their physical-chemical attributes. This last aspect can be utilized to define innovative process mineralogy strategies and to implement on-line procedures at processing level. The present study discusses the effects related to the adoption of different hardware configurations, the utilization of different logics to perform the analysis and the selection of different algorithms according to the different characterization, inspection and quality control actions to apply.
Mineral Mapping Using Simulated Worldview-3 Short-Wave-Infrared Imagery
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Sandra L. Perry
2013-05-01
Full Text Available WorldView commercial imaging satellites comprise a constellation developed by DigitalGlobe Inc. (Longmont, CO, USA. Worldview-3 (WV-3, currently planned for launch in 2014, will have 8 spectral bands in the Visible and Near-Infrared (VNIR, and an additional 8 bands in the Short-Wave-Infrared (SWIR; the approximately 1.0–2.5 μm spectral range. WV-3 will be the first commercial system with both high spatial resolution and multispectral SWIR capability. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS data collected at 3 m spatial resolution with 86 SWIR bands having 10 nm spectral resolution were used to simulate the new WV-3 SWIR data. AVIRIS data were converted to reflectance, geographically registered, and resized to the proposed 3.7 and 7.5 m spatial resolutions. WV-3 SWIR band pass functions were used to spectrally resample the data to the proposed 8 SWIR bands. Characteristic reflectance signatures extracted from the data for known mineral locations (endmembers were used to map spatial locations of specific minerals. The WV-3 results, when compared to spectral mapping using the full AVIRIS SWIR dataset, illustrate that the WV-3 spectral bands should permit identification and mapping of some key minerals, however, minerals with similar spectral features may be confused and will not be mapped with the same detail as using hyperspectral systems. The high spatial resolution should provide detailed mapping of complex alteration mineral patterns not achievable by current multispectral systems. The WV-3 simulation results are promising and indicate that this sensor will be a significant tool for geologic remote sensing.
Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.
2017-03-01
Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.
Wang, Teng
2015-09-05
Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.
Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł
2017-12-01
To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.
Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.
2015-12-01
Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.
Design of a nano-satellite demonstrator of an infrared imaging space interferometer: the HyperCube
Dohlen, Kjetil; Vives, Sébastien; Rakotonimbahy, Eddy; Sarkar, Tanmoy; Tasnim Ava, Tanzila; Baccichet, Nicola; Savini, Giorgio; Swinyard, Bruce
2014-07-01
The construction of a kilometer-baseline far infrared imaging interferometer is one of the big instrumental challenges for astronomical instrumentation in the coming decades. Recent proposals such as FIRI, SPIRIT, and PFI illustrate both science cases, from exo-planetary science to study of interstellar media and cosmology, and ideas for construction of such instruments, both in space and on the ground. An interesting option for an imaging multi-aperture interferometer with km baseline is the space-based hyper telescope (HT) where a giant, sparsely populated primary mirror is constituted of several free-flying satellites each carrying a mirror segment. All the segments point the same object and direct their part of the pupil towards a common focus where another satellite, containing recombiner optics and a detector unit, is located. In Labeyrie's [1] original HT concept, perfect phasing of all the segments was assumed, allowing snap-shot imaging within a reduced field of view and coronagraphic extinction of the star. However, for a general purpose observatory, image reconstruction using closure phase a posteriori image reconstruction is possible as long as the pupil is fully non-redundant. Such reconstruction allows for much reduced alignment tolerances, since optical path length control is only required to within several tens of wavelengths, rather than within a fraction of a wavelength. In this paper we present preliminary studies for such an instrument and plans for building a miniature version to be flown on a nano satellite. A design for recombiner optics is proposed, including a scheme for exit pupil re-organization, is proposed, indicating the focal plane satellite in the case of a km-baseline interferometer could be contained within a 1m3 unit. Different options for realization of a miniature version are presented, including instruments for solar observations in the visible and the thermal infrared and giant planet observations in the visible, and an
Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation
Song, Huihui
Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat
Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.
2018-04-01
A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.
Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics
International Nuclear Information System (INIS)
Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.
2014-01-01
Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models
Directory of Open Access Journals (Sweden)
P. Fischer
2018-04-01
Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.
Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.
2017-12-01
Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.
[Quantitative image of bone mineral content--dual energy subtraction in a single exposure].
Katoh, T
1990-09-25
A dual energy subtraction system was constructed on an experimental basis for the quantitative image of bone mineral content. The system consists of a radiography system and an image processor. Two radiograms were taken with dual x-ray energy in a single exposure using an x-ray beam dichromized by a tin filter. In this system, a film cassette was used where a low speed film-screen system, a copper filter and a high speed film-screen system were layered on top of each other. The images were read by a microdensitometer and processed by a personal computer. The image processing included the corrections of the film characteristics and heterogeneity in the x-ray field, and the dual energy subtraction in which the effect of the high energy component of the dichromized beam on the tube side image was corrected. In order to determine the accuracy of the system, experiments using wedge phantoms made of mixtures of epoxy resin and bone mineral-equivalent materials in various fractions were performed for various tube potentials and film processing conditions. The results indicated that the relative precision of the system was within +/- 4% and that the propagation of the film noise was within +/- 11 mg/cm2 for the 0.2 mm pixels. The results also indicated that the system response was independent of the tube potential and the film processing condition. The bone mineral weight in each phalanx of the freshly dissected hand of a rhesus monkey was measured by this system and compared with the ash weight. The results showed an error of +/- 10%, slightly larger than that of phantom experiments, which is probably due to the effect of fat and the variation of focus-object distance. The air kerma in free air at the object was approximately 0.5 mGy for one exposure. The results indicate that this system is applicable to clinical use and provides useful information for evaluating a time-course of localized bone disease.
Directory of Open Access Journals (Sweden)
Un-Seob Lee
2007-09-01
Full Text Available We developed a software for simulations and analyses of the Image Navigation and Registration (INR system, and compares the characteristics of Image Motion Compensation (IMC algorithms for the INR system. According to the orbit errors and attitude errors, the capabilities of the image distortions are analyzed. The distortions of images can be compensated by GOES IMC algorithm and Modified IMC (MIMC algorithm. The capabilities of each IMC algorithm are confirmed based on compensated images. The MIMC yields better results than GOES IMC although both the algorithms well compensate distorted images. The results of this research can be used as valuable asset to design of INR system for the Communication, Ocean, Meteorological Satellite (COMS.
A graph-based approach to detect spatiotemporal dynamics in satellite image time series
Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal
2017-08-01
Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.
Satellite Image Time Series Decomposition Based on EEMD
Directory of Open Access Journals (Sweden)
Yun-long Kong
2015-11-01
Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.
Alteration mineral mapping in inaccessible regions using target detection algorithms to ASTER data
International Nuclear Information System (INIS)
Pour, A B; Hashim, M; Park, Y
2017-01-01
In this study, the applications of target detection algorithms such as Constrained Energy Minimization (CEM), Orthogonal Subspace Projection (OSP) and Adaptive Coherence Estimator (ACE) to shortwave infrared bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data was investigated to extract geological information for alteration mineral mapping in poorly exposed lithologies in inaccessible domains. The Oscar II coast area north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping technique. It is an inaccessible region due to the remoteness of many rock exposures and the necessity to travel over sever mountainous and glacier-cover terrains for geological field mapping and sample collection. Fractional abundance of alteration minerals such as muscovite, kaolinite, illite, montmorillonite, epidote, chlorite and biotite were identified in alteration zones using CEM, OSP and ACE algorithms in poorly mapped and unmapped zones at district scale for the Oscar II coast area. The results of this investigation demonstrated the applicability of ASTER shortwave infrared spectral data for lithological and alteration mineral mapping in poorly exposed lithologies and inaccessible regions, particularly using the image processing algorithms that are capable to detect sub-pixel targets in the remotely sensed images, where no prior information is available. (paper)
Directory of Open Access Journals (Sweden)
Irene Erlyn Wina Rachmawan
2015-06-01
Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.
Ieda, Akimasa; Kauristie, Kirsti; Nishimura, Yukitoshi; Miyashita, Yukinaga; Frey, Harald U.; Juusola, Liisa; Whiter, Daniel; Nosé, Masahito; Fillingim, Matthew O.; Honary, Farideh; Rogers, Neil C.; Miyoshi, Yoshizumi; Miura, Tsubasa; Kawashima, Takahiro; Machida, Shinobu
2018-05-01
Substorm onset has originally been defined as a longitudinally extended sudden auroral brightening (Akasofu initial brightening: AIB) followed a few minutes later by an auroral poleward expansion in ground-based all-sky images (ASIs). In contrast, such clearly marked two-stage development has not been evident in satellite-based global images (GIs). Instead, substorm onsets have been identified as localized sudden brightenings that expand immediately poleward. To resolve these differences, optical substorm onset signatures in GIs and ASIs are compared in this study for a substorm that occurred on December 7, 1999. For this substorm, the Polar satellite ultraviolet global imager was operated with a fixed-filter (170 nm) mode, enabling a higher time resolution (37 s) than usual to resolve the possible two-stage development. These data were compared with 20-s resolution green-line (557.7 nm) ASIs at Muonio in Finland. The ASIs revealed the AIB at 2124:50 UT and the subsequent poleward expansion at 2127:50 UT, whereas the GIs revealed only an onset brightening that started at 2127:49 UT. Thus, the onset in the GIs was delayed relative to the AIB and in fact agreed with the poleward expansion in the ASIs. The fact that the AIB was not evident in the GIs may be attributed to the limited spatial resolution of GIs for thin auroral arc brightenings. The implications of these results for the definition of substorm onset are discussed herein.[Figure not available: see fulltext.
A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink
Directory of Open Access Journals (Sweden)
Salemi Eric
2008-01-01
Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.
A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink
Directory of Open Access Journals (Sweden)
Eric Salemi
2008-01-01
Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.
Directory of Open Access Journals (Sweden)
Giuseppe Scardozzi
2011-01-01
Full Text Available The paper is concerned with the contribution that a rich documentation of multitemporal optical satellite images with high resolution provides for the knowledge of the five great Assyrian capital cities (Ashur, Kar-Tukulti-Ninurta, Kalhu, Dur-Sharrukin, and Nineveh, in northern Iraq. These images also allow monitoring changes of landscape in the higher course of the Tigris during the last half century and document damages in archaeological sites during the two Gulf Wars. The data set, available for each city, consists of panchromatic and multispectral images taken between 2001 and 2007 by modern commercial satellites (Ikonos-2, QuickBird-2, and WorldView-1 and of panchromatic photographs of U.S. spy satellites operating between 1965 and 1969 (Corona KH-4B and Gambit KH-7. These photos were taken before diffusion of mechanized agriculture and the expansion of urban areas, so they are very useful to document many archaeological features and the landscape that has been modified in the last decades, as shown by recent satellite images.
Sun glitter imaging analysis of submarine sand waves in HJ-1A/B satellite CCD images
Zhang, Huaguo; He, Xiekai; Yang, Kang; Fu, Bin; Guan, Weibing
2014-11-01
Submarine sand waves are a widespread bed-form in tidal environment. Submarine sand waves induce current convergence and divergence that affect sea surface roughness thus become visible in sun glitter images. These sun glitter images have been employed for mapping sand wave topography. However, there are lots of effect factors in sun glitter imaging of the submarine sand waves, such as the imaging geometry and dynamic environment condition. In this paper, several sun glitter images from HJ-1A/B in the Taiwan Banks are selected. These satellite sun glitter images are used to discuss sun glitter imaging characteristics in different sensor parameters and dynamic environment condition. To interpret the imaging characteristics, calculating the sun glitter radiance and analyzing its spatial characteristics of the sand wave in different images is the best way. In this study, a simulated model based on sun glitter radiation transmission is adopted to certify the imaging analysis in further. Some results are drawn based on the study. Firstly, the sun glitter radiation is mainly determined by sensor view angle. Second, the current is another key factor for the sun glitter. The opposite current direction will cause exchanging of bright stripes and dark stripes. Third, brightness reversal would happen at the critical angle. Therefore, when using sun glitter image to obtain depth inversion, one is advised to take advantage of image properties of sand waves and to pay attention to key dynamic environment condition and brightness reversal.
International Nuclear Information System (INIS)
Hunter, D.
1998-01-01
location of the contaminant in the sample but also to which substrate it exhibits preferential binding. Chemical Imaging combines conventional imaging with micro-spot spectroscopy. In conventional imaging, a digitized image is stored as a series of intensity values at each image element or pixel. In chemical imaging light is recorded as both a function of wavelength and location. In the image domain, the data set contains a full image at each individual wavelength. In the spectroscopy domain, a fully resolved spectrum can be recorded at each individual pixel. As a result, the data contains both structural and compositional information, allowing samples to be probed, even dynamically, with unprecedented analytical power. Several examples will be shown where these modern spectroscopic techniques can be applied non-invasively to natural mineral bearing samples and a variety of inorganic contaminants where it can be demonstrated that even a minor mineral component can be the dominant control mechanism for contaminant binding and retardation in the environment
Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring
Directory of Open Access Journals (Sweden)
Pauline Dusseux
2014-06-01
Full Text Available The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four optical and five SAR satellite images with high/very high spatial resolutions acquired during the growing season. A vegetation index, namely the NDVI (Normalized Difference Vegetation Index, and two biophysical variables, the LAI (Leaf Area Index and the fCOVER (fraction of Vegetation Cover were computed using optical time series and polarization (HH, VV, HV, VH. The polarization ratio and polarimetric decomposition (Freeman–Durden and Cloude–Pottier were calculated using SAR time series. Then, variables derived from optical, SAR and both types of remotely-sensed data were successively classified using the Support Vector Machine (SVM technique. The results show that the classification accuracy of SAR variables is higher than those using optical data (0.98 compared to 0.81. They also highlight that the combination of optical and SAR time series data is of prime interest to discriminate grasslands from crops, allowing an improved classification accuracy.
Satellite Eye for Galathea 3. Annual report 2006
DEFF Research Database (Denmark)
Hasager, Charlotte Bay; Sørensen, Peter; Pedersen, Leif Toudal
The Satellite Eye for Galathea 3 project is collecting satellite images from many satellites and, in particular, from the European ENVISAT satellite along the Galathea 3 global route. The expedition takes place from 11 August 2006 to 27 April 2007. Prior to the expedition several satellite images...... Vædderen, pupils in the classrooms and the public at any moment can take a look at the conditions seen from the eyes of the Earth observing satellites....
Mobile satellite service communications tests using a NASA satellite
Chambers, Katherine H.; Koschmeder, Louis A.; Hollansworth, James E.; ONeill, Jack; Jones, Robert E.; Gibbons, Richard C.
1995-01-01
Emerging applications of commercial mobile satellite communications include satellite delivery of compact disc (CD) quality radio to car drivers who can select their favorite programming as they drive any distance; transmission of current air traffic data to aircraft; and handheld communication of data and images from any remote corner of the world. Experiments with the enabling technologies and tests and demonstrations of these concepts are being conducted before the first satellite is launched by utilizing an existing NASA spacecraft.
kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images
Directory of Open Access Journals (Sweden)
Yang Bai
2018-03-01
Full Text Available Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. However, most radiometric normalization methods are linear, and they cannot eliminate the regular nonlinear spectral differences. Here we introduce the well-established kernel canonical correlation analysis (kCCA into radiometric normalization for the first time to overcome this problem, which leads to a new kernel method. It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. It also perfectly eliminates the impact of nonlinear changes caused by seasonal variation of natural objects. Comparisons with the multivariate alteration detection (CCA-based normalization and the histogram matching, on Gaofen-1 (GF-1 data, indicate that the kCCA-based normalization can preserve more similarity and better correlation between an image-pair and effectively avoid the color error propagation. The proposed method not only builds the common scale or reference to make the radiometric consistency among GF-1 image sequences, but also highlights the interesting spectral changes while eliminates less interesting spectral changes. Our method enables the application of GF-1 data for change detection, land-use, land-cover change detection etc.
Application of SVM on satellite images to detect hotspots in Jharia coal field region of India
Energy Technology Data Exchange (ETDEWEB)
Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)
2008-07-01
The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.
Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.
2016-07-01
Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.
Impurity mapping in sulphide minerals using Time-resolved Ion Beam Induced Current imaging
International Nuclear Information System (INIS)
Laird, Jamie S.; Johnson, Brett C.; Ganesan, Kumaravelu; Kandasamy, Sasikaran; Davidson, Garry; Borg, Stacey; Ryan, Chris G.
2010-01-01
The semiconducting properties and charge transport within natural minerals like pyrite are postulated to drive certain geochemical processes which can lead to precious metal ore genesis. In this paper we outline electrical measurements on mineral samples and present spatio-temporally resolved Ion Beam Induced Charge or Current studies on a Schottky pyrite junction. Au-Schottky contacts were fabricated in regions selected by thermoelectric and 4-point probe resistivity measurements. The complexity in charge transport due to impurity variations results in imaging contrast which is deemed important for fluid electrochemistry. The relevance of understanding charge collection in pyrite in the context of complex geochemical processes is briefly discussed.
Cyclone track forecasting based on satellite images using artificial neural networks
Kovordanyi, Rita; Roy, Chandan
2009-01-01
Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on sate...
Khodaverdi zahraee, N.; Rastiveis, H.
2017-09-01
Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged area, the amount and type of damage can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. The purpose of this paper is to propose and implement an automatic approach for mapping destructed buildings after an earthquake using pre- and post-event high resolution satellite images. In the proposed method after preprocessing, segmentation of both images is performed using multi-resolution segmentation technique. Then, the segmentation results are intersected with ArcGIS to obtain equal image objects on both images. After that, appropriate textural features, which make a better difference between changed or unchanged areas, are calculated for all the image objects. Finally, subtracting the extracted textural features from pre- and post-event images, obtained values are applied as an input feature vector in an artificial neural network for classifying the area into two classes of changed and unchanged areas. The proposed method was evaluated using WorldView2 satellite images, acquired before and after the 2010 Haiti earthquake. The reported overall accuracy of 93% proved the ability of the proposed method for post-earthquake buildings change detection.
Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field
Directory of Open Access Journals (Sweden)
Hong Sun
2013-05-01
Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.
Directory of Open Access Journals (Sweden)
Peng Zhang
2014-03-01
Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.
Directory of Open Access Journals (Sweden)
Mehdi Maboudi
2016-08-01
Full Text Available Road networks are very important features in geospatial databases. Even though high-resolution optical satellite images have already been acquired for more than a decade, tools for automated extraction of road networks from these images are still rare. One consequence of this is the need for manual interaction which, in turn, is time and cost intensive. In this paper, a multi-stage approach is proposed which integrates structural, spectral, textural, as well as contextual information of objects to extract road networks from very high resolution satellite images. Highlights of the approach are a novel linearity index employed for the discrimination of elongated road segments from other objects and customized tensor voting which is utilized to fill missing parts of the network. Experiments are carried out with different datasets. Comparison of the achieved results with the results of seven state-of-the-art methods demonstrated the efficiency of the proposed approach.
International Nuclear Information System (INIS)
Kondo, Yuji
2003-01-01
Bone mineral density (BMD) increases through infancy and adolescence, reaching a maximum at 20-30 years of age. Thereafter, BMD gradually decreases with age in both sexes. The image contrast of radiographs of bones varies with the change in BMD owing to the changes in the X-ray absorption of bone. The image contrast of bone generally is higher in the young adult than in the older adult. To examine the relation between BMD and image visibility, we carried out the following experiments. We measured the image contrast of radiographs of a lumbar vertebra phantom in which BMD was equivalent to the average BMD for each developmental period. We examined image visibility at various levels of imaging contrast using the Howlett chart. The results indicated that differences in BMD affect the image contrast of radiographs, and, consequently, image visibility. It was also found that image visibility in the young adult was higher than that in the older adult. The findings showed that, in digital radiography of young adults with high BMD, X-ray exposure can be decreased according the ratio of improvement in image visibility. (author)
Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich
2017-08-01
In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.
International Nuclear Information System (INIS)
Jansen, Frank; Behrens, Joerg; Pospisil, Stanislav; Kudela, Karel
2011-01-01
We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.
Energy Technology Data Exchange (ETDEWEB)
Jansen, Frank, E-mail: frank.jansen@dlr.de [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Behrens, Joerg [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Pospisil, Stanislav [Czech Technical University, IEAP, 12800 Prague 2, Horska 3a/22 (Czech Republic); Kudela, Karel [Slovak Academy of Sciences, IEP, 04001 Kosice, Watsonova 47 (Slovakia)
2011-05-15
We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.
Oommen, T.; Chatterjee, S.
2017-12-01
NASA and the Indian Space Research Organization (ISRO) are generating Earth surface features data using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) within 380 to 2500 nm spectral range. This research focuses on the utilization of such data to better understand the mineral potential in India and to demonstrate the application of spectral data in rock type discrimination and mapping for mineral exploration by using automated mapping techniques. The primary focus area of this research is the Hutti-Maski greenstone belt, located in Karnataka, India. The AVIRIS-NG data was integrated with field analyzed data (laboratory scaled compositional analysis, mineralogy, and spectral library) to characterize minerals and rock types. An expert system was developed to produce mineral maps from AVIRIS-NG data automatically. The ground truth data from the study areas was obtained from the existing literature and collaborators from India. The Bayesian spectral unmixing algorithm was used in AVIRIS-NG data for endmember selection. The classification maps of the minerals and rock types were developed using support vector machine algorithm. The ground truth data was used to verify the mineral maps.
Materne, A.; Bardoux, A.; Geoffray, H.; Tournier, T.; Kubik, P.; Morris, D.; Wallace, I.; Renard, C.
2017-11-01
The PLEIADES-HR Earth observing satellites, under CNES development, combine a 0.7m resolution panchromatic channel, and a multispectral channel allowing a 2.8 m resolution, in 4 spectral bands. The 2 satellites will be placed on a sun-synchronous orbit at an altitude of 695 km. The camera operates in push broom mode, providing images across a 20 km swath. This paper focuses on the specifications, design and performance of the TDI detectors developed by e2v technologies under CNES contract for the panchromatic channel. Design drivers, derived from the mission and satellite requirements, architecture of the sensor and measurement results for key performances of the first prototypes are presented.
Inexpensive land-use maps extracted from satellite data
Barney, T. W.; Barr, D. J.; Elifrits, C. D.; Johannsen, C. J.
1979-01-01
Satellite images are interpretable with minimal skill and equipment by employing method which uses false color composite print of image of area transmitted from Landsat satellite. Method is effective for those who have little experience with satellite imagery, little time, and little money available.
Effects of satellite image spatial aggregation and resolution on estimates of forest land area
M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer
2009-01-01
Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...
Tsivrikos, Dimitrios; Dollinger, Daniel; Lermer, Eva
2018-01-01
Hand hygiene practice in hospitals is unfortunately still widely insufficient, even though it is known that transmitting pathogens via hands is the leading cause of healthcare-associated infections. Previous research has shown that improving knowledge, providing feedback on past behaviour and targeting social norms are promising approaches to improve hand hygiene practices. The present field experiment was designed to direct people on when to perform hand hygiene and prevent forgetfulness. This intervention is the first to examine the effect of inducing injunctive social norms via an emoticon-based feedback system on hand hygiene behaviour. Electronic monitoring and feedback devices were installed in hospital patient rooms on top of hand-rub dispensers, next to the doorway, for a period of 17 weeks. In the emoticon condition, screens at the devices activated whenever a person entered or exited the room. Before using the alcohol-based hand-rub dispenser, a frowny face was displayed, indicating that hand hygiene should be performed. If the dispenser was subsequently used, this picture changed to a smiley face to positively reinforce the correct behaviour. Hand hygiene behaviour in the emoticon rooms significantly outperformed the behaviour in three other tested conditions. The strong effect in this field experiment indicates that activating injunctive norms may be a promising approach to improve hand hygiene behaviour. Theoretical and practical implications of these findings are discussed. PMID:29782516
Gladish, James C; Duncan, Donald D
2017-01-20
Herein, we discuss the remote assessment of the subwavelength organizational structure of a medium. Specifically, we use spectral imaging polarimetry, as the vector nature of polarized light enables it to interact with optical anisotropies within a medium, while the spectral aspect of polarization is sensitive to small-scale structure. The ability to image these effects allows for inference of spatial structural organization parameters. This work describes a methodology for revealing structural organization by exploiting the Stokes/Mueller formalism and by utilizing measurements from a spectral imaging polarimeter constructed from liquid crystal variable retarders and a liquid crystal tunable filter. We provide results to validate the system and then show results from measurements on a mineral sample.
Post launch calibration and testing of the Advanced Baseline Imager on the GOES-R satellite
Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.
2016-05-01
The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.
Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites
Directory of Open Access Journals (Sweden)
Maocai Wang
2014-01-01
Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.
Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn
2017-10-01
Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.
Ship Detection in Optical Satellite Image Based on RX Method and PCAnet
Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting
2017-12-01
In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.
Bandwidth compression of the digitized HDTV images for transmission via satellites
Al-Asmari, A. KH.; Kwatra, S. C.
1992-01-01
This paper investigates a subband coding scheme to reduce the transmission bandwidth of the digitized HDTV images. The HDTV signals are decomposed into seven bands. Each band is then independently encoded. The based band is DPCM encoded and the high bands are encoded by using nonuniform Laplacian quantizers with a dead zone. By selecting the dead zone on the basis of energy in the high bands an acceptable image quality is achieved at an average of 45 Mbits/sec (Mbps) rate. This rate is comparable to some very hardware intensive schemes of transform compression or vector quantization proposed in the literature. The subband coding scheme used in this study is considered to be of medium complexity. The 45 Mbps rate is suitable for transmission of HDTV signals via satellites.
Liu, X.; Wang, M.
2016-02-01
For coastal and inland waters, complete (in spatial) and frequent satellite measurements are important in order to monitor and understand coastal biological and ecological processes and phenomena, such as diurnal variations. High-frequency images of the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)) derived from the Korean Geostationary Ocean Color Imager (GOCI) provide a unique opportunity to study diurnal variation of the water turbidity in coastal regions of the Bohai Sea, Yellow Sea, and East China Sea. However, there are lots of missing pixels in the original GOCI-derived Kd(490) images due to clouds and various other reasons. Data Interpolating Empirical Orthogonal Function (DINEOF) is a method to reconstruct missing data in geophysical datasets based on Empirical Orthogonal Function (EOF). In this study, the DINEOF is applied to GOCI-derived Kd(490) data in the Yangtze River mouth and the Yellow River mouth regions, the DINEOF reconstructed Kd(490) data are used to fill in the missing pixels, and the spatial patterns and temporal functions of the first three EOF modes are also used to investigate the sub-diurnal variation due to the tidal forcing. In addition, DINEOF method is also applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (SNPP) satellite to reconstruct missing pixels in the daily Kd(490) and chlorophyll-a concentration images, and some application examples in the Chesapeake Bay and the Gulf of Mexico will be presented.
Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng
2017-06-20
The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.
DEFF Research Database (Denmark)
Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai
2006-01-01
A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...
Greenberger, R. N.; Ehlmann, B. L.; Kelemen, P. B.; Manning, C. E.; Teagle, D. A. H.; Harris, M.; Michibayashi, K.; Takazawa, E.
2017-12-01
The Oman Drilling Project provides an unprecedented opportunity to study the formation and alteration of oceanic crust and peridotite. Key to answering the main questions of the project are a characterization of the primary and secondary minerals present within the drill core and their spatial relationships. To that end, we used the Caltech imaging spectrometer system to scan the entire 1.5-km archive half of the core from all four gabbro and listvenite boreholes (GT1A, GT2A, GT3A, and BT1B) at 250 µm/pixel aboard the JAMSTEC Drilling Vessel Chikyu during the ChikyuOman core description campaign. The instrument measures the visible and shortwave infrared reflectance spectra of the rocks as a function of wavelength from 0.4 to 2.6 µm. This wavelength range is sensitive to many mineral groups, including hydrated minerals (phyllosilicates, zeolites, amorphous silica polytypes), carbonates, sulfates, and transition metals, most commonly iron-bearing mineralogies. To complete the measurements, the core was illuminated with a halogen light source and moved below the spectrometer at 1 cm/s by the Chikyu's Geotek track. Data are corrected and processed to reflectance using measurements of dark current and a spectralon calibration panel. The data provide a unique view of the mineralogy at high spatial resolution. Analysis of the images for complete downhole trends is ongoing. Thus far, a variety of minerals have been identified within their petrologic contexts, including but not limited to magnesite, dolomite, calcite, quartz (through an Si-OH absorption due to minor H2O), serpentine, chlorite, epidote, zeolites, mica (fuchsite), kaolinite, prehnite, gypsum, amphibole, and iron oxides. Further analysis will likely identify more minerals. Results include rapidly distinguishing the cations present within carbonate minerals and identifying minerals of volumetrically-low abundance within the matrix and veins of core samples. This technique, for example, accurately identifies
Weather Satellite Pictures and How to Obtain Them.
Petit, Noel J.; Johnson, Philip
1982-01-01
An introduction to satellite meteorology is presented to promote use of live weather satellite photographs in the classroom. Topics addressed include weather satellites, how they work, earth emissions, satellite photography, satellite image analysis, obtaining satellite pictures, and future considerations. Includes sources for materials to…
High resolution satellite image indexing and retrieval using SURF features and bag of visual words
Bouteldja, Samia; Kourgli, Assia
2017-03-01
In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.
International Nuclear Information System (INIS)
Abdou Azaz, L.K.
2008-01-01
Alexandria is the second largest urban governorate in Egypt and has seen significant urban growth in its modern and contemporary history. This study investigates the urban growth phenomenon in Alexandria, Egypt, using the integration of remote sensing and GIS. The urban physical expansion and change were detected using Landsat satellite images. The satellite images of years 1984 and 1993 were first geo referenced, achieving a very small RMSE that provided high accuracy data for satellite image analysis. Then, the images were classified using a tailored classification scheme with accuracy of 93.82% and 95.27% for 1984 and 1993 images respectively. This high accuracy enabled detecting land use/land cover changes with high confidence using a post-classification comparison method. One of the most important findings here is the loss of cultivated land in favour of urban expansion. If the current loss rates continued, 75% of green lands would be lost by year 2191. These hazardous rates call for an urban growth management policy that can preserve such valuable resources to achieve sustainable urban development. Modelling techniques can help in defining the scenarios of urban growth. In this study, the SLEUTH urban growth model was applied to predict future urban expansion in Alexandria until the year 2055. The application of this model in Alexandria of Egypt with its different environmental characteristics is the first application outside USA and Europe. The results revealed that future urban growth would continue along the edges of the current urban extent. This means that the cultivated lands in the east and the southeast of the city will be decreased. To deal with such crisis, there is a serious need for a comprehensive urban growth management programme that can be based on the best practices in similar situations
Uygur, Merve; Karaman, Muhittin; Kumral, Mustafa
2016-04-01
Çürüksu (Denizli) Graben hosts various geothermal fields such as Kızıldere, Yenice, Gerali, Karahayıt, and Tekkehamam. Neotectonic activities, which are caused by extensional tectonism, and deep circulation in sub-volcanic intrusions are heat sources of hydrothermal solutions. The temperature of hydrothermal solutions is between 53 and 260 degree Celsius. Phyllic, argillic, silicic, and carbonatization alterations and various hydrothermal minerals have been identified in various research studies of these areas. Surfaced hydrothermal alteration minerals are one set of potential indicators of geothermal resources. Developing the exploration tools to define the surface indicators of geothermal fields can assist in the recognition of geothermal resources. Thermal and hyperspectral imaging and analysis can be used for defining the surface indicators of geothermal fields. This study tests the hypothesis that hyperspectral image analysis based on EO-1 Hyperion images can be used for the delineation and definition of surfaced hydrothermal alteration in geothermal fields. Hyperspectral image analyses were applied to images covering the geothermal fields whose alteration characteristic are known. To reduce data dimensionality and identify spectral endmembers, Kruse's multi-step process was applied to atmospherically and geometrically-corrected hyperspectral images. Minimum Noise Fraction was used to reduce the spectral dimensions and isolate noise in the images. Extreme pixels were identified from high order MNF bands using the Pixel Purity Index. n-Dimensional Visualization was utilized for unique pixel identification. Spectral similarities between pixel spectral signatures and known endmember spectrum (USGS Spectral Library) were compared with Spectral Angle Mapper Classification. EO-1 Hyperion hyperspectral images and hyperspectral analysis are sensitive to hydrothermal alteration minerals, as their diagnostic spectral signatures span the visible and shortwave
Dsm Based Orientation of Large Stereo Satellite Image Blocks
d'Angelo, P.; Reinartz, P.
2012-07-01
High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.
Quantitative analysis of geomorphic processes using satellite image data at different scales
Williams, R. S., Jr.
1985-01-01
When aerial and satellite photographs and images are used in the quantitative analysis of geomorphic processes, either through direct observation of active processes or by analysis of landforms resulting from inferred active or dormant processes, a number of limitations in the use of such data must be considered. Active geomorphic processes work at different scales and rates. Therefore, the capability of imaging an active or dormant process depends primarily on the scale of the process and the spatial-resolution characteristic of the imaging system. Scale is an important factor in recording continuous and discontinuous active geomorphic processes, because what is not recorded will not be considered or even suspected in the analysis of orbital images. If the geomorphic process of landform change caused by the process is less than 200 m in x to y dimension, then it will not be recorded. Although the scale factor is critical, in the recording of discontinuous active geomorphic processes, the repeat interval of orbital-image acquisition of a planetary surface also is a consideration in order to capture a recurring short-lived geomorphic process or to record changes caused by either a continuous or a discontinuous geomorphic process.
Kamangir, H.; Momeni, M.; Satari, M.
2017-09-01
This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.
Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.
2007-01-01
Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. ...
Technical and cost advantages of silicon carbide telescopes for small-satellite imaging applications
Kasunic, Keith J.; Aikens, Dave; Szwabowski, Dean; Ragan, Chip; Tinker, Flemming
2017-09-01
Small satellites ("SmallSats") are a growing segment of the Earth imaging and remote sensing market. Designed to be relatively low cost and with performance tailored to specific end-use applications, they are driving changes in optical telescope assembly (OTA) requirements. OTAs implemented in silicon carbide (SiC) provide performance advantages for space applications but have been predominately limited to large programs. A new generation of lightweight and thermally-stable designs is becoming commercially available, expanding the application of SiC to small satellites. This paper reviews the cost and technical advantages of an OTA designed using SiC for small satellite platforms. Taking into account faceplate fabrication quilting and surface distortion after gravity release, an optimized open-back SiC design with a lightweighting of 70% for a 125-mm SmallSat-class primary mirror has an estimated mass area density of 2.8 kg/m2 and an aspect ratio of 40:1. In addition, the thermally-induced surface error of such optimized designs is estimated at λ/150 RMS per watt of absorbed power. Cost advantages of SiC include reductions in launch mass, thermal-management infrastructure, and manufacturing time based on allowable assembly tolerances.
Lal, Swapnil; Zheng, Zhaoyu; Pavlov, Julius; Attygalle, Athula B
2018-05-23
Singly charged As2n+1 ion clusters (n = 2-11) were generated from elemental arsenic by negative-ion laser-ablation mass spectrometry. The overall abundance of the gaseous As ions generated upon laser irradiation was enhanced nearly a hundred times when As-bearing samples were admixed with sulfur. However, sulfur does not act purely as an inert matrix: irradiating arsenic-sulfur mixtures revealed a novel pathway to generate and detect a series of [AsSn]- clusters (n = 2-6). Intriguingly, the spectra recorded from As2O3, NaAsO2, Na3AsO4, cacodylic acid and 3-amino-4-hydroxyphenylarsonic acid together with sulfur as the matrix were remarkably similar to that acquired from an elemental arsenic and sulfur mixture. This result indicated that arsenic sulfide cluster-ions are generated directly from arsenic compounds by a hitherto unknown pathway. The mechanism of elemental sulfur extracting chemically bound arsenic from compounds and forming [AsSn]- clusters is enigmatic; however, this discovery has a practical value as a general detection method for arsenic compounds. For example, the method was employed for the detection of As in its minerals, and for the imaging of arsenic distribution in minerals such as domeykite. LDI-MS data recorded from a latent image imprinted on a piece of paper from a flat mineral surface, and wetting the paper with a solution of sulfur, enabled the localization of arsenic in the mineral. The distribution of As was visualized as false-color images by extracting from acquired data the relative intensities of m/z 139 (AsS2-) and m/z 171 (AsS3-) ions.
Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe
2012-01-01
Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived
Directory of Open Access Journals (Sweden)
Miodrag D. Regodić
2010-10-01
Full Text Available Neažurnost sadržaja topografskih karata (TK, uslovljena ponajviše stvarnim ekonomskim teškoćama pri izradi novih i dopuni postojećih izdanja, kao i nedovoljnost i sve teže stanje pri izradi ostalih geotopografskih materijala (GTM, u velikoj meri otežavaju geotopografsko obezbeđenje (GTOb vojske u miru, kao i u svim periodima pripreme i vođenja ratnih dejstava. Rešenje ovog problema je u iznalaženju adekvatnog načina upotrebe proizvoda svih vrsta daljinskih snimanja, a naročito u obradi kvalitetnih satelitskih snimaka. Kao najbolji pokazatelj velikih mogućnosti daljinske detekcije, korišćenjem satelitskih snimaka, u kartografskoj praksi primenom kvalitetnih softverskih rešenja, u radu je predstavljena dopuna topografske karte nedostajućim topografskim sadržajem. / Lack of updated content of topographic maps (TMs, mainly due to economic issues regarding the publishing of existing or revised TMs, substantially affects geo-topographic supply (GTS of the Army both in peace and warfare time, as well as shortage of other geo-topographic materials (GTMs. The solution to this problem is in finding an appropriate method of using products of all types of remote sensing, high quality satellite images in particular. Having shown the best possibilities of remote sensing while using satellite images in mapping through the quality software solutions, the author presents an addition to topographic maps based on missing topographic data. Introduction Numerous natural and social phenomena are constantly observed, surveyed, registered and analyzed. Permanent or periodical satellite surveillance and recording for different purposes are growing in importance. The purposes can range from meteorological issues, through study of large water surfaces to military intelligence, etc. These recording can be used in making topographic, thematic and working maps as well as other geo-topographic material. Processing and analyzing of ikonos2 satellite images
TESIS experiment on XUV imaging spectroscopy of the Sun onboard the CORONAS-PHOTON satellite
Kuzin, S. V.; Zhitnik, I. A.; Bogachev, S. A.; Shestov, S. V.; Bugaenko, O. I.; Suhodrev, N. K.; Pertsov, A. A.; Mitrofanov, A. V.; Ignat'ev, A. P.; Slemzin, V. A.
We present a brief description of new complex of space telescopes and spectrographs, TESIS, which will be placed aboard the CORONAS-PHOTON satellite. The complex is intended for high-resolution imaging observation of full Sun in the coronal spectral lines and in the spectral lines of the solar transition region. TESIS will be launched at the end of 2007 - early of 2008. About 25 % of the daily TESIS images will be free for use and for downloading from the TESIS data center that is planned to open 2 months before the TESIS launching at http://www.tesis.lebedev.ru
Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming
Benzouai, Siham; Smara, Youcef
2010-12-01
The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.
Energy Technology Data Exchange (ETDEWEB)
Ramirez Santigosa, L.; Mora Lopez, L.; Sidrach de Cardona Ortin, M.; Navarro Fernandez, A. A.; Varela conde, M.; Cruz Echeandia, M. de la
2003-07-01
In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been revaluate to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar,impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyranometric measures in a concrete localise, but it provides a very valid indicator in places in which, it not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs.
Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.
2018-04-01
Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.
Simulation of seagrass bed mapping by satellite images based on the radiative transfer model
Sagawa, Tatsuyuki; Komatsu, Teruhisa
2015-06-01
Seagrass and seaweed beds play important roles in coastal marine ecosystems. They are food sources and habitats for many marine organisms, and influence the physical, chemical, and biological environment. They are sensitive to human impacts such as reclamation and pollution. Therefore, their management and preservation are necessary for a healthy coastal environment. Satellite remote sensing is a useful tool for mapping and monitoring seagrass beds. The efficiency of seagrass mapping, seagrass bed classification in particular, has been evaluated by mapping accuracy using an error matrix. However, mapping accuracies are influenced by coastal environments such as seawater transparency, bathymetry, and substrate type. Coastal management requires sufficient accuracy and an understanding of mapping limitations for monitoring coastal habitats including seagrass beds. Previous studies are mainly based on case studies in specific regions and seasons. Extensive data are required to generalise assessments of classification accuracy from case studies, which has proven difficult. This study aims to build a simulator based on a radiative transfer model to produce modelled satellite images and assess the visual detectability of seagrass beds under different transparencies and seagrass coverages, as well as to examine mapping limitations and classification accuracy. Our simulations led to the development of a model of water transparency and the mapping of depth limits and indicated the possibility for seagrass density mapping under certain ideal conditions. The results show that modelling satellite images is useful in evaluating the accuracy of classification and that establishing seagrass bed monitoring by remote sensing is a reliable tool.
Duval, Joseph S.
1985-01-01
Because the display and interpretation of satellite and aircraft remote-sensing data make extensive use of color film products, accurate reproduction of the color images is important. To achieve accurate color reproduction, the exposure and chemical processing of the film must be monitored and controlled. By using a combination of sensitometry, densitometry, and transfer functions that control film response curves, all of the different steps in the making of film images can be monitored and controlled. Because a sensitometer produces a calibrated exposure, the resulting step wedge can be used to monitor the chemical processing of the film. Step wedges put on film by image recording machines provide a means of monitoring the film exposure and color balance of the machines.
GUST86 - An analytical ephemeris of the Uranian satellites. [General Uranus Satellite Theory
Laskar, J.; Jacobson, R. A.
1987-01-01
The General Uranus Satellite Theory GUST (Laskar, 1986) is used for the construction of an analytical ephemeris for the Uranian satellites. The theory is fitted against earth-based observations from 1911 to 1986, and all radio and optical data obtained during Voyager encounter with Uranus. Earth-based observations alone allow the determination of masses which are within 15 percent of the values determined by the Uranus flyby. The analysis of all the observations confirm the values of the masses obtained during the encounter (Stone and Miner, 1986) and give a complete set of dynamical parameters for the analytical theory. An analytical ephemeris, GUST86, with an estimated precision of about 100 km with respect to Uranus is obtained.
Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman
2018-06-01
Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.
Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.
2017-12-01
The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.
Extracting oil palm crown from WorldView-2 satellite image
Korom, A.; Phua, M.-H.; Hirata, Y.; Matsuura, T.
2014-02-01
Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1').
Extracting oil palm crown from WorldView-2 satellite image
International Nuclear Information System (INIS)
Korom, A; Phua, M-H; Hirata, Y; Matsuura, T
2014-01-01
Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1')
Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response
Niu, X. N.; Tang, H.; Wu, L. X.
2018-04-01
an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.
Budakoǧlu, Murat; Karaman, Muhittin; Damla Uça Avcı, Z.; Kumral, Mustafa; Geredeli (Yılmaz), Serpil
2014-05-01
Salinity of a lake is an important characteristic since, these are potentially industrial lakes and the degree of salinity can significantly be used for determination of mineral resources and for the production management. In the literature, there are many studies of using satellite data for salinity related lake studies such as determination of salinity distribution and detection of potential freshwater sources in less salt concentrated regions. As the study area Lake Acigol, located in Denizli (Turkey) was selected. With it's saline environment, it's the major sodium sulphate production resource of Turkey. In this study, remote sensing data and data from a field study was used and correlated. Remote sensing is an efficient tool to monitor and analyze lake properties by using it complementary to field data. Worldview-2 satellite data was used in this study which consists of 8 bands. At the same time with the satellite data acquisition, a field study was conducted to collect the salinity values in 17 points of the laker with using YSI 556 Multiparametre for measurements. The values were measured as salinity amount in grams per kilogram solution and obtained as ppt unit. It was observed that the values vary from 34 ppt - 40.1 ppt and the average is 38.056 ppt. In Thalassic serie, the lake was in mixoeuhaline state in the time of issue. As a first step, ATCOR correction was performed on satellite image for atmospheric correction. There were some clouds on the lake field, hence it was decided to continue the study by using the 12 sampling points which were clear on the image. Then, for each sampling point, a spectral value was obtained by calculating the average at a 11*11 neighborhood. The relation between the spectral reflectance values and the salinity was investigated. The 4-band algorithm, which was used for determination of chlorophyll-a distribution in highly turbid coastal environment by Wei (2012) was applied. Salinity α (Λi-1 / Λj-1) * (Λk-1 / Λm-1) (i
Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René
2018-03-01
Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.
Assessment of different topographic corrections in AWiFS satellite ...
Indian Academy of Sciences (India)
Snow and Avalanche Study Establishment, Defence Research and Development Organisation,. Chandigarh 160 ... IRS P6 satellite images and the qualitative and quantitative comparative analysis in detail. Both .... Top: AWiFS satellite image of Western Himalaya and bottom: zoom image of the study area shown with white.
Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.
2015-12-01
Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively
Development of a Lyman-α Imaging Solar Telescope for the Satellite
Directory of Open Access Journals (Sweden)
M. Jang
2005-09-01
Full Text Available Long term observations of full-disk Lyman-α irradiance have been made by the instruments on various satellites. In addition, several sounding rockets dating back to the 1950s and up through the present have measured the Lyman-α irradiance. Previous full disk Lyman-α images of the sun have been very interesting and useful scientifically, but have been only five-minute ``snapshots" obtained on sounding rocket flights. All of these observations to date have been snapshots, with no time resolution to observe changes in the chromospheric structure as a result of the evolving magnetic field, and its effect on the Lyman-α intensity. The Lyman-α Imaging Solar Telescope(LIST can provide a unique opportunity for the study of the sun in the Lyman-α region with the high time and spatial resolution for the first time. Up to the 2nd year development, the preliminary design of the optics, mechanical structure and electronics system has been completed. Also the mechanical structure analysis, thermal analysis were performed and the material for the structure was chosen as a result of these analyses. And the test plan and the verification matrix were decided. The operation systems, technical and scientific operation, were studied and finally decided. Those are the technical operation, mechanical working modes for the observation and safety, the scientific operation and the process of the acquired data. The basic techniques acquired through the development of satellite based solar telescope are essential for the construction of space environment forecast system in the future. The techniques which we developed through this study, like mechanical, optical and data processing techniques, could be applied extensively not only to the process of the future production of flight models of this kind, but also to the related industries. Also, we can utilize the scientific achievements which are obtained throughout the project. And these can be utilized to build a high
Directory of Open Access Journals (Sweden)
Hassan Mohamed
2018-05-01
Full Text Available Benthic habitat monitoring is essential for many applications involving biodiversity, marine resource management, and the estimation of variations over temporal and spatial scales. Nevertheless, both automatic and semi-automatic analytical methods for deriving ecologically significant information from towed camera images are still limited. This study proposes a methodology that enables a high-resolution towed camera with a Global Navigation Satellite System (GNSS to adaptively monitor and map benthic habitats. First, the towed camera finishes a pre-programmed initial survey to collect benthic habitat videos, which can then be converted to geo-located benthic habitat images. Second, an expert labels a number of benthic habitat images to class habitats manually. Third, attributes for categorizing these images are extracted automatically using the Bag of Features (BOF algorithm. Fourth, benthic cover categories are detected automatically using Weighted Majority Voting (WMV ensembles for Support Vector Machines (SVM, K-Nearest Neighbor (K-NN, and Bagging (BAG classifiers. Fifth, WMV-trained ensembles can be used for categorizing more benthic cover images automatically. Finally, correctly categorized geo-located images can provide ground truth samples for benthic cover mapping using high-resolution satellite imagery. The proposed methodology was tested over Shiraho, Ishigaki Island, Japan, a heterogeneous coastal area. The WMV ensemble exhibited 89% overall accuracy for categorizing corals, sediments, seagrass, and algae species. Furthermore, the same WMV ensemble produced a benthic cover map using a Quickbird satellite image with 92.7% overall accuracy.
Zahra Afshooni, Seyedeh; Esmaeily, Dariush
2010-05-01
Kahang ore deposit located in 73 km to the northeast of Isfahan city and 10 km to the east of Zefreh town, covering an area about 18.6 km2. This ore deposit is a part of Uromieh-Dokhtar volcanopolotonic belt. The rocks of the area included Andesite, Porphyritic Andesite, Dacite, Porphyritic, Rhyodacite, Diorite, Quartz Monzonite and Porphyry Micro Granite. In plutons, there is a trend from basic to acid features along with decreasing of age from margin to center of massive. Kahang region is an alteration and breccia zone. The occurrence of alteration zones and iron oxides were confirmed by satellite images processing. Generally, more than 90% of rocks of this region have been affected by hydrothermal fluids. Remote sensing refers to detection and measurement from a distance. For the first time, this exploration area was studied using satellite images processing (TM) and primary results showed that is suitable place for resources of Copper (Cu) and Molybdenum (Mo). Hydrothermal alteration commonly occurs in geothermal areas in association with ore deposits producing alteration assemblages typically dominated by silicates, sulfides, sulfates and carbonates. In the alteration zones studies the subject discussed is the study of existing minerals in such zones and study of chemical specifications of altering fluids. Four alteration zones Based on observations derived from the study of thin sections, XRD analysis and deep remote sensing using TM and Aster satellite images studies could be identified in this area: propylitic alteration zone with chlorite, epidot, calcite; argillic alteration zone with clay minerals; phyllic (qartz-sericite) alteration zone with quartz, sericite and pyrite and silicic alteration zone with abundant quartz.
Seagrass mapping in Greek territorial waters using Landsat-8 satellite images
Topouzelis, Konstantinos; Makri, Despina; Stoupas, Nikolaos; Papakonstantinou, Apostolos; Katsanevakis, Stelios
2018-05-01
Seagrass meadows are among the most valuable coastal ecosystems on earth due to their structural and functional roles in the coastal environment. This study demonstrates remote sensing's capacity to produce seagrass distribution maps on a regional scale. The seagrass coverage maps provided here describe and quantify for the first time the extent and the spatial distribution of seagrass meadows in Greek waters. This information is needed for identifying priority conservation sites and to help coastal ecosystem managers and stakeholders to develop conservation strategies and design a resilient network of protected marine areas. The results were based on an object-based image analysis of 50 Landsat-8 satellite images. The time window of image acquisition was between June 2013 and July 2015. In total, the seagrass coverage in Greek waters was estimated at 2619 km2. The largest coverages of individual seagrass meadows were found around Lemnos Island (124 km2), Corfu Island (46 km2), and East Peloponnese (47 km2). The accuracy assessment of the detected areas was based on 62 Natura 2000 sites, for which habitat maps were available. The mean total accuracy for all 62 sites was estimated at 76.3%.
Satellite Images-Based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles
Directory of Open Access Journals (Sweden)
Mehmet Bodur
2015-12-01
Full Text Available In this study, a method for the generation of tracking trajectory points, detection and positioning of obstacles in agricultural fields have been presented. Our principal contribution is to produce traceable GPS trajectories for agricultural vehicles to be utilized by path planning algorithms, rather than a new path planning algorithm. The proposed system works with minimal initialization requirements, specifically, a single geographical coordinate entry of an agricultural field. The automation of agricultural plantation requires many aspects to be addressed, many of which have been covered in previous studies. Depending on the type of crop, different agricultural vehicles may be used in the field. However, regardless of their application, they all follow a specified trajectory in the field. This study takes advantage of satellite images for the detection and positioning of obstacles, and the generation of GPS trajectories in the agricultural realm. A set of image processing techniques is applied in Matlab for detection and positioning.
Galileo's first images of Jupiter and the Galilean satellites
Belton, M.J.S.; Head, J. W.; Ingersoll, A.P.; Greeley, R.; McEwen, A.S.; Klaasen, K.P.; Senske, D.; Pappalardo, R.; Collins, G.; Vasavada, A.R.; Sullivan, R.; Simonelli, D.; Geissler, P.; Carr, M.H.; Davies, M.E.; Veverka, J.; Gierasch, P.J.; Banfield, D.; Bell, M.; Chapman, C.R.; Anger, C.; Greenberg, R.; Neukum, G.; Pilcher, C.B.; Beebe, R.F.; Burns, J.A.; Fanale, F.; Ip, W.; Johnson, T.V.; Morrison, D.; Moore, J.; Orton, G.S.; Thomas, P.; West, R.A.
1996-01-01
The first images of Jupiter, Io, Europa, and Ganymede from the Galileo spacecraft reveal new information about Jupiter's Great Red Spot (GRS) and the surfaces of the Galilean satellites. Features similar to clusters of thunderstorms were found in the GRS. Nearby wave structures suggest that the GRS may be a shallow atmospheric feature. Changes in surface color and plume distribution indicate differences in resurfacing processes near hot spots on lo. Patchy emissions were seen while Io was in eclipse by Jupiter. The outer margins of prominent linear markings (triple bands) on Europa are diffuse, suggesting that material has been vented from fractures. Numerous small circular craters indicate localized areas of relatively old surface. Pervasive brittle deformation of an ice layer appears to have formed grooves on Ganymede. Dark terrain unexpectedly shows distinctive albedo variations to the limit of resolution.
Ortolano, Gaetano; Visalli, Roberto; Godard, Gaston; Cirrincione, Rosolino
2018-06-01
We present a new ArcGIS®-based tool developed in the Python programming language for calibrating EDS/WDS X-ray element maps, with the aim of acquiring quantitative information of petrological interest. The calibration procedure is based on a multiple linear regression technique that takes into account interdependence among elements and is constrained by the stoichiometry of minerals. The procedure requires an appropriate number of spot analyses for use as internal standards and provides several test indexes for a rapid check of calibration accuracy. The code is based on an earlier image-processing tool designed primarily for classifying minerals in X-ray element maps; the original Python code has now been enhanced to yield calibrated maps of mineral end-members or the chemical parameters of each classified mineral. The semi-automated procedure can be used to extract a dataset that is automatically stored within queryable tables. As a case study, the software was applied to an amphibolite-facies garnet-bearing micaschist. The calibrated images obtained for both anhydrous (i.e., garnet and plagioclase) and hydrous (i.e., biotite) phases show a good fit with corresponding electron microprobe analyses. This new GIS-based tool package can thus find useful application in petrology and materials science research. Moreover, the huge quantity of data extracted opens new opportunities for the development of a thin-section microchemical database that, using a GIS platform, can be linked with other major global geoscience databases.
Numerical investigation of debris materials prior to debris flow hazards using satellite images
Zhang, N.; Matsushima, T.
2018-05-01
The volume of debris flows occurred in mountainous areas is mainly affected by the volume of debris materials deposited at the valley bottom. Quantitative evaluation of debris materials prior to debris flow hazards is important to predict and prevent hazards. At midnight on 7th August 2010, two catastrophic debris flows were triggered by the torrential rain from two valleys in the northern part of Zhouqu City, NW China, resulting in 1765 fatalities and huge economic losses. In the present study, a depth-integrated particle method is adopted to simulate the debris materials, based on 2.5 m resolution satellite images. In the simulation scheme, the materials are modeled as dry granular solids, and they travel down from the slopes and are deposited at the valley bottom. The spatial distributions of the debris materials are investigated in terms of location, volume and thickness. Simulation results show good agreement with post-disaster satellite images and field observation data. Additionally, the effect of the spatial distributions of the debris materials on subsequent debris flows is also evaluated. It is found that the spatial distributions of the debris materials strongly influence affected area, runout distance and flow discharge. This study might be useful in hazard assessments prior to debris flow hazards by investigating diverse scenarios in which the debris materials are unknown.
Parida, P. K.; Sanabada, M. K.; Tripathi, S.
2014-11-01
Advancements in satellite sensor technology enabling capturing of geometrically accurate images of earth's surface coupled with DGPS/ETS and GIS technology holds the capability of large scale mapping of land resources at cadastral level. High Resolution Satellite Images depict field bunds distinctly. Thus plot parcels are to be delineated from cloud free ortho-images and obscured/difficult areas are to be surveyed using DGPS and ETS. The vector datasets thus derived through RS/DGPS/ETS survey are to be integrated in GIS environment to generate the base cadastral vector datasets for further settlement/title confirmation activities. The objective of this paper is to illustrate the efficacy of a hybrid methodology employed in Pitambarpur Sasana village under Digapahandi Tahasil of Ganjam district, as a pilot project, particularly in Odisha scenario where the land parcel size is very small. One of the significant observations of the study is matching of Cadastral map area i.e. 315.454 Acres, the image map area i.e. 314.887 Acres and RoR area i.e. 313.815 Acre. It was revealed that 79 % of plots derived by high-tech survey method show acceptable level of accuracy despite the fact that the mode of area measurement by ground and automated method has significant variability. The variations are more in case of Government lands, Temple/Trust lands, Common Property Resources and plots near to river/nalas etc. The study indicates that the adopted technology can be extended to other districts and cadastral resurvey and updating work can be done for larger areas of the country using this methodology.
Directory of Open Access Journals (Sweden)
Mateja Jemec
2008-12-01
Full Text Available Flash floods in Slovenia, which was exposed on September 18th 2007, demanded 6 lives, several thousand houses and over one thousand kilometres of roads were damaged and more also than 50 bridges. The highest amount of rain fell at west and north-west parts of Slovenia (northern Primorska region and southern Gorenjska region,from where heavy rain spread eastwards over the central Slovenia and in east part of Slovenia. In the article we focused on area of western and north-western part of Slovenia. The aim of present research was in the first phase to describe methodology to determine landslide occurrences from satellite images before and after natural disaster on Železniki region. Second phase was based on comparison of obtained results with the existing models for prediction of slope mass movements, and finally also to determine identificability of landslide types on a satellite image.Results have shown, that the highest part of obtaining area from supervised and unsupervised classification of satellite images, are comparable with classes of landslide susceptibility, where occurrences of landslide are largest.
Hansell, Richard Allen, Jr.
The radiative effects of dust aerosol on our climate system have yet to be fully understood and remain a topic of contemporary research. To investigate these effects, detection/retrieval methods for dust events over major dust outbreak and transport areas have been developed using satellite and ground-based approaches. To this end, both the shortwave and longwave surface radiative forcing of dust aerosol were investigated. The ground-based remote sensing approach uses the Atmospheric Emitted Radiance Interferometer brightness temperature spectra to detect mineral dust events and to retrieve their properties. Taking advantage of the high spectral resolution of the AERI instrument, absorptive differences in prescribed thermal IR window sub-band channels were exploited to differentiate dust from cirrus clouds. AERI data collected during the UAE2 at Al-Ain UAE was employed for dust retrieval. Assuming a specified dust composition model a priori and using the light scattering programs of T-matrix and the finite difference time domain methods for oblate spheroids and hexagonal plates, respectively, dust optical depths have been retrieved and compared to those inferred from a collocated and coincident AERONET sun-photometer dataset. The retrieved optical depths were then used to determine the dust longwave surface forcing during the UAE2. Likewise, dust shortwave surface forcing is investigated employing a differential technique from previous field studies. The satellite-based approach uses MODIS thermal infrared brightness temperature window data for the simultaneous detection/separation of mineral dust and cirrus clouds. Based on the spectral variability of dust emissivity at the 3.75, 8.6, 11 and 12 mum wavelengths, the D*-parameter, BTD-slope and BTD3-11 tests are combined to identify dust and cirrus. MODIS data for the three dust-laden scenes have been analyzed to demonstrate the effectiveness of this detection/separation method. Detected daytime dust and cloud
Livo, K. Eric; Clark, Roger N.
2002-01-01
This preliminary study for the First Quarterly Report has spectrally mapped hydrothermally altered minerals useful in assisting in assessment of water quality of the Red River. Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) data was analyzed to characterize mined and unmined ground at Questa, New Mexico. AVIRIS data covers the Red River drainage north of the river, from between the town of Questa on the west, to east of the town of Red River. The data was calibrated and analyzed using U.S. Geological Survey custom software and spectral mineral library. AVIRIS data was tested for spectral features that matched similar features in the spectral mineral library. Goodness-of-fit and band-depth were calculated for each comparison of spectral features and used to identify surface mineralogy. Mineral distribution, mineral associations, and AVIRIS pixel spectra were examined. Mineral maps show the distribution of iron hydroxides, iron sulfates, clays, micas, carbonates, and other minerals. Initial results show a system of alteration suites that overprint each other. Quartz-sericite-pyrite (QSP) alteration grading out to propylitic alteration (epidote and calcite) was identified at the Questa Mine (molybdenum porphyry) and a similar alteration pattern was mapped at the landslide (?scar?) areas. Supergene weathering overprints the altered rock, as shown by jarosite, kaolinite, and gypsum. In the spectral analysis, hydrothermally altered ground appears to be more extensive at the unmined Goat Hill Gulch and the mined ground, than the ?scars? to the east. Though the ?scars? have similar overall altered mineral suites, there are differences between the ?scars? in sericite, kaolinite, jarosite, gypsum, and calcite abundance. Fieldwork has verified the results at the central unmined ?scar? areas.
Looking at Earth from space: Direct readout from environmental satellites
1994-01-01
Direct readout is the capability to acquire information directly from meteorological satellites. Data can be acquired from NASA-developed, National Oceanic and Atmospheric Administration (NOAA)-operated satellites, as well as from other nations' meteorological satellites. By setting up a personal computer-based ground (Earth) station to receive satellite signals, direct readout may be obtained. The electronic satellite signals are displayed as images on the computer screen. The images can display gradients of the Earth's topography and temperature, cloud formations, the flow and direction of winds and water currents, the formation of hurricanes, the occurrence of an eclipse, and a view of Earth's geography. Both visible and infrared images can be obtained. This booklet introduces the satellite systems, ground station configuration, and computer requirements involved in direct readout. Also included are lists of associated resources and vendors.
Multispectral image enhancement processing for microsat-borne imager
Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin
2017-10-01
With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.
Abedi, Maysam; Norouzi, Gholam-Hossain
2016-04-01
This work presents the promising application of three variants of TOPSIS method (namely the conventional, adjusted and modified versions) as a straightforward knowledge-driven technique in multi criteria decision making processes for data fusion of a broad exploratory geo-dataset in mineral potential/prospectivity mapping. The method is implemented to airborne geophysical data (e.g. potassium radiometry, aeromagnetic and frequency domain electromagnetic data), surface geological layers (fault and host rock zones), extracted alteration layers from remote sensing satellite imagery data, and five evidential attributes from stream sediment geochemical data. The central Iranian volcanic-sedimentary belt in Kerman province at the SE of Iran that is embedded in the Urumieh-Dokhtar Magmatic Assemblage arc (UDMA) is chosen to integrate broad evidential layers in the region of prospect. The studied area has high potential of ore mineral occurrences especially porphyry copper/molybdenum and the generated mineral potential maps aim to outline new prospect zones for further investigation in future. Two evidential layers of the downward continued aeromagnetic data and its analytic signal filter are prepared to be incorporated in fusion process as geophysical plausible footprints of the porphyry type mineralization. The low values of the apparent resistivity layer calculated from the airborne frequency domain electromagnetic data are also used as an electrical criterion in this investigation. Four remote sensing evidential layers of argillic, phyllic, propylitic and hydroxyl alterations were extracted from ASTER images in order to map the altered areas associated with porphyry type deposits, whilst the ETM+ satellite imagery data were used as well to map iron oxide layer. Since potassium alteration is generally the mainstay of porphyry ore mineralization, the airborne potassium radiometry data was used. The geochemical layers of Cu/B/Pb/Zn elements and the first component of PCA
Aslett, Zan; Taranik, James V.; Riley, Dean N.
2018-02-01
Aerial spatially enhanced broadband array spectrograph system (SEBASS) long-wave infrared (LWIR) hyperspectral image data were used to map the distribution of rock-forming minerals indicative of sedimentary and meta-sedimentary lithologies around Boundary Canyon, Death Valley, California, USA. Collection of data over the Boundary Canyon detachment fault (BCDF) facilitated measurement of numerous lithologies representing a contact between the relatively unmetamorphosed Grapevine Mountains allochthon and the metamorphosed core complex of the Funeral Mountains autochthon. These included quartz-rich sandstone, quartzite, conglomerate, and alluvium; muscovite-rich schist, siltstone, and slate; and carbonate-rich dolomite, limestone, and marble, ranging in age from late Precambrian to Quaternary. Hyperspectral data were reduced in dimensionality and processed to statistically identify and map unique emissivity spectra endmembers. Some minerals (e.g., quartz and muscovite) dominate multiple lithologies, resulting in a limited ability to differentiate them. Abrupt variations in image data emissivity amongst pelitic schists corresponded to amphibolite; these rocks represent gradation from greenschist- to amphibolite-metamorphic facies lithologies. Although the full potential of LWIR hyperspectral image data may not be fully utilized within this study area due to lack of measurable spectral distinction between rocks of similar bulk mineralogy, the high spectral resolution of the image data was useful in characterizing silicate- and carbonate-based sedimentary and meta-sedimentary rocks in proximity to fault contacts, as well as for interpreting some mineral mixtures.
CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE
Directory of Open Access Journals (Sweden)
K.-Y. Lee
2016-06-01
Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate
Cloud Detection of Optical Satellite Images Using Support Vector Machine
Lee, Kuan-Yi; Lin, Chao-Hung
2016-06-01
Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection
PRELIMINARY RESULTS OF THE COMPARISON OF SATELLITE IMAGERS USING TUZ GÖLÜ AS A REFERENCE STANDARD
Directory of Open Access Journals (Sweden)
H. Özen
2012-07-01
Full Text Available Earth surfaces, such as deserts, salt lakes, and playas, have been widely used in the vicarious radiometric calibration of optical earth observation satellites. In 2009, the Infrared and Visible Optical Sensors (IVOS sub-group of the Committee of Earth Observation Satellites (CEOS Working Group on Calibration and Validation (WGCV designated eight LANDNET reference sites to focus international efforts, facilitate traceability and enable the establishment of measurement "best practices." With support from the European Space Agency (ESA, one of the LANDNET sites, the Tuz Gölü salt lake located in central Turkey, was selected to host a cross-comparison of measurement instrumentation and methodologies conducted by 11 different ground teams across the globe. This paper provides an overview of the preliminary results of the cross-comparison of the ground-based spectral measurements made during the CEOS Land Comparison 13-27 August, 2010 with the simultaneous satellite image data acquisitions of the same site.
International Nuclear Information System (INIS)
Moester, Martiene J.C.; Schoeman, Monique A.E.; Oudshoorn, Ineke B.; Beusekom, Mara M. van; Mol, Isabel M.; Kaijzel, Eric L.; Löwik, Clemens W.G.M.; Rooij, Karien E. de
2014-01-01
Highlights: •We validate a simple and fast method of quantification of in vitro mineralization. •Fluorescently labeled agents can detect calcium deposits in the mineralized matrix of cell cultures. •Fluorescent signals of the probes correlated with Alizarin Red S staining. -- Abstract: Alizarin Red S staining is the standard method to indicate and quantify matrix mineralization during differentiation of osteoblast cultures. KS483 cells are multipotent mouse mesenchymal progenitor cells that can differentiate into chondrocytes, adipocytes and osteoblasts and are a well-characterized model for the study of bone formation. Matrix mineralization is the last step of differentiation of bone cells and is therefore a very important outcome measure in bone research. Fluorescently labelled calcium chelating agents, e.g. BoneTag and OsteoSense, are currently used for in vivo imaging of bone. The aim of the present study was to validate these probes for fast and simple detection and quantification of in vitro matrix mineralization by KS483 cells and thus enabling high-throughput screening experiments. KS483 cells were cultured under osteogenic conditions in the presence of compounds that either stimulate or inhibit osteoblast differentiation and thereby matrix mineralization. After 21 days of differentiation, fluorescence of stained cultures was quantified with a near-infrared imager and compared to Alizarin Red S quantification. Fluorescence of both probes closely correlated to Alizarin Red S staining in both inhibiting and stimulating conditions. In addition, both compounds displayed specificity for mineralized nodules. We therefore conclude that this method of quantification of bone mineralization using fluorescent compounds is a good alternative for the Alizarin Red S staining
Energy Technology Data Exchange (ETDEWEB)
Moester, Martiene J.C. [Department of Radiology, Leiden University Medical Center (Netherlands); Schoeman, Monique A.E. [Department of Orthopedic Surgery, Leiden University Medical Center (Netherlands); Oudshoorn, Ineke B. [Department of Radiology, Leiden University Medical Center (Netherlands); Percuros BV, Leiden (Netherlands); Beusekom, Mara M. van [Department of Radiology, Leiden University Medical Center (Netherlands); Mol, Isabel M. [Department of Radiology, Leiden University Medical Center (Netherlands); Percuros BV, Leiden (Netherlands); Kaijzel, Eric L.; Löwik, Clemens W.G.M. [Department of Radiology, Leiden University Medical Center (Netherlands); Rooij, Karien E. de, E-mail: k.e.de_rooij@lumc.nl [Department of Radiology, Leiden University Medical Center (Netherlands); Percuros BV, Leiden (Netherlands)
2014-01-03
Highlights: •We validate a simple and fast method of quantification of in vitro mineralization. •Fluorescently labeled agents can detect calcium deposits in the mineralized matrix of cell cultures. •Fluorescent signals of the probes correlated with Alizarin Red S staining. -- Abstract: Alizarin Red S staining is the standard method to indicate and quantify matrix mineralization during differentiation of osteoblast cultures. KS483 cells are multipotent mouse mesenchymal progenitor cells that can differentiate into chondrocytes, adipocytes and osteoblasts and are a well-characterized model for the study of bone formation. Matrix mineralization is the last step of differentiation of bone cells and is therefore a very important outcome measure in bone research. Fluorescently labelled calcium chelating agents, e.g. BoneTag and OsteoSense, are currently used for in vivo imaging of bone. The aim of the present study was to validate these probes for fast and simple detection and quantification of in vitro matrix mineralization by KS483 cells and thus enabling high-throughput screening experiments. KS483 cells were cultured under osteogenic conditions in the presence of compounds that either stimulate or inhibit osteoblast differentiation and thereby matrix mineralization. After 21 days of differentiation, fluorescence of stained cultures was quantified with a near-infrared imager and compared to Alizarin Red S quantification. Fluorescence of both probes closely correlated to Alizarin Red S staining in both inhibiting and stimulating conditions. In addition, both compounds displayed specificity for mineralized nodules. We therefore conclude that this method of quantification of bone mineralization using fluorescent compounds is a good alternative for the Alizarin Red S staining.
Arabian Red Sea coastal soils as potential mineral dust sources
Prakash, P. Jish
2016-09-26
Both Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) satellite observations suggest that the narrow heterogeneous Red Sea coastal region is a frequent source of airborne dust that, because of its proximity, directly affects the Red Sea and coastal urban centers. The potential of soils to be suspended as airborne mineral dust depends largely on soil texture, moisture content and particle size distributions. Airborne dust inevitably carries the mineralogical and chemical signature of a parent soil. The existing soil databases are too coarse to resolve the small but important coastal region. The purpose of this study is to better characterize the mineralogical, chemical and physical properties of soils from the Arabian Red Sea coastal plain, which in turn will help to improve assessment of dust effects on the Red Sea, land environmental systems and urban centers. Thirteen surface soils from the hot-spot areas of windblown mineral dust along the Red Sea coastal plain were sampled for analysis. Analytical methods included optical microscopy, X-ray diffraction (XRD), inductively coupled plasma optical emission spectrometry (ICP-OES), ion chromatography (IC), scanning electron microscopy (SEM) and laser particle size analysis (LPSA). We found that the Red Sea coastal soils contain major components of quartz and feldspar, as well as lesser but variable amounts of amphibole, pyroxene, carbonate, clays and micas, with traces of gypsum, halite, chlorite, epidote and oxides. The range of minerals in the soil samples was ascribed to the variety of igneous and metamorphic provenance rocks of the Arabian Shield forming the escarpment to the east of the Red Sea coastal plain. The analysis revealed that the samples contain compounds of nitrogen, phosphorus and iron that are essential nutrients to marine life. The analytical results from this study will provide a valuable input into dust emission models used in climate
Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad
2018-06-01
Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.
Strengthening IAEA safeguards using high-resolution commercial satellite imagery
International Nuclear Information System (INIS)
Zhang Hui
2001-01-01
Full text: In May 1997, the IAEA Board of Governors adopted the Additional Safeguards Protocol to improve its ability to detect the undeclared production of fissile material. This new strengthened safeguards system has opened the door for the IAEA to use of all types of information, including the potential use of commercial satellite imagery. We have therefore been investigating the feasibility of strengthening IAEA safeguards using commercial satellite imagery. Based on our analysis on a number of one-meter resolution IKONOS satellite images of military nuclear production facilities at nuclear states including Russia, China, India, Pakistan and Israel, we found that the new high-resolution commercial satellite imagery would play a new and valuable role in strengthening IAEA safeguards. Since 1999, images with a resolution of one meter have been available commercially from Space Imaging's IKONOS satellite. One-meter images from other companies are expected to enter the market soon. Although still an order of magnitude less capable than military imaging satellites, the capabilities of these new high-resolution commercial satellites are good enough to detect and identify the major visible characteristics of nuclear production facilities and sites. Unlike the classified spy satellite photos limited to few countries, the commercial satellite imagery is commercially available to anyone who wants to purchase it. Therefore, the new commercial satellite open a new chance that each state, international organizations, and non-governmental groups could use the commercial images to play a more proactive role in monitoring the nuclear activities in related countries and verifying the compliance of non-proliferation agreements. This could help galvanize support for intensified efforts to slow the pace of nuclear proliferation. To produce fissile materials (plutonium and highly enriched uranium) for weapons, a country would operate dedicated plutonium-production reactors and the
Utilization of satellite images to understand the dynamics of Pampas shallow lakes
Directory of Open Access Journals (Sweden)
V. S. Aliaga
2016-06-01
Full Text Available The aim of this study was to analyze satellite images of different spatial resolutions to interpret the morphometric behavior of six shallow lakes of the Pampas, Argentina. These are characterized by having different rainfall regimes. Morphometric response considering each location, site conditions and dry and wet extreme events is analyzed. Standardized Precipitation Index (IEP for determination of wet, dry and normal years was used. This analysis showed that the Pampas shallow lakes do not behave in the same way to the rainfall events. Its origin, socio-economic use and rainfall patterns affect their spatiotemporal variation and morphometric.
Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.
2015-04-01
To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is
Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.
2008-07-01
SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.
JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis
Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.
2016-12-01
The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating
International Nuclear Information System (INIS)
Linares-Rodriguez, Alvaro; Ruiz-Arias, José Antonio; Pozo-Vazquez, David; Tovar-Pescador, Joaquin
2013-01-01
An optimized artificial neural network ensemble model is built to estimate daily global solar radiation over large areas. The model uses clear-sky estimates and satellite images as input variables. Unlike most studies using satellite imagery based on visible channels, our model also exploits all information within infrared channels of the Meteosat 9 satellite. A genetic algorithm is used to optimize selection of model inputs, for which twelve are selected – eleven 3-km Meteosat 9 channels and one clear-sky term. The model is validated in Andalusia (Spain) from January 2008 through December 2008. Measured data from 83 stations across the region are used, 65 for training and 18 independent ones for testing the model. At the latter stations, the ensemble model yields an overall root mean square error of 6.74% and correlation coefficient of 99%; the generated estimates are relatively accurate and errors spatially uniform. The model yields reliable results even on cloudy days, improving on current models based on satellite imagery. - Highlights: • Daily solar radiation data are generated using an artificial neural network ensemble. • Eleven Meteosat channels observations and a clear sky term are used as model inputs. • Model exploits all information within infrared Meteosat channels. • Measured data for a year from 83 ground stations are used. • The proposed approach has better performance than existing models on daily basis
Classification Of Cluster Area Forsatellite Image
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Thwe Zin Phyo
2015-06-01
Full Text Available Abstract This paper describes area classification for Landsat7 satellite image. The main purpose of this system is to classify the area of each cluster contained in a satellite image. To classify this image firstly need to clusterthe satellite image into different land cover types. Clustering is an unsupervised learning method that aimsto classify an image into homogeneous regions. This system is implemented based on color features with K-means clustering unsupervised algorithm. This method does not need to train image before clustering.The clusters of satellite image are grouped into a set of three clusters for Landsat7 satellite image. For this work the combined band 432 from Landsat7 satellite is used as an input. Satellite imageMandalay area in 2001 is chosen to test the segmentation method. After clustering a specific range for three clustered images must be defined in order to obtain greenland water and urbanbalance.This system is implemented by using MATLAB programming language.
Niazmardi, S.; Safari, A.; Homayouni, S.
2017-09-01
Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.
Ring structures and copper mineralization in Kerman porphyry copper belt, SE Iran
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Gholamreza Mirzababaei
2012-10-01
Full Text Available The role of some ring structures in the distribution of porphyry copper deposits in south Kerman porphyry copper belt is discussed. In the study area, ring structures are circular or elliptical shaped features which are partly recognized on satellite images. In this study, Landsat multispectral images were used to identify ring structures in the area. The rudimentary identification stages of the circles were mainly based on their circular characteristics on the images. These structures match with the regional tectonic features and can be seen mainly in two types; namely, large-magnitude and small scale circles. The associated mineralization in the study area is mainly porphyry Cu and vein type base metal sulfide deposits. There is a sensible relationship between the large circles and mineralization. These circles have encompassed almost entire Cu deposits and prospects in south part of Kerman porphyry copper belt. The small circles seem to be external traces of (porphyritic intrusive bodies that appear on surface as small circles. Formation of the large circular structures do not appear to be related to the external processes and there is no clear indication of how they came into existence but, their arrangement around the edges of a positive residual anomaly area shows the probable role of this anomaly in their formation. This matter is also recognized on the generalized crustal thickness map of the region in which an updoming of the upper mantle is observed. This study can improve our collective knowledge for copper exploration in this region.
International Nuclear Information System (INIS)
Riano M, Orlando
2002-01-01
In this article the considerations and methods are presented for the changes detection in the earth covering, using two images Landsat TM of different dates for an area of the municipality of Paipa, Boyaca. The changes detection has become an important application of the multi-spectral data and multi-temporal of the satellites programs for studies of natural resources Landsat, TM and Spot, in such a way that is possible to determine the types and extension of the changes that are given in the environment. To carry out this process some digital techniques they have been used for changes detection, such as: images superposition, differences between images and analysis of main components. These techniques allowed to observe and to analyze changes in the use and covering of the earth in this municipality
Mozgovoy, Dmitry k.; Hnatushenko, Volodymyr V.; Vasyliev, Volodymyr V.
2018-04-01
Vegetation and water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. A methodology of automated recognition of vegetation and water bodies on the territory of megacities in satellite images of sub-meter spatial resolution of the visible and IR bands is proposed. By processing multispectral images from the satellite SuperView-1A, vector layers of recognized plant and water objects were obtained. Analysis of the results of image processing showed a sufficiently high accuracy of the delineation of the boundaries of recognized objects and a good separation of classes. The developed methodology provides a significant increase of the efficiency and reliability of updating maps of large cities while reducing financial costs. Due to the high degree of automation, the proposed methodology can be implemented in the form of a geo-information web service functioning in the interests of a wide range of public services and commercial institutions.
Mineral mapping in the western Kunlun Mountains using Tiangong-1 hyperspectral imagery
Ge, W.; Cheng, Q.; Jing, L.; Chen, Y.; Guo, X.; Ding, H.; Liu, Q.
2016-04-01
The unmanned Chinese space module Tiangong-1 was launched in September 2011 with a hyperspectral sensor on board. The sensor combines high spatial and spectral resolution suitable for mineral mapping. In this study, Tiangong-1 hyperspectral data were employed for mineral mapping in the western Kunlun Mountains, an important metallogenic belt in China. A Spectral Hourglass Wizard method was applied to detect common minerals from the Tiangong- 1 shortwave infrared data with reference to a set of spectral libraries. Spectral information on minerals, such as zoisite, mica, quartz, sodalite, dolomite, and actinolite, was extracted from the data. The resulting mineral interpretation maps were highly correlated with the reference geological maps and information from ASTER satellite imagery, suggesting that the hyperspectral data are suitable for mineral mapping.
In vivo imaging of free radicals produced by multivitamin-mineral supplements
Buettner, Garry R.; Fink, Bruno
2015-01-01
Background Redox active minerals in dietary supplements can catalyze unwanted and potentially harmful oxidations. Methods To determine if this occurs in vivo we employed electron paramagnetic (EPR) imaging. We used 1-hydroxy-3-carboxy-2,2,5,5-tetramethylpyrrolidine (CPH) as a reporter for one-electron oxidations, e.g. free radical-mediated oxidations; the one-electron oxidation product of CPH, 3-carboxy-2,2,5,5-tetramethyl-1-pyrrolidinyloxy (CP•), is a nitroxide free radical that is relatively persistent in vivo and detectable by EPR. As model systems, we used research formulations of vitamin mineral supplements (RVM) that are typical of commercial products. Results In in vitro experiments, upon suspension of RVM in aqueous solution, we observed: (1) the uptake of oxygen in the solution, consistent with oxidation of the components in the RVM; (2) the ascorbate free radical, a real-time indicator of ongoing oxidations; and (3) when amino acid/oligosaccharide (AAOS; glycinate or aspartate with non-digestible oligofructose) served as the matrix in the RVM, the rate of oxidation was significantly slowed. In a murine model, EPR imaging showed that the ingestion of RVM along with CPH results in the one-electron oxidation of CPH by RVM in the digestive system. The resulting CP• distributes throughout the body. Inclusion of AAOS in the RVM formulation diminished the oxidation of CPH to CP• in vivo. Conclusions These data demonstrate that typical formulations of multivitamin/multimineral dietary supplements can initiate the oxidation of bystander substances and that AAOS-complexes of essential redox active metals, e.g. copper and iron, have reduced ability to catalyze free radical formation and associated detrimental oxidations when a part of a multivitamin/multimineral formulation. PMID:26705481
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Mehdi Rahnama
2014-06-01
Full Text Available Geological structures, such as faults and fractures, appear as image discontinuities or lineaments in remote sensing data. Geologic lineament mapping is a very important issue in geo-engineering, especially for construction site selection, seismic, and risk assessment, mineral exploration and hydrogeological research. Classical methods of lineaments extraction are based on semi-automated (or visual interpretation of optical data and digital elevation models. We developed a freely available Matlab based toolbox TecLines (Tectonic Lineament Analysis for locating and quantifying lineament patterns using satellite data and digital elevation models. TecLines consists of a set of functions including frequency filtering, spatial filtering, tensor voting, Hough transformation, and polynomial fitting. Due to differences in the mathematical background of the edge detection and edge linking procedure as well as the breadth of the methods, we introduce the approach in two-parts. In this first study, we present the steps that lead to edge detection. We introduce the data pre-processing using selected filters in spatial and frequency domains. We then describe the application of the tensor-voting framework to improve position and length accuracies of the detected lineaments. We demonstrate the robustness of the approach in a complex area in the northeast of Afghanistan using a panchromatic QUICKBIRD-2 image with 1-meter resolution. Finally, we compare the results of TecLines with manual lineament extraction, and other lineament extraction algorithms, as well as a published fault map of the study area.
Hasegawa, Tomoka
2015-10-01
Bone mineralization can be divided into two phases ; one is primary mineralization associated with osteoblastic bone formation, and the other is secondary mineralization which gradually increases mineral density of bone matrix after the primary mineralization. Primary mineralization is initiated by matrix vesicles synthesized by mature osteoblasts. Crystalline calcium phosphates are nucleated inside these matrix vesicles, and then, get out of them forming spherical mineralized nodule, which can grow more by being supplied with Ca2+ and PO4(3-) (matrix vesicle mineralization). Thereafter, the mineralized nodules make contacts with surrounding collagen fibrils, extending mineralization along with their longitudinal axis from the contact points (collagen mineralization). In this review, the ultrastructural findings on bone mineralization, specially, primary mineralization will be provided.
Corucci, Linda; Masini, Andrea; Cococcioni, Marco
2011-01-01
This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.
A Multi-stage Method to Extract Road from High Resolution Satellite Image
International Nuclear Information System (INIS)
Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang
2014-01-01
Extracting road information from high-resolution satellite images is complex and hardly achieves by exploiting only one or two modules. This paper presents a multi-stage method, consisting of automatic information extraction and semi-automatic post-processing. The Multi-scale Enhancement algorithm enlarges the contrast of human-made structures with the background. The Statistical Region Merging segments images into regions, whose skeletons are extracted and pruned according to geometry shape information. Setting the start and the end skeleton points, the shortest skeleton path is constructed as a road centre line. The Bidirectional Adaptive Smoothing technique smoothens the road centre line and adjusts it to right position. With the smoothed line and its average width, a Buffer algorithm reconstructs the road region easily. Seen from the last results, the proposed method eliminates redundant non-road regions, repairs incomplete occlusions, jumps over complete occlusions, and reserves accurate road centre lines and neat road regions. During the whole process, only a few interactions are needed
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Dimitris Stratoulias
2017-10-01
Full Text Available Earth Observation has become a progressively important source of information for land use and land cover services over the past decades. At the same time, an increasing number of reconnaissance satellites have been set in orbit with ever increasing spatial, temporal, spectral, and radiometric resolutions. The available bulk of data, fostered by open access policies adopted by several agencies, is setting a new landscape in remote sensing in which timeliness and efficiency are important aspects of data processing. This study presents a fully automated workflow able to process a large collection of very high spatial resolution satellite images to produce actionable information in the application framework of smallholder farming. The workflow applies sequential image processing, extracts meaningful statistical information from agricultural parcels, and stores them in a crop spectrotemporal signature library. An important objective is to follow crop development through the season by analyzing multi-temporal and multi-sensor images. The workflow is based on free and open-source software, namely R, Python, Linux shell scripts, the Geospatial Data Abstraction Library, custom FORTRAN, C++, and the GNU Make utilities. We tested and applied this workflow on a multi-sensor image archive of over 270 VHSR WorldView-2, -3, QuickBird, GeoEye, and RapidEye images acquired over five different study areas where smallholder agriculture prevails.
Absence of satellites of asteroids
International Nuclear Information System (INIS)
Gehrels, T.; Drummond, J.D.; Levenson, N.A.
1987-01-01
The absence of satellites within 0.1-7.0 arcmin of minor planets noted in the present CCD imaging survey is judged consistent with previous theoretical studies of collisions in which it is held that satellites would have to be larger than about 30 km in order to be collisionally stable. In view of tidal stability, the only main belt asteroid satellites which could conceivably possess stability over eons are near-contact binaries. Any recent collisional debris would be chaotic and collisionally unstable. 15 references
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Marc Wieland
2014-03-01
Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.
Imaging and Analytical Approaches for Characterization of Soil Mineral Weathering
Energy Technology Data Exchange (ETDEWEB)
Dohnalkova, Alice; Arey, Bruce; Varga, Tamas; Miller, Micah; Kovarik, Libor
2017-07-01
Soil minerals weathering is the primary natural source of nutrients necessary to sustain productivity in terrestrial ecosystems. Soil microbial communities increase soil mineral weathering and mineral-derived nutrient availability through physical and chemical processes. Rhizosphere, the zone immediately surrounding plant roots, is a biogeochemical hotspot with microbial activity, soil organic matter production, mineral weathering, and secondary phase formation all happening in a small temporally ephemeral zone of steep geochemical gradients. The detailed exploration of the micro-scale rhizosphere is essential to our better understanding of large-scale processes in soils, such as nutrient cycling, transport and fate of soil components, microbial-mineral interactions, soil erosion, soil organic matter turnover and its molecular-level characterization, and predictive modeling.
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Chandi Witharana
2016-04-01
Full Text Available The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR satellite imagery and closely examined the transferability of knowledge-based GEOBIA rules across different study sites focusing on the same semantic class. We systematically gauged the segmentation quality, classification accuracy, and the reproducibility of fuzzy rules. A master ruleset was developed based on one study site and it was re-tasked “without adaptation” and “with adaptation” on candidate image scenes comprising guano stains. Our results suggest that object-based methods incorporating the spectral, textural, spatial, and contextual characteristics of guano are capable of successfully detecting guano stains. Reapplication of the master ruleset on candidate scenes without modifications produced inferior classification results, while adapted rules produced comparable or superior results compared to the reference image. This work provides a road map to an operational “image-to-assessment pipeline” that will enable Antarctic wildlife researchers to seamlessly integrate VHSR imagery into on-demand penguin population census.
Real time deforestation detection using ann and satellite images the Amazon rainforest study case
Nunes Kehl, Thiago; Roberto Veronez, Maurício; Cesar Cazella, Silvio
2015-01-01
The foremost aim of the present study was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks. The developed tool provides parameterization of the configuration for the neural network training to enable us to select the best neural architecture to address the problem. The tool makes use of confusion matrices to determine the degree of success of the network. A spectrum-temporal analysis of the study area was done on 57 images from May 20 to July 15, 2003 using the trained neural network. The analysis enabled verification of quality of the implemented neural network classification and also aided in understanding the dynamics of deforestation in the Amazon rainforest, thereby highlighting the vast potential of neural networks for image classification. However, the complex task of detection of predatory actions at the beginning, i.e., generation of consistent alarms, instead of false alarms has not bee...
Enhanced ionosphere-magnetosphere data from the DMSP satellites
International Nuclear Information System (INIS)
Rich, F.J.; Hardy, D.A.; Gussenhoven, M.S.
1985-01-01
The satellites of the Defense Meteorological Satellite Program (DMSP) represent a series of low-altitude (835 km) polar-orbiting satellites. Their primary objective is related to the observation of the tropospheric weather with a high-resolution white light and infrared imaging system. It is also possible to make images of auroras. On a daily basis, information about auroras is used to assist various communication systems which are affected by the ionospheric disturbances associated with auroras. In the past few years, there have been several improvements in the ionospheric monitoring instrumentation. Since the high-latitude ionosphere is connected to the magnetosphere, the DMSP data are used to monitor magnetospheric processes. The instrumentation of the DMSP satellites is discussed, taking into account the data provided by them. 7 references
Operational digital image processing within the Bureau of Land Management
International Nuclear Information System (INIS)
Work, E.A.; Story, M.
1991-01-01
An overview of the use of operational digital image processing at the U.S. Bureau of Land Management (BLM) is presented. The BLM digital image analysis facility for the processing and analysis of aerial photography and satellite data is described, and its role within the Bureau's operational structure is explained. Attention is given to examples of BLM digital data analysis projects that have utilized Landsat (MSS and TM), NOAA-AVHRR, or SPOT data. These projects include: landcover mapping to assist land use planning or special projects; monitoring of wilderness units to detect unauthorized activities; stratification aid for detailed field inventories; identification/quantification of unauthorized use (agricultural and mineral trespass); and fire fuels mapping and updates. 3 refs
International Nuclear Information System (INIS)
Kim, Jae Duk
2003-01-01
To determine whether the mandibular radiomorphometric indices in panoramic radiography are correlated with the bone mineral density of Cu-equivalent images in intraoral film. The bone mineral density (BMD) of the mandibular premolar area was measured in the Cu-equivalent image of intraoral film. The Panoramic Mandibular Index (PMI) and Mandibular Cortical Width (MCW) were measured in panoramic radiographs of six dry mandibles, and the Pearson correlation between PMI, MCW, and BMD were tested. There were no significant correlations between PMI and BMD (r=0.280), nor between MCW and BMD (r=0.237). The results show that PMI and MCW were poor diagnostic indicators of mandibular BMD in the six dry mandibles used in this study. The correlationship between the mandibular radiomorphometric indices (PMI and MCW) and mandibular BMD needs to be researched further using large in vivo patient samples.
Deep and shallow structures in the Arctic region imaged by satellite magnetic and gravity data
Gaina, Carmen; Panet, Isabelle; Shephard, Grace
2016-07-01
, volcanic crust, but, as in the case of other oceanic Large Igneous Provinces, only deep sea drilling will be able to reveal the true nature of the underlying crust at the core of the Arctic. The oldest continental crust, usually found in the cratonic areas and as Proterozoic accreted crust, generates the largest positive magnetic anomalies. This crust contains large and deep volcanic bodies in the North American shield, Greenland, the Baltic shield in Eurasia and the Siberian platform in NE Asia, and are imaged by the satellite data. Furthermore, satellite data is not only restricted to revealing crustal and lithospheric depths. Recent workflows have shown that subducted remnants of ocean basins, now located in the lower mantle, as well as large, antipodal features on the core-mantle boundary, can be imaged by satellite gravity. Seismic tomography provides evidence for an extinct Mesozoic Arctic ocean lying around 1400 km under present-day Greenland. However, the variable resolution of seismic tomography at high latitudes, as well as ambiguity in plate reconstructions, renders the existence of the slab open to interpretation. Critically, the current location of the slab also matches perturbations in long-wavelength gravity gradients, providing further support for a deep density anomaly and a slab origin. Gravity data therefore provides a complementary and independent link in linking surface events and deep mantle structure in frontier regions like the Arctic. By revealing the present-day structure, satellite-derived magnetics and gravity offer a critical component in our understanding of Arctic history, over timescales of millions of years and scales of thousands of kilometers.
Duru, Umit
2017-08-01
The research summarized here determines historical shoreline changes along Lake Sapanca by using Remote Sensing (RS) and Geographical Information Systems (GIS). Six multi-temporal satellite images of Landsat Multispectral Scanner (L1-5 MMS), Enhanced Thematic Mapper Plus (L7 ETM+), and Operational Land Imager Sensors (L8 OLI), covering the period between 17 June 1975 and 15 July 2016, were used to monitor shoreline positions and estimate change rates along the coastal zone. After pre-possessing routines, the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and supervised classification techniques were utilized to extract six different shorelines. Digital Shoreline Analysis System (DSAS), a toolbox that enables transect-based computations of shoreline displacement, was used to compute historical shoreline change rates. The average rate of shoreline change for the entire cost was 2.7 m/year of progradation with an uncertainty of 0.2 m/year. While the great part of the lake shoreline remained stable, the study concluded that the easterly and westerly coasts and deltaic coasts are more vulnerable to shoreline displacements over the last four decades. The study also reveals that anthropogenic activities, more specifically over extraction of freshwater from the lake, cyclic variation in rainfall, and deposition of sediment transported by the surrounding creeks dominantly control spatiotemporal shoreline changes in the region. Monitoring shoreline changes using multi-temporal satellite images is a significant component for the coastal decision-making and management.
An Automatic Cloud Detection Method for ZY-3 Satellite
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CHEN Zhenwei
2015-03-01
Full Text Available Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products. For the browse images cataloged by ZY-3 satellite, the tree discriminate structure is adopted to carry out cloud detection. The image was divided into sub-images and their features were extracted to perform classification between clouds and grounds. However, due to the high complexity of clouds and surfaces and the low resolution of browse images, the traditional classification algorithms based on image features are of great limitations. In view of the problem, a prior enhancement processing to original sub-images before classification was put forward in this paper to widen the texture difference between clouds and surfaces. Afterwards, with the secondary moment and first difference of the images, the feature vectors were extended in multi-scale space, and then the cloud proportion in the image was estimated through comprehensive analysis. The presented cloud detection algorithm has already been applied to the ZY-3 application system project, and the practical experiment results indicate that this algorithm is capable of promoting the accuracy of cloud detection significantly.
International Nuclear Information System (INIS)
Arellano, Paul; Tansey, Kevin; Balzter, Heiko; Boyd, Doreen S.
2015-01-01
The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI 705 ) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. - Highlights: • Leaf biochemical alterations in the rainforest are caused by petroleum pollution. • Lower levels of chlorophyll content are symptom of vegetation stress in polluted sites. • Increased foliar water content was found in vegetation near polluted sites. • Vegetation stress was detected by using vegetation indices from satellite images. • Polluted sites and hydrocarbon seepages in rainforest can be identified from space. - Hydrocarbon pollution in the Amazon forest is observed for first time from satellite data
Tsuchiyama, A.; Nakano, T.; Uesugi, K.; Uesugi, M.; Takeuchi, A.; Suzuki, Y.; Noguchi, R.; Matsumoto, T.; Matsuno, J.; Nagano, T.; Imai, Y.; Nakamura, T.; Ogami, T.; Noguchi, T.; Abe, M.; Yada, T.; Fujimura, A.
2013-09-01
We developed a novel technique called "analytical dual-energy microtomography" that uses the linear attenuation coefficients (LACs) of minerals at two different X-ray energies to nondestructively obtain three-dimensional (3D) images of mineral distribution in materials such as rock specimens. The two energies are above and below the absorption edge energy of an abundant element, which we call the "index element". The chemical compositions of minerals forming solid solution series can also be measured. The optimal size of a sample is of the order of the inverse of the LAC values at the X-ray energies used. We used synchrotron-based microtomography with an effective spatial resolution of >200 nm to apply this method to small particles (30-180 μm) collected from the surface of asteroid 25143 Itokawa by the Hayabusa mission of the Japan Aerospace Exploration Agency (JAXA). A 3D distribution of the minerals was successively obtained by imaging the samples at X-ray energies of 7 and 8 keV, using Fe as the index element (the K-absorption edge of Fe is 7.11 keV). The optimal sample size in this case is of the order of 50 μm. The chemical compositions of the minerals, including the Fe/Mg ratios of ferromagnesian minerals and the Na/Ca ratios of plagioclase, were measured. This new method is potentially applicable to other small samples such as cosmic dust, lunar regolith, cometary dust (recovered by the Stardust mission of the National Aeronautics and Space Administration [NASA]), and samples from extraterrestrial bodies (those from future sample return missions such as the JAXA Hayabusa2 mission and the NASA OSIRIS-REx mission), although limitations exist for unequilibrated samples. Further, this technique is generally suited for studying materials in multicomponent systems with multiple phases across several research fields.
Directory of Open Access Journals (Sweden)
Federico Raspini
2015-11-01
Full Text Available Pre- event and event landslide deformations have been detected and measured for the landslide that occurred on 3 December 2013 on the south-western slope of the Montescaglioso village (Basilicata Region, southern Italy. In this paper, ground displacements have been mapped through an integrated analysis based on a series of high resolution SAR (Synthetic Aperture Radar images acquired by the Italian constellation of satellites COSMO-SkyMed. Analysis has been performed by exploiting both phase (through multi-image SAR interferometry and amplitude information (through speckle tracking techniques of the satellite images. SAR Interferometry, applied to images taken before the event, revealed a general pre-event movement, in the order of a few mm/yr, in the south-western slope of the Montescaglioso village. Highest pre-event velocities, ranging between 8 and 12 mm/yr, have been recorded in the sector of the slope where the first movement of the landslide took place. Speckle tracking, applied to images acquired before and after the event, allowed the retrieval of the 3D deformation field produced by the landslide. It also showed that ground displacements produced by the landslide have a dominant SSW component, with values exceeding 10 m for large sectors of the landslide area, with local peaks of 20 m in its central and deposit areas. Two minor landslides with a dominant SSE direction, which were detected in the upper parts of the slope, likely also occurred as secondary phenomena as consequence of the SSW movement of the main Montescaglioso landslide.
7 CFR 611.22 - Availability of satellite imagery.
2010-01-01
... 7 Agriculture 6 2010-01-01 2010-01-01 false Availability of satellite imagery. 611.22 Section 611... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image of...
Rockwell, Barnaby W.
2010-01-01
Multispectral remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were analyzed to identify and map minerals, vegetation groups, and volatiles (water and snow) in support of geologic studies of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada. Digital mineral and vegetation mapping results are presented in both portable document format (PDF) and ERDAS Imagine format (.img). The ERDAS-format files are suitable for integration with other geospatial data in Geographic Information Systems (GIS) such as ArcGIS. The ERDAS files showing occurrence of 1) iron-bearing minerals, vegetation, and water, and 2) clay, sulfate, mica, carbonate, Mg-OH, and hydrous quartz minerals have been attributed according to identified material, so that the material detected in a pixel can be queried with the interactive attribute identification tools of GIS and image processing software packages (for example, the Identify Tool of ArcMap and the Inquire Cursor Tool of ERDAS Imagine). All raster data have been orthorectified to the Universal Transverse Mercator (UTM) projection using a projective transform with ground-control points selected from orthorectified Landsat Thematic Mapper data and a digital elevation model from the U.S. Geological Survey (USGS) National Elevation Dataset (1/3 arc second, 10 m resolution). Metadata compliant with Federal Geographic Data Committee (FGDC) standards for all ERDAS-format files have been included, and contain important information regarding geographic coordinate systems, attributes, and cross-references. Documentation regarding spectral analysis methodologies employed to make the maps is included in these cross-references.
Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter
2018-03-01
An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.
Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images
Directory of Open Access Journals (Sweden)
Sriram Ganapathi Subramanian
2018-04-01
Full Text Available Machine learning algorithms have increased tremendously in power in recent years but have yet to be fully utilized in many ecology and sustainable resource management domains such as wildlife reserve design, forest fire management, and invasive species spread. One thing these domains have in common is that they contain dynamics that can be characterized as a spatially spreading process (SSP, which requires many parameters to be set precisely to model the dynamics, spread rates, and directional biases of the elements which are spreading. We present related work in artificial intelligence and machine learning for SSP sustainability domains including forest wildfire prediction. We then introduce a novel approach for learning in SSP domains using reinforcement learning (RL where fire is the agent at any cell in the landscape and the set of actions the fire can take from a location at any point in time includes spreading north, south, east, or west or not spreading. This approach inverts the usual RL setup since the dynamics of the corresponding Markov Decision Process (MDP is a known function for immediate wildfire spread. Meanwhile, we learn an agent policy for a predictive model of the dynamics of a complex spatial process. Rewards are provided for correctly classifying which cells are on fire or not compared with satellite and other related data. We examine the behavior of five RL algorithms on this problem: value iteration, policy iteration, Q-learning, Monte Carlo Tree Search, and Asynchronous Advantage Actor-Critic (A3C. We compare to a Gaussian process-based supervised learning approach and also discuss the relation of our approach to manually constructed, state-of-the-art methods from forest wildfire modeling. We validate our approach with satellite image data of two massive wildfire events in Northern Alberta, Canada; the Fort McMurray fire of 2016 and the Richardson fire of 2011. The results show that we can learn predictive, agent
Direct microCT imaging of non-mineralized connective tissues at high resolution.
Naveh, Gili R S; Brumfeld, Vlad; Dean, Mason; Shahar, Ron; Weiner, Steve
2014-01-01
The 3D imaging of soft tissues in their native state is challenging, especially when high resolution is required. An X-ray-based microCT is, to date, the best choice for high resolution 3D imaging of soft tissues. However, since X-ray attenuation of soft tissues is very low, contrasting enhancement using different staining materials is needed. The staining procedure, which also usually involves tissue fixation, causes unwanted and to some extent unknown tissue alterations. Here, we demonstrate that a method that enables 3D imaging of soft tissues without fixing and staining using an X-ray-based bench-top microCT can be applied to a variety of different tissues. With the sample mounted in a custom-made loading device inside a humidity chamber, we obtained soft tissue contrast and generated 3D images of fresh, soft tissues with a resolution of 1 micron voxel size. We identified three critical conditions which make it possible to image soft tissues: humidified environment, mechanical stabilization of the sample and phase enhancement. We demonstrate the capability of the technique using different specimens: an intervertebral disc, the non-mineralized growth plate, stingray tessellated radials (calcified cartilage) and the collagenous network of the periodontal ligament. Since the scanned specimen is fresh an interesting advantage of this technique is the ability to scan a specimen under load and track the changes of the different structures. This method offers a unique opportunity for obtaining valuable insights into 3D structure-function relationships of soft tissues.
Gholoum, M.; Bruce, D.; Hazeam, S. Al
2012-07-01
A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine the quality of the
Directory of Open Access Journals (Sweden)
M. Gholoum
2012-07-01
Full Text Available A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine
Haigang, Sui; Zhina, Song
2016-06-01
Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.
Kavzoglu, Taskin; Erdemir, Merve Yildiz; Tonbul, Hasan
2017-07-01
In object-based image analysis, obtaining representative image objects is an important prerequisite for a successful image classification. The major threat is the issue of scale selection due to the complex spatial structure of landscapes portrayed as an image. This study proposes a two-stage approach to conduct regionalized multiscale segmentation. In the first stage, an initial high-level segmentation is applied through a "broadscale," and a set of image objects characterizing natural borders of the landscape features are extracted. Contiguous objects are then merged to create regions by considering their normalized difference vegetation index resemblance. In the second stage, optimal scale values are estimated for the extracted regions, and multiresolution segmentation is applied with these settings. Two satellite images with different spatial and spectral resolutions were utilized to test the effectiveness of the proposed approach and its transferability to different geographical sites. Results were compared to those of image-based single-scale segmentation and it was found that the proposed approach outperformed the single-scale segmentations. Using the proposed methodology, significant improvement in terms of segmentation quality and classification accuracy (up to 5%) was achieved. In addition, the highest classification accuracies were produced using fine-scale values.
Carter, William D.
1981-01-01
A large number of Earth-observation satellites orbit our world several times each day, providing new information about the land and sea surfaces and the overlying thin layer of atmosphere that makes our planet unique. Meteorological satellites have had the longest history of experimental use and most are now considered operational. The geologic information collected by the Landsat, Polar Orbiting Geophysical Observatory (POGO), Magsat, Heat Capacity Mapping Mission (HCMM) and Seasat land and ocean observation systems is being thoroughly tested, and some of these systems are now approaching operational use.
Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia
Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.
2015-03-01
Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.
Energy Technology Data Exchange (ETDEWEB)
Grazzini, Jacopo [Los Alamos National Laboratory; Dillard, Scott [PNNL; Soille, Pierre [EC JRC
2010-10-21
This paper addresses the problem of semi-automatic extraction of road or hydrographic networks in satellite images. For that purpose, we propose an approach combining concepts arising from mathematical morphology and hydrology. The method exploits both geometrical and topological characteristics of rivers/roads and their tributaries in order to reconstruct the complete networks. It assumes that the images satisfy the following two general assumptions, which are the minimum conditions for a road/river network to be identifiable and are usually verified in low- to mid-resolution satellite images: (i) visual constraint: most pixels composing the network have similar spectral signature that is distinguishable from most of the surrounding areas; (ii) geometric constraint: a line is a region that is relatively long and narrow, compared with other objects in the image. While this approach fully exploits local (roads/rivers are modeled as elongated regions with a smooth spectral signature in the image and a maximum width) and global (they are structured like a tree) characteristics of the networks, further directional information about the image structures is incorporated. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the target network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given network seed with this metric is combined with hydrological operators for overland flow simulation to extract the paths which contain most line evidence and identify them with the target network.
International Nuclear Information System (INIS)
Xiao, Kun; Zou, Changchun; Xiang, Biao; Yue, Xuyuan; Zhou, Xinpeng; Li, Jianguo; Zhao, Bin
2014-01-01
The hole NLSD-2, one of the deepest scientific drilling projects in the metallic ore districts of China, is the second scientific drilling deep hole in the Nanling district. Its ultimate depth is 2012.12 m. This hole was created through the implementation of continuous coring, and the measuring of a variety of geophysical well logging methods was performed over the course of the drilling process. This paper analyzes the characteristic responses of the fracture and fractured zone by ultrasonic imaging log data, and characterizes various rules of fracture parameters which change according to drilling depth. It then discusses the denotative meaning of the log results of polymetallic mineralization layers. The formation fractures develop most readily in a depth of 100∼200 m, 600∼850 m and 1450∼1550 m of the hole NLSD-2, and high angle fractures develop most prominently. The strike direction of the fractures is mainly NW-SE, reflecting the orientation of maximum horizontal principal stress. For the polymetallic mineralization layer that occurred in the fractured zone, the characteristic response of ultrasonic imaging log is a wide dark zone, and the characteristic responses of conventional logs displayed high polarizability, high density, high acoustic velocity and low resistivity. All the main polymetallic mineralization layers are developed in fractures or fractured zones, and the fractures and fractured zones can be identified by an ultrasonic imaging log, thus the log results indirectly indicate the occurrence of polymetallic mineralization layers. Additionally, the relationship between the dip direction of fractures and the well deviation provides guidance for straightening of the drilling hole. (paper)
A prototype method for diagnosing high ice water content probability using satellite imager data
Yost, Christopher R.; Bedka, Kristopher M.; Minnis, Patrick; Nguyen, Louis; Strapp, J. Walter; Palikonda, Rabindra; Khlopenkov, Konstantin; Spangenberg, Douglas; Smith, William L., Jr.; Protat, Alain; Delanoe, Julien
2018-03-01
Recent studies have found that ingestion of high mass concentrations of ice particles in regions of deep convective storms, with radar reflectivity considered safe for aircraft penetration, can adversely impact aircraft engine performance. Previous aviation industry studies have used the term high ice water content (HIWC) to define such conditions. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: (1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, (2) tropopause-relative infrared brightness temperature, and (3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m-3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.
Huang, F.; Hui, W.; Li, X.; Liu, R.; Zhang, Z.; Zheng, Y.; Kang, N.
2017-12-01
The Lightning Mapping Imager (LMI) on the FY-4A satellite, which was launched successfully in December 2016, is the first satellite-based lightning detector from space independently developed in China, and one of the world's first two stationary satellite LMIs. The optical imaging technique with a 400x600 CCD array plane and a frequency of 500 frames/s is adopted in the FY-4A LMI to perform real-time and continuous observation of total lightening in the Chinese mainland and adjacent areas. As of July 2017, the in-orbit test shows that the lightening observation date could be accurately obtained by the FY-4A LMI, and that the geo-location could be verified by the ground lightening observation network over China. Since the beginning of the 2017 flood season, every process of strong thunderstorms has been monitored by the FY-4A LMI throughout the various areas of China, and of these are used as a typical application case in this talk. On April 8 and 9, 2017, a strong convective precipitation process occurred in the middle-lower reaches of the Yangtze River, China. The observation data of the FY-4A LMI are used to monitor the occurrence, development, shift and extinction of the thunderstorm track. By means of analyzing the station's synchronous precipitation observation data, it is indicated that the moving track of the thunderstorm is not completely consistent with that of the precipitation center, and while the distribution areas of thunderstorm and precipitation are consistent to a certain extent, a significant difference also exists. This difference is mainly caused by the convective precipitation and stratus precipitation area during the precipitation process. Through comparative analysis, the preliminary satellite and foundation lightening observation data show a higher consistency. However, the time of lightening activity observed by satellite is one hour earlier than that of the ground observation, which is likely related to the total lightning observation by
Satellite-based Tropical Cyclone Monitoring Capabilities
Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.
2012-12-01
Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.
Tracking target objects orbiting earth using satellite-based telescopes
De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J
2014-10-14
A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.
High resolution satellite imagery : from spies to pipeline management
Energy Technology Data Exchange (ETDEWEB)
Adam, S. [Canadian Geomatic Solutions Ltd., Calgary, AB (Canada); Farrell, M. [TransCanada Transmission, Calgary, AB (Canada)
2000-07-01
The launch of Space Imaging's IKONOS satellite in September 1999 has opened the door for corridor applications. The technology has been successfully implemented by TransCanada PipeLines in mapping over 1500 km of their mainline. IKONOS is the world's first commercial high resolution satellite which collects data at 1-meter black/white and 4-meter multi-spectral. Its use is regulated by the U.S. government. It is the best source of high resolution satellite image data. Other sources include the Indian Space Agency's IRS-1 C/D satellite and the Russian SPIN-2 which provides less reliable coverage. In addition, two more high resolution satellites may be launched this year to provide imagery every day of the year. IKONOS scenes as narrow as 5 km can be purchased. TransCanada conducted a pilot study to determine if high resolution satellite imagery is as effective as ortho-photos for identifying population structures within a buffer of TransCanada's east line right-of-way. The study examined three unique segments where residential, commercial, industrial and public features were compared. It was determined that IKONOS imagery is as good as digital ortho-photos for updating structures from low to very high density areas. The satellite imagery was also logistically easier than ortho-photos to acquire. This will be even more evident when the IKONOS image archives begins to grow. 4 tabs., 3 figs.
Automatic Mosaicking of Satellite Imagery Considering the Clouds
Kang, Yifei; Pan, Li; Chen, Qi; Zhang, Tong; Zhang, Shasha; Liu, Zhang
2016-06-01
With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.
Arabian Red Sea coastal soils as potential mineral dust sources
Directory of Open Access Journals (Sweden)
P. Jish Prakash
2016-09-01
Full Text Available Both Moderate Resolution Imaging Spectroradiometer (MODIS and Spinning Enhanced Visible and InfraRed Imager (SEVIRI satellite observations suggest that the narrow heterogeneous Red Sea coastal region is a frequent source of airborne dust that, because of its proximity, directly affects the Red Sea and coastal urban centers. The potential of soils to be suspended as airborne mineral dust depends largely on soil texture, moisture content and particle size distributions. Airborne dust inevitably carries the mineralogical and chemical signature of a parent soil. The existing soil databases are too coarse to resolve the small but important coastal region. The purpose of this study is to better characterize the mineralogical, chemical and physical properties of soils from the Arabian Red Sea coastal plain, which in turn will help to improve assessment of dust effects on the Red Sea, land environmental systems and urban centers. Thirteen surface soils from the hot-spot areas of windblown mineral dust along the Red Sea coastal plain were sampled for analysis. Analytical methods included optical microscopy, X-ray diffraction (XRD, inductively coupled plasma optical emission spectrometry (ICP-OES, ion chromatography (IC, scanning electron microscopy (SEM and laser particle size analysis (LPSA. We found that the Red Sea coastal soils contain major components of quartz and feldspar, as well as lesser but variable amounts of amphibole, pyroxene, carbonate, clays and micas, with traces of gypsum, halite, chlorite, epidote and oxides. The range of minerals in the soil samples was ascribed to the variety of igneous and metamorphic provenance rocks of the Arabian Shield forming the escarpment to the east of the Red Sea coastal plain. The analysis revealed that the samples contain compounds of nitrogen, phosphorus and iron that are essential nutrients to marine life. The analytical results from this study will provide a valuable input into dust emission models
International Nuclear Information System (INIS)
Tao Zhangsheng; Zhao Yingjun
2008-01-01
Based on the application status of satellite remote sensing technology to nuclear safeguards, advantage of satellite remote sensing technology is analyzed, main types of satellite image used in nuclear safeguards are elaborated and the main application of satellite images is regarded to detect, verify and monitor nuclear activities; verify additional protocol declaration and design information, support performing complementary access inspections; investigate alleged undeclared activities based on open source or the third party information. Application examples of satellite image in nuclear safeguards to analyze nuclear facilities by other countries, the ability of remote sensing technology in nuclear safeguards is discussed. (authors)
Leonardo-BRDF: A New Generation Satellite Constellation
Esper, Jaime; Neeck, Steven; Wiscombe, Warren; Ryschkewitsch, Michael; Andary, J. (Technical Monitor)
2000-01-01
Instantaneous net radiation flux at the top of the atmosphere is one of the primary drivers of climate and global change. Since the dawn of the satellite era, great efforts and expense have gone into measuring this flux from single satellites and even (for a several-year period) from a constellation of three satellites called ERBE. However, the reflected solar flux is an angular and spectral integral over the so-called "BRDF" or Bidirectional Reflectance Distribution Function, which is the angular distribution of reflected solar radiation for each solar zenith angle and each wavelength. Previous radiation flux satellites could not measure instantaneous BRDF, so scientists have had to fall back on models or composites. Because their range of observed solar zenith angles was very limited due to sunsynchronous orbits, the resultant flux maps are too inaccurate to see the dynamics of radiation flux or to reliably correlate it with specific phenomena (hurricanes, biomass fires, urban pollution, dust outbreaks, etc.). Accuracy only becomes acceptable after monthly averaging, but this washes out almost all cause-and-effect information, further exacerbated by the lack of spectral resolution. Leonardo-BRDF is a satellite system designed to measure the instantaneous spectral BRDF using a formation of highly coordinated satellites, all pointing at the same Earth targets at the same time. It will allow scientists for the first time to assess the radiative forcing of climate due to specific phenomena, which is bound to be important in the ongoing debate about global warming and what is causing it. The formation is composed of two satellite types having, as instrument payloads, single highly-integrated miniature imaging spectrometers or radiometers. Two nearby "keystone" satellites anchor the formation and fly in static orbits. They employ wide field of view imaging spectrometers that are extremely light and compact. The keystone satellites are identical and can operate in
Desormeaux, Yves; Rossow, William B.; Brest, Christopher L.; Campbell, G. G.
1993-01-01
Procedures are described for normalizing the radiometric calibration of image radiances obtained from geostationary weather satellites that contributed data to the International Satellite Cloud Climatology Project. The key step is comparison of coincident and collocated measurements made by each satellite and the concurrent AVHRR on the 'afternoon' NOAA polar-orbiting weather satellite at the same viewing geometry. The results of this comparison allow transfer of the AVHRR absolute calibration, which has been established over the whole series, to the radiometers on the geostationary satellites. Results are given for Meteosat-2, 3, and 4, for GOES-5, 6, and 7, for GMS-2, 3, and 4 and for Insat-1B. The relative stability of the calibrations of these radiance data is estimated to be within +/- 3 percent; the uncertainty of the absolute calibrations is estimated to be less than 10 percent. The remaining uncertainties are at least two times smaller than for the original radiance data.
Method of the Aquatic Environment Image Processing for Determining the Mineral Suspension Parameters
Directory of Open Access Journals (Sweden)
D.A. Antonenkov
2016-10-01
Full Text Available The present article features the developed method to determine the mineral suspension characteristics by obtaining and following processing of the aquatic environment images. This method is capable of maintaining its performance under the conditions of considerable dynamic activity of the water masses. The method feature consists in application of the developed computing algorithm, simultaneous use of morphological filters and histogram methods for image processing, and in a special calibration technique. As a whole it provides a possibility to calculate size and concentration of the particles on the images obtained. The developed technical means permitting to get the environment images of the required quality are briefly described. The algorithm of the developed software operation is represented. The examples of numerical and weight distribution of the particles according to their sizes, and the totals of comparing the results obtained by the standard and developed methods are represented. The developed method makes it possible to obtain the particle size data in the range of 50–1000 μm and also to determine the suspension concentration with ~12 % error. This method can be technically implemented for the instruments intended for in situ measurements using the gauges, allowing obtaining exposure time short values, such as applying the electron-optical converter, which acts as the image intensifier, and the high-speed electronic shutter. The completed method testing in the laboratory makes possible to obtain the results similar in accuracy with the results of the in situ measurements.
Cultures in orbit: Satellite technologies, global media and local practice
Parks, Lisa Ann
Since the launch of Sputnik in 1957, satellite technologies have had a profound impact upon cultures around the world. "Cultures in Orbit" examines these seemingly disembodied, distant relay machines in relation to situated social and cultural processes on earth. Drawing upon a range of materials including NASA and UNESCO documents, international satellite television broadcasts, satellite 'development' projects, documentary and science fiction films, remote sensing images, broadcast news footage, World Wide Web sites, and popular press articles I delineate and analyze a series of satellite mediascapes. "Cultures in Orbit" analyzes uses of satellites for live television relay, surveillance, archaeology and astronomy. The project examines such satellite media as the first live global satellite television program Our World, Elvis' Aloha from Hawaii concert, Aboriginal Australian satellite programs, and Star TV's Asian music videos. In addition, the project explores reconnaissance images of mass graves in Bosnia, archaeological satellite maps of Cleopatra's underwater palace in Egypt, and Hubble Space Telescope images. These case studies are linked by a theoretical discussion of the satellite's involvement in shifting definitions of time, space, vision, knowledge and history. The satellite fosters an aesthetic of global realism predicated on instantaneous transnational connections. It reorders linear chronologies by revealing traces of the ancient past on the earth's surface and by searching in deep space for the "edge of time." On earth, the satellite is used to modernize and develop "primitive" societies. Satellites have produced new electronic spaces of international exchange, but they also generate strategic maps that advance Western political and cultural hegemony. By technologizing human vision, the satellite also extends the epistemologies of the visible, the historical and the real. It allows us to see artifacts and activities on earth from new vantage points
García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun
2016-10-01
This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.
Lemmens, R.; Maathuis, B.; Mannaerts, C.; Foerster, T.; Schaeffer, B.; Wytzisk, A.
2009-12-01
This paper involves easy accessible integrated web-based analysis of satellite images with a plug-in based open source software. The paper is targeted to both users and developers of geospatial software. Guided by a use case scenario, we describe the ILWIS software and its toolbox to access satellite images through the GEONETCast broadcasting system. The last two decades have shown a major shift from stand-alone software systems to networked ones, often client/server applications using distributed geo-(web-)services. This allows organisations to combine without much effort their own data with remotely available data and processing functionality. Key to this integrated spatial data analysis is a low-cost access to data from within a user-friendly and flexible software. Web-based open source software solutions are more often a powerful option for developing countries. The Integrated Land and Water Information System (ILWIS) is a PC-based GIS & Remote Sensing software, comprising a complete package of image processing, spatial analysis and digital mapping and was developed as commercial software from the early nineties onwards. Recent project efforts have migrated ILWIS into a modular, plug-in-based open source software, and provide web-service support for OGC-based web mapping and processing. The core objective of the ILWIS Open source project is to provide a maintainable framework for researchers and software developers to implement training components, scientific toolboxes and (web-) services. The latest plug-ins have been developed for multi-criteria decision making, water resources analysis and spatial statistics analysis. The development of this framework is done since 2007 in the context of 52°North, which is an open initiative that advances the development of cutting edge open source geospatial software, using the GPL license. GEONETCast, as part of the emerging Global Earth Observation System of Systems (GEOSS), puts essential environmental data at the
Satellite image atlas of glaciers of the world
Williams, Richard S.; Ferrigno, Jane G.; Williams, Richard S.; Ferrigno, Jane G.
1988-01-01
U.S. Geological Survey Professional Paper 1386, Satellite Image Atlas of Glaciers of the World, contains 11 chapters designated by the letters A through K. Chapter A provides a comprehensive, yet concise, review of the "State of the Earth's Cryosphere at the Beginning of the 21st Century: Glaciers, Global Snow Cover, Floating Ice, and Permafrost and Periglacial Environments," and a "Map/Poster of the Earth's Dynamic Cryosphere," and a set of eight "Supplemental Cryosphere Notes" about the Earth's Dynamic Cryosphere and the Earth System. The next 10 chapters, B through K, are arranged geographically and present glaciological information from Landsat and other sources of historic and modern data on each of the geographic areas. Chapter B covers Antarctica; Chapter C, Greenland; Chapter D, Iceland; Chapter E, Continental Europe (except for the European part of the former Soviet Union), including the Alps, the Pyrenees, Norway, Sweden, Svalbard (Norway), and Jan Mayen (Norway); Chapter F, Asia, including the European part of the former Soviet Union, China, Afghanistan, Pakistan, India, Nepal, and Bhutan; Chapter G, Turkey, Iran, and Africa; Chapter H, Irian Jaya (Indonesia) and New Zealand; Chapter I, South America; Chapter J, North America (excluding Alaska); and Chapter K, Alaska. Chapters A–D each include map plates.
Using Satellite Images for Wireless Network Planing in Baku City
Gojamanov, M.; Ismayilov, J.
2013-04-01
It is a well known fact that the Information-Telecommunication and Space research technologies are the fields getting much more benefits from the achievements of the scientific and technical progress. In many cases, these areas supporting each other have improved the conditions for their further development. For instance, the intensive development in the field of the mobile communication has caused the rapid progress of the Space research technologies and vice versa.Today it is impossible to solve one of the most important tasks of the mobile communication as Radio Frecance planning without the 2D and 3D digital maps. The compiling of such maps is much more efficient by means of the space images. Because the quality of the space images has been improved and developed, especially at the both spectral and spatial resolution points. It has been possible to to use 8 Band images with the spatial resolution of 50 sm. At present, in relation to the function 3G of mobile communications one of the main issues facing mobile operator companies is a high-precision 3D digital maps. It should be noted that the number of mobile phone users in the Republic of Azerbaijan went forward other Community of Independent States Countries. Of course, using of aerial images for 3D mapping would be optimal. However, depending on a number of technical and administrative problems aerial photography cannot be used. Therefore, the experience of many countries shows that it will be more effective to use the space images with the higher resolution for these issues. Concerning the fact that the mobile communication within the city of Baku has included 3G function there were ordered stereo images wih the spatial resolution of 50 cm for the 150 sq.km territory occupying the central part of the city in order to compile 3D digital maps. The images collected from the WorldView-2 satellite are 4-Band Bundle(Pan+MS1) stereo images. Such kind of imagery enable to automatically classificate some required
Target Matching Recognition for Satellite Images Based on the Improved FREAK Algorithm
Directory of Open Access Journals (Sweden)
Yantong Chen
2016-01-01
Full Text Available Satellite remote sensing image target matching recognition exhibits poor robustness and accuracy because of the unfit feature extractor and large data quantity. To address this problem, we propose a new feature extraction algorithm for fast target matching recognition that comprises an improved feature from accelerated segment test (FAST feature detector and a binary fast retina key point (FREAK feature descriptor. To improve robustness, we extend the FAST feature detector by applying scale space theory and then transform the feature vector acquired by the FREAK descriptor from decimal into binary. We reduce the quantity of data in the computer and improve matching accuracy by using the binary space. Simulation test results show that our algorithm outperforms other relevant methods in terms of robustness and accuracy.
Gallium-67 citrate imaging in underground coal miners
International Nuclear Information System (INIS)
Kanner, R.E.; Barkman, H.W. Jr.; Rom, W.N.; Taylor, A.T. Jr.
1985-01-01
Twenty-two underground coal workers with 27 or more years of coal dust exposure were studied with gallium-67 citrate (Ga-67) imaging. Radiographic evidence of coal workers indicates that pneumoconiosis (CWP) was present in 12 subjects. The Ga-67 scan was abnormal in 11 of 12 with, and 9 of 10 without, CWP. The Ga-67 uptake index was significantly correlated with total dust exposure (p less than 0.01) and approached significant correlation with the radiographic profusion of the nodules (0.10 greater than p greater than 0.05). There was no correlation between Ga-67 uptake and spirometric function, which was normal in this group of patients; furthermore, increased lung uptake of gallium did not indicate a poor prognosis in subjects no longer exposed to coal dust. While coal dust exposure may be associated with positive Ga-67 lung scan in coal miners with many years of coal dust exposure, the scan provided no information not already available from a careful exposure history and a chest radiograph. Since Ga-67 scanning is a relatively expensive procedure the authors would recommend that its use in subjects with asymptomatic CWP be limited to an investigative role and not be made part of a routine evaluation
Visual attitude propagation for small satellites
Rawashdeh, Samir A.
As electronics become smaller and more capable, it has become possible to conduct meaningful and sophisticated satellite missions in a small form factor. However, the capability of small satellites and the range of possible applications are limited by the capabilities of several technologies, including attitude determination and control systems. This dissertation evaluates the use of image-based visual attitude propagation as a compliment or alternative to other attitude determination technologies that are suitable for miniature satellites. The concept lies in using miniature cameras to track image features across frames and extracting the underlying rotation. The problem of visual attitude propagation as a small satellite attitude determination system is addressed from several aspects: related work, algorithm design, hardware and performance evaluation, possible applications, and on-orbit experimentation. These areas of consideration reflect the organization of this dissertation. A "stellar gyroscope" is developed, which is a visual star-based attitude propagator that uses relative motion of stars in an imager's field of view to infer the attitude changes. The device generates spacecraft relative attitude estimates in three degrees of freedom. Algorithms to perform the star detection, correspondence, and attitude propagation are presented. The Random Sample Consensus (RANSAC) approach is applied to the correspondence problem to successfully pair stars across frames while mitigating falsepositive and false-negative star detections. This approach provides tolerance to the noise levels expected in using miniature optics and no baffling, and the noise caused by radiation dose on orbit. The hardware design and algorithms are validated using test images of the night sky. The application of the stellar gyroscope as part of a CubeSat attitude determination and control system is described. The stellar gyroscope is used to augment a MEMS gyroscope attitude propagation
Optical neural network system for pose determination of spinning satellites
Lee, Andrew; Casasent, David
1990-01-01
An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.
Directory of Open Access Journals (Sweden)
Matteo Picchiani
2015-03-01
Full Text Available This work shows the potential use of neural networks in the characterization of eruptive events monitored by satellite, through fast and automatic classification of multispectral images. The algorithm has been developed for the MODIS instrument and can easily be extended to other similar sensors. Six classes have been defined paying particular attention to image regions that represent the different surfaces that could possibly be found under volcanic ash clouds. Complex cloudy scenarios composed by images collected during the Icelandic eruptions of the Eyjafjallajökull (2010 and Grimsvötn (2011 volcanoes have been considered as test cases. A sensitivity analysis on the MODIS TIR and VIS channels has been performed to optimize the algorithm. The neural network has been trained with the first image of the dataset, while the remaining data have been considered as independent validation sets. Finally, the neural network classifier’s results have been compared with maps classified with several interactive procedures performed in a consolidated operational framework. This comparison shows that the automatic methodology proposed achieves a very promising performance, showing an overall accuracy greater than 84%, for the Eyjafjalla - jökull event, and equal to 74% for the Grimsvötn event.
Hutsinpiller, Amy
1988-01-01
The purpose of this study is to use airborne imaging spectrometer data to discriminate hydrothermal alteration mineral assemblages associated with silver and gold mineralization at Virginia City, NV. The data is corrected for vertical striping and sample gradients, and converted to flat-field logarithmic residuals. Log residual spectra from areas known to be altered are compared to field spectra for kaolinitic, illitic, sericitic, and propylitic alteration types. The areal distributions of these alteration types are estimated using a spectral matching technique. Both visual examination of spectra and the matching techniques are effective in distinguishing kaolinitic, illitic, and propylitic alteration types from each other. However, illitic and sericitic alteration cannot be separated using these techniques because the spectra of illite and sericite are very similar. A principal components analysis of 14 channels in the 2.14-2.38 micron wavelength region is also successful in discriminating and mapping illitic, kaolinitic, and propylitic alteration types.
Directory of Open Access Journals (Sweden)
Hongying Zhang
2016-10-01
Full Text Available Given the low accuracy of the traditional remote sensing image processing software when orthorectifying satellite images that cover mountainous areas, and in order to make a full use of mutually compatible and complementary characteristics of the remote sensing image processing software PCI-RPC (Rational Polynomial Coefficients and ArcGIS-Spline, this study puts forward a new operational and effective image processing procedure to improve the accuracy of image orthorectification. The new procedure first processes raw image data into an orthorectified image using PCI with RPC model (PCI-RPC, and then the orthorectified image is further processed using ArcGIS with the Spline tool (ArcGIS-Spline. We used the high-resolution CBERS-02C satellite images (HR1 and HR2 scenes with a pixel size of 2 m acquired from Yangyuan County in Hebei Province of China to test the procedure. In this study, when separately using PCI-RPC and ArcGIS-Spline tools directly to process the HR1/HR2 raw images, the orthorectification accuracies (root mean square errors, RMSEs for HR1/HR2 images were 2.94 m/2.81 m and 4.65 m/4.41 m, respectively. However, when using our newly proposed procedure, the corresponding RMSEs could be reduced to 1.10 m/1.07 m. The experimental results demonstrated that the new image processing procedure which integrates PCI-RPC and ArcGIS-Spline tools could significantly improve image orthorectification accuracy. Therefore, in terms of practice, the new procedure has the potential to use existing software products to easily improve image orthorectification accuracy.
Satellite imagery in a nuclear age
International Nuclear Information System (INIS)
Baines, P.J.
1998-01-01
Increasingly, high resolution satellite imaging systems are becoming available from multiple and diverse sources with capabilities useful for answering security questions. With increased supply, data availability and data authenticity may be assured. In a commercial market a supplier can ill afford the loss in market share that would result from any falsification of data. Similarly rising competitors willing to sell imagery of national security sites will decrease the tendency to endure self-imposed restrictions on sales of those sites. International organizations operating in the security interests of all nations might also gain preferential access. Costa for imagery will also fall to the point were individuals can afford purchases of satellite images. International organizations will find utility in exploiting imagery for solving international security problems. Housed within international organizations possessing competent staff, procedures, and 'shared destiny' stakes in resolving compliance discrepancies, the use of satellite imagery may provide a degree of stability in a world in which individuals, non-governmental organizations and governments may choose to exploit the available information for political gain. The use of satellite imagery outside these international organizations might not necessarily be aimed at seeking mutually beneficial solutions for international problems
Reconstructing Global-scale Ionospheric Outflow With a Satellite Constellation
Liemohn, M. W.; Welling, D. T.; Jahn, J. M.; Valek, P. W.; Elliott, H. A.; Ilie, R.; Khazanov, G. V.; Glocer, A.; Ganushkina, N. Y.; Zou, S.
2017-12-01
The question of how many satellites it would take to accurately map the spatial distribution of ionospheric outflow is addressed in this study. Given an outflow spatial map, this image is then reconstructed from a limited number virtual satellite pass extractions from the original values. An assessment is conducted of the goodness of fit as a function of number of satellites in the reconstruction, placement of the satellite trajectories relative to the polar cap and auroral oval, season and universal time (i.e., dipole tilt relative to the Sun), geomagnetic activity level, and interpolation technique. It is found that the accuracy of the reconstructions increases sharply from one to a few satellites, but then improves only marginally with additional spacecraft beyond 4. Increased dwell time of the satellite trajectories in the auroral zone improves the reconstruction, therefore a high-but-not-exactly-polar orbit is most effective for this task. Local time coverage is also an important factor, shifting the auroral zone to different locations relative to the virtual satellite orbit paths. The expansion and contraction of the polar cap and auroral zone with geomagnetic activity influences the coverage of the key outflow regions, with different optimal orbit configurations for each level of activity. Finally, it is found that reconstructing each magnetic latitude band individually produces a better fit to the original image than 2-D image reconstruction method (e.g., triangulation). A high-latitude, high-altitude constellation mission concept is presented that achieves acceptably accurate outflow reconstructions.
Data manage and communication of lunar orbital X-ray imaging analyzer in CE-1 satellite
International Nuclear Information System (INIS)
Wang Jinzhou; Wang Huanyu; Zhang Chengmo; Liang Xiaohua; Gao Min; CaoXuelei; Zhang Jiayu; Peng Wenxi; Cui Xingzhu; Xu Yupeng; Zhang Yongjie
2006-01-01
We present the software design for data management and communication software designed for the Lunar Orbital X-ray Imaging Analyzer in CE-1 Satellite. The software uses the appropriate format to assemble science data package and appropriate command respond mode, realizes the data transferring tasks through the 1553B bus on time, event though the channel bandwidth is under the limited. Also, the memory distribution and management of LOXIA (remote terminal) that fitted the communication with BC(Bus Controller) was introduced. Furthermore, for the spatial application, the security and reliability of software are emphasized. (authors)
Courtland, Hayden-William; Nasser, Philip; Goldstone, Andrew B; Spevak, Lyudmila; Boskey, Adele L; Jepsen, Karl J
2008-11-01
Fracture susceptibility is heritable and dependent upon bone morphology and quality. However, studies of bone quality are typically overshadowed by emphasis on bone geometry and bone mineral density. Given that differences in mineral and matrix composition exist in a variety of species, we hypothesized that genetic variation in bone quality and tissue-level mechanical properties would also exist within species. Sixteen-week-old female A/J, C57BL/6J (B6), and C3H/HeJ (C3H) inbred mouse femora were analyzed using Fourier transform infrared imaging and tissue-level mechanical testing for variation in mineral composition, mineral maturity, collagen cross-link ratio, and tissue-level mechanical properties. A/J femora had an increased mineral-to-matrix ratio compared to B6. The C3H mineral-to-matrix ratio was intermediate of A/J and B6. C3H femora had reduced acid phosphate and carbonate levels and an increased collagen cross-link ratio compared to A/J and B6. Modulus values paralleled mineral-to-matrix values, with A/J femora being the most stiff, B6 being the least stiff, and C3H having intermediate stiffness. In addition, work-to-failure varied among the strains, with the highly mineralized and brittle A/J femora performing the least amount of work-to-failure. Inbred mice are therefore able to differentially modulate the composition of their bone mineral and the maturity of their bone matrix in conjunction with tissue-level mechanical properties. These results suggest that specific combinations of bone quality and morphological traits are genetically regulated such that mechanically functional bones can be constructed in different ways.
CBERS-2B Brazilian remote sensing satellite to help to monitor the Bolivia-Brazil gas pipeline
Energy Technology Data Exchange (ETDEWEB)
Hernandes, Gilberto Luis Sanches [TBG Transportadora Brasileira Gasoduto Bolivia-Brasil, Rio de Janeiro, RJ (Brazil)
2009-07-01
This paper presents the results of CBERS-2B' Brazilian Remote Sensing Satellite to help to monitor the Bolivia-Brazil Gas Pipeline. The CBERS-2B is the third satellite launched in 2007 by the CBERS Program (China-Brazil Earth Resources Satellite) and the innovation was the HRC camera that produces high resolution images. It will be possible to obtain one complete coverage of the country every 130 days. In this study, 2 images from different parts of the Bolivia- Brazil Gas Pipeline were selected. Image processing involved the geometric registration of CBERS-2B satellite images with airborne images, contrast stretch transform and pseudo color. The analysis of satellite and airborne images in a GIS software to detect third party encroachment was effective to detect native vegetation removal, street construction, growth of urban areas, farming and residential/industrial land development. Very young, the CBERS-2B is a good promise to help to inspect the areas along the pipelines. (author)
Observation of GEO Satellite Above Thailand’s Sky
Kasonsuwan, K.; Wannawichian, S.; Kirdkao, T.
2017-09-01
The direct observations of Geostationary Orbit (GEO) satellites above Thailand’s sky by 0.7-meters telescope were proceeded at Inthanon Mt., Chiang Mai, Thailand. The observation took place at night with Sidereal Stare Mode (SSM). With this observing mode, the moving object will appear as a streak. The star identification for image calibration is based on (1) a star catalogue, (2) the streak detection of the satellite using the software and (3) the extraction of the celestial coordinate of the satellite as a predicted position. Finally, the orbital elements for GEO satellites were calculated.
Evaluating minerals of environmental concern using spectroscopy
Swayze, G.A.; Clark, R.N.; Higgins, C.T.; Kokaly, R.F.; Livo, K. Eric; Hoefen, T.M.; Ong, C.; Kruse, F.A.
2006-01-01
Imaging spectroscopy has been successfully used to aid researchers in characterizing potential environmental impacts posed by acid-rock drainage, ore-processing dust on mangroves, and asbestos in serpentine mineral deposits and urban dust. Many of these applications synergistically combine field spectroscopy with remote sensing data, thus allowing more-precise data calibration, spectral analysis of the data, and verification of mapping. The increased accuracy makes these environmental evaluation tools efficient because they can be used to focus field work on those areas most critical to the research effort. The use of spectroscopy to evaluate minerals of environmental concern pushes current imaging spectrometer technology to its limits; we present laboratory results that indicate the direction for future designs of imaging spectrometers.
USING SATELLITE IMAGES FOR WIRELESS NETWORK PLANING IN BAKU CITY
Directory of Open Access Journals (Sweden)
M. Gojamanov
2013-04-01
Full Text Available It is a well known fact that the Information-Telecommunication and Space research technologies are the fields getting much more benefits from the achievements of the scientific and technical progress. In many cases, these areas supporting each other have improved the conditions for their further development. For instance, the intensive development in the field of the mobile communication has caused the rapid progress of the Space research technologies and vice versa.Today it is impossible to solve one of the most important tasks of the mobile communication as Radio Frecance planning without the 2D and 3D digital maps. The compiling of such maps is much more efficient by means of the space images. Because the quality of the space images has been improved and developed, especially at the both spectral and spatial resolution points. It has been possible to to use 8 Band images with the spatial resolution of 50 sm. At present, in relation to the function 3G of mobile communications one of the main issues facing mobile operator companies is a high-precision 3D digital maps. It should be noted that the number of mobile phone users in the Republic of Azerbaijan went forward other Community of Independent States Countries. Of course, using of aerial images for 3D mapping would be optimal. However, depending on a number of technical and administrative problems aerial photography cannot be used. Therefore, the experience of many countries shows that it will be more effective to use the space images with the higher resolution for these issues. Concerning the fact that the mobile communication within the city of Baku has included 3G function there were ordered stereo images wih the spatial resolution of 50 cm for the 150 sq.km territory occupying the central part of the city in order to compile 3D digital maps. The images collected from the WorldView-2 satellite are 4-Band Bundle(Pan+MS1 stereo images. Such kind of imagery enable to automatically
Combining high-resolution satellite images and altimetry to estimate the volume of small lakes
Baup, F.; Frappart, F.; Maubant, J.
2014-05-01
This study presents an approach to determining the volume of water in small lakes (manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches (HRBV and ABV) are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2ABV = 0.98, RMSEABV = 5%, R2HRBV = 0.90, and RMSEABV = 7.4%), assuming a time-varying triangular shape for the shore slope of the lake (this form is well adapted since it implies a difference inferior to 2% between the theoretical volume of the lake and the one estimated from bathymetry). The third method (AHRBVC) combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2AHRBVC = 0.98) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.
Landsat—Earth observation satellites
,
2015-11-25
Since 1972, Landsat satellites have continuously acquired space-based images of the Earth’s land surface, providing data that serve as valuable resources for land use/land change research. The data are useful to a number of applications including forestry, agriculture, geology, regional planning, and education. Landsat is a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). NASA develops remote sensing instruments and the spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and data distribution. The result of this program is an unprecedented continuing record of natural and human-induced changes on the global landscape.
Analysis of Visual Interpretation of Satellite Data
Svatonova, H.
2016-06-01
Millions of people of all ages and expertise are using satellite and aerial data as an important input for their work in many different fields. Satellite data are also gradually finding a new place in education, especially in the fields of geography and in environmental issues. The article presents the results of an extensive research in the area of visual interpretation of image data carried out in the years 2013 - 2015 in the Czech Republic. The research was aimed at comparing the success rate of the interpretation of satellite data in relation to a) the substrates (to the selected colourfulness, the type of depicted landscape or special elements in the landscape) and b) to selected characteristics of users (expertise, gender, age). The results of the research showed that (1) false colour images have a slightly higher percentage of successful interpretation than natural colour images, (2) colourfulness of an element expected or rehearsed by the user (regardless of the real natural colour) increases the success rate of identifying the element (3) experts are faster in interpreting visual data than non-experts, with the same degree of accuracy of solving the task, and (4) men and women are equally successful in the interpretation of visual image data.
ANALYSIS OF VISUAL INTERPRETATION OF SATELLITE DATA
Directory of Open Access Journals (Sweden)
H. Svatonova
2016-06-01
Full Text Available Millions of people of all ages and expertise are using satellite and aerial data as an important input for their work in many different fields. Satellite data are also gradually finding a new place in education, especially in the fields of geography and in environmental issues. The article presents the results of an extensive research in the area of visual interpretation of image data carried out in the years 2013 - 2015 in the Czech Republic. The research was aimed at comparing the success rate of the interpretation of satellite data in relation to a the substrates (to the selected colourfulness, the type of depicted landscape or special elements in the landscape and b to selected characteristics of users (expertise, gender, age. The results of the research showed that (1 false colour images have a slightly higher percentage of successful interpretation than natural colour images, (2 colourfulness of an element expected or rehearsed by the user (regardless of the real natural colour increases the success rate of identifying the element (3 experts are faster in interpreting visual data than non-experts, with the same degree of accuracy of solving the task, and (4 men and women are equally successful in the interpretation of visual image data.
Cunha-Lignon, M.; Kampel, M.; Menghini, R.P.; Schaeffer-Novelli, Y.; Cintrón, G.; Dahdouh-Guebas, F.
2011-01-01
The current paper examines the growth and spatio-temporal variation of mangrove forests in response to depositional processes and different salinity conditions. Data from mangrove vegetation structure collected at permanent plots and satellite images were used. In the northern sector important environmental changes occurred due to an artificial channel producing modifications in salinity. The southern sector is considered the best conserved mangrove area along the coast of São Paulo State, Br...
International Nuclear Information System (INIS)
Fraser, R H; Olthof, I; Carrière, M; Deschamps, A; Pouliot, D
2011-01-01
Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM + satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1–25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.
Mineral exploration with ERTS imagery. [Colorado
Nicolais, S. M.
1974-01-01
Ten potential target areas for metallic mineral exploration were selected on the basis of a photo-lineament interpretation of the ERTS image 1172-17141 in central Colorado. An evaluation of bias indicated that prior geologic knowledge of the region had little, if any, effect on target selection. In addition, a contoured plot of the frequency of photo-lineament intersections was made to determine what relationships exist between the photo-lineaments and mineral districts. Comparison of this plot with a plot of the mineral districts indicates that areas with a high frequency of intersections commonly coincide with known mineral districts. The results of this experiment suggest that photo-lineaments are fractures or fracture-controlled features, and their distribution may be a guide to metallic mineral deposits in Colorado, and probably other areas as well.
Hoang, Nguyen Tien; Koike, Katsuaki
2018-03-01
Hyperspectral remote sensing generally provides more detailed spectral information and greater accuracy than multispectral remote sensing for identification of surface materials. However, there have been no hyperspectral imagers that cover the entire Earth surface. This lack points to a need for producing pseudo-hyperspectral imagery by hyperspectral transformation from multispectral images. We have recently developed such a method, a Pseudo-Hyperspectral Image Transformation Algorithm (PHITA), which transforms Landsat 7 ETM+ images into pseudo-EO-1 Hyperion images using multiple linear regression models of ETM+ and Hyperion band reflectance data. This study extends the PHITA to transform TM, OLI, and EO-1 ALI sensor images into pseudo-Hyperion images. By choosing a part of the Fish Lake Valley geothermal prospect area in the western United States for study, the pseudo-Hyperion images produced from the TM, ETM+, OLI, and ALI images by PHITA were confirmed to be applicable to mineral mapping. Using a reference map as the truth, three main minerals (muscovite and chlorite mixture, opal, and calcite) were identified with high overall accuracies from the pseudo-images (> 95% and > 42% for excluding and including unclassified pixels, respectively). The highest accuracy was obtained from the ALI image, followed by ETM+, TM, and OLI images in descending order. The TM, OLI, and ALI images can be alternatives to ETM+ imagery for the hyperspectral transformation that aids the production of pseudo-Hyperion images for areas without high-quality ETM+ images because of scan line corrector failure, and for long-term global monitoring of land surfaces.
NOAA Geostationary Operational Environmental Satellite (GOES) Imager Data
National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Geostationary Operational Environmental Satellite (GOES) series provides continuous measurements of the atmosphere and surface over the Western Hemisphere....
Near-infrared detection of ammonium minerals at Ivanhoe Hot Springs, Nevada
Krohn, M. D.
1986-01-01
Airborne Imaging Spectrometer (AIS) data were collected over the fossil hot spring deposit at Ivanhoe, Nevada in order to determine the surface distribution of NH4-bearing minerals. Laboratory studies show that NH4-bearing minerals have characteristic absorption features in the near-infrared (NIR). Ammonium-bearing feldspars and alunites were observed at the surface of Ivanhoe using a hand-held radiometer. However, first look analysis of the AIS images showed that the line was about 500 m east of its intended mark, and the vegetation cover was sufficiently dense to inhibit preliminary attempts at making relative reflectance images for detection of ammonium minerals.
A world of minerals in your mobile device
Jenness, Jane E.; Ober, Joyce A.; Wilkins, Aleeza M.; Gambogi, Joseph
2016-09-15
Mobile phones and other high-technology communications devices could not exist without mineral commodities. More than one-half of all components in a mobile device—including its electronics, display, battery, speakers, and more—are made from mined and semiprocessed materials (mineral commodities). Some mineral commodities can be recovered as byproducts during the production and processing of other commodities. As an example, bauxite is mined for its aluminum content, but gallium is recovered during the aluminum production process. The images show the ore minerals (sources) of some mineral commodities that are used to make components of a mobile device. On the reverse side, the map and table depict the major source countries producing these mineral commodities along with how these commodities are used in mobile devices. For more information on minerals, visit http://minerals.usgs.gov.
Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images
Chiang, Y.; Chen, K.
2013-12-01
This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.
Satellite-Based Sunshine Duration for Europe
Directory of Open Access Journals (Sweden)
Bodo Ahrens
2013-06-01
Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.
International Nuclear Information System (INIS)
2001-01-01
This survey is based on the scope of work signed between the Japanese government and the Oriental Republic of Uruguay on 24 November 2000. The purpose of this is to clarify both the geologic appearance and the occurrence of the ore fields of mineral deposits in the San Jose and Arroyo Grande area in this country, with the aim of discovering new ore deposits. In addition, another purpose is to transfer the technology to the involved organizations of the object country. The survey is conceived as a three year project initiated in 2000, and this fiscal year falls on the first phase.This survey consist of this existing data analysis, the geological interpretation of satellite image data, the geological survey and geochemical prospecting
Energy Technology Data Exchange (ETDEWEB)
NONE
2001-07-01
This survey is based on the scope of work signed between the Japanese government and the Oriental Republic of Uruguay on 24 November 2000. The purpose of this is to clarify both the geologic appearance and the occurrence of the ore fields of mineral deposits in the San Jose and Arroyo Grande area in this country, with the aim of discovering new ore deposits. In addition, another purpose is to transfer the technology to the involved organizations of the object country. The survey is conceived as a three year project initiated in 2000, and this fiscal year falls on the first phase.This survey consist of this existing data analysis, the geological interpretation of satellite image data, the geological survey and geochemical prospecting
SUPERPIXEL BASED FACTOR ANALYSIS AND TARGET TRANSFORMATION METHOD FOR MARTIAN MINERALS DETECTION
Directory of Open Access Journals (Sweden)
X. Wu
2018-04-01
Full Text Available The Factor analysis and target transformation (FATT is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.
Operational Analysis of Time-Optimal Maneuvering for Imaging Spacecraft
2013-03-01
Figure 1. In-Track Stereo Satellite Image Collection. From [7] ............................ 3 Figure 2. NASA MODIS Terra Satellite Image of Oil...satellites for remote sensing ranges from military applications to tracking global weather patterns, tectonic activity, surface vegetation , ocean...imagery [22]. Figure 2 shows an example of a satellite image captured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra
Soto-Pinto, C.; Poblete, A.; Arellano-Baeza, A. A.; Sanchez, G.
2010-12-01
A software for extraction and analysis of the lineaments has been developed and applied for the tracking of the accumulation/relaxation of stress in the Earth’s crust due to seismic and volcanic activity. A lineament is a straight or a somewhat curved feature in a satellite image, which reflects, at least partially, presence of faults in the crust. The technique of lineament extraction is based on the application of directional filters and Hough transform. The software has been checked for several earthquakes occurred in the Pacific coast of the South America with the magnitude > 4 Mw, analyzing temporal sequences of the ASTER/TERRA multispectral satellite images for the regions around an epicenter. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changes significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth’s crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion.
Applications of Geostationary Satellite Data to Aviation
Ellrod, Gary P.; Pryor, Kenneth
2018-03-01
Weather is by far the most important factor in air traffic delays in the United States' National Airspace System (NAS) according to the Federal Aviation Administration (FAA). Geostationary satellites have been an effective tool for the monitoring of meteorological conditions that affect aviation operations since the launch of the first Synchronous Meteorological Satellite (SMS) in the United States in 1974. This paper will review the global use of geostationary satellites in support of aviation weather since their inception, with an emphasis on the latest generation of satellites, such as Geostationary Operational Environmental Satellite (GOES)-R (16) with its Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM). Specific applications discussed in this paper include monitoring of convective storms and their associated hazards, fog and low stratus, turbulence, volcanic hazards, and aircraft icing.
Framework of Jitter Detection and Compensation for High Resolution Satellites
Directory of Open Access Journals (Sweden)
Xiaohua Tong
2014-05-01
Full Text Available Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1 The first one is based on multispectral images using parallax between two different bands in the image; (2 The second is based on stereo images using rational polynomial coefficients (RPCs; (3 The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1 The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2 The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer, LRO (Lunar Reconnaissance Orbiter and ZY-3 (ZiYuan-3 demonstrate the promising performance and feasibility of the proposed framework.
National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 1999 on board the Terra satellite platform (a...
National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 2002 on board the Aqua satellite platform (a...
Buxner, S.; Orchard, A.; Colodner, D.; Schwartz, K.; Crown, D. A.; King, B.; Baldridge, A.
2012-03-01
The Laurel Clark Earth Camp program provides middle and high school students and teachers opportunities to explore local environmental issues and global change through field-experiences, inquiry exercises, and exploring satellite images.
Salama, M.; Radwan, M.; van der Velde, R.
2012-01-01
This paper describes a hydro-optical model for deriving water quality variables from satellite images, hereafter HydroSat. HydroSat corrects images for atmospheric interferences and simultaneously retrieves water quality variables. An application of HydroSat to Landsat Enhanced Thematic Mapper (ETM)
NOAA-L satellite arrives at Vandenberg AFB
2000-01-01
Outside the B16-10 spacecraft processing hangar at Vandenberg Air Force Base, Calif., a crated National Oceanic and Atmospheric Administration (NOAA-L) satellite is lowered to the ground before being moved inside. NOAA-L is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket. The Use of Backscattered Electron Imaging and Transmission Electron Microscopy to Assess Bone Architecture and Mineral Loci: Effect of Intermittent Slow-Release Sodium Fluoride Therapy
Zerwekh, Joseph E.; Bellotto, Dennis; Prostak, Kenneth S.; Hagler, Herbert K.; Pak, Charles Y. C.
1996-04-01
Backscattered electron imaging (BEI) and transmission electron microscopy (TEM) were used to examine the effects of treatment with intermittent slow-release sodium fluoride (SRNaF) and continuous calcium citrate on bone architecture and crystallinity. Examination was performed in nondecalcified biopsies obtained from patients following up to four years of therapy (placebo or SRNaF) and compared to pretreatment biopsies from each patient, as well as to bone from young, normal subjects. BEI images disclosed increased areas of recent bone formation following fluoride administration. There was no evidence of a mineralization defect in any biopsy and both cortical and trabecular architecture remained normal. TEM analysis demonstrated intrafibrillar platelike crystals and extrafibrillar needlelike crystals for both the pre- and post-treatment biopsies as well as for the bone from young normal subjects. There was no evidence of increased crystal size or of an increase in extrafibrillar mineral deposition. These observations suggest that intermittent SRNaF and continuous calcium therapy exerts an anabolic action on the skeleton not accompanied by a mineralization defect or an alteration of bone mineral deposition. The use of BEI and TEM holds promise for the study of the pathophysiology and treatment of metabolic bone diseases.
Ramsey, Elijah W.; Werle, Dirk; Lu, Zhong; Rangoonwala, Amina; Suzuoki, Yukihiro
2009-01-01
The synergistic application of optical and radar satellite imagery improves emergency response and advance coastal monitoring from the realm of “opportunistic” to that of “strategic.” As illustrated by the Hurricane Ike example, synthetic aperture radar imaging capabilities are clearly applicable for emergency response operations, but they are also relevant to emergency environmental management. Integrated with optical monitoring, the nearly real-time availability of synthetic aperture radar provides superior consistency in status and trends monitoring and enhanced information concerning causal forces of change that are critical to coastal resource sustainability, including flooding extent, depth, and frequency.
SatelliteDL: a Toolkit for Analysis of Heterogeneous Satellite Datasets
Galloy, M. D.; Fillmore, D.
2014-12-01
SatelliteDL is an IDL toolkit for the analysis of satellite Earth observations from a diverse set of platforms and sensors. The core function of the toolkit is the spatial and temporal alignment of satellite swath and geostationary data. The design features an abstraction layer that allows for easy inclusion of new datasets in a modular way. Our overarching objective is to create utilities that automate the mundane aspects of satellite data analysis, are extensible and maintainable, and do not place limitations on the analysis itself. IDL has a powerful suite of statistical and visualization tools that can be used in conjunction with SatelliteDL. Toward this end we have constructed SatelliteDL to include (1) HTML and LaTeX API document generation,(2) a unit test framework,(3) automatic message and error logs,(4) HTML and LaTeX plot and table generation, and(5) several real world examples with bundled datasets available for download. For ease of use, datasets, variables and optional workflows may be specified in a flexible format configuration file. Configuration statements may specify, for example, a region and date range, and the creation of images, plots and statistical summary tables for a long list of variables. SatelliteDL enforces data provenance; all data should be traceable and reproducible. The output NetCDF file metadata holds a complete history of the original datasets and their transformations, and a method exists to reconstruct a configuration file from this information. Release 0.1.0 distributes with ingest methods for GOES, MODIS, VIIRS and CERES radiance data (L1) as well as select 2D atmosphere products (L2) such as aerosol and cloud (MODIS and VIIRS) and radiant flux (CERES). Future releases will provide ingest methods for ocean and land surface products, gridded and time averaged datasets (L3 Daily, Monthly and Yearly), and support for 3D products such as temperature and water vapor profiles. Emphasis will be on NPP Sensor, Environmental and
Rowan, L.C.; Hook, S.J.; Abrams, M.J.; Mars, J.C.
2003-01-01
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 14-band multispectral instrument on board the Earth Observing System (EOS), TERRA. The three bands between 0.52 and 0.86 ??m and the six bands from 1.60 and 2.43 ??m, which have 15- and 30-m spatial resolution, respectively, were selected primarily for making remote mineralogical determinations. The Cuprite, Nevada, mining district comprises two hydrothermal alteration centers where Tertiary volcanic rocks have been hydrothermally altered mainly to bleached silicified rocks and opalized rocks, with a marginal zone of limonitic argilized rocks. Country rocks are mainly Cambrian phyllitic siltstone and limestone. Evaluation of an ASTER image of the Cuprite district shows that spectral reflectance differences in the nine bands in the 0.52 to 2.43 ??m region provide a basis for identifying and mapping mineralogical components which characterize the main hydrothermal alteration zones: opal is the spectrally dominant mineral in the silicified zone; whereas, alunite and kaolinite are dominant in the opalized zone. In addition, the distribution of unaltered country rocks was mapped because of the presence of spectrally dominant muscovite in the siltstone and calcite in limestone, and the tuffaceous rocks and playa deposits were distinguishable due to their relatively flat spectra and weak absorption features at 2.33 and 2.20 ??m, respectively. An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) image of the study area was processed using a similar methodology used with the ASTER data. Comparison of the ASTER and AVIRIS results shows that the results are generally similar, but the higher spectral resolution of AVIRIS (224 bands) permits identification of more individual minerals, including certain polymorphs. However, ASTER has recorded images of more than 90 percent of the Earth's land surface with less than 20 percent cloud cover, and these data are available at nominal or no cost
Tele-ultrasound using ATM over a T-1 satellite connection
Williamson, Morgan P.; Suitor, Charles T.; de Treville, Robert E.; Freckleton, Michael W.; Kinsey, Van; Goeringer, Fred; Lyche, David K.; Hunter, Bruce; Jennings, Neal E.; Shelton, Philip D.; Marcy, Jon; Poore, Tom; North, Jack
1996-04-01
In September 1995 the United States military conducted a demonstration project to provide live ultrasound video and diagnostic DICOM still images using GTE's asynchronous transfer mode (ATM) technologies over an Orion T-1 satellite link. Still images were frame-grabbed from a Diasonics ultrasound and sent to the ALI Wide Area Network system. A group of diagnostic images was then sent in DICOM 3.0 format over a virtual ethernet satellite link from Chantilly, Virginia to Dayton, Ohio. These images came across a DICOM gateway into the Medical Diagnostic Imaging Support (MDIS) System. Live video from the ultrasound was also routed through a CLI Radiance VTC over the satellite to a VTC in Ohio. The video bandwidth was progressively narrowed with two radiologists determining the minimal acceptable bandwidth for detecting test objects in a phantom. The radiologists accepted live video ultrasound at bandwidths as low as 384 kbps from the hands of an experienced ultrasonographer located hundreds of miles away. DICOM still images were sent uncompressed and were of acceptable image quality when viewed on the MDIS system. The technology demonstrated holds great promise for both deployed U.S. Military Forces and civil uses of remote radiology. Detailed network drawings and videotapes of the ultrasound examinations at the remote site are provided.
Adsorption of dextrin on hydrophobic minerals.
Beaussart, Audrey; Mierczynska-Vasilev, Agnieszka; Beattie, David A
2009-09-01
The adsorption of dextrin on talc, molybdenite, and graphite (three naturally hydrophobic minerals) has been compared. Adsorption isotherms and in situ tapping mode atomic force microscope (TMAFM) imaging have enabled polymer adsorbed amount and morphology of the adsorbed layer (area coverage and polymer domain size) to be determined and also the amount of hydration water in the structure of the adsorbed layer. The effect of the polymer on the mineral contact angles, measured by the captive bubble method on cleaved mineral surfaces, indicates clear correlations between the hydrophobicity reduction of the minerals, the adsorbed amount, and the surface coverage of the adsorbed polymer. Predictions of the flotation recovery of the treated mineral phases have been confirmed by performing batch flotation experiments. The influence of the polymer surface coverage on flotation recovery has highlighted the importance of this key parameter in the predictions of depressant efficiency. The roles of the initial hydrophobicity and the surface structure of the mineral basal plane in determining adsorption parameters and flotation response of the polymer-treated minerals are also discussed.
Definition imaging of an orebody with the radio imaging method (RIM)
International Nuclear Information System (INIS)
Stolarczyk, L.G.
1992-01-01
Waste rock dilution is an economic concern in the planning and design of mining methods for mineralized ore zones. Diamond core drilling and mineralogical examination of core are routinely used to determine the general shape of the ore body. Drilling on closer centers enhances the definition of the mineralization and oregrade across the orebody. In a practical sense, drilling time and cost limit definition. Crosshole scanning between drillholes with the radio imaging method (RIM) has been used to map changes in mineralization in the rock mass. The magnitude and phase of the RIM radio wave depend on the electrical conductivity of the rock mass. The conductivity strongly depends on the percent mineralization. Since the attenuation rate and phase constants of the radio wave are proportional to the one half power of conductivity, the measured crosshole radio wave data can be processed in a tomography algorithm to reconstruct images (map the change in conductivity (mineralization)). The tomography image enhances definition in the orebody while reducing the number of drillholes. This paper compares reconstructed images of the radio wave propagation constants to percent mineralization in the ore body
Roads Data Conflation Using Update High Resolution Satellite Images
Abdollahi, A.; Riyahi Bakhtiari, H. R.
2017-11-01
Urbanization, industrialization and modernization are rapidly growing in developing countries. New industrial cities, with all the problems brought on by rapid population growth, need infrastructure to support the growth. This has led to the expansion and development of the road network. A great deal of road network data has made by using traditional methods in the past years. Over time, a large amount of descriptive information has assigned to these map data, but their geometric accuracy and precision is not appropriate to today's need. In this regard, the improvement of the geometric accuracy of road network data by preserving the descriptive data attributed to them and updating of the existing geo databases is necessary. Due to the size and extent of the country, updating the road network maps using traditional methods is time consuming and costly. Conversely, using remote sensing technology and geographic information systems can reduce costs, save time and increase accuracy and speed. With increasing the availability of high resolution satellite imagery and geospatial datasets there is an urgent need to combine geographic information from overlapping sources to retain accurate data, minimize redundancy, and reconcile data conflicts. In this research, an innovative method for a vector-to-imagery conflation by integrating several image-based and vector-based algorithms presented. The SVM method for image classification and Level Set method used to extract the road the different types of road intersections extracted from imagery using morphological operators. For matching the extracted points and to find the corresponding points, matching function which uses the nearest neighborhood method was applied. Finally, after identifying the matching points rubber-sheeting method used to align two datasets. Two residual and RMSE criteria used to evaluate accuracy. The results demonstrated excellent performance. The average root-mean-square error decreased from 11.8 to 4.1 m.
Study of Arabian Red Sea coastal soils as potential mineral dust sources
Prakash, P. Jish; Stenchikov, Georgiy L.; Tao, Weichun; Yapici, Tahir; Warsama, Bashir H.; Engelbrecht, Johann
2016-01-01
Both Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) satellite observations suggest that the narrow heterogeneous Red Sea coastal region is a frequent source of airborne dust that, because of its proximity, directly affects the Red Sea and coastal urban centers. The potential of soils to be suspended as airborne mineral dust depends largely on soil texture, moisture content, and particle size distributions. Airborne dust inevitably carries the mineralogical and chemical signature of a parent soil. The existing soil databases are too coarse to resolve the small but important coastal region. The purpose of this study is to better characterize the mineralogical, chemical and physical properties of soils from the Red Sea Arabian coastal plane, which in turn will help to improve assessment of dust effect on the Red Sea and land environmental systems and urban centers. Thirteen surface soils from the hot-spot areas of wind-blown mineral dust along the Red Sea coastal plain were sampled for analysis. Analytical methods included Optical Microscopy, X-ray diffraction (XRD), Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), Ion Chromatography (IC), Scanning Electron Microscopy (SEM), and Laser Particle Size Analysis (LPSA). We found that the Red Sea coastal soils contain major components of quartz and feldspar, as well as lesser but variable amounts of amphibole, pyroxene, carbonate, clays, and micas, with traces of gypsum, halite, chlorite, epidote and oxides. The wide range of minerals in the soil samples was ascribed to the variety of igneous and metamorphic provenance rocks of the Arabian Shield forming the escarpment to the east of the Red Sea coastal plain. The analysis revealed that the samples contain compounds of nitrogen, phosphorus and iron that are essential nutrients to marine life. The analytical results from this study will provide a valuable input into dust emission models used
Study of Arabian Red Sea coastal soils as potential mineral dust sources
Prakash, P. Jish
2016-03-23
Both Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) satellite observations suggest that the narrow heterogeneous Red Sea coastal region is a frequent source of airborne dust that, because of its proximity, directly affects the Red Sea and coastal urban centers. The potential of soils to be suspended as airborne mineral dust depends largely on soil texture, moisture content, and particle size distributions. Airborne dust inevitably carries the mineralogical and chemical signature of a parent soil. The existing soil databases are too coarse to resolve the small but important coastal region. The purpose of this study is to better characterize the mineralogical, chemical and physical properties of soils from the Red Sea Arabian coastal plane, which in turn will help to improve assessment of dust effect on the Red Sea and land environmental systems and urban centers. Thirteen surface soils from the hot-spot areas of wind-blown mineral dust along the Red Sea coastal plain were sampled for analysis. Analytical methods included Optical Microscopy, X-ray diffraction (XRD), Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), Ion Chromatography (IC), Scanning Electron Microscopy (SEM), and Laser Particle Size Analysis (LPSA). We found that the Red Sea coastal soils contain major components of quartz and feldspar, as well as lesser but variable amounts of amphibole, pyroxene, carbonate, clays, and micas, with traces of gypsum, halite, chlorite, epidote and oxides. The wide range of minerals in the soil samples was ascribed to the variety of igneous and metamorphic provenance rocks of the Arabian Shield forming the escarpment to the east of the Red Sea coastal plain. The analysis revealed that the samples contain compounds of nitrogen, phosphorus and iron that are essential nutrients to marine life. The analytical results from this study will provide a valuable input into dust emission models used
Ferrán, Ángel; Bernabé, Sergio; García-Rodríguez, Pablo; Plaza, Antonio
2012-10-01
In this paper, we develop a new web-based system for unsupervised classification of satellite images available from the Google Maps engine. The system has been developed using the Google Maps API and incorporates functionalities such as unsupervised classification of image portions selected by the user (at the desired zoom level). For this purpose, we use a processing chain made up of the well-known ISODATA and k-means algorithms, followed by spatial post-processing based on majority voting. The system is currently hosted on a high performance server which performs the execution of classification algorithms and returns the obtained classification results in a very efficient way. The previous functionalities are necessary to use efficient techniques for the classification of images and the incorporation of content-based image retrieval (CBIR). Several experimental validation types of the classification results with the proposed system are performed by comparing the classification accuracy of the proposed chain by means of techniques available in the well-known Environment for Visualizing Images (ENVI) software package. The server has access to a cluster of commodity graphics processing units (GPUs), hence in future work we plan to perform the processing in parallel by taking advantage of the cluster.
Surface analytical techniques applied to minerals processing
International Nuclear Information System (INIS)
Smart, R.St.C.
1991-01-01
An understanding of the chemical and physical forms of the chemically altered layers on the surfaces of base metal sulphides, particularly in the form of hydroxides, oxyhydroxides and oxides, and the changes that occur in them during minerals processing lies at the core of a complete description of flotation chemistry. This paper reviews the application of a variety of surface-sensitive techniques and methodologies applied to the study of surface layers on single minerals, mixed minerals, synthetic ores and real ores. Evidence from combined XPS/SAM/SEM studies have provided images and analyses of three forms of oxide, oxyhydroxide and hydroxide products on the surfaces of single sulphide minerals, mineral mixtures and complex sulphide ores. 4 refs., 2 tabs., 4 figs
Time-lapse Raman imaging of osteoblast differentiation
Hashimoto, Aya; Yamaguchi, Yoshinori; Chiu, Liang-Da; Morimoto, Chiaki; Fujita, Katsumasa; Takedachi, Masahide; Kawata, Satoshi; Murakami, Shinya; Tamiya, Eiichi
2015-07-01
Osteoblastic mineralization occurs during the early stages of bone formation. During this mineralization, hydroxyapatite (HA), a major component of bone, is synthesized, generating hard tissue. Many of the mechanisms driving biomineralization remain unclear because the traditional biochemical assays used to investigate them are destructive techniques incompatible with viable cells. To determine the temporal changes in mineralization-related biomolecules at mineralization spots, we performed time-lapse Raman imaging of mouse osteoblasts at a subcellular resolution throughout the mineralization process. Raman imaging enabled us to analyze the dynamics of the related biomolecules at mineralization spots throughout the entire process of mineralization. Here, we stimulated KUSA-A1 cells to differentiate into osteoblasts and conducted time-lapse Raman imaging on them every 4 hours for 24 hours, beginning 5 days after the stimulation. The HA and cytochrome c Raman bands were used as markers for osteoblastic mineralization and apoptosis. From the Raman images successfully acquired throughout the mineralization process, we found that β-carotene acts as a biomarker that indicates the initiation of osteoblastic mineralization. A fluctuation of cytochrome c concentration, which indicates cell apoptosis, was also observed during mineralization. We expect time-lapse Raman imaging to help us to further elucidate osteoblastic mineralization mechanisms that have previously been unobservable.
A Comparative Study of Quantitative Assessment of Bone Mineral Density of Mandible
International Nuclear Information System (INIS)
Park, Won Kyl; Choi, Eui Hwan; Kim, Jae Duk
1999-01-01
This study was performed to compare the bone mineral densities measured at mandibular premolar area by copper-equivalent image and hydroxyapatite phantom with those measured at radius by dual energy absorptiometry and to evaluate the clinical usefulness of Digital system with slide scanner, copper-equivalent image, and hydroxyapatite phantom. For experiment, intraoral radiograms of 15 normal subjects ranged from 20 years old to 67 old were taken with copper-step wedge at mandibular premolar area and bone mineral densities calculated by conversion equation to bone mineral density of hydroxyapatite were compared with those measured at radius distal 1/3 area by Hologic QDR-1000. Obtained results as follows: 1) The conversion equation was Y=5.97X-0.25 and its determination coefficient was 0.9967. The coefficient of variation in the measurement of copper-equivalent value ranged from 4% to 8% and showed high reproducibility. 2) The coefficient of variation in the measurement of bone mineral density by the equation ranged from 7% to 8% and showed high reproducibility. 3) The bone mineral densities ranged from 0.35 to 0.79 g/cm 2 at mandibular premolar area. 4) The correlation coefficient between bone mineral densities at mandibular premolar area and those at radius distal 1/3 area was 0.8965. As summary, digital image analyzing system using copper-equivalent image and hydroxyapatite phantom appeared to be clinically useful to measure the bone mineral density at dental area.
Green, R. O.; Realmuto, V. J.; Thompson, D. R.; Mahowald, N. M.; Pérez García-Pando, C.; Miller, R. L.; Clark, R. N.; Swayze, G. A.; Okin, G. S.
2015-12-01
Mineral dust emitted from the Earth's surface is a principal contributor to direct radiative forcing over the arid regions, where shifts in climate have a significant impact on agriculture, precipitation, and desert encroachment around the globe. Dust particles contribute to both positive and negative forcing, depending on the composition of the particles. Particle composition is a function of the surface mineralogy of dust source regions, but poor knowledge of surface mineralogy on regional to global scales limits the skill of Earth System models to predict shifts in regional climate around the globe. Earth System models include the source, emission, transport and deposition phases of the dust cycle. In addition to direct radiative forcing contributions, mineral dust impacts include indirect radiative forcing, modification of the albedo and melting rates of snow and ice, kinetics of tropospheric photochemistry, formation and deposition of acidic aerosols, supply of nutrients to aquatic and terrestrial ecosystems, and impact on human health and safety. We demonstrate the ability to map mineral dust source composition in the Salton Sea dust source region with imaging spectroscopy measurements acquired as part of the NASA HyspIRI preparatory airborne campaign. These new spectroscopically derived compositional measurements provide a six orders of magnitude improvement over current atlases for this dust source region and provide a pathfinder example for a remote measurement approach to address this critical dust composition gap for global Earth System models.
Online Visualization and Analysis of Global Half-Hourly Infrared Satellite Data
Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory
2011-01-01
nfrared (IR) images (approximately 11-micron channel) recorded by satellite sensors have been widely used in weather forecasting, research, and classroom education since the Nimbus program. Unlike visible images, IR imagery can reveal cloud features without sunlight illumination; therefore, they can be used to monitor weather phenomena day and night. With geostationary satellites deployed around the globe, it is possible to monitor weather events 24/7 at a temporal resolution that polar-orbiting satellites cannot achieve at the present time. When IR data from multiple geostationary satellites are merged to form a single product--also known as a merged product--it allows for observing weather on a global scale. Its high temporal resolution (e.g., every half hour) also makes it an ideal ancillary dataset for supporting other satellite missions, such as the Tropical Rainfall Measuring Mission (TRMM), etc., by providing additional background information about weather system evolution.
Artificial Satellites and How to Observe Them
Schmude, Jr , Richard
2012-01-01
Astronomers' Observing Guides provide up-to-date information for amateur astronomers who want to know all about what it is they are observing. This is the basis for the first part of the book. The second part details observing techniques for practical astronomers, working with a range of different instruments. Every amateur astronomer sees "stars" that aren't natural objects steadily slide across the background of the sky. Artificial satellites can be seen on any night, and some are as bright as the planets. But can you identify which satellite or spent launch vehicle casing you are seeing? Do you know how to image it? Artificial Satellites and How to Observe Them describes all of the different satellites that can be observed, including communication, scientific, spy satellites, and of course, the International Space Station. Richard Schmude describes how to recognize them and even how to predict their orbits. The book tells how to observe artificial satellites with the unaided eye, binoculars and with telesc...
National Oceanic and Atmospheric Administration, Department of Commerce — The Visible and Infrared Imager/Radiometer Suite (VIIRS) is a multi-disciplinary instrument that is being flown on the Joint Polar Satellite System (JPSS) series of...
International Nuclear Information System (INIS)
Smith, Andrew J.A.; Grainger, Roy G.
2014-01-01
Mineral dust aerosol is a major component of natural airborne particulates. Using satellite measurements from the visible and near-infrared, there is insufficient information to retrieve a full microphysical and chemical description of an aerosol distribution. As such, refractive index is one of many parameters that must be implicitly assumed in order to obtain an optical depth retrieval. This is essentially a proxy for the dust mineralogy. Using a global soil map, it is shown that as long as a reasonable refractive index for dust is assumed, global dust variability is unlikely to cause significant variation in the optical properties of a dust aerosol distribution in the short-wave, and so should not greatly affect retrievals of mineral dust aerosol from space by visible and near-infrared radiometers. Errors in aerosol optical depth due to this variation are expected to be ≲1%. The work is framed around the ORAC AATSR aerosol retrieval, but is equally applicable to similar satellite retrievals. In this case, variations in the top-of-atmosphere reflectance caused by mineral variation are within the noise limits of the instrument. -- Highlights: • Global variation in dust aerosol refractive index is quantified using soil maps. • Resulting visible light scattering properties have limited variability. • Satellite aerosol retrievals do not need to account for varying dust refractive indices
Energy Technology Data Exchange (ETDEWEB)
Aranha, J.T. [Dept. Florestal, UTAD, 5001-801 Vila Real (Portugal); Viana, H.F. [Instituto Politecnico de Viseu, Escola Superior Agraria, Viseu (Portugal); Rodrigues, R. [Bioflag - Consulting - Santo Tirso (Portugal)
2008-07-01
The expected increase in Forest Biomass demand for energy production leads to derive expeditious and non-expensive techniques in order to classify vegetal land cover and evaluate the available biomass like to be harvested. Satellite image processing and classification, combined to field work, is a suitable tool to achieve these aims. A vegetation index (NDVI) was created by means of a Landsat TM image, from 2006, manipulation, in order to create a general vegetation map. Then, the same image was submitted to a supervised classification process in order to produce a land cover map (overall accuracy of 85%). In a second stage, they were collected NDVI values for each sampling plot, in order to update the database previous developed with data collected within forestry stands and shrubland. This data merging enabled to transform general vegetation map into available biomass within forestry stands and shrubland. The results showed a range of values from 0.25 up to 6.00 dry ton./ha for recent and former burnt areas recovered by Pinus pinaster (maritime pine) young trees and from 2.00 up to 9.00 dry ton./ha for recent and former burnt areas recovered by shrubs (e.g. genista or broom).
Estimating Advective Near-surface Currents from Ocean Color Satellite Images
2015-01-01
on the SuomiNational Polar-Orbiting Partner- ship (S- NPP ) satellite. The GOCI is the world’s first geostationary orbit satellite sensor over the...radiance Lwn at several wave - lengths. These spectral Lwn channels are used to derive several in- water bio-optical properties (Lee, Carder, & Arnone...the same surface flow, it is the inter-product similarities, instead of the differences, that are more likely to stand for the surface advection. If
Satellite Eye for the Galathea 3 ship expedition: Global tour 2006-2007
DEFF Research Database (Denmark)
Hasager, Charlotte Bay; Badger, Merete; Sørensen, Peter
2007-01-01
Satellite Eye for Galathea 3 (www.satellitecye.dk contains education at the internet for secondary and upper secondary schools and the public. The Galathea 3 ship expedition circumnavigated the globe starting from Denmark 11 August 2006, visiting Greenland, Azores, South Africa, Australia, Solomon...... of the expedition and these classes in particular used the Satellite Eye teaching material. In Google Earth satellite images of many themes are shown. These include sea ice, sea surface temperature, ocean wind, wave height, sea surface level, ozone, clouds and radar images of ocean and land. Also high spatial...
Super-resolution post-processing for satellites with yaw-steering capability
CSIR Research Space (South Africa)
Van den Dool, R
2012-10-01
Full Text Available We describe a method for improving Earth observation satellite image resolution, for specific areas of interest where the sensor design resolution is insufficient. Our method may be used for satellites with yaw-steering capability, such as Nigeria...
The UNOSAT-GRID Project: Access to Satellite Imagery through the Grid Environment
Méndez-Lorenzo, P; Lamanna, M; Meyer, X; Lazeyras, M; Bjorgo, E; Retiere, A; Falzone, A; Venuti, N; Maccarone, S; Ugolotti, B
2007-01-01
UNOSAT is a United Nations activity to provide access to satellite images and geographic system services for humanitarian operations for rescue or aid activities. UNOSAT is implemented by the UN Institute for Training and Research (UNITAR) and managed by the UN Office for Project Services (UNOPS). In addition, partners from different organizations constitute the UNOSAT consortium. Among these partners, CERN participates actively providing the required computational and storage resources. The critical part of the UNOSAT activity is the storage and processing of large quantities of satellite images. The fast and secure access to these images from any part of the world is mandatory during these activities. Based on two successful CERN-GRID/UNOSAT pilot projects (data storage/compression/download and image access through mobile phone), the GRIDUNOSAT project has consolidated the considerable work undertaken so far in the present activity. The main use case already demonstrated is the delivery of satellite images ...
Foodstuff survey around a major nuclear facility with test of satellite images application
International Nuclear Information System (INIS)
Twining, S.; Strydom, J.; Rosson, R.; Koffman, L.; Fledderman, P.; Kahn, B.
2000-01-01
A foodstuff survey was performed around the Savannah River Site, Aiken, South Carolina. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of the Savannah River Site center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined by the usual process of applying county agricultural statistics reported by state agencies. This process was compared to crop analysis of two LANDSAT Thematic Mapper images. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the site and by 16-km distance intervals from 16 km to 80 km. The median areas per section devoted to each of four food crops based on county agricultural statistics were about two-thirds of those based on satellite image analysis. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption
Tree Species Classification in Temperate Forests Using Formosat-2 Satellite Image Time Series
Directory of Open Access Journals (Sweden)
David Sheeren
2016-09-01
Full Text Available Mapping forest composition is a major concern for forest management, biodiversity assessment and for understanding the potential impacts of climate change on tree species distribution. In this study, the suitability of a dense high spatial resolution multispectral Formosat-2 satellite image time-series (SITS to discriminate tree species in temperate forests is investigated. Based on a 17-date SITS acquired across one year, thirteen major tree species (8 broadleaves and 5 conifers are classified in a study area of southwest France. The performance of parametric (GMM and nonparametric (k-NN, RF, SVM methods are compared at three class hierarchy levels for different versions of the SITS: (i a smoothed noise-free version based on the Whittaker smoother; (ii a non-smoothed cloudy version including all the dates; (iii a non-smoothed noise-free version including only 14 dates. Noise refers to pixels contaminated by clouds and cloud shadows. The results of the 108 distinct classifications show a very high suitability of the SITS to identify the forest tree species based on phenological differences (average κ = 0 . 93 estimated by cross-validation based on 1235 field-collected plots. SVM is found to be the best classifier with very close results from the other classifiers. No clear benefit of removing noise by smoothing can be observed. Classification accuracy is even improved using the non-smoothed cloudy version of the SITS compared to the 14 cloud-free image time series. However conclusions of the results need to be considered with caution because of possible overfitting. Disagreements also appear between the maps produced by the classifiers for complex mixed forests, suggesting a higher classification uncertainty in these contexts. Our findings suggest that time-series data can be a good alternative to hyperspectral data for mapping forest types. It also demonstrates the potential contribution of the recently launched Sentinel-2 satellite for
Space technology in the discovery and development of mineral and energy resources
Lowman, P. D.
1977-01-01
Space technology, applied to the discovery and extraction of mineral and energy resources, is summarized. Orbital remote sensing for geological purposes has been widely applied through the use of LANDSAT satellites. These techniques also have been of value for protection against environmental hazards and for a better understanding of crustal structure.
Li, Dong; Mao, Song Shou; Khazai, Bahram; Hyder, Joseph A; Allison, Matthew; McClelland, Robyn; de Boer, Ian; Carr, J Jeffrey; Criqui, Michael H; Gao, Yanlin; Budoff, Matthew J
2013-05-01
Cardiac computer tomography (CT) image-based vertebral bone mineral density (BMD) assessment and the influence of cardiovascular disease risk factors on BMD have not been systematically evaluated, especially in a community-based, multiethnic population. A cross-sectional study design is used to determine if cardiac CT image is a reliable source to assess vertebral BMD, and a total of 2028 CT images were obtained from the Multi-Ethnic Study of Atherosclerosis, a large, diverse US cohort of adults 45 to 84 years of age. Cardiac CT image allows the rapid assessment of vertebral BMD and related fractures. The mean BMD was significantly higher in men compared with women for thoracic vertebrae (143.2 ± 41.2 vs 138.7 ± 42.7 mg/cm³, respectively, P = .014), as well as for lumbar vertebrae (125.0 ± 37.9 vs 117.2 ± 39.4 mg/cm³, respectively, P images to garner and assess vertebral BMD is a feasible and reliable method. Cardiac CT has the additional advantages of evaluate vertebral bone health while assessing cardiovascular disease risk with no extra cost or radiation exposure. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.
Characteristics of mineral dust impacting the Persian Gulf
Ahmady-Birgani, Hesam; McQueen, Kenneth G.; Mirnejad, Hassan
2018-02-01
It is generally assumed that severe dust events in western Iran could be responsible for elevated levels of toxic and radioactive elements in the region. Over a period of 5 months, from January 2012 to May 2012, dust particles in the size range PM10 (i.e. chemical compositions of dust and aerosol samples collected during the non-dusty periods and during two severe dust events. Results of ICP-MS analysis of components indicate that during dust events the concentrations of major elements such as Ca, Mg, Al and K increase relative to ambient conditions when Fe and trace elements such as Cu, Cr, Ni, Pb and Zn are in higher proportions. Toxic trace elements that are generally ascribed to human activities, including industrial and urban pollution, are thus proportionately more abundant in the dust under calm conditions than during dust events, when their concentration is diluted by more abundant mineral particles of quartz, calcite and clay. The variability of chemical species during two dust events, noted by tracking the dust plumes in satellite images, was also assessed and the results relate to two different source areas, namely northern Iraq and northwestern Syria.
International Nuclear Information System (INIS)
Pasachoff, Jay M.; Schneider, Glenn; Widemann, Thomas
2011-01-01
This paper presents the only space-borne optical-imaging observations of the 2004 June 8 transit of Venus, the first such transit visible from Earth since AD 1882. The high-resolution, high-cadence satellite images we arranged from NASA's Transition Region and Coronal Explorer (TRACE) reveal the onset of visibility of Venus's atmosphere and give further information about the black-drop effect, whose causes we previously demonstrated from TRACE observations of a transit of Mercury. The atmosphere is gradually revealed before second contact and after third contact, resulting from the changing depth of atmospheric layers refracting the photospheric surface into the observer's direction. We use Venus Express observations to relate the atmospheric arcs seen during the transit to the atmospheric structure of Venus. Finally, we relate the transit images to current and future exoplanet observations, providing a sort of ground truth showing an analog in our solar system to effects observable only with light curves in other solar systems with the Kepler and CoRoT missions and ground-based exoplanet-transit observations.
PLEIADES-HR IMAGE QUALITY COMMISSIONING
Directory of Open Access Journals (Sweden)
L. Lebègue
2012-07-01
Full Text Available PLEIADES is the highest resolution civilian earth observing system ever developed in Europe. This imagery program is conducted by the French National Space Agency, CNES. It operates since 2012 a first satellite PLEIADES-HR launched on 2011 December 17th, a second one should be launched by the end of the year. Each satellite is designed to provide optical 70 cm resolution coloured images to civilian and defence users. The Image Quality requirements were defined from users studies from the different spatial imaging applications, taking into account the trade-off between on-board technological complexity and ground processing capacity. The assessment of the image quality and the calibration operation have been performed by CNES Image Quality team during the 6 month commissioning phase that followed the satellite launch. These activities cover many topics gathered in two families : radiometric and geometric image quality. The new capabilities offered by PLEIADES-HR agility allowed to imagine new methods of image calibration and performance assessment. Starting from an overview of the satellite characteristics, this paper presents all the calibration operations that were conducted during the commissioning phase and also gives the main results for every image quality performance.
Use of Openly Available Satellite Images for Remote Sensing Education
Wang, C.-K.
2011-09-01
With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.
User Validation of VIIRS Satellite Imagery
Directory of Open Access Journals (Sweden)
Don Hillger
2015-12-01
Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.
Satellite-based ET estimation using Landsat 8 images and SEBAL model
Directory of Open Access Journals (Sweden)
Bruno Bonemberger da Silva
Full Text Available ABSTRACT Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Paraná, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.
A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification
Directory of Open Access Journals (Sweden)
Huai Yu
2016-03-01
Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.
Pleskachevsky, A. L.; Rosenthal, W.; Lehner, S.
2016-09-01
The German Bight of the North Sea is the area with highly variable sea state conditions, intensive ship traffic and with a high density of offshore installations, e.g. wind farms in use and under construction. Ship navigation and the docking on offshore constructions is impeded by significant wave heights HS > 1.3 m. For these reasons, improvements are required in recognition and forecasting of sea state HS in the range 0-3 m. Thus, this necessitates the development of new methods to determine the distribution of meteo-marine parameters from remote sensing data with an accuracy of decimetres for HS. The operationalization of these methods then allows the robust automatic processing in near real time (NRT) to support forecast agencies by providing validations for model results. A new empirical algorithm XWAVE_C (C = coastal) for estimation of significant wave height from X-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed, adopted for coastal applications using TerraSAR-X (TS-X) and Tandem-X (TD-X) satellites in the German Bight and implemented into the Sea Sate Processor (SSP) for fully automatic processing for NRT services. The algorithm is based on the spectral analysis of subscenes and the model function uses integrated image spectra parameters as well as local wind information from the analyzed subscene. The algorithm is able to recognize and remove the influence of non-sea state produced signals in the Wadden Sea areas such as dry sandbars as well as nonlinear SAR image distortions produced by e.g. short wind waves and breaking waves. Also parameters of very short waves, which are not visible in SAR images and produce only unsystematic clutter, can be accurately estimated. The SSP includes XWAVE_C, a pre-filtering procedure for removing artefacts such as ships, seamarks, buoys, offshore constructions and slicks, and an additional procedure performing a check of results based on the statistics of the whole scene. The SSP allows an
A method for generating high resolution satellite image time series
Guo, Tao
2014-10-01
There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation
Ko, Hoon; Jeong, Kwanmoon; Lee, Chang-Hoon; Jun, Hong Young; Jeong, Changwon; Lee, Myeung Su; Nam, Yunyoung; Yoon, Kwon-Ha; Lee, Jinseok
2016-01-01
Image artifacts affect the quality of medical images and may obscure anatomic structure and pathology. Numerous methods for suppression and correction of scattered image artifacts have been suggested in the past three decades. In this paper, we assessed the feasibility of use of information on scattered artifacts for estimation of bone mineral density (BMD) without dual-energy X-ray absorptiometry (DXA) or quantitative computed tomographic imaging (QCT). To investigate the relationship between scattered image artifacts and BMD, we first used a forearm phantom and cone-beam computed tomography. In the phantom, we considered two regions of interest-bone-equivalent solid material containing 50 mg HA per cm(-3) and water-to represent low- and high-density trabecular bone, respectively. We compared the scattered image artifacts in the high-density material with those in the low-density material. The technique was then applied to osteoporosis patients and healthy subjects to assess its feasibility for BMD estimation. The high-density material produced a greater number of scattered image artifacts than the low-density material. Moreover, the radius and ulna of healthy subjects produced a greater number of scattered image artifacts than those from osteoporosis patients. Although other parameters, such as bone thickness and X-ray incidence, should be considered, our technique facilitated BMD estimation directly without DXA or QCT. We believe that BMD estimation based on assessment of scattered image artifacts may benefit the prevention, early treatment and management of osteoporosis.
Directory of Open Access Journals (Sweden)
A. Beiranvand Pour
2015-10-01
Full Text Available This study evaluates the capability of Earth Observing-1 (EO1 Advanced Land Imager (ALI data for hydrothermal alteration mapping in the Meiduk and Sar Cheshmeh porphyry copper mining districts, SE Iran. Feature-oriented principal components selection, 4/2, 8/9, 5/4 band ratioing were applied to ALI data for enhancing the hydrothermally altered rocks associated with porphyry copper mineralization, lithological units and vegetation. Mixture-tuned matched-filtering (MTMF was tested to discriminate the hydrothermal alteration areas of porphyry copper mineralization from surrounding environment using the shortwave infrared bands of ALI. Results indicate that the tested methods are able to yield spectral information for identifying vegetation, iron oxide/hydroxide and clay minerals, lithological units and the discrimination of hydrothermally altered rocks from unaltered rocks using ALI data.
European Space Imaging & Skybox Imaging
International Nuclear Information System (INIS)
Clark, J.; Schichor, P.
2015-01-01
Skybox and European Space Imaging have partnered to bring timely, Very High-Resolution imagery to customers in Europe and North Africa. Leveraging Silicon Valley ingenuity and world-class aerospace expertise, Skybox designs, builds, and operates a fleet of imaging satellites. With two satellites currently on-orbit, Skybox is quickly advancing towards a planned constellation of 24+ satellites with the potential for daily or sub-daily imaging at 70-90 cm resolution. With consistent, high-resolution imagery and video, European customers can monitor the dynamic units of human activity - cars, trucks, shipping containers, ships, aircraft, etc. - and derive valuable insights about the global economy. With multiple imaging opportunities per day, the Skybox constellation provides unprecedented access to imagery and information about critical targets that require rapid analysis. Skybox's unique capability to deliver high-definition video from space enables European customers to monitor a network of globally distributed assets with full-motion snapshots, without the need to deploy an aircraft or field team. The movement captured in these 30-90 second video windows yield unique insights that improve operational decisions. Skybox and EUSI are excited to offer a unique data source that can drive a better understanding of our world through supply chain monitoring, natural resource management, infrastructure monitoring, and crisis response. (author)
TREND ASSESSMENT OF SPATIO-TEMPORAL CHANGE OF TEHRAN HEAT ISLAND USING SATELLITE IMAGES
Directory of Open Access Journals (Sweden)
M. R. Saradjian
2015-12-01
Full Text Available Numerous investigations on Urban Heat Island (UHI show that land cover change is the main factor of increasing Land Surface Temperature (LST in urban areas, especially conversion of vegetation and bare soil to concrete, asphalt and other man-made structures. On the other hand, other human activities like those which cause to burning fossil fuels, that increase the amount of carbon dioxide, may raise temperature in global scale in comparison with small scales (urban areas. In this study, multiple satellite images with different spatial and temporal resolutions have been used to determine Land Surface Temperature (LST variability in Tehran metropolitan area. High temporal resolution of AVHRR images have been used as the main data source when investigating temperature variability in the urban area. The analysis shows that UHI appears more significant at afternoon and night hours. But the urban class temperature is almost equal to its surrounding vegetation and bare soil classes at around noon. It also reveals that there is no specific difference in UHI intense during the days throughout the year. However, it can be concluded that in the process of city expansion in years, UHI has been grown both spatially and in magnitude. In order to locate land-cover types and relate them to LST, Thematic Mapper (TM images have been exploited. The influence of elevation on the LST has also been studied, using digital elevation model derived from SRTM database.
Satellite imagery in safeguards: progress and prospects
International Nuclear Information System (INIS)
Niemeyer, I.; Listner, C.
2013-01-01
The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)
Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.
Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian
2018-04-13
Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.
Directory of Open Access Journals (Sweden)
A. Beiranvand Pour
2016-06-01
Full Text Available The Bentong-Raub Suture Zone (BRSZ of Peninsular Malaysia is one of the significant structural zones in Sundaland, Southeast Asia. It forms the boundary between the Gondwana-derived Sibumasu terrane in the west and Sukhothai arc in the east. The BRSZ is also genetically related to the sediment-hosted/orogenic gold deposits associated with the major lineaments and form-lines in the central gold belt Central Gold Belt of Peninsular Malaysia. In tropical environments, heavy tropical rainforest and intense weathering makes it impossible to map geological structures over long distances. Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR satellite remote sensing data were used to analyse major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the BRSZ, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for large inaccessible regions in tropical environments.
DEFF Research Database (Denmark)
Hoey, Hilary; Lange, Karin; Skinner, Tc
2017-01-01
Background: Few diabetes-specific quality of life (QOL) tools are available for young children. Objectives: To design and evaluate, a new age-specific QOL questionnaire and its associations with treatment regimens and metabolic control. Methods: Clinical, demographic data and centrally analyzed Hb...... item measures separate aspects of children's satisfaction construct. Convergent validity assessed by comparison to the HrQOL KIDSCREEN-10 Index showed moderate correlation coefficient 0.501. Factor analysis revealed 3 factors explaining 51% of the variance. Children reported good QOL with most items...... positive, mean values between 1 and 2 on a 5-point scale (lower scores indicating greater QOL). Diabetes satisfaction was unrelated to age, diabetes duration, HbA1c, or severe hypoglycemia. Girls were more satisfied than boys. Children on intensive regimens reported better QOL (P
Use of high-resolution satellite images for detection of geothermal reservoirs
Arellano-Baeza, A. A.
2012-12-01
Chile has an enormous potential to use the geothermal resources for electric energy generation. The main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT and ASTER satellites have been used to delineate the geological structures related to the Calerias geothermal field located at the northern end of the Southern Volcanic Zone of Chile and Puchuldiza geothermal field located in the Region of Tarapaca. It was done by applying the lineament extraction technique developed by author. These structures have been compared with the distribution of main geological structures obtained in the fields. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields.
Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite
Energy Technology Data Exchange (ETDEWEB)
Garrett, A.J.
2000-01-03
Sandia National Laboratories (SNL), Los Alamos National Laboratory (LANL), and the Savannah River Technology Center (SRTC) have developed a diverse group of algorithms for processing and analyzing the data that will be collected by the Multispectral Thermal Imager (MTI) after launch late in 1999. Each of these algorithms must be verified by comparison to independent surface and atmospheric measurements. SRTC has selected 13 sites in the continental U.S. for ground truth data collections. These sites include a high altitude cold water target (Crater Lake), cooling lakes and towers in the warm, humid southeastern US, Department of Energy (DOE) climate research sites, the NASA Stennis satellite Validation and Verification (V and V) target array, waste sites at the Savannah River Site, mining sites in the Four Corners area and dry lake beds in the southwestern US. SRTC has established mutually beneficial relationships with the organizations that manage these sites to make use of their operating and research data and to install additional instrumentation needed for MTI algorithm V and V.
Sonbul, Abdullah R.; El-Shafei, Mohamed K.; Bishta, Adel Z.
2016-05-01
Modern earth resource satellites provide huge amounts of digital imagery at different resolutions. These satellite imageries are considered one of the most significant sources of data for mineral exploration. Image processing techniques were applied to the exposed rocks around the Al-Aqiq area of the Asir terrane in the southern part of the Arabian Shield. The area under study has two sub-parallel N-S trending metamorphic belts of green-schist facies. The first belt is located southeast of Al-Aqiq, where the Al-Hajar Gold Mine is situated. It is essentially composed of metavolcanics and metasedimentary rocks, and it is intruded by different plutonic rocks of primarily diorite, syenite and porphyritic granite. The second belt is located northwest of Al-Aqiq, and it is composed of metavolcanics and metasedimentary rocks and is intruded by granite bodies. The current study aimed to distinguish the lithological units, detect and map the alteration zones, and extract the major fault lineaments around the Al-Hajar gold prospect. Digital satellite imageries, including Landsat 7 ETM + multispectral and panchromatic and SPOT-5 were used in addition to field verification. Areas with similar spectral signatures to the prospect were identified in the nearby metamorphic belt; it was considered as a target area and was inspected in the field. The relationships between the alteration zones, the mineral deposits and the structural elements were used to locate the ore-bearing zones in the subsurface. The metasedimentary units of the target area showed a dextral-ductile shearing top-to-the-north and the presence of dominant mineralized quartz vein-system. The area to the north of the Al-Hajar prospect showed also sub-parallel shear zones along which different types of alterations were detected. Field-based criteria such as hydrothermal breccia, jasper, iron gossans and porphyritic granite strongly indicate the presence of porphyry-type ore deposits in Al-Hajar metamorphic belt that
An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring.
Alirezaie, Marjan; Kiselev, Andrey; Längkvist, Martin; Klügl, Franziska; Loutfi, Amy
2017-11-05
This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment-central Stockholm-in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as "find all regions close to schools and far from the flooded area". The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.
An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring
Directory of Open Access Journals (Sweden)
Marjan Alirezaie
2017-11-01
Full Text Available This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.
Directory of Open Access Journals (Sweden)
Hyangsun Han
2015-07-01
Full Text Available As convective clouds in Northeast Asia are accompanied by various hazards related with heavy rainfall and thunderstorms, it is very important to detect convective initiation (CI in the region in order to mitigate damage by such hazards. In this study, a novel approach for CI detection using images from Meteorological Imager (MI, a payload of the Communication, Ocean, and Meteorological Satellite (COMS, was developed by improving the criteria of the interest fields of Rapidly Developing Cumulus Areas (RDCA derivation algorithm, an official CI detection algorithm for Multi-functional Transport SATellite-2 (MTSAT-2, based on three machine learning approaches—decision trees (DT, random forest (RF, and support vector machines (SVM. CI was defined as clouds within a 16 × 16 km window with the first detection of lightning occurrence at the center. A total of nine interest fields derived from visible, water vapor, and two thermal infrared images of MI obtained 15–75 min before the lightning occurrence were used as input variables for CI detection. RF produced slightly higher performance (probability of detection (POD of 75.5% and false alarm rate (FAR of 46.2% than DT (POD of 70.7% and FAR of 46.6% for detection of CI caused by migrating frontal cyclones and unstable atmosphere. SVM resulted in relatively poor performance with very high FAR ~83.3%. The averaged lead times of CI detection based on the DT and RF models were 36.8 and 37.7 min, respectively. This implies that CI over Northeast Asia can be forecasted ~30–45 min in advance using COMS MI data.
Earth mapping - aerial or satellite imagery comparative analysis
Fotev, Svetlin; Jordanov, Dimitar; Lukarski, Hristo
Nowadays, solving the tasks for revision of existing map products and creation of new maps requires making a choice of the land cover image source. The issue of the effectiveness and cost of the usage of aerial mapping systems versus the efficiency and cost of very-high resolution satellite imagery is topical [1, 2, 3, 4]. The price of any remotely sensed image depends on the product (panchromatic or multispectral), resolution, processing level, scale, urgency of task and on whether the needed image is available in the archive or has to be requested. The purpose of the present work is: to make a comparative analysis between the two approaches for mapping the Earth having in mind two parameters: quality and cost. To suggest an approach for selection of the map information sources - airplane-based or spacecraft-based imaging systems with very-high spatial resolution. Two cases are considered: area that equals approximately one satellite scene and area that equals approximately the territory of Bulgaria.
Energy Technology Data Exchange (ETDEWEB)
Kotera, Y [Japan Energy Corp., Tokyo (Japan); Ochi, M [Nikko Exploration and Development Co. Ltd., Tokyo (Japan); Hato, M [Earth Remote Sensing Data Analysis Center, Tokyo (Japan)
1997-05-27
Assuming a two-dimensional seismic survey in a mangrove jungle in the southeast part of People`s Republic of Bangladesh and trially making a basemap for the survey plan from images of satellites such as LANDSAT, the paper considered the use and marginal use in the case of using satellite remote sensing for such a use field. When utilizing water channels in the mangrove jungle in the southwest of Bangladesh and using the seismic survey method for shallow sea, it is important to grasp the distribution of channels in the planning stage of the survey. Satellite remote sensing data are extremely important for knowing the wide-regional information including factors of hourly variations. In the area for this survey, for directly recognizing the channel, it is good only if the difference in reflectance between water and substances except water is indicated in the image because of flatness of the topography. There was seen few difference in accuracy between the passive multispectral image and the active SAR image which is sensitive to topographical changes. 2 figs.
Directory of Open Access Journals (Sweden)
Athos Agapiou
2017-06-01
Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall
Satellite Ocean Biology: Past, Present, Future
McClain, Charles R.
2012-01-01
Since 1978 when the first satellite ocean color proof-of-concept sensor, the Nimbus-7 Coastal Zone Color Scanner, was launched, much progress has been made in refining the basic measurement concept and expanding the research applications of global satellite time series of biological and optical properties such as chlorophyll-a concentrations. The seminar will review the fundamentals of satellite ocean color measurements (sensor design considerations, on-orbit calibration, atmospheric corrections, and bio-optical algorithms), scientific results from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate resolution Imaging Spectroradiometer (MODIS) missions, and the goals of future NASA missions such as PACE, the Aerosol, Cloud, Ecology (ACE), and Geostationary Coastal and Air Pollution Events (GeoCAPE) missions.
International Nuclear Information System (INIS)
Burns, J.A.; Matthews, M.S.
1986-01-01
The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system
Modelling patterns of pollinator species richness and diversity using satellite image texture.
Directory of Open Access Journals (Sweden)
Sylvia Hofmann
Full Text Available Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013 from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees. While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.
Modelling patterns of pollinator species richness and diversity using satellite image texture.
Hofmann, Sylvia; Everaars, Jeroen; Schweiger, Oliver; Frenzel, Mark; Bannehr, Lutz; Cord, Anna F
2017-01-01
Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.
Disturbances in Tooth Mineralization and Forensic Dental Age Estimations
DEFF Research Database (Denmark)
Jensen, Niels Dyrgaard; Arge, Sára Oladóttir; Larsen, Sara Tangmose
When performing a forensic dental age assessment, mineralization disturbances of the teeth and the possible consequences these may have upon the reliability of the assessment must be taken into consideration. Furthermore, mineralization disturbances of a general character in the teeth may be seen...... as an indicator of more systemic insults during tooth formation and thus supplement the examination performed by the forensic pathologist. At our department the forensic dental age assessment is based upon a dental panoramic image, intra oral images of the third molars as well as a clinical photograph...
Processing Satellite Imagery To Detect Waste Tire Piles
Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine
2007-01-01
A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed
Chic, Òscar
2010-01-01
Within the tasks devoted to operational oceanography, Coastal Ocean Observatory at Institut de Ciències del Mar (CSIC) has acquired an European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Broadcast System for Environmental Data (EUMETCast reception system) to replace a satellite direct broadcast system that receives data via High Resolution Picture Transmission (HRPT). EUMETCast system can receive data based on standard Digital Video Broadcastin...
The fusion of satellite and UAV data: simulation of high spatial resolution band
Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata
2017-10-01
Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.
3D CAPABILITIES OF PLEIADES SATELLITE
Directory of Open Access Journals (Sweden)
M. Bernard
2012-08-01
Full Text Available End of 2011 a new optical satellite, called Pléiades, was launched by the French space agency (CNES. It provides 20 km x 20 km images at 0.5 meters. This agile acquisition system is able to relocate very rapidly and scan the earth in any direction. The agility of the system offers the ability to acquire multi viewing angle images of the same area during the same orbit. This ability to capture, from a single stereoscopic pair, to a sequence of 25 images, allows enhancing the quality and the completeness of automatically extracted 3D maps. The aim of the study is to validate and quantify the capacity of the Pléiades system to perform 3D mapping. The analysis explores the advantages in terms of quality and automatism to use more than 2 stereoscopic images. In the last 10 years, automatic 3D processing of digital images became more and more popular and efficient. Thanks to aerial images with very large overlap and very high resolution satellite images, new methodologies and algorithms have been implemented to improve the quality and accuracy of automatic 3D processing. We propose to experiment the same type of approaches using Pléiades images to produce digital elevation models (DEM. A focus is made on analysing the 3D processing using video like (multi viewing acquisitions. Different reference sites with very accurate 3D control points are used to quantify the quality of the Pléiades DEM. Different acquisition modes are explored from a single stereo pair to a sequence of 17 images.
King, Trude V. V.; Clark, Roger N.; Ager, Cathy; Swayze, Gregg A.
1995-01-01
We have demonstrated the unique utility of imaging spectroscopy in mapping mineral distribution. In the Summitville mining region we have shown that the mine site does not contribute clay minerals to the Alamosa River, but does contribute Fe-bearing minerals. Such minerals have the potential to carry heavy metals. This application illustrates only one specific environmental application of imaging spectroscopy data. For instance, the types of minerals we can map with confidence are those frequently associated with environmental problems related to active and abandoned mine lands. Thus, the potential utility of this technology to the field of environmental science has yet to be fully explored.
Using high-resolution satellite imagery and double sampling as a ...
African Journals Online (AJOL)
QuickBird satellite images were used to extract auxiliary variables (image data), such as photogrammetric crown diameter and number of stems, using visual interpretation and measuring tools offered by Erdas 8.7 geographic imaging software. Field inventory data (terrestric data) collected in 2002 were used to obtain the ...
Sun, Y. S.; Zhang, L.; Xu, B.; Zhang, Y.
2018-04-01
The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image - GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.
Magnetic resonance imaging for the wrist joint of the coal miners in vibration department
Energy Technology Data Exchange (ETDEWEB)
Zhao, X.Z.; Liu, R.L.; Hu, S.D.; Zhang, W.; Xu, W.X.; Ge, L.X. [Central Hospital of Zaozhuang Mine Corporation, Zaozhuang (China)
2006-04-15
To study the magnetic resonance imaging (MRI) in the wrist joint of coal miners who work in excavation and vibration department. Forty-three coal miners with the hand-arm vibration disease served as the observation group while 20 workers who were not working in the vibration department acted as the control group. The patients in the observation group were divided into five subgroups according to the time when they received vibration. The regularity of the development of signs and symptoms of MRI was observed and analyzed. The hydroarthrosis was most found in MRI. There were significant difference in hydroarthrosis osteoporosis and osteomyelitis between the observation group and the control group. The edema of bone marrow and the avascular necrosis of ossa carpi were found only in the observation group and not found in the control group. The hydroarthrosis and the edema of bone marrow occurred most in the early stage of vibration. The signal in the edema of the bone marrow of the distal end of the radius was decreased in the GE sequence with the specificity. Changes in the wrist joint occur in the early stage of the vibration work, and can be found in the MRI. The edema of the bone marrow of the distal end of the radius is of great value in the diagnosis of the hand-arm vibration disease.
Sensor and computing resource management for a small satellite
Bhatia, Abhilasha; Goehner, Kyle; Sand, John; Straub, Jeremy; Mohammad, Atif; Korvald, Christoffer; Nervold, Anders Kose
A small satellite in a low-Earth orbit (e.g., approximately a 300 to 400 km altitude) has an orbital velocity in the range of 8.5 km/s and completes an orbit approximately every 90 minutes. For a satellite with minimal attitude control, this presents a significant challenge in obtaining multiple images of a target region. Presuming an inclination in the range of 50 to 65 degrees, a limited number of opportunities to image a given target or communicate with a given ground station are available, over the course of a 24-hour period. For imaging needs (where solar illumination is required), the number of opportunities is further reduced. Given these short windows of opportunity for imaging, data transfer, and sending commands, scheduling must be optimized. In addition to the high-level scheduling performed for spacecraft operations, payload-level scheduling is also required. The mission requires that images be post-processed to maximize spatial resolution and minimize data transfer (through removing overlapping regions). The payload unit includes GPS and inertial measurement unit (IMU) hardware to aid in image alignment for the aforementioned. The payload scheduler must, thus, split its energy and computing-cycle budgets between determining an imaging sequence (required to capture the highly-overlapping data required for super-resolution and adjacent areas required for mosaicking), processing the imagery (to perform the super-resolution and mosaicking) and preparing the data for transmission (compressing it, etc.). This paper presents an approach for satellite control, scheduling and operations that allows the cameras, GPS and IMU to be used in conjunction to acquire higher-resolution imagery of a target region.
Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO
Choi, Michael K.
2014-01-01
This paper uses phase change material (PCM) in the scan cavity of an imager or sounder on satellites in geostationary orbit (GEO) to maintain the telescope temperature stable. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the telescope warm. It has no moving parts or bimetallic springs. It reduces heater power required to make up the heat lost by radiation to space through the aperture. It is an attractive thermal control option to a radiator with a louver and a sunshade.
Li, Lili; Liu, Yihong; Wang, Yunpeng
2017-07-01
Urban air pollution is influenced not only by local emission sources including industry and vehicles, but also greatly by regional atmospheric pollutant transportation from the surrounding areas, especially in developed city clusters, like the Pearl River Delta (PRD). Taking an air pollution episode in Shenzhen as an example, this paper investigates the occurrence and evolution of the pollution episode and identifies the transport pathways of air pollutants in Shenzhen by combining MODIS satellite images and HYSPLIT back trajectory analysis. Results show that this pollution episode is mainly caused by the local emission of pollutants in PRD and oceanic air masses under specific weather conditions.
Satellite instrument provides nighttime sensing capability
Showstack, Randy
2012-12-01
"This is not your father's low-light sensor," Steve Miller, senior research scientist and deputy director of the Cooperative Institute for Research in the Atmosphere at Colorado State University, Fort Collins, said at a 5 December news briefing at the AGU Fall Meeting. He and others at the briefing were showing off the nighttime sensing capability of the day/night band of the Visible Infrared Imaging Radiometer Suite (VIIRS) of instruments onboard the Suomi National Polar-orbiting Partnership (NPP) Earth-observing research satellite, a joint NASA and National Oceanic and Atmospheric Administration (NOAA) satellite that was launched on 28 October 2011. Noting that low-light satellite technology has been available for about 40 years, Miller said that the VIIRS day/night band "is truly a paradigm shift in the technology and capability."
NEPR World View 2 Satellite Mosaic - NOAA TIFF Image
National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a mosaic of World View 2 panchromatic satellite imagery of Northeast Puerto Rico that contains the shallow water area (0-35m deep) surrounding...
Volumetric Forest Change Detection Through Vhr Satellite Imagery
Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro
2016-06-01
Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in
Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio
2017-05-01
WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.
International Nuclear Information System (INIS)
Kuji, M.; Uchiyama, A.
2002-01-01
Retrieval of precipitable water (vertically integrated water vapor amount) is proposed using near infrared channels og Global Imager onboard Advanced Earth Observing Satellite-II (GLI/ADEOS-II). The principle of retrieval algorithm is based upon that adopted with Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System (EOS) satellite series. Simulations were carried out with GLI Signal Simulator (GSS) to calculate the radiance ratio between water vapor absorbing bands and non-absorbing bands. As a result, it is found that for the case of high spectral reflectance background (a bright target) such as the land surface, the calibration curves are sensitive to the precipitable water variation. For the case of low albedo background (a dark target) such as the ocean surface, on the contrary, the calibration curve is not very sensitive to its variation under conditions of the large water vapor amount. It turns out that aerosol loading has little influence on the retrieval over a bright target for the aerosol optical thickness less than about 1.0 at 500nm. It is also anticipated that simultaneous retrieval of the water vapor amount using GLI data along with other channels will lead to improved accuracy of the determination of surface geophysical properties, such as vegetation, ocean color, and snow and ice, through the better atmospheric correction
RETRIEVAL OF MINERAL ABUNDANCES OF THE DELTA REGION IN EBERSWALDE, MARS
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X. Wu
2017-07-01
Full Text Available Eberswalde Crater, a hotspot of Mars exploration, possesses an unambiguous hydrological system. However, little research has been performed on the large-scale mineral abundances retrieval in this region. Hence, we employed hyperspectral unmixing technology to quantitatively retrieve mineral abundances of the delta region in Eberswalde. In this paper, the single-scattering albedos were calculated by the Hapke bidirectional reflectance function from Compact Reconnaissance Imaging Spectrometer for Mars (CRISM data (FRT000060DD and CRISM spectral library respectively, and a sparse unmixing algorithm was adopted to quantitatively retrieve mineral abundances. The abundance maps show that there are six kinds of minerals (pyroxene, olivine, plagioclase, siderite, diaspore, and tremolite. By comparing minerals spectra obtained from images with corresponding spectra in spectral library, we found the similar trend in both curves. Besides, the mineral abundance maps derived in this study agree well spatially with CRISM parameter maps. From the perspective of mineralogy, the instability of pyroxene and olivine indicates the area in which they distribute is close to provenance, and the original provenance is ultrabasic rock (e.g. peridotite and basic rock (e.g. gabbro, respectively. And minerals, existing in the area of alluvial fan, also distribute in the outside of alluvial fan, which might be caused by fluid transportation.
Near-infrared laboratory spectroscopy of mineral chemistry: A review
Meer, Freek van der
2018-03-01
Spectroscopy is the science concerned with the investigation and measurement of spectra produced when materials interacts with or emits electromagnetic radiation. Commercial infrared spectrometer were designed from the 1950's onward and found their way into the pharmaceutical and chemical industries. In the 1970's and 1980's also natural sciences notably mineralogy and vegetation science started systematically to measure optical properties of leaves and minerals/rocks with spectrometers. In the last decade spectroscopy has made the step from qualitative observations of mineral classes, soil type and vegetation biomass to quantitative estimates of mineral, soil and vegetation chemistry. This resulted in geothermometers used to characterize metamorphic and hydrothermal systems and to the advent of foliar biochemistry. More research is still needed to bridge the gap between laboratory spectroscopy and field spectroscopy. Empirical studies of minerals either as soil or rock constituents (and vegetation parameters) derived from regression analysis of spectra against chemistry is important in understanding the physics of the interaction of electromagnetic radiation and matter which in turn is important in the design of future satellite missions. Physics based models and retrievals are needed to operationalize these relationships and implement them in future earth observation missions as these are more robust and easy to transfer to other areas and data sets.
Sentinel-2: next generation satellites for optical land observation from space
Lautenschläger, G.; Gessner, R.; Gockel, W.; Haas, C.; Schweickert, G.; Bursch, S.; Welsch, M.; Sontag, H.
2013-10-01
The first Sentinel-2 satellites, which constitute the next generation of operational Earth observation satellites for optical land monitoring from space, are undergoing completion in the facilities at Astrium ready for launch end 2014. Sentinel-2 will feature a major breakthrough in the area of optical land observation since it will for the first time enable continuous and systematic acquisition of all land surfaces world-wide with the Multi-Spectral Instrument (MSI), thus providing the basis for a truly operational service. Flying in the same orbital plane and spaced at 180°, the constellation of two satellites, designed for an in-orbit nominal operational lifetime of 7 years each, will acquire all land surfaces in only 5 days at the equator. In order to support emergency operations, the satellites can further be operated in an extended observation mode allowing to image any point on Earth even on a daily basis. MSI acquires images in 13 spectral channels from Visible-to-Near Infrared (VNIR) to Short Wave Infrared (SWIR) with a swath of almost 300 km on ground and a spatial resolution up to 10 m. The data ensure continuity to the existing data sets produced by the series of Landsat and SPOT satellites, and will further provide detailed spectral information to enable derivation of biophysical or geophysical products. Excellent geometric image quality performances are achieved with geolocation better than 16 m, thanks to an innovative instrument design in conjunction with a high-performance satellite AOCS subsystem centered around a 2-band GPS receiver, high-performance star trackers and a fiberoptic gyro. To cope with the high data volume on-board, data are compressed using a state-of-the-art wavelet compression scheme. Thanks to a powerful mission data handling system built around a newly developed very large solid-state mass memory based on flash technology, on-board compression losses will be kept to a minimum. The Sentinel-2 satellite design features a highly
Barras, John A.
2007-01-01
Introduction Hurricane Katrina made landfall on the eastern coastline of Louisiana on August 29, 2005; Hurricane Rita made landfall on the western coastline of Louisiana on September 24, 2005. Comparison of Landsat Thematic Mapper (TM) satellite imagery acquired before and after the landfalls of Katrina and Rita and classified to identify land and water demonstrated that water area increased by 217 mi2 (562 km2) in coastal Louisiana as a result of the storms. Approximately 82 mi2 (212 km2) of new water areas were in areas primarily impacted by Hurricane Katrina (Mississippi River Delta basin, Breton Sound basin, Pontchartrain basin, and Pearl River basin), whereas 99 mi2 (256 km2) were in areas primarily impacted by Hurricane Rita (Calcasieu/Sabine basin, Mermentau basin, Teche/Vermilion basin, Atchafalaya basin, and Terrebonne basin). Barataria basin contained new water areas caused by both hurricanes, resulting in some 18 mi2 (46.6 km2) of new water areas. The fresh marsh and intermediate marsh communities' land areas decreased by 122 mi2 (316 km2) and 90 mi2 (233.1 km2), respectively, and the brackish marsh and saline marsh communities' land areas decreased by 33 mi2 (85.5 km2) and 28 mi2 (72.5 km2), respectively. These new water areas represent land losses caused by direct removal of wetlands. They also indicate transitory changes in water area caused by remnant flooding, removal of aquatic vegetation, scouring of marsh vegetation, and water-level variation attributed to normal tidal and meteorological variation between satellite images. Permanent losses cannot be estimated until several growing seasons have passed and the transitory impacts of the hurricanes are minimized. The purpose of this study was to provide preliminary information on water area changes in coastal Louisiana acquired shortly after the landfalls of both hurricanes (detectable with Landsat TM imagery) and to serve as a regional baseline for monitoring posthurricane wetland recovery. The land
Characterization of the deforestation effect in a semi-arid region by the use of satellite images
Benhanifia, Khatir; Haddouche, Driss; Smahi, Zakaria; Bensaid, Abdelkrim; Hamimed, Abderrahmane
2004-02-01
In Algeria, arid and semi-arid regions occupy over than 95% of whole territory. Forests in the semi arid zone constitutes a front face to the advance of the desert towards northern sides. Like in other regions of the world, deforestation phenomenon have a serious consequences on the fragile ecosystem. Severe continuous drought, fires, pasture, insects as well as the absence of a clear forest politics are so many factors that reduced forest areas in this country. However, the conservation of this patrimony must be a priority of any regional development project. This paper describes an evaluating study of the deforestation impact on forests in the region of Djelfa situated in the Saharian Atlas using multitemporal satellite remote sensing data. In order to establish a forest change map, a methodology based on the comparison between normalized difference vegetation indexes (NDVI) generated from satellite images was adopted. For this purpose, a pair of Landsat and (ETM+) images acquired over the region on April 11th, 1987 and march 24th, 2001 have been used. Until being processed, data used have been geometrically and atmospherically corrected. Then, an (NDVI) have been produced for each date. Resulting from compared (NDVI) image presents the forest change map in the study area. Radiometric values of resulting image have been regrouped into three classes according to change types as follow : Increased radiometry = more active vegetation Decreased radiometry = deterioration in vegetation activity Non changed areas = Non changed Investigations made on the terrain permitted to interpret many causes of detected evolutions. Regressive changes were considerable and demonstrates however, the degradation effect on the vegetation state. Some of regressed radiometry are related to forest fires that affected the region in 1994. Almost of regressive changes are due to a deterioration of vegetation caused by multiple factors. Drought, deceases, pasture and infection are considered
Satellite SAR inventory of Gulf of Mexico oil seeps and shallow gas hydrates
Garcia, O.; MacDonald, I. R.; Zimmer, B.; Shedd, W.; Frye, M.
2009-04-01
.S. territorial waters, with 481 formations, and Mexican territorial waters, with 78 formations. The formations were ground-truthed against a comprehensive database of 3D seismic cubes that cover the entire northern Gulf of Mexico (Frye 2008). Formations defined by SAR slick targets were consistently associated with gas hydrate prone regions of high surface amplitude and migration features in the sub-bottom. Many of the isolated slicks also appeared to be associated with migration features in the seismic data. Temporal variation among the slicks includes examples of intermittent individual vents within a single formation and broad-scale off-again, on-again appearance of slicks over entire images covering the same areas. References: De Beukelaer, S. M., MacDonald, I., Guinnasso, N. L. J. and Murray, J. A. (2003). Distinct side-scan sonar, RADARSAT SAR, and acoustic profiler signatures of gas and oil seeps on the Gulf of Mexico slope. Geo-Mar Lett 23: 177-186 Frye, M. (2008). Preliminary Evaluation of In-Place Gas Hydrate Resources: Gulf of Mexico Outer Continental Shelf. OCS Report, MMS U.S. Department of the Interior. Minerals Management Service. Resource Evaluation Division MacDonald, I., Leifer, I., Sassen, R. and Stine, P. (2002). Transfer of hydrocarbons from natural seeps to the water column and atmosphere. Geofluids, Blackwell Science Ltd 2(2): 95-107 Mitchell, R., MacDonald, I. R. and Kvenvolden, K. A. (1999). Estimation of total hydrocarbon seepage into the Gulf of Mexico based on satellite remote sensing images. Transactions, American Geophysical Union 80(49): Ocean Sciences Meeting Supplement, OS242
Wu, D.; Du, Y.; Su, F.; Huang, W.; Zhang, L.
2018-04-01
The topographic measurement of muddy tidal flat is restricted by the difficulty of access to the complex, wide-range and dynamic tidal conditions. Then the waterline detection method (WDM) has the potential to investigate the morph-dynamics quantitatively by utilizing large archives of satellite images. The study explores the potential for using WDM with BJ-1 small satellite images to construct a digital elevation model (DEM) of a wide and grading mudflat. Three major conclusions of the study are as follows: (1) A new intelligent correlating model of waterline detection considering different tidal stages and local geographic conditions was explored. With this correlative algorithm waterline detection model, a series of waterlines were extracted from multi-temporal remotely sensing images collected over the period of a year. The model proved to detect waterlines more efficiently and exactly. (2) The spatial structure of elevation superimposing on the points of waterlines was firstly constructed and a more accurate hydrodynamic ocean tide grid model was used. By the newly constructed abnormal hydrology evaluation model, a more reasonable and reliable set of waterline points was acquired to construct a smoother TIN and GRID DEM. (3) DEM maps of Bohai Bay, with a spatial resolution of about 30 m and height accuracy of about 0.35 m considering LiDAR and 0.19 m considering RTK surveying were constructed over an area of about 266 km2. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible and is an effective tool for monitoring the tidal flats.
Horais, Brian J.
Remote sensing applications and systems, small satellites for sensing missions, and supporting technologies are the broad topics discussed. Particular papers are presented on small satellites for water cycle experiments, low-cost spacecraft buses for remote sensing applications, Webersat (a low-cost imaging satellite), DARPA initiatives in small-satellite technologies, a solid-state magnetic azimuth sensor for small satellites, and thermal analysis of a small expendable tether satellite package. (For individual items see A93-24152 to A93-24175)
Directory of Open Access Journals (Sweden)
Nobuoto Nojima
2010-09-01
Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.
Satellite-Relayed Intercontinental Quantum Network.
Liao, Sheng-Kai; Cai, Wen-Qi; Handsteiner, Johannes; Liu, Bo; Yin, Juan; Zhang, Liang; Rauch, Dominik; Fink, Matthias; Ren, Ji-Gang; Liu, Wei-Yue; Li, Yang; Shen, Qi; Cao, Yuan; Li, Feng-Zhi; Wang, Jian-Feng; Huang, Yong-Mei; Deng, Lei; Xi, Tao; Ma, Lu; Hu, Tai; Li, Li; Liu, Nai-Le; Koidl, Franz; Wang, Peiyuan; Chen, Yu-Ao; Wang, Xiang-Bin; Steindorfer, Michael; Kirchner, Georg; Lu, Chao-Yang; Shu, Rong; Ursin, Rupert; Scheidl, Thomas; Peng, Cheng-Zhi; Wang, Jian-Yu; Zeilinger, Anton; Pan, Jian-Wei
2018-01-19
We perform decoy-state quantum key distribution between a low-Earth-orbit satellite and multiple ground stations located in Xinglong, Nanshan, and Graz, which establish satellite-to-ground secure keys with ∼kHz rate per passage of the satellite Micius over a ground station. The satellite thus establishes a secure key between itself and, say, Xinglong, and another key between itself and, say, Graz. Then, upon request from the ground command, Micius acts as a trusted relay. It performs bitwise exclusive or operations between the two keys and relays the result to one of the ground stations. That way, a secret key is created between China and Europe at locations separated by 7600 km on Earth. These keys are then used for intercontinental quantum-secured communication. This was, on the one hand, the transmission of images in a one-time pad configuration from China to Austria as well as from Austria to China. Also, a video conference was performed between the Austrian Academy of Sciences and the Chinese Academy of Sciences, which also included a 280 km optical ground connection between Xinglong and Beijing. Our work clearly confirms the Micius satellite as a robust platform for quantum key distribution with different ground stations on Earth, and points towards an efficient solution for an ultralong-distance global quantum network.
Satellite-Relayed Intercontinental Quantum Network
Liao, Sheng-Kai; Cai, Wen-Qi; Handsteiner, Johannes; Liu, Bo; Yin, Juan; Zhang, Liang; Rauch, Dominik; Fink, Matthias; Ren, Ji-Gang; Liu, Wei-Yue; Li, Yang; Shen, Qi; Cao, Yuan; Li, Feng-Zhi; Wang, Jian-Feng; Huang, Yong-Mei; Deng, Lei; Xi, Tao; Ma, Lu; Hu, Tai; Li, Li; Liu, Nai-Le; Koidl, Franz; Wang, Peiyuan; Chen, Yu-Ao; Wang, Xiang-Bin; Steindorfer, Michael; Kirchner, Georg; Lu, Chao-Yang; Shu, Rong; Ursin, Rupert; Scheidl, Thomas; Peng, Cheng-Zhi; Wang, Jian-Yu; Zeilinger, Anton; Pan, Jian-Wei
2018-01-01
We perform decoy-state quantum key distribution between a low-Earth-orbit satellite and multiple ground stations located in Xinglong, Nanshan, and Graz, which establish satellite-to-ground secure keys with ˜kHz rate per passage of the satellite Micius over a ground station. The satellite thus establishes a secure key between itself and, say, Xinglong, and another key between itself and, say, Graz. Then, upon request from the ground command, Micius acts as a trusted relay. It performs bitwise exclusive or operations between the two keys and relays the result to one of the ground stations. That way, a secret key is created between China and Europe at locations separated by 7600 km on Earth. These keys are then used for intercontinental quantum-secured communication. This was, on the one hand, the transmission of images in a one-time pad configuration from China to Austria as well as from Austria to China. Also, a video conference was performed between the Austrian Academy of Sciences and the Chinese Academy of Sciences, which also included a 280 km optical ground connection between Xinglong and Beijing. Our work clearly confirms the Micius satellite as a robust platform for quantum key distribution with different ground stations on Earth, and points towards an efficient solution for an ultralong-distance global quantum network.
Future development of IR thermovision weather satellite equipment
Listratov, A. V.
1974-01-01
The self radiation of the surface being viewed is used for image synthesis in IR thermovision equipment. The installation of such equipment aboard weather satellites makes it possible to obtain cloud cover pictures of the earth's surface in a complete orbit, regardless of the illumination conditions, and also provides quantitative information on the underlying surface temperature and cloud top height. Such equipment is used successfully aboard the Soviet satellites of the Meteor system, and experimentally on the American satellites of the Nimbus series. With regard to surface resolution, the present-day IR weather satellite equipment is inferior to the television equipment. This is due primarily to the comparatively low detectivity of the IR detectors used. While IR equipment has several fundamental advantages in comparison with the conventional television equipment, the problem arises of determining the possibility for future development of weather satellite IR thermovision equipment. Criteria are examined for evaluating the quality of IR.
Soto-Pinto, C. A.; Arellano-Baeza, A. A.; Ouzounov, D. P.
2011-12-01
We study the temporal evolution of the stress patterns in the crust by using high-resolution (10-300 m) satellite images from MODIS and ASTER satellite sensors. We are able to detect some changes in density and orientation of lineaments preceding earthquake events. A lineament is generally defined as a straight or a somewhat curved feature in the landscape visible in a satellite image as an aligned sequence of pixels of a contrasting intensity compared to the background. The system of lineaments extracted from the satellite images is not identical to the geological lineaments; nevertheless, it generally reflects the structure of the faults and fractures in the Earth's crust. Our analysis has shown that the system of lineaments is very dynamical, and the significant number of lineaments appeared approximately one month before an earthquake, while one month after the earthquake the lineament configuration returned to its initial state. These features were not observed in the test areas that are free of any seismic activity in that period (null hypothesis). We have designed a computational prototype capable to detect lineament evolution and to utilize both ASTER and MODIS satellite L1/L2. We will demonstrate the first successful test results for several Mw> 5 earthquakes in Chile, Peru, China, and California (USA).
Olivo, Alessandro; Robinson, Ian
2014-03-06
A double event, supported as part of the Royal Society scientific meetings, was organized in February 2013 in London and at Chicheley Hall in Buckinghamshire by Dr A. Olivo and Prof. I. Robinson. The theme that joined the two events was the use of X-ray phase in novel imaging approaches, as opposed to conventional methods based on X-ray attenuation. The event in London, led by Olivo, addressed the main roadblocks that X-ray phase contrast imaging (XPCI) is encountering in terms of commercial translation, for clinical and industrial applications. The main driver behind this is the development of new approaches that enable XPCI, traditionally a synchrotron method, to be performed with conventional laboratory sources, thus opening the way to its deployment in clinics and industrial settings. The satellite meeting at Chicheley Hall, led by Robinson, focused on the new scientific developments that have recently emerged at specialized facilities such as third-generation synchrotrons and free-electron lasers, which enable the direct measurement of the phase shift induced by a sample from intensity measurements, typically in the far field. The two events were therefore highly complementary, in terms of covering both the more applied/translational and the blue-sky aspects of the use of phase in X-ray research.
Carter, W. D. (Principal Investigator)
1975-01-01
The author has identified the following significant results. Work with the Image 100 clearly demonstrates that radiance values of LANDSAT data can be used for correlation of geologic formations across international boundaries. The Totora Formation of the Corocoro Group of Tertiary age was traced from known outcrops near Tiahuanaco, Bolivia, along the south side of Lake Titicaca westward into Peru where the same rocks are considered to be Cretaceous in age. This inconsistency suggests: (1) that a review of this formation is needed by joint geological surveys of both countries to determine similarities, differences, and the true age; (2) that recognition of the extension of the copper-bearing Totora Formation of Bolivia into Peru may provide Peru with a new target for exploration. Equal radiance maps made by use of the Image 100 system show as many as eight different units within salar deposits (salt flats) of the Bolivian Altiplano. Standard film processed images show them as nearly uniform areas of white because of lack of dynamic range in film products. The Image 100 system, therefore, appears to be of great assistance in subdividing the salt flats on the basis of moisture distribution, surface roughness, and distribution of windblown materials. Field work is needed to determine these relationships to mineral composition and distribution. Images representing seasonal changes should also improve the accuracy of such maps. Radiance values of alteration zones related to the occurrence of porphyry copper ores were measured at the San Juan del Abra deposit of northern Chile using the Image 100 system. The extent to which these same values may be used to detect similar alteration zones in other areas has not yet been tested.