WorldWideScience

Sample records for satellite high resolution

  1. Structural High-resolution Satellite Image Indexing

    OpenAIRE

    Xia, Gui-Song; YANG, WEN; Delon, Julie; Gousseau, Yann; Sun, Hong; Maître, Henri

    2010-01-01

    International audience; Satellite images with high spatial resolution raise many challenging issues in image understanding and pattern recognition. First, they allow measurement of small objects maybe up to 0.5 m, and both texture and geometrical structures emerge simultaneously. Second, objects in the same type of scenes might appear at different scales and orientations. Consequently, image indexing methods should combine the structure and texture information of images and comply with some i...

  2. 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.

  3. Vehicle Detection and Classification from High Resolution Satellite Images

    Science.gov (United States)

    Abraham, L.; Sasikumar, M.

    2014-11-01

    In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.

  4. Updating Maps Using High Resolution Satellite Imagery

    Science.gov (United States)

    Alrajhi, Muhamad; Shahzad Janjua, Khurram; Afroz Khan, Mohammad; Alobeid, Abdalla

    2016-06-01

    Kingdom of Saudi Arabia is one of the most dynamic countries of the world. We have witnessed a very rapid urban development's which are altering Kingdom's landscape on daily basis. In recent years a substantial increase in urban populations is observed which results in the formation of large cities. Considering this fast paced growth, it has become necessary to monitor these changes, in consideration with challenges faced by aerial photography projects. It has been observed that data obtained through aerial photography has a lifecycle of 5-years because of delay caused by extreme weather conditions and dust storms which acts as hindrances or barriers during aerial imagery acquisition, which has increased the costs of aerial survey projects. All of these circumstances require that we must consider some alternatives that can provide us easy and better ways of image acquisition in short span of time for achieving reliable accuracy and cost effectiveness. The approach of this study is to conduct an extensive comparison between different resolutions of data sets which include: Orthophoto of (10 cm) GSD, Stereo images of (50 cm) GSD and Stereo images of (1 m) GSD, for map updating. Different approaches have been applied for digitizing buildings, roads, tracks, airport, roof level changes, filling stations, buildings under construction, property boundaries, mosques buildings and parking places.

  5. Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

    Science.gov (United States)

    Kandylakis, Z.; Karantzalos, K.

    2016-06-01

    In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

  6. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images.

    Science.gov (United States)

    Li, Lin; Wang, Wei; Luo, Heng; Ying, Shen

    2017-05-07

    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images.

  7. Approximate Approaches to Geometric Corrections of High Resolution Satellite Imagery

    Institute of Scientific and Technical Information of China (English)

    SHI Wenzhong; Ahmed Shaker

    2004-01-01

    The exploitation of different non-rigorous mathematical models as opposed to the satellite rigorous models is discussed for geometric corrections and topographic/thematic maps production of high-resolution satellite imagery (HRSI). Furthermore, this paper focuses on the effects of the number of GCPs and the terrain elevation difference within the area covered by the images on the obtained ground points accuracy. From the research, it is obviously found that non-rigorous orientation and triangulation models can be used successfully in most cases for 2D rectification and 3D ground points determination without a camera model or the satellite ephemeris data. In addition, the accuracy up to the sub-pixel level in plane and about one pixel in elevation can be achieved with a modest number of GCPs.

  8. High resolution spectroscopy from low altitude satellites. [gamma ray astronomy

    Science.gov (United States)

    Nakano, G. H.; Imhof, W. L.

    1978-01-01

    The P 78 1 satellite to be placed in a synchronous polar orbit at an altitude of 550-660 km will carry two identical high resolution spectrometers each consisting of a single (approximately 85 cc) intrinsic germanium IGE detector. The payload also includes a pair of phoswitch scintillators, an array of CdTe detectors and several particle detectors, all of which are mounted on the wheel of the satellite. The intrinsic high purity IGE detectors receive cooling from two Stirling cycle refrigerators and facilitate the assembly of large and complex detector arrays planned for the next generation of high sensitivity instruments such as those planned for the gamma ray observatory. The major subsystems of the spectrometer are discussed as well as its capabilities.

  9. Exploring NASA Satellite Data with High Resolution Visualization

    Science.gov (United States)

    Wei, J. C.; Yang, W.; Johnson, J. E.; Shen, S.; Zhao, P.; Gerasimov, I. V.; Vollmer, B.; Vicente, G. A.; Pham, L.

    2013-12-01

    Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme event (such as volcano eruption, dust storm, ...etc) interpretation from satellite. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by providing satellite data as ';Images' with accurate pixel-level (Level 2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We will present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting various visualization and data accessing capabilities from satellite Level 2 data (non-aggregated and un-gridded) at high spatial resolution. Functionality will include selecting data sources (e.g., multiple parameters under the same measurement, like NO2 and SO2 from Ozone Monitoring Instrument (OMI), or same parameter with different methods of aggregation, like NO2 in OMNO2G and OMNO2D products), defining area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting and reformatting. The portal interface will connect to the backend services with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. The interface will also be able to connect to other OGC WMS and WCS servers, which will greatly enhance its expandability to integrate additional outside data/map sources.

  10. High-Resolution Imaging of Asteroids/Satellites with AO

    Science.gov (United States)

    Merline, William

    2012-02-01

    We propose to make high-resolution observations of asteroids using AO, to measure size, shape, and pole position (spin vectors), and/or to search for satellites. We have demonstrated that AO imaging allows determination of the pole/dimensions in 1 or 2 nights on a single target, rather than the years of observations with lightcurve inversion techniques that only yield poles and axial ratios, not true dimensions. Our new technique (KOALA) combines AO imaging with lightcurve and occultation data for optimum size/shape determinations. We request that LGS be available for faint targets, but using NGS AO, we will measure several large and intermediate asteroids that are favorably placed in spring/summer of 2012 for size/shape/pole. Accurately determining the volume from the often-irregular shape allows us to derive densities to much greater precision in cases where the mass is known, e.g., from the presence of a satellite. We will search several d! ozen asteroids for the presence of satellites, particularly in under-studied populations, particularly NEOs (we have recently achieved the first-ever optical image of an NEO binary [Merline et al. 2008b, IAUC 8977]). Satellites provide a real-life lab for testing collisional models. We will search for satellites around special objects at the request of lightcurve observers, and we will make a search for debris in the vicinity of Pluto, in support of the New Horizons mission. Our shape/size work requires observations over most of a full rotation period (typically several hours).

  11. COMPARATIVE ASSESSMENT OF VERY HIGH RESOLUTION SATELLITE AND AERIAL ORTHOIMAGERY

    Directory of Open Access Journals (Sweden)

    P. Agrafiotis

    2015-03-01

    Full Text Available This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO provided by NCMA S.A (Hellenic Cadastre from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

  12. Comparative Assessment of Very High Resolution Satellite and Aerial Orthoimagery

    Science.gov (United States)

    Agrafiotis, P.; Georgopoulos, A.

    2015-03-01

    This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO) provided by NCMA S.A (Hellenic Cadastre) from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD) from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO) were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

  13. High resolution gravity models combining terrestrial and satellite data

    Science.gov (United States)

    Rapp, Richard H.; Pavlis, Nikolaos K.; Wang, Yan M.

    1992-01-01

    Spherical harmonic expansions to degree 360 have been developed that combine satellite potential coefficient information, terrestrial gravity data, satellite altimeter information as a direct tracking data type and topographic information. These models define improved representations of the Earth's gravitational potential beyond that available from just satellite or terrestrial data. The development of the degree 360 models, however, does not imply a uniform accuracy in the determination of the gravity field as numerous geographic areas are devoid of terrestrial data or the resolution of such data is limited to, for example, 100 km. This paper will consider theoretical and numerical questions related to the combination of the various data types. Various models of the combination process are discussed with a discussion of various correction terms for the different models. Various sources of gravity data will be described. The new OSU91 360 model will be discussed with comparisons made to previous 360 models and to other potential coefficient models that are complete to degree 50. Future directions in high degree potential coefficient models will be discussed.

  14. Evaluating large scale orthophotos derived from high resolution satellite imagery

    Science.gov (United States)

    Ioannou, Maria Teresa; Georgopoulos, Andreas

    2013-08-01

    For the purposes of a research project, for the compilation of the archaeological and environmental digital map of the island of Antiparos, the production of updated large scale orthophotos was required. Hence suitable stereoscopic high resolution satellite imagery was acquired. Two Geoeye-1 stereopairs were enough to cover this small island of the Cyclades complex in the central Aegean. For the orientation of the two stereopairs numerous ground control points were determined using GPS observations. Some of them would also serve as check points. The images were processed using commercial stereophotogrammetric software suitable to process satellite stereoscopic imagery. The results of the orientations are evaluated and the digital terrain model was produced using automated and manual procedures. The DTM was checked both internally and externally with comparison to other available DTMs. In this paper the procedures for producing the desired orthophotography are critically presented and the final result is compared and evaluated for its accuracy, completeness and efficiency. The final product is also compared against the orthophotography produced by Ktimatologio S.A. using aerial images in 2007. The orthophotography produced has been evaluated metrically using the available check points, while qualitative evaluation has also been performed. The results are presented and a critical approach for the usability of satellite imagery for the production of large scale orthophotos is attempted.

  15. 3D mapping from high resolution satellite images

    Science.gov (United States)

    Goulas, D.; Georgopoulos, A.; Sarakenos, A.; Paraschou, Ch.

    2013-08-01

    In recent years 3D information has become more easily available. Users' needs are constantly increasing, adapting to this reality and 3D maps are in more demand. 3D models of the terrain in CAD or other environments have already been common practice; however one is bound by the computer screen. This is why contemporary digital methods have been developed in order to produce portable and, hence, handier 3D maps of various forms. This paper deals with the implementation of the necessary procedures to produce holographic 3D maps and three dimensionally printed maps. The main objective is the production of three dimensional maps from high resolution aerial and/or satellite imagery with the use of holography and but also 3D printing methods. As study area the island of Antiparos was chosen, as there were readily available suitable data. These data were two stereo pairs of Geoeye-1 and a high resolution DTM of the island. Firstly the theoretical bases of holography and 3D printing are described, and the two methods are analyzed and there implementation is explained. In practice a x-axis parallax holographic map of the Antiparos Island is created and a full parallax (x-axis and y-axis) holographic map is created and printed, using the holographic method. Moreover a three dimensional printed map of the study area has been created using 3dp (3d printing) method. The results are evaluated for their usefulness and efficiency.

  16. High resolution Doppler imager on the Upper Atmosphere Research Satellite

    Energy Technology Data Exchange (ETDEWEB)

    Skinner, W.R.; Hays, P.B.; Grassl, H.J.; Gell, D.A.; Burrage, M.D.; Marshall, A.R.; Ortland, D.A. [Univ. of Michigan, Ann Arbor, MI (United States)

    1994-12-31

    The High Resolution Doppler Imager (HRDI) on the Upper Atmosphere Research Satellite has been providing measurements of the wind field in the stratosphere, mesosphere and lower thermosphere since November 1991. Examination of various calibration data indicates the instrument has remained remarkably stable since launch. The instrument has a thermal drift of about 30 m/s/{degree}C (slightly dependent on wavelength) and a long-term temporal drift that has amounted to about 80 m/s since launch. These effects are removed in the data processing leaving an uncertainty in the instrument stability of {minus}2 nVs. The temperature control of the instrument has improved significantly since launch as a new method was implemented. The initial temperature control held the instrument temperature at about {+-}1{degree}C. The improved method, which holds constant the temperature of the optical bench instead of the radiator, keeps the instrument temperature at about 0.2{degree}C. The calibrations indicate very little change in the sensitivity of the instrument. The detector response has shown no degradation and the optics have not changed their transmittance.

  17. High-Resolution Satellite Data Open for Government Research

    Science.gov (United States)

    Neigh, Christopher S. R.; Masek, Jeffrey G.; Nickeson, Jaime E.

    2013-01-01

    U.S. satellite commercial imagery (CI) with resolution less than 1 meter is a common geospatial reference used by the public through Web applications, mobile devices, and the news media. However, CI use in the scientific community has not kept pace, even though those who are performing U.S. government research have access to these data at no cost.Previously, studies using multiple CI acquisitions from IKONOS-2, Quickbird-2, GeoEye-1, WorldView-1, and WorldView-2 would have been cost prohibitive. Now, with near-global submeter coverage and online distribution, opportunities abound for future scientific studies. This archive is already quite extensive (examples are shown in Figure 1) and is being used in many novel applications.

  18. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Estimated shallow-water, depth maps were produced using rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations in the...

  19. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Estimated shallow-water, depth maps were produced using rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations in the...

  20. High Resolution Imaging of Satellites with Ground-Based 10-m Astronomical Telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Marois, C

    2007-01-04

    High resolution imaging of artificial satellites can play an important role in current and future space endeavors. One such use is acquiring detailed images that can be used to identify or confirm damage and aid repair plans. It is shown that a 10-m astronomical telescope equipped with an adaptive optics system (AO) to correct for atmospheric turbulence using a natural guide star can acquire high resolution images of satellites in low-orbits using a fast shutter and a near-infrared camera even if the telescope is not capable of tracking satellites. With the telescope pointing towards the satellite projected orbit and less than 30 arcsec away from a guide star, multiple images of the satellite are acquired on the detector using the fast shutter. Images can then be shifted and coadded by post processing to increase the satellite signal to noise ratio. Using the Keck telescope typical Strehl ratio and anisoplanatism angle as well as a simple diffusion/reflection model for a satellite 400 km away observed near Zenith at sunset or sunrise, it is expected that such system will produced > 10{sigma} K-band images at a resolution of 10 cm inside a 60 arcsec diameter field of view. If implemented, such camera could deliver the highest resolution satellite images ever acquired from the ground.

  1. High Resolution Imaging of Satellites with Ground-Based 10-m Astronomical Telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Marois, C

    2007-01-04

    High resolution imaging of artificial satellites can play an important role in current and future space endeavors. One such use is acquiring detailed images that can be used to identify or confirm damage and aid repair plans. It is shown that a 10-m astronomical telescope equipped with an adaptive optics system (AO) to correct for atmospheric turbulence using a natural guide star can acquire high resolution images of satellites in low-orbits using a fast shutter and a near-infrared camera even if the telescope is not capable of tracking satellites. With the telescope pointing towards the satellite projected orbit and less than 30 arcsec away from a guide star, multiple images of the satellite are acquired on the detector using the fast shutter. Images can then be shifted and coadded by post processing to increase the satellite signal to noise ratio. Using the Keck telescope typical Strehl ratio and anisoplanatism angle as well as a simple diffusion/reflection model for a satellite 400 km away observed near Zenith at sunset or sunrise, it is expected that such system will produced > 10{sigma} K-band images at a resolution of 10 cm inside a 60 arcsec diameter field of view. If implemented, such camera could deliver the highest resolution satellite images ever acquired from the ground.

  2. Multipath sparse coding for scene classification in very high resolution satellite imagery

    Science.gov (United States)

    Fan, Jiayuan; Tan, Hui Li; Lu, Shijian

    2015-10-01

    With the rapid development of various satellite sensors, automatic and advanced scene classification technique is urgently needed to process a huge amount of satellite image data. Recently, a few of research works start to implant the sparse coding for feature learning in aerial scene classification. However, these previous research works use the single-layer sparse coding in their system and their performances are highly related with multiple low-level features, such as scale-invariant feature transform (SIFT) and saliency. Motivated by the importance of feature learning through multiple layers, we propose a new unsupervised feature learning approach for scene classification on very high resolution satellite imagery. The proposed unsupervised feature learning utilizes multipath sparse coding architecture in order to capture multiple aspects of discriminative structures within complex satellite scene images. In addition, the dense low-level features are extracted from the raw satellite data by using different image patches with varying size at different layers, and this approach is not limited to a particularly designed feature descriptors compared with the other related works. The proposed technique has been evaluated on two challenging high-resolution datasets, including the UC Merced dataset containing 21 different aerial scene categories with a 1 foot resolution and the Singapore dataset containing 5 land-use categories with a 0.5m spatial resolution. Experimental results show that it outperforms the state-of-the-art that uses the single-layer sparse coding. The major contributions of this proposed technique include (1) a new unsupervised feature learning approach to generate feature representation for very high-resolution satellite imagery, (2) the first multipath sparse coding that is used for scene classification in very high-resolution satellite imagery, (3) a simple low-level feature descriptor instead of many particularly designed low-level descriptor

  3. 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...

  4. Updating Object for GIS Database Information Using High Resolution Satellite Images: a Case Study Zonguldak

    Science.gov (United States)

    Alkan, M.; Arca, D.; Bayik, Ç.; Marangoz, A. M.

    2011-09-01

    Nowadays Geographic Information Systems (GIS) uses Remote Sensing (RS) data for a lot of applications. One of the application areas is the updating of the GIS database using high resolution imagery. In this context high resolution satellite imagery data is very important for many applications areas today's and future. And also, high resolution satellite imagery data will be used in many applications for different purposes. Information systems needs to high resolution imagery data for updating. Updating is very important component for the any of the GIS systems. One of this area will be updated and kept alive GIS database information. High resolution satellite imagery is used with different data base which serve map information via internet and different aims of information systems applications in future topographic and cartographic information systems will very important in our country in this sense use of the satellite images will be unavoidable. In this study explain to how is acquired to satellite images and how is use this images in information systems for object and roads. Firstly, pan-sharpened two of the IKONOS's images have been produced by fusion of high resolution PAN and MS images using PCI Geomatica v9.1 software package. Automatic object extraction has been made using eCognition v4.0.6. On the other hand, these objects have been manually digitized from high resolution images using ArcGIS v9.3. software package. Application section of in this study, satellite images data will be compared each other and GIS objects and road database. It is also determined which data is useful in Geographic Information Systems. Finally, this article explains that integration of remote sensing technology and GIS applications.

  5. Tree Species Classification By Multiseasonal High Resolution Satellite Data

    Science.gov (United States)

    Elatawneh, Alata; Wallner, Adelheid; Straub, Christoph; Schneider, Thomas; Knoke, Thomas

    2013-12-01

    Accurate forest tree species mapping is a fundamental issue for sustainable forest management and planning. Forest tree species mapping with the means of remote sensing data is still a topic to be investigated. The Bavaria state institute of forestry is investigating the potential of using digital aerial images for forest management purposes. However, using aerial images is still cost- and time-consuming, in addition to their acquisition restrictions. The new space-born sensor generations such as, RapidEye, with a very high temporal resolution, offering multiseasonal data have the potential to improve the forest tree species mapping. In this study, we investigated the potential of multiseasonal RapidEye data for mapping tree species in a Mid European forest in Southern Germany. The RapidEye data of level A3 were collected on ten different dates in the years 2009, 2010 and 2011. For data analysis, a model was developed, which combines the Spectral Angle Mapper technique with a 10-fold- cross-validation. The analysis succeeded to differentiate four tree species; Norway spruce (Picea abies L.), Silver Fir (Abies alba Mill.), European beech (Fagus sylvatica) and Maple (Acer pseudoplatanus). The model success was evaluated using digital aerial images acquired in the year 2009 and inventory point records from 2008/09 inventory. Model results of the multiseasonal RapidEye data analysis achieved an overall accuracy of 76%. However, the success of the model was evaluated only for all the identified species and not for the individual.

  6. Building identification from very high-resolution satellite images

    Science.gov (United States)

    Lhomme, Stephane

    Urbanisation still remains one of the main problems worldwide. The extent and rapidity of the urban growth induce a number of socio-economic and environmental conflicts everywhere. In order to reduce these problems, urban planners need to integrate spatial information in planning tools. Actually high expectations are made on Very High Spatial Resolution imagery (VHSR). These high-spatial resolution images are available at a reasonable price and due to short revisit periods, they offer a high degree of actuality. However, interpretation methods seem not to be adapted to this new type of images. The aim of our study is to develop a new method for semi-automatic building extraction with VHSR. The different steps performed to achieve our objective are each presented in a chapter. In the first chapter, the general context of our research is described with the definition of our objective. After a short historical review of urbanisation, we focus on urban growth and associated problems. In the following we discuss the possible contributions of geography to reduce these problems. After discussing concepts, theories and methodologies of geographical analysis in urban areas, we present existing general urban planning tools. Finally, we show the special interest of our study that is due to a growing need to integrate spatial information in these decision support tools. In the second chapter we verify the possibility of reaching our objective by analysing the technical characteristics of the images, the noise and the distortions which affect the images. Quality and interpretability of the studied image is analysed in order to show the capacity of these image to represent urban objects as close to reality as possible. The results confirm the potential of VHSR Imagery for urban objects analysis. The third chapter deal with the preliminary steps necessary for the elaboration of our method of building extraction. First, we evaluate the quality of the Sherbrooke Ikonos image

  7. Advanced Extraction of Spatial Information from High Resolution Satellite Data

    Science.gov (United States)

    Pour, T.; Burian, J.; Miřijovský, J.

    2016-06-01

    In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  8. ADVANCED EXTRACTION OF SPATIAL INFORMATION FROM HIGH RESOLUTION SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    T. Pour

    2016-06-01

    Full Text Available In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  9. High resolution earth observation satellites and services in the next decade a European perspective

    Science.gov (United States)

    Schreier, Gunter; Dech, Stefan

    2005-07-01

    Projects to use very high resolution optical satellite sensor data started in the late 90s and are believed to be the major driver for the commercialisation of earth observation. The global political security situation and updated legislative frameworks created new opportunities for high resolution, dual use satellite systems. In addition to new optical sensors, very high resolution synthetic aperture radars will become in the next few years an important component in the imaging satellite fleet. The paper will review the development in this domain so far, and give perspectives on future emerging markets and opportunities. With dual-use satellite initiatives and new political frameworks agreed between the European Commission and the European Space Agency (ESA), the European market becomes very attractive for both service suppliers and customers. The political focus on "Global Monitoring for Environment and Security" (GMES) and the "European Defence and Security Policy" drive and amplify this demand which ranges from low resolution climate monitoring to very high resolution reconnaissance tasks. In order to create an operational and sustainable GMES in Europe by 2007, the European infrastructure need to be adapted and extended. This includes the ESA SENTINEL and OXYGEN programmes, aiming for a fleet of earth observation satellites and an open and operational earth observation ground segment. The harmonisation of national and regional geographic information is driven by the European Commission's INSPIRE programme. The necessary satellite capacity to complement existing systems in the delivery of space based data required for GMES is currently under definition. Embedded in a market with global competition and in the global political framework of a Global Earth Observation System of Systems, European companies, agencies and research institutions are now contributing to this joint undertaking. The paper addresses the chances, risks and options for the future.

  10. High-resolution satellite imagery is an important yet underutilized resource in conservation biology.

    Science.gov (United States)

    Boyle, Sarah A; Kennedy, Christina M; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E; de la Sancha, Noé U

    2014-01-01

    Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

  11. High-Resolution Satellite Imagery Is an Important yet Underutilized Resource in Conservation Biology

    Science.gov (United States)

    Boyle, Sarah A.; Kennedy, Christina M.; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E.; de la Sancha, Noé U.

    2014-01-01

    Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making. PMID:24466287

  12. Vast planes of satellites in a high resolution simulation of the Local Group: comparison to Andromeda

    CERN Document Server

    Gillet, N; Knebe, A; Libeskind, N; Yepes, G; Gottlober, S; Hoffman, Y

    2014-01-01

    We search for vast planes of satellites (VPoS) in a high resolution simulation of the Local Group performed by the CLUES project, which improves significantly the resolution of former similar studies. We use a simple method for detecting planar configurations of satellites, and validate it on the known plane of M31. We implement a range of prescriptions for modelling the satellite populations, roughly reproducing the variety of recipes used in the literature, and investigate the occurence and properties of planar structures in these populations. The structure of the simulated satellite systems is strongly non-random and contains planes of satellites, predominantly co-rotating, with, in some cases, sizes comparable to the plane observed in M31 by Ibata et al.. However the latter is slightly richer in satellites, slightly thinner and has stronger co-rotation, which makes it stand out as overall more exceptional than the simulated planes, when compared to a random population. Although the simulated planes we fin...

  13. Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

    Science.gov (United States)

    AlShamsi, Meera R.

    2016-10-01

    Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

  14. 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.

  15. Environmental monitoring of El Hierro Island submarine volcano, by combining low and high resolution satellite imagery

    Science.gov (United States)

    Eugenio, F.; Martin, J.; Marcello, J.; Fraile-Nuez, E.

    2014-06-01

    El Hierro Island, located at the Canary Islands Archipelago in the Atlantic coast of North Africa, has been rocked by thousands of tremors and earthquakes since July 2011. Finally, an underwater volcanic eruption started 300 m below sea level on October 10, 2011. Since then, regular multidisciplinary monitoring has been carried out in order to quantify the environmental impacts caused by the submarine eruption. Thanks to this natural tracer release, multisensorial satellite imagery obtained from MODIS and MERIS sensors have been processed to monitor the volcano activity and to provide information on the concentration of biological, chemical and physical marine parameters. Specifically, low resolution satellite estimations of optimal diffuse attenuation coefficient (Kd) and chlorophyll-a (Chl-a) concentration under these abnormal conditions have been assessed. These remote sensing data have played a fundamental role during field campaigns guiding the oceanographic vessel to the appropriate sampling areas. In addition, to analyze El Hierro submarine volcano area, WorldView-2 high resolution satellite spectral bands were atmospherically and deglinted processed prior to obtain a high-resolution optimal diffuse attenuation coefficient model. This novel algorithm was developed using a matchup data set with MERIS and MODIS data, in situ transmittances measurements and a seawater radiative transfer model. Multisensor and multitemporal imagery processed from satellite remote sensing sensors have demonstrated to be a powerful tool for monitoring the submarine volcanic activities, such as discolored seawater, floating material and volcanic plume, having shown the capabilities to improve the understanding of submarine volcanic processes.

  16. The Compact High Resolution Imaging Spectrometer (CHRIS): the future of hyperspectral satellite sensors. Imagery of Oostende coastal and inland waters

    OpenAIRE

    B. De Mol; Ruddick, K

    2004-01-01

    The gap between airborne imaging spectroscopy and traditional multi spectral satellite sensors is decreasing thanks to a new generation of satellite sensors of which CHRIS mounted on the small and low-cost PROBA satellite is the prototype. Although image acquisition and analysis are still in a test phase, the high spatial and spectral resolution and pointability have proved their potential. Because of the high resolution small features, which were before only visible on airborne images, becom...

  17. Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

    Science.gov (United States)

    Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

    2016-04-01

    Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

  18. Flood and Landslide Applications of High Time Resolution Satellite Rain Products

    Science.gov (United States)

    Adler, Robert F.; Hong, Yang; Huffman, George J.

    2006-01-01

    Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system

  19. Improvement in Background Error Covariances Using Ensemble Forecasts for Assimilation of High-Resolution Satellite Data

    Institute of Scientific and Technical Information of China (English)

    Seung-Woo LEE; Dong-Kyou LEE

    2011-01-01

    Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC (National Meteorological Center) method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data.In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors.The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated.

  20. A surge of Perseibreen, Svalbard, examined using aerial photography and ASTER high resolution satellite imagery

    OpenAIRE

    Dowdeswell, Julian A.; Benham, Toby J.

    2003-01-01

    The identification of surge activity is important in assessing the duration of the active and quiescent phases of the surge cycle of Svalbard glaciers. Satellite and aerial photographic images are used to identify and describe the form and flow of Perseibreen, a valley glacier of 59 km2 on the east coast of Spitsbergen. Heavy surface crevassing and a steep ice front, indicative of surge activity, were first observed on Perseibreen in April 2002. Examination of high resolution (15 m) Advanced ...

  1. Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images

    CERN Document Server

    Kodge, B G

    2011-01-01

    In this paper, we study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery, and to detect changes from the extracted open space area during the period 2003, 2006 and 2008. This automatic extraction and change detection algorithm uses some filters, segmentation and grouping that are applied on satellite images. The resultant images may be used to calculate the total available open space area and the built up area. It may also be used to compare the difference between present and past open space area using historical urban satellite images of that same projection, which is an important geo spatial data management application.

  2. a Detailed Study about Digital Surface Model Generation Using High Resolution Satellite Stereo Imagery

    Science.gov (United States)

    Gong, K.; Fritsch, D.

    2016-06-01

    Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coefficients (RPCs) Bundle Block Adjustment is applied to image orientation and the rectification of stereo scenes is realized based on the Project-Trajectory-Based Epipolarity (PTE) Model. Very dense DSMs are generated from WorldView-2 satellite stereo imagery using the dense image matching module of the C/C++ library LibTsgm. We carry out various tests to evaluate the quality of generated DSMs regarding robustness and precision. The results have verified that the presented pipeline of DSM generation from high resolution satellite imagery is applicable, reliable and very promising.

  3. Air quality estimates in Mediterranean cities using high resolution satellite technologies

    Science.gov (United States)

    Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie

    2016-04-01

    Satellite imaging is an essential tool for monitoring air pollution because, unlike ground observations, it supplies continuous data with global coverage of terrestrial and atmospheric components. Satellite-based Aerosol Optical Depth (AOD) retrievals reflect particle abundance in the atmospheric column. This data provide some indication on the extent of particle concentrations. However, it is difficult to retrieve AOD at high spatial resolution above areas with high surface reflectance and heterogeneous land cover, such as urban areas. Therefore, many crowded regions worldwide including Israel, AOD climatology are still uncertain because of the high ground reflectance and coarse spatial resolution. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. This study aims to investigate the spatial variability of AOD within Israeli and several other Mediterranean cities. In addition, we aim to characterize the impact of climatic condition on pollution patterns in-and-between cities and to identify days when cities exhibit the highest variability in AOD. Furthermore, we assessed the differences in pollution levels between adjacent locations. We will report on spatial variability in AOD levels derived from high 1km resolution MAIAC AOD algorithm on a temporal basis, in relation to season and synoptic-meteorological conditions.

  4. Research on the flywheel components' disturbance mechanism of a high resolution optical satellite

    Science.gov (United States)

    Lin, Li; Dong, Wang; Sitong, Zhou; Tan, Luyang

    2016-10-01

    According to the picture of a sub-meter resolution optical satellite acquired on the orbit, there is a phenomenon of jitter in the process of taking pictures. The flywheel as the main attitude control component of the satellite, the disturbance that it caused has great influence on the high resolution optical satellite in its normal action. This paper has respectively researched the flywheel components' disturbance mechanism from three parts, including uneven rotator, rotator friction, bearing disturbance, builds the mathematics model of disturbance to analysis the characteristic of disturbance. we get that the vibration system is not a fully linear system, the system is linear before the occurrence of rubbing. It also can be seen that the system has a number of different cross rigidity, it will often appear unstable motion that resulting in damage, or becomes the ultimate destruction due to the role of nonlinear damping. When the rolling roll in the surface, it will produce an alternative excitation force if there exist defects or damage in the rolling surface. This research would offer guidance for system optimization design and vibrating isolation compensation of the later type of improved satellite.

  5. Generation of high resolution sea surface temperature using multi-satellite data for operational oceanography

    Institute of Scientific and Technical Information of China (English)

    YANG Chan-Su; KIM Sun-Hwa; OUCHI Kazuo; BACK Ji-Hun

    2015-01-01

    In the present article, we introduce a high resolution sea surface temperature (SST) product generated daily by Korea Institute of Ocean Science and Technology (KIOST). The SST product is comprised of four sets of data including eight-hour and daily average SST data of 1 km resolution, and is based on the four infrared (IR) satellite SST data acquired by advanced very high resolution radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Multifunctional Transport Satellites-2 (MTSAT-2) Imager and Meteorological Imager (MI), two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2 (AMSR2), and WindSAT within-situ temperature data. These input satellite andin-situ SST data are merged by using the optimal interpolation (OI) algorithm. The root-mean-square-errors (RMSEs) of satellite andin-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from January to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71°C and the bias value was –0.08°C. The largest RMSE and bias were 0.86 and –0.26°C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Japan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60°C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature (GHRSST) product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System (KOOS) as an input parameter for data assimilation.

  6. Automated Generation of the Alaska Coastline Using High-Resolution Satellite Imagery

    Science.gov (United States)

    Roth, G.; Porter, C. C.; Cloutier, M. D.; Clementz, M. E.; Reim, C.; Morin, P. J.

    2015-12-01

    Previous campaigns to map Alaska's coast at high resolution have relied on airborne, marine, or ground-based surveying and manual digitization. The coarse temporal resolution, inability to scale geographically, and high cost of field data acquisition in these campaigns is inadequate for the scale and speed of recent coastal change in Alaska. Here, we leverage the Polar Geospatial Center (PGC) archive of DigitalGlobe, Inc. satellite imagery to produce a state-wide coastline at 2 meter resolution. We first select multispectral imagery based on time and quality criteria. We then extract the near-infrared (NIR) band from each processed image, and classify each pixel as water or land with a pre-determined NIR threshold value. Processing continues with vectorizing the water-land boundary, removing extraneous data, and attaching metadata. Final coastline raster and vector products maintain the original accuracy of the orthorectified satellite data, which is often within the local tidal range. The repeat frequency of coastline production can range from 1 month to 3 years, depending on factors such as satellite capacity, cloud cover, and floating ice. Shadows from trees or structures complicate the output and merit further data cleaning. The PGC's imagery archive, unique expertise, and computing resources enabled us to map the Alaskan coastline in a few months. The DigitalGlobe archive allows us to update this coastline as new imagery is acquired, and facilitates baseline data for studies of coastal change and improvement of topographic datasets. Our results are not simply a one-time coastline, but rather a system for producing multi-temporal, automated coastlines. Workflows and tools produced with this project can be freely distributed and utilized globally. Researchers and government agencies must now consider how they can incorporate and quality-control this high-frequency, high-resolution data to meet their mapping standards and research objectives.

  7. Benchmarking Deep Learning Frameworks for the Classification of Very High Resolution Satellite Multispectral Data

    Science.gov (United States)

    Papadomanolaki, M.; Vakalopoulou, M.; Zagoruyko, S.; Karantzalos, K.

    2016-06-01

    In this paper we evaluated deep-learning frameworks based on Convolutional Neural Networks for the accurate classification of multispectral remote sensing data. Certain state-of-the-art models have been tested on the publicly available SAT-4 and SAT-6 high resolution satellite multispectral datasets. In particular, the performed benchmark included the AlexNet, AlexNet-small and VGG models which had been trained and applied to both datasets exploiting all the available spectral information. Deep Belief Networks, Autoencoders and other semi-supervised frameworks have been, also, compared. The high level features that were calculated from the tested models managed to classify the different land cover classes with significantly high accuracy rates i.e., above 99.9%. The experimental results demonstrate the great potentials of advanced deep-learning frameworks for the supervised classification of high resolution multispectral remote sensing data.

  8. UNSUPERVISED CLASSIFICATION OF HIGH RESOLUTION SATELLITE IMAGERY BY SELF-ORGANIZING NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    ÁRPÁD BARSI

    2010-06-01

    Full Text Available The current paper discusses the importance of the modern high resolution satellite imagery. The acquired high amount of data must be processed by an efficient way, where the used Kohonen-type self-organizing map has been proven as a suitable tool. The paper gives an introduction to this interesting method. The tests have shown that the multispectral image information can be taken after a resampling step as neural network inputs, and then the derived network weights are able to evaluate the whole image with acceptable thematic accuracy.

  9. Satellite-based monitoring of particulate matter pollution at very high resolution: the HOTBAR method

    Science.gov (United States)

    Wilson, Robin; Milton, Edward; Nield, Joanna

    2016-04-01

    Particulate matter air pollution is a major health risk, and is responsible for millions of premature deaths each year. Concentrations tend to be highest in urban areas - particularly in the mega-cities of rapidly industrialising countries, where there are limited ground monitoring networks. Satellite-based monitoring has been used for many years to assess regional-scale trends in air quality, but currently available satellite products produce data at 1-10km resolution: too coarse to discern the small-scale patterns of sources and sinks seen in urban areas. Higher-resolution satellite products are required to provide accurate assessments of particulate matter concentrations in these areas, and to allow analysis of localised air quality effects on health. The Haze Optimized Transform-based Aerosol Retrieval (HOTBAR) method is a novel method which provides estimates of PM2.5 concentrations from high-resolution (approximately 30m) satellite imagery. This method is designed to work over a wide range of land covers and performs well over the complex land-cover mosaic found in urban areas. It requires only standard visible and near-infrared data, making it applicable to a range of data from sensors such as Landsat, SPOT and Sentinel-2. The method is based upon an extension of the Haze Optimized Transform (HOT), which was originally designed for assessing areas of thick haze in satellite imagery. This was done by calculating a 'haziness' value for each pixel in an image as the distance from a 'Clear Line' in feature space, defined by the high correlation between visible bands. Here, we adapt the HOT method and use it to estimate Aerosol Optical Thickness (a measure of the column-integrated haziness of the atmosphere) instead, from which PM2.5 concentrations can then be estimated. Significant extensions to the original HOT method include Monte Carlo estimation of the 'Clear Line', object-based correction for land cover, and estimation of AOT from the haziness values

  10. Object-Based Forest Cover Monitoring Using GAOFEN-2 High Resolution Satellite Images

    Science.gov (United States)

    Li, S. M.; Li, Z. Y.; Chen, E. X.; Liu, Q. W.

    2016-10-01

    Forest cover monitoring is an important part of forest management in local or regional area. The structure and tones of forest can be identified in high spatial remote sensing images. When forests cover change, the spectral characteristics of forests is also changed. In this paper a method on object-based forest cover monitoring with data transformation from time series of high resolution images is put forward. First the NDVI difference image and the composite of PC3,PC4, PC5 of the stacked 8 layers of time series of high resolution satellites are segmented into homogeneous objects. With development of the object-based ruleset classification system, the spatial extent of deforestation and afforestation can be identified over time across the landscape. Finally the change accuracy is achieved with reference data.

  11. High resolution satellite derived erodibility factors for WRF/Chem windblown dust simulations in Argentina

    Science.gov (United States)

    Cremades, Pablo Gabriel; Fernandez, Rafael Pedro; Allend, David; Mulena, Celeste; Puliafito, Salvador Enrique

    2017-04-01

    A proper representation of dust sources is critical to accurately predict atmospheric particle concentrations in regional windblown dust simulations. The Weather Research and Forecasting model with Chemistry (WRF/Chem) includes a topographic-based erodibility map originally conceived for global scale modeling, which fails to identify the geographical location of dust sources in many regions of Argentina. Therefore, this study aims at developing a method to obtain a high-resolution erodibility map suitable for regional or local scale modeling using WRF/Chem. We present two independent approaches based on global methods to estimate soil erodibility using satellite retrievals, i.e. topography from the Shuttle Radar Topography Mission (SRTM) and surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). Simulation results of a severe Zonda wind episode in the arid central-west Argentina serve as bases for the analysis of these methods. Simulated dust concentration at surface level is compared with particulate matter measurements at one site in Mendoza city. In addition, we use satellite aerosol optical depth (AOD) retrievals to investigate model performance in reproducing spatial distribution of dust emissions. The erodibility map based on surface reflectance from MODIS improves the representation of small scale features, and increases the overall dust aerosol loading with respect to the standard map included by default. Simulated concentrations are in good agreement with measurements as well as satellite derived dust spatial distribution.

  12. Assessing Usefulness of High-Resolution Satellite Imagery (HRSI) for Re-Survey of Cadastral Maps

    Science.gov (United States)

    Rao, S. S.; Sharma, J. R.; Rajashekar, S. S.; Rao, D. S. P.; Arepalli, A.; Arora, V.; Kuldeep; Singh, R. P.; Kanaparthi, M.

    2014-11-01

    The Government of India has initiated "National Land Records Modernization Programme (NLRMP)" with emphasis to modernize management of land records, minimize scope of land/property disputes, enhance transparency in the land records maintenance system, and facilitate moving eventually towards guaranteed conclusive titles to immovable properties in the country. One of the major components of the programme is survey/re-survey and updating of all survey and settlement records including creation of original cadastral records wherever necessary. The use of ETS/GPS, Aerial or High Resolution Satellite Images (HRSI) and hybrid method of images are suggested for re-survey in the guidelines. The emerging new satellite technologies enabling earth observation at a spatial resolution of 1.0m or 0.5m or even 0.41m have brought revolutionary changes in the field of cadastral survey. The highresolution satellite imagery (HRSI) is showing its usefulness for cadastral surveys in terms of clear identification of parcel boundaries and other cultural features due to which traditional cadastre and land registration systems have been undergoing major changes worldwide. In the present research study, cadastral maps are derived from ETS/GPS, HRSI of 1.0m and 0.5m and used for comparison. The differences in areas, perimeter and position of parcels derived from HRSI are compared vis-a-vis ETS/GPS boundaries. An assessment has been made on the usefulness of HRSI for re-survey of cadastral maps vis-a-vis conventional ground survey.

  13. Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming

    Science.gov (United States)

    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*.

  14. 3D-Information Fusion from Very High Resolution Satellite Sensors

    OpenAIRE

    Krauss, T; P. d'Angelo; G. Kuschk; Tian, J.; T. Partovi

    2015-01-01

    In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pl´eiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground ...

  15. Using high-resolution satellite imagery to assess populations of animals in the Antarctic

    Science.gov (United States)

    LaRue, Michelle Ann

    The Southern Ocean is one of the most rapidly-changing ecosystems on the planet due to the effects of climate change and commercial fishing for ecologically-important krill and fish. It is imperative that populations of indicator species, such as penguins and seals, be monitored at regional- to global scales to decouple the effects of climate and anthropogenic changes for appropriate ecosystem-based management of the Southern Ocean. Remotely monitoring populations through high-resolution satellite imagery is currently the only feasible way to gain information about population trends of penguins and seals in Antarctica. In my first chapter, I review the literature where high-resolution satellite imagery has been used to assess populations of animals in polar regions. Building on this literature, my second chapter focuses on estimating changes in abundance in the Weddell seal population in Erebus Bay. I found a strong correlation between ground and satellite counts, and this finding provides an alternate method for assessing populations of Weddell seals in areas where less is known about population status. My third chapter explores how size of the guano stain of Adelie penguins can be used to predict population size. Using high-resolution imagery and ground counts, I built a model to estimate the breeding population of Adelie penguins using a supervised classification to estimate guano size. These results suggest that the size of guano stain is an accurate predictor of population size, and can be applied to estimate remote Adelie penguin colonies. In my fourth chapter, I use air photos, satellite imagery, climate and mark-resight data to determine that climate change has positively impacted the population of Adelie penguins at Beaufort Island through a habitat release that ultimately affected the dynamics within the southern Ross Sea metapopulation. Finally, for my fifth chapter I combined the literature with observations from aerial surveys and satellite imagery to

  16. Optimization of post-classification processing of high-resolution satellite image: A case study

    Institute of Scientific and Technical Information of China (English)

    DONG; Rencai; DONG; Jiajia; WU; Gang; DENG; Hongbing

    2006-01-01

    The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 rn resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of

  17. Spatial disaggregation of satellite-derived irradiance using a high-resolution digital elevation model

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz-Arias, Jose A.; Tovar-Pescador, Joaquin [Department of Physics, University of Jaen (Spain); Cebecauer, Tomas [European Commission, Joint Research Centre, Ispra (Italy); GeoModel s.r.o., Bratislava (Slovakia); Institute of Geography, Slovak Academy of Sciences, Bratislava (Slovakia); Suri, Marcel [European Commission, Joint Research Centre, Ispra (Italy); GeoModel s.r.o., Bratislava (Slovakia)

    2010-09-15

    Downscaling of the Meteosat-derived solar radiation ({proportional_to}5 km grid resolution) is based on decomposing the global irradiance and correcting the systematic bias of its components using the elevation and horizon shadowing that are derived from the SRTM-3 digital elevation model (3 arc sec resolution). The procedure first applies the elevation correction based on the difference between coarse and high spatial resolution. Global irradiance is split into direct, diffuse circumsolar and diffuse isotropic components using statistical models, and then corrections due to terrain shading and sky-view fraction are applied. The effect of reflected irradiance is analysed only in the theoretical section. The method was applied in the eastern Andalusia, Spain, and the validation was carried out for 22 days on April, July and December 2006 comparing 15-min estimates of the satellite-derived solar irradiance and observations from nine ground stations. Overall, the corrections of the satellite estimates in the studied region strongly reduced the mean bias of the estimates for clear and cloudy days from roughly 2.3% to 0.4%. (author)

  18. High-resolution satellite-gauge merged precipitation climatologies of the Tropical Andes

    Science.gov (United States)

    Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Lavado, Waldo; Willems, Bram; Robles, Luis Alberto; Rodríguez-Sánchez, Juan-Pablo

    2016-02-01

    Satellite precipitation products are becoming increasingly useful to complement rain gauge networks in regions where these are too sparse to capture spatial precipitation patterns, such as in the Tropical Andes. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) was active for 17 years (1998-2014) and has generated one of the longest single-sensor, high-resolution, and high-accuracy rainfall records. In this study, high-resolution (5 km) gridded mean monthly climatological precipitation is derived from the raw orbital TPR data (TRMM 2A25) and merged with 723 rain gauges using multiple satellite-gauge (S-G) merging approaches. The resulting precipitation products are evaluated by cross validation and catchment water balances (runoff ratios) for 50 catchments across the Tropical Andes. Results show that the TPR captures major synoptic and seasonal precipitation patterns and also accurately defines orographic gradients but underestimates absolute monthly rainfall rates. The S-G merged products presented in this study constitute an improved source of climatological rainfall data, outperforming the gridded TPR product as well as a rain gauge-only product based on ordinary Kriging. Among the S-G merging methods, performance of inverse distance interpolation of satellite-gauge residuals was similar to that of geostatistical methods, which were more sensitive to gauge network density. High uncertainty and low performance of the merged precipitation products predominantly affected regions with low and intermittent precipitation regimes (e.g., Peruvian Pacific coast) and is likely linked to the low TPR sampling frequency. All S-G merged products presented in this study are available in the public domain.

  19. A fast and automatic mosaic method for high-resolution satellite images

    Science.gov (United States)

    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.

  20. Using pan-sharpened high resolution satellite data to improve impervious surfaces estimation

    Science.gov (United States)

    Xu, Ru; Zhang, Hongsheng; Wang, Ting; Lin, Hui

    2017-05-01

    Impervious surface is an important environmental and socio-economic indicator for numerous urban studies. While a large number of researches have been conducted to estimate the area and distribution of impervious surface from satellite data, the accuracy for impervious surface estimation (ISE) is insufficient due to high diversity of urban land cover types. This study evaluated the use of panchromatic (PAN) data in very high resolution satellite image for improving the accuracy of ISE by various pan-sharpening approaches, with a further comprehensive analysis of its scale effects. Three benchmark pan-sharpening approaches, Gram-Schmidt (GS), PANSHARP and principal component analysis (PCA) were applied to WorldView-2 in three spots of Hong Kong. The on-screen digitization were carried out based on Google Map and the results were viewed as referenced impervious surfaces. The referenced impervious surfaces and the ISE results were then re-scaled to various spatial resolutions to obtain the percentage of impervious surfaces. The correlation coefficient (CC) and root mean square error (RMSE) were adopted as the quantitative indicator to assess the accuracy. The accuracy differences between three research areas were further illustrated by the average local variance (ALV) which was used for landscape pattern analysis. The experimental results suggested that 1) three research regions have various landscape patterns; 2) ISE accuracy extracted from pan-sharpened data was better than ISE from original multispectral (MS) data; and 3) this improvement has a noticeable scale effects with various resolutions. The improvement was reduced slightly as the resolution became coarser.

  1. Very High Resolution Satellite Image Classification Using Fuzzy Rule-Based Systems

    Directory of Open Access Journals (Sweden)

    Yun Zhang

    2013-11-01

    Full Text Available The aim of this research is to present a detailed step-by-step method for classification of very high resolution urban satellite images (VHRSI into specific classes such as road, building, vegetation, etc., using fuzzy logic. In this study, object-based image analysis is used for image classification. The main problems in high resolution image classification are the uncertainties in the position of object borders in satellite images and also multiplex resemblance of the segments to different classes. In order to solve this problem, fuzzy logic is used for image classification, since it provides the possibility of image analysis using multiple parameters without requiring inclusion of certain thresholds in the class assignment process. In this study, an inclusive semi-automatic method for image classification is offered, which presents the configuration of the related fuzzy functions as well as fuzzy rules. The produced results are compared to the results of a normal classification using the same parameters, but with crisp rules. The overall accuracies and kappa coefficients of the presented method stand higher than the check projects.

  2. Mapping urban and peri-urban agriculture using high spatial resolution satellite data

    Science.gov (United States)

    Forster, Dionys; Buehler, Yves; Kellenberger, Tobias W.

    2009-03-01

    In rapidly changing peri-urban environments where biophysical and socio-economic processes lead to spatial fragmentation of agricultural land, remote sensing offers an efficient tool to collect land cover/land use (LCLU) data for decision-making. Compared to traditional pixel-based approaches, remote sensing with object-based classification methods is reported to achieve improved classification results in complex heterogeneous landscapes. This study assessed the usefulness of object-oriented analysis of Quickbird high spatial resolution satellite data to classify urban and peri-urban agriculture in a limited peri-urban area of Hanoi, Vietnam. The results revealed that segmentation was essential in developing the object-oriented classification approach. Accurate segmentation of shape and size of an object enhanced classification with spectral, textural, morphological, and topological features. A qualitative, visual comparison of the classification results showed successful localisation and identification of most LCLU classes. Quantitative evaluation was conducted with a classification error matrix reaching an overall accuracy of 67% and a kappa coefficient of 0.61. In general, object-oriented classification of high spatial resolution satellite data proved the promising approach for LCLU analysis at village level. Capturing small-scale urban and peri-urban agricultural diversity offers a considerable potential for environmental monitoring. Challenges remain with the delineation of field boundaries and LCLU diversity on more spatially extensive datasets.

  3. Oil Palm Tree Detection with High Resolution Multi-Spectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Panu Srestasathiern

    2014-10-01

    Full Text Available Oil palm tree is an important cash crop in Thailand. To maximize the productivity from planting, oil palm plantation managers need to know the number of oil palm trees in the plantation area. In order to obtain this information, an approach for palm tree detection using high resolution satellite images is proposed. This approach makes it possible to count the number of oil palm trees in a plantation. The process begins with the selection of the vegetation index having the highest discriminating power between oil palm trees and background. The index having highest discriminating power is then used as the primary feature for palm tree detection. We hypothesize that oil palm trees are located at the local peak within the oil palm area. To enhance the separability between oil palm tree crowns and background, the rank transformation is applied to the index image. The local peak on the enhanced index image is then detected by using the non-maximal suppression algorithm. Since both rank transformation and non-maximal suppression are window based, semi-variogram analysis is used to determine the appropriate window size. The performance of the proposed method was tested on high resolution satellite images. In general, our approach uses produced very accurate results, e.g., about 90 percent detection rate when compared with manual labeling.

  4. Best period for high spatial resolution satellite images for the detection of marks of buried structures

    Directory of Open Access Journals (Sweden)

    Dimitrios Kaimaris

    2012-06-01

    Full Text Available Improvements in sensor technology in recent decades led to the creation of ground, air and space imaging systems, whose data can be used in archaeological studies. Greece is one of the lucky areas that are rich in archaeological heritage. The detection of prehistoric/historic undiscovered constructions on satellite images or aerial photos is a complex and complicated matter. These marks are not visible from the ground, they can, however, be traced on satellite or aerial images, because of the differences in tone and texture. These differences appear as crop, soil and shadow marks. Undoubtedly, the detection of buried structures requires a suitable spatial resolution image, taken under appropriate meteorological conditions and during the best period of the vegetation growing cycle. According to the pertinent literature, detecting covered memorials may be achieved either accidentally or, usually, after a systematic investigation based on historical narratives. The purpose of this study is to determine the factors that facilitate or hinder the detection of buried structures through high spatial resolution satellite imagery. In this study, pan sharpened images from the QuickBird-2 satellite were used, of a spatial resolution of 0.60-0.70 m. This study concerns the detection of marks of the ancient Via Egnatia, from the ancient Amphipolis to Philippi (Eastern Macedonia, Greece. We studied different types of vegetation in the region and their phenological cycle. Taking into account the vegetation phenological cycle of the study area as well as the meteorological data, four pan sharpened QuickBird-2 images of a spatial resolution of 0.60–0.70 m. were used, during four different seasons. By processing the four images, we can determine the one acquired during the most appropriate conditions for the detection of buried structures. The application of this methodology in the study area had positive results, and not only was the main purpose of this

  5. Determination of Destructed and Infracted Forest Areas with Multi-temporal High Resolution Satellite Images

    Science.gov (United States)

    Seker, D. Z.; Unal, A.; Kaya, S.; Alganci, U.

    2015-12-01

    Migration from rural areas to city centers and their surroundings is an important problem of not only our country but also the countries that under development stage. This uncontrolled and huge amount of migration brings out urbanization and socio - economic problems. The demand on settling the industrial areas and commercial activities nearby the city centers results with a negative change in natural land cover on cities. Negative impacts of human induced activities on natural resources and land cover has been continuously increasing for decades. The main human activities that resulted with destruction and infraction of forest areas can be defined as mining activities, agricultural activities, industrial / commercial activities and urbanization. Temporal monitoring of the changes in spatial distribution of forest areas is significantly important for effective management and planning progress. Changes can occur as spatially large destructions or small infractions. Therefore there is a need for reliable, fast and accurate data sources. At this point, satellite images proved to be a good data source for determination of the land use /cover changes with their capability of monitoring large areas with reasonable temporal resolutions. Spectral information derived from images provides discrimination of land use/cover types from each other. Developments in remote sensing technology in the last decade improved the spatial resolution of satellites and high resolution images were started to be used to detect even small changes in the land surface. As being the megacity of Turkey, Istanbul has been facing a huge migration for the last 20 years and effects of urbanization and other human based activities over forest areas are significant. Main focus of this study is to determine the destructions and infractions in forest areas of Istanbul, Turkey with 2.5m resolution SPOT 5 multi-temporal satellite imagery. Analysis was mainly constructed on threshold based classification of

  6. Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

    Directory of Open Access Journals (Sweden)

    Nahuel R. Peralta

    2016-10-01

    Full Text Available A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington of Kansas (total of 457 ha. Three basic tests were conducted on the data: (1 spatial dependence on each of the yield and vegetation indices (VIs using Moran’s I test; (2 model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS and spatial econometric (SPL models; and (3 model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG was tested positive and statistically significant for most of the fields (p < 0.05, except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02 was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to

  7. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    KAUST Repository

    McCabe, Matthew

    2016-10-25

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-Agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  8. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    Science.gov (United States)

    McCabe, Matthew F.; Houborg, Rasmus; Lucieer, Arko

    2016-10-01

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  9. Mapping of CO2 at High Spatiotemporal Resolution using Satellite Observations: Global distributions from OCO-2

    Science.gov (United States)

    Hammerling, Dorit M.; Michalak, Anna M.; Kawa, S. Randolph

    2012-01-01

    Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/ GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1deg latitude x 1.25deg longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

  10. Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

    Science.gov (United States)

    Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

    2016-10-01

    Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

  11. 3D-information fusion from very high resolution satellite sensors

    Science.gov (United States)

    Krauss, T.; d'Angelo, P.; Kuschk, G.; Tian, J.; Partovi, T.

    2015-04-01

    In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pl'eiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground objects are derived. Combining these elevation based data with a spectral classification allows detection and extraction of objects from the satellite scenes. Beside the object extraction also the DSM and DTM can directly be used for simulation and monitoring of environmental issues. Examples are the simulation of floodings, building-volume and people estimation, simulation of noise from roads, wave-propagation for cellphones, wind and light for estimating renewable energy sources, 3D change detection, earthquake preparedness and crisis relief, urban development and sprawl of informal settlements and much more. Also outside of urban areas volume information brings literally a new dimension to earth oberservation tasks like the volume estimations of forests and illegal logging, volume of (illegal) open pit mining activities, estimation of flooding or tsunami risks, dike planning, etc. In this paper we present the preprocessing from the original level-1 satellite data to digital surface models (DSMs), corresponding VHR ortho images and derived digital terrain models (DTMs). From these components we present how a monitoring and decision fusion based 3D change detection can be realized by using different acquisitions. The results are analyzed and assessed to derive quality parameters for the presented method. Finally the usability of 3D information fusion from VHR satellite imagery is discussed and evaluated.

  12. High resolution modeling of CO2 over Europe: implications for representation errors of satellite retrievals

    Directory of Open Access Journals (Sweden)

    T. Koch

    2010-01-01

    Full Text Available Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO2 from the high resolution modeling framework WRF-VPRM, which links CO2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km2 horizontal resolution. Sub-grid variability of column averaged CO2, i.e. the variability not resolved by global models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO2 fluxes as well as resolved mixing ratio of CO2, a linear model can be formulated that could explain about 50% of the spatial patterns in the systematic (bias or correlated error component of representation error in column and near-surface CO2 during day- and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.

  13. Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery

    Science.gov (United States)

    Garrity, Steven R.; Allen, Craig D.; Brumby, Steven P.; Gangodagamage, Chandana; McDowell, Nate G.; Cai, D. Michael

    2013-01-01

    Widespread tree mortality events have recently been observed in several biomes. To effectively quantify the severity and extent of these events, tools that allow for rapid assessment at the landscape scale are required. Past studies using high spatial resolution satellite imagery have primarily focused on detecting green, red, and gray tree canopies during and shortly after tree damage or mortality has occurred. However, detecting trees in various stages of death is not always possible due to limited availability of archived satellite imagery. Here we assess the capability of high spatial resolution satellite imagery for tree mortality detection in a southwestern U.S. mixed species woodland using archived satellite images acquired prior to mortality and well after dead trees had dropped their leaves. We developed a multistep classification approach that uses: supervised masking of non-tree image elements; bi-temporal (pre- and post-mortality) differencing of normalized difference vegetation index (NDVI) and red:green ratio (RGI); and unsupervised multivariate clustering of pixels into live and dead tree classes using a Gaussian mixture model. Classification accuracies were improved in a final step by tuning the rules of pixel classification using the posterior probabilities of class membership obtained from the Gaussian mixture model. Classifications were produced for two images acquired post-mortality with overall accuracies of 97.9% and 98.5%, respectively. Classified images were combined with land cover data to characterize the spatiotemporal characteristics of tree mortality across areas with differences in tree species composition. We found that 38% of tree crown area was lost during the drought period between 2002 and 2006. The majority of tree mortality during this period was concentrated in piñon-juniper (Pinus edulis-Juniperus monosperma) woodlands. An additional 20% of the tree canopy died or was removed between 2006 and 2011, primarily in areas

  14. Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

    Science.gov (United States)

    Husak, G.J.; Marshall, M. T.; Michaelsen, J.; Pedreros, Diego; Funk, Christopher C.; Galu, G.

    2008-01-01

    Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

  15. Automatic cloud detection for high resolution satellite stereo images and its application in terrain extraction

    Science.gov (United States)

    Wu, Teng; Hu, Xiangyun; Zhang, Yong; Zhang, Lulin; Tao, Pengjie; Lu, Luping

    2016-11-01

    The automatic extraction of terrain from high-resolution satellite optical images is very difficult under cloudy conditions. Therefore, accurate cloud detection is necessary to fully use the cloud-free parts of images for terrain extraction. This paper addresses automated cloud detection by introducing an image matching based method under a stereo vision framework, and the optimization usage of non-cloudy areas in stereo matching and the generation of digital surface models (DSMs). Given that clouds are often separated from the terrain surface, cloudy areas are extracted by integrating dense matching DSM, worldwide digital elevation model (DEM) (i.e., shuttle radar topography mission (SRTM)) and gray information from the images. This process consists of the following steps: an image based DSM is firstly generated through a multiple primitive multi-image matcher. Once it is aligned with the reference DEM based on common features, places with significant height differences between the DSM and the DEM will suggest the potential cloud covers. Detecting cloud at these places in the images then enables precise cloud delineation. In the final step, elevations of the reference DEM within the cloud covers are assigned to the corresponding region of the DSM to generate a cloud-free DEM. The proposed approach is evaluated with the panchromatic images of the Tianhui satellite and has been successfully used in its daily operation. The cloud detection accuracy for images without snow is as high as 95%. Experimental results demonstrate that the proposed method can significantly improve the usage of the cloudy panchromatic satellite images for terrain extraction.

  16. AN EFFICIENT APPROACH FOR EXTRACTION OF LINEAR FEATURES FROM HIGH RESOLUTION INDIAN SATELLITE IMAGERIES

    Directory of Open Access Journals (Sweden)

    DK Bhattacharyya

    2010-07-01

    Full Text Available This paper presents an Object oriented feature extraction approach in order to classify the linear features like drainage, roads etc. from high resolution Indian satellite imageries. It starts with the multiresolution segmentations of image objects for optimal separation and representation of image regions or objects. Fuzzy membership functions were defined for a selected set of image object parameters such as mean, ratio, shape index, area etc. for representation of required image objects. Experiment was carried out for both panchromatic (CARTOSAT-I and multispectral (IRSP6 LISS IV Indiansatellite imageries. Experimental results show that the extractionof linear features can be achieved in a satisfactory level throughproper segmentation and appropriate definition & representationof key parameters of image objects.

  17. High-resolution satellite image segmentation using Hölder exponents

    Indian Academy of Sciences (India)

    Debasish Chakraborty; Gautam Kumar Sen; Sugata Hazra

    2009-10-01

    Texture in high-resolution satellite images requires substantial amendment in the conventional segmentation algorithms. A measure is proposed to compute the Hölder exponent (HE) to assess the roughness or smoothness around each pixel of the image. The localized singularity information is incorporated in computing the HE. An optimum window size is evaluated so that HE reacts to localized singularity. A two-step iterative procedure for clustering the transformed HE image is adapted to identify the range of HE, densely occupied in the kernel and to partition Hölder exponents into a cluster that matches with the range. Hölder exponent values (noise or not associated with the other cluster) are clubbed to a nearest possible cluster using the local maximum likelihood analysis.

  18. Automatic Blocked Roads Assessment after Earthquake Using High Resolution Satellite Imagery

    Science.gov (United States)

    Rastiveis, H.; Hosseini-Zirdoo, E.; Eslamizade, F.

    2015-12-01

    In 2010, an earthquake in the city of Port-au-Prince, Haiti, happened quite by chance an accident and killed over 300000 people. According to historical data such an earthquake has not occurred in the area. Unpredictability of earthquakes has necessitated the need for comprehensive mitigation efforts to minimize deaths and injuries. Blocked roads, caused by debris of destroyed buildings, may increase the difficulty of rescue activities. In this case, a damage map, which specifies blocked and unblocked roads, can be definitely helpful for a rescue team. In this paper, a novel method for providing destruction map based on pre-event vector map and high resolution world view II satellite images after earthquake, is presented. For this purpose, firstly in pre-processing step, image quality improvement and co-coordination of image and map are performed. Then, after extraction of texture descriptor from the image after quake and SVM classification, different terrains are detected in the image. Finally, considering the classification results, specifically objects belong to "debris" class, damage analysis are performed to estimate the damage percentage. In this case, in addition to the area objects in the "debris" class their shape should also be counted. The aforementioned process are performed on all the roads in the road layer.In this research, pre-event digital vector map and post-event high resolution satellite image, acquired by Worldview-2, of the city of Port-au-Prince, Haiti's capital, were used to evaluate the proposed method. The algorithm was executed on 1200×800 m2 of the data set, including 60 roads, and all the roads were labelled correctly. The visual examination have authenticated the abilities of this method for damage assessment of urban roads network after an earthquake.

  19. AUTOMATIC BLOCKED ROADS ASSESSMENT AFTER EARTHQUAKE USING HIGH RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    H. Rastiveis

    2015-12-01

    Full Text Available In 2010, an earthquake in the city of Port-au-Prince, Haiti, happened quite by chance an accident and killed over 300000 people. According to historical data such an earthquake has not occurred in the area. Unpredictability of earthquakes has necessitated the need for comprehensive mitigation efforts to minimize deaths and injuries. Blocked roads, caused by debris of destroyed buildings, may increase the difficulty of rescue activities. In this case, a damage map, which specifies blocked and unblocked roads, can be definitely helpful for a rescue team. In this paper, a novel method for providing destruction map based on pre-event vector map and high resolution world view II satellite images after earthquake, is presented. For this purpose, firstly in pre-processing step, image quality improvement and co-coordination of image and map are performed. Then, after extraction of texture descriptor from the image after quake and SVM classification, different terrains are detected in the image. Finally, considering the classification results, specifically objects belong to “debris” class, damage analysis are performed to estimate the damage percentage. In this case, in addition to the area objects in the “debris” class their shape should also be counted. The aforementioned process are performed on all the roads in the road layer.In this research, pre-event digital vector map and post-event high resolution satellite image, acquired by Worldview-2, of the city of Port-au-Prince, Haiti's capital, were used to evaluate the proposed method. The algorithm was executed on 1200×800 m2 of the data set, including 60 roads, and all the roads were labelled correctly. The visual examination have authenticated the abilities of this method for damage assessment of urban roads network after an earthquake.

  20. Satellite-Based Derivation of High-Resolution Forest Information Layers for Operational Forest Management

    Directory of Open Access Journals (Sweden)

    Johannes Stoffels

    2015-06-01

    Full Text Available A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.

  1. Proximity graph analysis for linear networks extraction from high-resolution satellite imagery

    Science.gov (United States)

    Skourikhine, Alexei N.

    2006-05-01

    Reliable and accurate methods for detection and extraction of linear network, such as road networks, in satellite imagery are essential to many applications. We present an approach to the road network extraction from high-resolution satellite imagery that is based on proximity graph analysis. We are jumping off from the classification provided by existing spectral and textural classification tools, which produce a set of candidate road patches. Then, constrained Delaunay triangulation and Chordal Axis transform are used to extract centerline characterization of the delineated candidate road patches. We refine produced center lines to reduce noise influence on patch boundaries, resulting in a smaller set of robust center lines authentically representing their road patches. Refined center lines are triangulated using constrained Delaunay triangulation (CDT) algorithm to generate a sub-optimal mesh of interconnections among them. The generated triangle edges connecting different center lines are used for spatial analysis of the center lines relations. A subset of the Delaunay tessellation grid contains the Euclidian Minimum Spanning Tree (EMST) that provides an approximation of road network. The approach can be generalized to the multi-criteria MST and multi-criteria shortest path algorithms to integrate other factors important for road network extraction, in addition to proximity relations considered by standard EMST.

  2. The Black Sea coastal zone in the high resolution satellite images

    Science.gov (United States)

    Yurovskaya, Maria; Dulov, Vladimir; Kozlov, Igor

    2016-04-01

    Landsat data with spatial resolution of 30-100 m provide the ability of regular monitoring of ocean phenomena with scale of 100-1000 m. Sentinel-1 is equipped with C-band synthetic aperture radar. The images allow recognizing the features that affect either the sea surface roughness, or its color characteristics. The possibilities of using the high spatial resolution satellite data are considered for observation and monitoring of Crimean coastal zone. The analyzed database includes all Landsat-8 (Level 1) multi-channel images from January 2013 to August 2015 and all Sentinel-1 radar images in May-August 2015. The goal of the study is to characterize the descriptiveness of these data for research and monitoring of the Crimean coastal areas. The observed marine effects are reviewed and the physical mechanisms of their signatures in the satellite images are described. The effects associated with the roughness variability are usually manifested in all bands, while the subsurface phenomena are visible only in optical data. Confidently observed structures include internal wave trains, filamentous natural slicks, which reflect the eddy coastal dynamics, traces of moving ships and the oil films referred to anthropogenic pollution of marine environment. The temperature fronts in calm conditions occur due to surfactant accumulation in convergence zone. The features in roughness field can also be manifested in Sentinel-1 data. Subsurface processes observed in Landsat-8 images primarily include transport and distribution of suspended matter as a result of floods and sandy beach erosion. The surfactant always concentrates on the sea surface in contaminated areas, so that these events are also observed in Sentinel-1 images. A search of wastewater discharge manifestations is performed. The investigation provides the basis for further development of approaches to obtain quantitative characteristics of the phenomena themselves. Funding by Russian Science Foundation under grant 15

  3. Retrieval Using Texture Features in High Resolution Multi-spectral Satellite Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Newsam, S D; Kamath, C

    2004-01-22

    Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region types. Much of the work done thus far has focused on panchromatic imagery at low to moderate spatial resolutions, such as images from Landsat 1-7 which have a resolution of 15-30 m/pixel, and from SPOT 1-5 which have a resolution of 2.5-20 m/pixel. However, it is not clear which texture representation works best for the new classes of high resolution panchromatic (60-100 cm/pixel) and multi-spectral (4 bands for red, green, blue, and near infra-red at 2.4-4 m/pixel) imagery. It is also not clear how the different spectral bands should be combined. In this paper, we investigate the retrieval performance of several different texture representations using multi-spectral satellite images from IKONOS. A query-by-example framework, along with a manually chosen ground truth dataset, allows different combinations of texture representations and spectral bands to be compared. We focus on the specific problem of retrieving inhabited regions from images of urban and rural scenes. Preliminary results show that (1) the use of all spectral bands improves the retrieval performance, and (2) co-occurrence, wavelet and Gabor texture features perform comparably.

  4. Using very high resolution satellite images to identify coastal zone dynamics at North Western Black Sea

    Science.gov (United States)

    Florin Zoran, Liviu; Ionescu Golovanov, Carmen; Zoran, Maria

    2010-05-01

    The availability of updated information about the extension and characteristics of land cover is a crucial issue in the perspective of a correct landscape planning and management of marine coastal zones. Satellite remote sensing data can provide accurate information about land coverage at different scales and the recent availability of very high resolution images definitely improved the precision of coastal zone spatio-temporal changes. The Romanian North Western coastal and shelf zones of the Black Sea and Danube delta are a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in the Black Sea's ecosystem and resources are due to natural and anthropogenic causes (increase in the nutrient and pollutant load of rivers input, industrial and municipal wastewater pollution along the coast, and dumping on the open sea). A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic processes, coastal erosion, sedimentation dynamics, mapping of macrophyte fields, water quality, and climatic change effects. Use of satellite images is of great help for coastal zone monitoring and environmental impact assessment. Synergetic use of in situ measurements with multisensors satellite data could provide a complex assessment of spatio-temporal changes. In this study was developed a method for extracting coastal zone features information as well as landcover dynamics from IKONOS, very high resolution images for North-Western Black Sea marine coastal zone. The main objective was obtaining reliable data about the spatio-temporal coastal zone changes in two study areas located in Constanta urban area and Danube Delta area. We used an object-oriented approach based on preliminary segmentation and classification of the resulting object. First of all, segmentation parameters were tested and selected comparing segmented polygons with

  5. High-spatial resolution multispectral and panchromatic satellite imagery for mapping perennial desert plants

    Science.gov (United States)

    Alsharrah, Saad A.; Bruce, David A.; Bouabid, Rachid; Somenahalli, Sekhar; Corcoran, Paul A.

    2015-10-01

    The use of remote sensing techniques to extract vegetation cover information for the assessment and monitoring of land degradation in arid environments has gained increased interest in recent years. However, such a task can be challenging, especially for medium-spatial resolution satellite sensors, due to soil background effects and the distribution and structure of perennial desert vegetation. In this study, we utilised Pleiades high-spatial resolution, multispectral (2m) and panchromatic (0.5m) imagery and focused on mapping small shrubs and low-lying trees using three classification techniques: 1) vegetation indices (VI) threshold analysis, 2) pre-built object-oriented image analysis (OBIA), and 3) a developed vegetation shadow model (VSM). We evaluated the success of each approach using a root of the sum of the squares (RSS) metric, which incorporated field data as control and three error metrics relating to commission, omission, and percent cover. Results showed that optimum VI performers returned good vegetation cover estimates at certain thresholds, but failed to accurately map the distribution of the desert plants. Using the pre-built IMAGINE Objective OBIA approach, we improved the vegetation distribution mapping accuracy, but this came at the cost of over classification, similar to results of lowering VI thresholds. We further introduced the VSM which takes into account shadow for further refining vegetation cover classification derived from VI. The results showed significant improvements in vegetation cover and distribution accuracy compared to the other techniques. We argue that the VSM approach using high-spatial resolution imagery provides a more accurate representation of desert landscape vegetation and should be considered in assessments of desertification.

  6. Hitomi X-ray Astronomy Satellite: Power of High-Resolution Spectroscopy

    Science.gov (United States)

    Odaka, Hirokazu; Aff001

    2017-01-01

    Hitomi (ASTRO-H) is an X-ray observatory developed by an international collaboration led by JAXA. An X-ray microcalorimeter onboard this satellite has opened a new window of high-resolution spectroscopy with an unprecedented energy resolution of 5 eV (FWHM) at 6 keV. The spacecraft was launched on February 17, 2016 from Tanegashima Island, Japan, and we completed initial operations including deployment of the hard X-ray imagers on the extensible optical bench. All scientific instruments had successfully worked until the sudden loss of the mission on March 26. We have obtained a spectrum showing fully resolved emission lines through the first-light observation of the Perseus Cluster. The line-of-sight velocity dispersion of 164 +/- 10 km s-1 reveals the quiescent environment of intracluster medium at the cluster core, implying that measured cluster mass requires little correction for the turbulent pressure. We also discuss observations to the Galactic Center which could be performed with Hitomi.

  7. [Design and study of a high resolution vacuum ultraviolet imaging spectrometer carried by satellite].

    Science.gov (United States)

    Yu, Lei; Lin, Guan-yu; Qu, Yi; Wang, Shu-rong; Wang, Long-qi

    2011-12-01

    A high resolution vacuum ultraviolet imaging spectrometer prototype carried by satellite applied to the atmosphere detection of particles distribution in 115-300 nm was developed for remote sensing. First, based on the analysis of advanced loads, the optical system including an off-axis parabolic mirror as the telescope and Czerny-Turner structure as the imaging spectrometer was chosen Secondly, the 2-D photon counting detector with MCP was adopted for the characteristic that the radiation is weak in vacuum ultraviolet waveband. Then the geometric method and 1st order differential calculation were introduced to improve the disadvantages that aberrations in the traditional structure can not be corrected homogeneously to achieve perfect broadband imaging based on the aberration theory. At last, an advanced example was designed. The simulation and calculation of results demonstrate that the modulation transfer function (MTF) of total field of view is more than 0.6 in the broadband, and the spectral resolution is 1.23 nm. The structure is convenient and predominant. It proves that the design is feasible.

  8. VAST PLANES OF SATELLITES IN A HIGH-RESOLUTION SIMULATION OF THE LOCAL GROUP: COMPARISON TO ANDROMEDA

    Energy Technology Data Exchange (ETDEWEB)

    Gillet, N.; Ocvirk, P.; Aubert, D. [Observatoire astronomique de Strasbourg, Université de Strasbourg, CNRS, UMR 7550, 11 rue de lUniversité, F-67000 Strasbourg (France); Knebe, A.; Yepes, G. [Departamento de Física Teórica, Módulo, Universidad Autónomade Madrid, Cantoblanco E-28049 (Spain); Libeskind, N.; Gottlöber, S. [Leibniz-Institute für Astrophysik Potsdam (AIP), An der Sternwarte 16, D-14482 Potsdam (Germany); Hoffman, Y. [Racah Institute of Physics, Hebrew University, Jerusalem 91904 (Israel)

    2015-02-10

    We search for vast planes of satellites (VPoS) in a high-resolution simulation of the Local Group performed by the CLUES project, which improves significantly the resolution of previous similar studies. We use a simple method for detecting planar configurations of satellites, and validate it on the known plane of M31. We implement a range of prescriptions for modeling the satellite populations, roughly reproducing the variety of recipes used in the literature, and investigate the occurrence and properties of planar structures in these populations. The structure of the simulated satellite systems is strongly non-random and contains planes of satellites, predominantly co-rotating, with, in some cases, sizes comparable to the plane observed in M31 by Ibata et al. However, the latter is slightly richer in satellites, slightly thinner, and has stronger co-rotation, which makes it stand out as overall more exceptional than the simulated planes, when compared to a random population. Although the simulated planes we find are generally dominated by one real structure forming its backbone, they are also partly fortuitous and are thus not kinematically coherent structures as a whole. Provided that the simulated and observed planes of satellites are indeed of the same nature, our results suggest that the VPoS of M31 is not a coherent disk and that one-third to one-half of its satellites must have large proper motions perpendicular to the plane.

  9. A procedure for semi-Automatic Orthophoto Generation from High Resolution Satellite Imagery

    Science.gov (United States)

    Alrajhi, M. N.; Jacobsen, K.; Heipke, C.

    2013-10-01

    The General Directorate of Surveying and Mapping (GDSM), under the Ministry of Municipal and Rural Affairs (MOMRA) is responsible for the production and dissemination of accurate geospatial data for all the metropolitan cities, towns and rural settlements in the Kingdom of Saudi Arabia. GDSM maintains digital geospatial databases that support the production of conventional line and orthophoto maps at scales ranging from 1:1,000 to 1:20,000. The current procedures for the acquisition of new aerial imagery cover a long time cycle of three or more years. Consequently, the availability of recently acquired High Resolution Satellite Imagery (HRSI) presents an attractive alternative image data source for rapid response to updated geospatial data needs. The direct sensor orientation of HRSI is not accurate enough requiring ground control points (GCP). A field survey of GCP is time consuming and costly. Seeking an alternative approach, a research study has recently been completed to use existing image and data base information instead of traditional ground control for the orthoprojection of HRSI in order to automate and speed up as much as possible the whole process. Based on a series of practical experiments, the ability for automated matching of aerial and satellite images by using the Speeded-Up Robust Features (SURF) algorithm is demonstrated to be useful for this task. Practical results from matching with SURF validate the ability for multi-scale, multi-sensor and multi-season matching of aerial and satellite images. The matched tie points are then used to transform the satellite orthophoto to the aerial orthophoto through a 2D affine coordinate transformation. GeoEye-1 and IKONOS imagery, when geo-referenced through SURF-based matching and transformed meet the MOMRA Map Accuracy Standards for 1:10,000 and 1:20,000 scale. However, a similarly processed SPOT-5 image does not meet these standards. This research has led to the development of a simple and efficient tool

  10. Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India

    Science.gov (United States)

    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.

  11. Demarcation of Prime Farmland Protection Areas around a Metropolis Based on High-Resolution Satellite Imagery

    Science.gov (United States)

    Xia, Nan; Wang, Yajun; Xu, Hao; Sun, Yuefan; Yuan, Yi; Cheng, Liang; Jiang, Penghui; Li, Manchun

    2016-12-01

    Prime farmland (PF) is defined as high-quality farmland and a prime farmland protection area (PFPA, including related roads, waters and facilities) is a region designated for the special protection of PF. However, rapid urbanization in China has led to a tremendous farmland loss and to the degradation of farmland quality. Based on remote sensing and geographic information system technology, this study developed a semiautomatic procedure for designating PFPAs using high-resolution satellite imagery (HRSI), which involved object-based image analysis, farmland composite evaluation, and spatial analysis. It was found that the HRSIs can provide elaborate land-use information, and the PFPA demarcation showed strong correlation with the farmland area and patch distance. For the benefit of spatial planning and management, different demarcation rules should be applied for suburban and exurban areas around a metropolis. Finally, the overall accuracy of HRSI classification was about 80% for the study area, and high-quality farmlands from evaluation results were selected as PFs. About 95% of the PFs were demarcated within the PFPAs. The results of this study will be useful for PFPA planning and the methods outlined could help in the automatic designation of PFPAs from the perspective of the spatial science.

  12. Evaluating the Road Safety Design through High Resolution Satellite Image: A Case Study of Karachi Metropolitan

    Directory of Open Access Journals (Sweden)

    Zubair Salman

    2016-01-01

    Full Text Available Humanity is suffering from numerous natural, technological and health related hazards. Urban Road crash is one of the growing health issues these days in both developed and developing countries. Pakistan stands 1st in Asia and 48th in the world in this regard. Similarly, the metropolitan city of Pakistan, Karachi; ranks fourth in the list. Various reasons are responsible for these crashes in Karachi. Around 34% of crashes in the city were accounted due to errors in road geometry. In this study use of high resolution satellite imagery made it possible for identifying geometrical errors at the U-turns on major arteries of the city. It was also recognized that most of the U-turns were built on the fastest lane of the roads with average distance of 1.1 Km apart, are marked as vulnerable for considerable number of severe injury and fatal crashes. Moreover, inlet wall of all median U-turns were found broken, suggested that the car crash had occurred at least once. To cross check this observation, nearly 120 U-turns were surveyed and marked on the satellite imagery based on convenience. Trained professionals interviewed the people working/living nearby the U-turns. Out of 120 U-turns studied, 72.5% were without wall/median and 27.5% were with wall/median. Average number of people got injured or died due to crashes were statistically significant (p<0.05 between the above mentioned types of U-turns. In order to reduce geometrical errors use of RS (Remote Sensing and GIS (Geographical Information System techniques are strongly suggested to be incorporated while planning road design in the city. This would certainly save the resources particularly the lives of the people.

  13. Exploring image data assimilation in the prospect of high-resolution satellite oceanic observations

    Science.gov (United States)

    Durán Moro, Marina; Brankart, Jean-Michel; Brasseur, Pierre; Verron, Jacques

    2017-07-01

    Satellite sensors increasingly provide high-resolution (HR) observations of the ocean. They supply observations of sea surface height (SSH) and of tracers of the dynamics such as sea surface salinity (SSS) and sea surface temperature (SST). In particular, the Surface Water Ocean Topography (SWOT) mission will provide measurements of the surface ocean topography at very high-resolution (HR) delivering unprecedented information on the meso-scale and submeso-scale dynamics. This study investigates the feasibility to use these measurements to reconstruct meso-scale features simulated by numerical models, in particular on the vertical dimension. A methodology to reconstruct three-dimensional (3D) multivariate meso-scale scenes is developed by using a HR numerical model of the Solomon Sea region. An inverse problem is defined in the framework of a twin experiment where synthetic observations are used. A true state is chosen among the 3D multivariate states which is considered as a reference state. In order to correct a first guess of this true state, a two-step analysis is carried out. A probability distribution of the first guess is defined and updated at each step of the analysis: (i) the first step applies the analysis scheme of a reduced-order Kalman filter to update the first guess probability distribution using SSH observation; (ii) the second step minimizes a cost function using observations of HR image structure and a new probability distribution is estimated. The analysis is extended to the vertical dimension using 3D multivariate empirical orthogonal functions (EOFs) and the probabilistic approach allows the update of the probability distribution through the two-step analysis. Experiments show that the proposed technique succeeds in correcting a multivariate state using meso-scale and submeso-scale information contained in HR SSH and image structure observations. It also demonstrates how the surface information can be used to reconstruct the ocean state below

  14. High resolution 3-D temperature and salinity fields derived from in situ and satellite observations

    Directory of Open Access Journals (Sweden)

    S. Guinehut

    2012-10-01

    Full Text Available This paper describes an observation-based approach that efficiently combines the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 yr are merged with the lower accuracy but high-resolution synthetic data derived from satellite altimeter and sea surface temperature observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations, and salinity fields from altimeter observations, through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolutionary nature of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method, and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50% of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30% of the signal can be reconstructed from altimeter observations, making the in situ observing system essential for salinity estimates. The in situ observations (step 2 of the method further reduce the differences between the gridded products and the observations by up to 20% for the temperature field in the mixed layer, and the main contribution is for salinity and the near surface layer with an improvement up to 30%. Compared to estimates derived using in situ observations only, the

  15. High Resolution 3-D temperature and salinity fields derived from in situ and satellite observations

    Directory of Open Access Journals (Sweden)

    S. Guinehut

    2012-03-01

    Full Text Available This paper describes an observation-based approach that combines efficiently the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 years are merged with the lower accuracy but high-resolution synthetic data derived from altimeter and sea surface temperature satellite observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations and salinity fields from altimeter observations through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolution of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50 % of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30 % of the signal can be reconstructed from altimeter observations, making the in situ observing system mandatory for salinity estimates. The in situ observations (step 2 of the method reduce additionally the error by up to 20 % for the temperature field in the mixed layer and the main contribution is for salinity and the near surface layer with an improvement up to 30 %. Compared to estimates derived using in situ observations only, the merged fields provide a better reconstruction of the high

  16. Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

    Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

  17. A Multi-stage Method to Extract Road from High Resolution Satellite Image

    Science.gov (United States)

    Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang

    2014-03-01

    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.

  18. 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.

  19. Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents a preliminary result on the retrieval of atmospheric ozone profiles using an im proved regression technique and utilizing the data from the Atmospheric InfraRed Sounder (AIRS), a hyper-spectral instrument expected to be flown on the EOS-AQUA platform in 2002. Simulated AIRS spectra were used to study the sensitivity of AIRS radiance on the tropospheric and stratospheric ozone changes, and to study the impact of various channel combinations on the ozone profile retrieval. Sensitivity study results indicate that the AIRS high resolution spectral channels between the wavenumber 650- 800 cm-1 provide very useful information to accurately retrieve tropospheric and stratospheric ozone pro files. Eigenvector decomposition of AIRS spectra indicate that no more than 100 eigenvectors are needed to retrieve very accurate ozone profiles. The accuracy of the retrieved atmospheric ozone profile from the pres ent technique and utilizing the AIRS data was compared with the accuracy obtained from current Advanced TIROS Operational Vertical Sounder (ATOVS) data aboard National Oceanic and Atmospheric Admini stration (NOAA) satellites. As expected, a comparison of retrieval results confirms that the ozone profile re trieved with the AIRS data is superior to that of ATOVS.

  20. Change detection from very high resolution satellite time series with variable off-nadir angle

    Science.gov (United States)

    Barazzetti, Luigi; Brumana, Raffaella; Cuca, Branka; Previtali, Mattia

    2015-06-01

    Very high resolution (VHR) satellite images have the potential for revealing changes occurred overtime with a superior level of detail. However, their use for metric purposes requires accurate geo-localization with ancillary DEMs and GCPs to achieve sub-pixel terrain correction, in order to obtain images useful for mapping applications. Change detection with a time series of VHS images is not a simple task because images acquired with different off-nadir angles have a lack of pixel-to-pixel image correspondence, even after accurate geo-correction. This paper presents a procedure for automatic change detection able to deal with variable off-nadir angles. The case study concerns the identification of damaged buildings from pre- and post-event images acquired on the historic center of L'Aquila (Italy), which was struck by an earthquake in April 2009. The developed procedure is a multi-step approach where (i) classes are assigned to both images via object-based classification, (ii) an initial alignment is provided with an automated tile-based rubber sheeting interpolation on the extracted layers, and (iii) change detection is carried out removing residual mis-registration issues resulting in elongated features close to building edges. The method is fully automated except for some thresholds that can be interactively set to improve the visualization of the damaged buildings. The experimental results proved that damages can be automatically found without additional information, such as digital surface models, SAR data, or thematic vector layers.

  1. Improved global high resolution precipitation estimation using multi-satellite multi-spectral information

    Science.gov (United States)

    Behrangi, Ali

    In respond to the community demands, combining microwave (MW) and infrared (IR) estimates of precipitation has been an active area of research since past two decades. The anticipated launching of NASA's Global Precipitation Measurement (GPM) mission and the increasing number of spectral bands in recently launched geostationary platforms will provide greater opportunities for investigating new approaches to combine multi-source information towards improved global high resolution precipitation retrievals. After years of the communities' efforts the limitations of the existing techniques are: (1) Drawbacks of IR-only techniques to capture warm rainfall and screen out no-rain thin cirrus clouds; (2) Grid-box- only dependency of many algorithms with not much effort to capture the cloud textures whether in local or cloud patch scale; (3) Assumption of indirect relationship between rain rate and cloud-top temperature that force high intensity precipitation to any cold cloud; (4) Neglecting the dynamics and evolution of cloud in time; (5) Inconsistent combination of MW and IR-based precipitation estimations due to the combination strategies and as a result of above described shortcomings. This PhD dissertation attempts to improve the combination of data from Geostationary Earth Orbit (GEO) and Low-Earth Orbit (LEO) satellites in manners that will allow consistent high resolution integration of the more accurate precipitation estimates, directly observed through LEO's PMW sensors, into the short-term cloud evolution process, which can be inferred from GEO images. A set of novel approaches are introduced to cope with the listed limitations and is consist of the following four consecutive components: (1) starting with the GEO part and by using an artificial-neural network based method it is demonstrated that inclusion of multi-spectral data can ameliorate existing problems associated with IR-only precipitating retrievals; (2) through development of Precipitation Estimation

  2. The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation

    Science.gov (United States)

    Williams, Jason E.; Folkert Boersma, K.; Le Sager, Phillipe; Verstraeten, Willem W.

    2017-02-01

    We provide a comprehensive description of the high-resolution version of the TM5-MP global chemistry transport model, which is to be employed for deriving highly resolved vertical profiles of nitrogen dioxide (NO2), formaldehyde (CH2O), and sulfur dioxide (SO2) for use in satellite retrievals from platforms such as the Ozone Monitoring Instrument (OMI) and the Sentinel-5 Precursor, and the TROPOspheric Monitoring Instrument (tropOMI). Comparing simulations conducted at horizontal resolutions of 3° × 2° and 1° × 1° reveals differences of ±20 % exist in the global seasonal distribution of 222Rn, being larger near specific coastal locations and tropical oceans. For tropospheric ozone (O3), analysis of the chemical budget terms shows that the impact on globally integrated photolysis rates is rather low, in spite of the higher spatial variability of meteorological data fields from ERA-Interim at 1° × 1°. Surface concentrations of O3 in high-NOx regions decrease between 5 and 10 % at 1° × 1° due to a reduction in NOx recycling terms and an increase in the associated titration term of O3 by NO. At 1° × 1°, the net global stratosphere-troposphere exchange of O3 decreases by ˜ 7 %, with an associated shift in the hemispheric gradient. By comparing NO, NO2, HNO3 and peroxy-acetyl-nitrate (PAN) profiles against measurement composites, we show that TM5-MP captures the vertical distribution of NOx and long-lived NOx reservoirs at background locations, again with modest changes at 1° × 1°. Comparing monthly mean distributions in lightning NOx and applying ERA-Interim convective mass fluxes, we show that the vertical re-distribution of lightning NOx changes with enhanced release of NOx in the upper troposphere. We show that surface mixing ratios in both NO and NO2 are generally underestimated in both low- and high-NOx scenarios. For Europe, a negative bias exists for [NO] at the surface across the whole domain, with lower biases at 1° × 1° at only ˜ 20

  3. The application of very high resolution satellite image in urban vegetation cover investigation: a case study of Xiamen City

    Institute of Scientific and Technical Information of China (English)

    CHENGChengqi; LiBin; MATing

    2003-01-01

    With the technological improvements of satellite sensors, we will acquire more information about the earth so that we have reached a new application epoch of observation on earth environmental change and cartography. But with the enhancement of spatial resolution, some questions have arisen in the application of using traditional image processing and classification methods. Aiming for such questions, we studied the application of IKONOS very high resolution image (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the difference between the very high resolution image and traditional low spatial resolution image at classification,information abstraction etc. It is an advantageous test for the large-scale application of very high resolution data in the future.

  4. Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery

    Directory of Open Access Journals (Sweden)

    CAO Yungang

    2016-10-01

    Full Text Available A novel approach for road centerline extraction from high spatial resolution satellite imagery is proposed by fusing both pixel-based and object-based features. Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps. Then, extracted multiple features are utilized in the fusion framework of Dempster-Shafer evidence theory to roughly identify the road network regions. Finally, an automatic noise removing algorithm combined with the tensor voting strategy is presented to accurately extract the road centerline. Experimental results using high-resolution satellite imageries with different scenes and spatial resolutions showed that the proposed approach compared favorably with the traditional methods, particularly in the aspect of eliminating the salt noise and conglutination phenomenon.

  5. Satellite monitoring at high spatial resolution of water bodies used for irrigation purposes

    Science.gov (United States)

    Baup, F.; Flanquart, S.; Marais-Sicre, C.; Fieuzal, R.

    2012-04-01

    In a changing climate context, with an increase of the need for food, it becomes increasingly important to improve our knowledge for monitoring agricultural surfaces by satellite for a better food management and to reduce the waste of natural resources (water storages and shortages, irrigation management, increase of soil and water salinity, soil erosion, threats on biodiversity). The main objective of this study is to evaluate the potentialities of multi-spectral and multi-resolution satellites for monitoring the temporal evolution of water bodies surfaces (mainly used for irrigation purposes). This analysis is based on the use of a series of images acquired between the years 2003 and 2011. The year 2010 is considered as a reference, with 110 acquisitions performed during the MCM'10 campaign (Multispectral Crop Monitoring 2010, http://www.cesbio.ups-tlse.fr/us/mcm.html). Those images are provided by 8 satellites (optical, thermal and RADAR) such as ALOS, TERRASAR-X, RADARSAT-2, FORMOSAT-2, SPOT-2, SPOT-4, SPOT-5, LANDSAT-5. The studied area is situated in the South-West of Toulouse in France; in a region governed by a temperate climate. The irrigated cultures represent almost 12% of the cultivated surface in 2009. The method consists in estimating the water bodies surfaces by using a generic approach suitable for all images, whatever the wavelength (optical, infrared, RADAR). The supervised parallelepiped classification allows discriminating four types of surfaces coverage: forests, water expanses, crops and bare soils. All RADAR images are filtered (Gamma) to reduce speckle effects and false detections of water bodies. In the context if the "South-West" project of the CESBIO laboratory, two spatial coverages are analyzed: SPOT 4 (4800km2) and FORMOSAT 2 (576km2). At these scales, 154 and 38 water bodies are identify. They respectively represent 4.85 km2 (0.10% of the image cover) and 2.06 km2 (0.36% of the image cover). Statistical analyses show that 8% of lakes

  6. High Resolution Imagery and Three-line Array Imagery Automatic Registration for China’s TH-1 Satellite Imagery

    OpenAIRE

    2014-01-01

    An automatic image registration method of high resolution (HR) imagery and three-line array imagery for China’s TH-1 mapping satellite is invented. The 2m resolution HR imagery is normalized to 5m resolution three-line array imagery firstly. Then using precise point prediction model (P3M) matching method, thousands of correspondent points can be matched. Based on these matched points, feature points collected on HR imagery can be converted onto three-line array imagery automatically. Conseque...

  7. Delineating Tree Types in a Complex Tropical Forest Setting Using High Resolution Multispectral Satellite Imagery

    Science.gov (United States)

    Cross, M.

    2016-12-01

    An improved process for the identification of tree types from satellite imagery for tropical forests is needed for more accurate assessments of the impact of forests on the global climate. La Selva Biological Station in Costa Rica was the tropical forest area selected for this particular study. WorldView-3 imagery was utilized because of its high spatial, spectral and radiometric resolution, its availability, and its potential to differentiate species in a complex forest setting. The first-step was to establish confidence in the high spatial and high radiometric resolution imagery from WorldView-3 in delineating tree types within a complex forest setting. In achieving this goal, ASD field spectrometer data were collected of specific tree species to establish solid ground control within the study site. The spectrometer data were collected from the top of each specific tree canopy utilizing established towers located at La Selva Biological Station so as to match the near-nadir view of the WorldView-3 imagery. The ASD data was processed utilizing the spectral response functions for each of the WorldView-3 bands to convert the ASD data into a band specific reflectivity. This allowed direct comparison of the ASD spectrometer reflectance data to the WorldView-3 multispectral imagery. The WorldView-3 imagery was processed to surface reflectance using two standard atmospheric correction procedures and the proprietary DigitalGlobe Atmospheric Compensation (AComp) product. The most accurate correction process was identified through comparison to the spectrometer data collected. A series of statistical measures were then utilized to access the accuracy of the processed imagery and which imagery bands are best suited for tree type identification. From this analysis, a segmentation/classification process was performed to identify individual tree type locations within the study area. It is envisioned the results of this study will improve traditional forest classification

  8. High-resolution multispectral satellite imagery for extracting bathymetric information of Antarctic shallow lakes

    Science.gov (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-05-01

    High-resolution pansharpened images from WorldView-2 were used for bathymetric mapping around Larsemann Hills and Schirmacher oasis, east Antarctica. We digitized the lake features in which all the lakes from both the study areas were manually extracted. In order to extract the bathymetry values from multispectral imagery we used two different models: (a) Stumpf model and (b) Lyzenga model. Multiband image combinations were used to improve the results of bathymetric information extraction. The derived depths were validated against the in-situ measurements and root mean square error (RMSE) was computed. We also quantified the error between in-situ and satellite-estimated lake depth values. Our results indicated a high correlation (R = 0.60 0.80) between estimated depth and in-situ depth measurements, with RMSE ranging from 0.10 to 1.30 m. This study suggests that the coastal blue band in the WV-2 imagery could retrieve accurate bathymetry information compared to other bands. To test the effect of size and dimension of lake on bathymetry retrieval, we distributed all the lakes on the basis of size and depth (reference data), as some of the lakes were open, some were semi frozen and others were completely frozen. Several tests were performed on open lakes on the basis of size and depth. Based on depth, very shallow lakes provided better correlation (≈ 0.89) compared to shallow (≈ 0.67) and deep lakes (≈ 0.48). Based on size, large lakes yielded better correlation in comparison to medium and small lakes.

  9. Comparison of different "along the track" high resolution satellite stereo-pair for DSM extraction

    Science.gov (United States)

    Nikolakopoulos, Konstantinos G.

    2013-10-01

    The possibility to create DEM from stereo pairs is based on the Pythagoras theorem and on the principles of photogrammetry that are applied to aerial photographs stereo pairs for the last seventy years. The application of these principles to digital satellite stereo data was inherent in the first satellite missions. During the last decades the satellite stereo-pairs were acquired across the track in different days (SPOT, ERS etc.). More recently the same-date along the track stereo-data acquisition seems to prevail (Terra ASTER, SPOT5 HRS, Cartosat, ALOS Prism) as it reduces the radiometric image variations (refractive effects, sun illumination, temporal changes) and thus increases the correlation success rate in any image matching.Two of the newest satellite sensors with stereo collection capability is Cartosat and ALOS Prism. Both of them acquire stereopairs along the track with a 2,5m spatial resolution covering areas of 30X30km. In this study we compare two different satellite stereo-pair collected along the track for DSM creation. The first one is created from a Cartosat stereopair and the second one from an ALOS PRISM triplet. The area of study is situated in Chalkidiki Peninsula, Greece. Both DEMs were created using the same ground control points collected with a Differential GPS. After a first control for random or systematic errors a statistical analysis was done. Points of certified elevation have been used to estimate the accuracy of these two DSMs. The elevation difference between the different DEMs was calculated. 2D RMSE, correlation and the percentile value were also computed and the results are presented.

  10. Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

    Directory of Open Access Journals (Sweden)

    Hao Guo

    2015-06-01

    Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.

  11. Determination of global Earth outgoing radiation at high temporal resolution using a theoretical constellation of satellites

    Science.gov (United States)

    Gristey, Jake J.; Chiu, J. Christine; Gurney, Robert J.; Han, Shin-Chan; Morcrette, Cyril J.

    2017-01-01

    New, viable, and sustainable observation strategies from a constellation of satellites have attracted great attention across many scientific communities. Yet the potential for monitoring global Earth outgoing radiation using such a strategy has not been explored. To evaluate the potential of such a constellation concept and to investigate the configuration requirement for measuring radiation at a time resolution sufficient to resolve the diurnal cycle for weather and climate studies, we have developed a new recovery method and conducted a series of simulation experiments. Using idealized wide field-of-view broadband radiometers as an example, we find that a baseline constellation of 36 satellites can monitor global Earth outgoing radiation reliably to a spatial resolution of 1000 km at an hourly time scale. The error in recovered daily global mean irradiance is 0.16 W m-2 and -0.13 W m-2, and the estimated uncertainty in recovered hourly global mean irradiance from this day is 0.45 W m-2 and 0.15 W m-2, in the shortwave and longwave spectral regions, respectively. Sensitivity tests show that addressing instrument-related issues that lead to systematic measurement error remains of central importance to achieving similar accuracies in reality. The presented error statistics therefore likely represent the lower bounds of what could currently be achieved with the constellation approach, but this study demonstrates the promise of an unprecedented sampling capability for better observing the Earth's radiation budget.

  12. A calibrated, high-resolution goes satellite solar insolation product for a climatology of Florida evapotranspiration

    Science.gov (United States)

    Paech, S.J.; Mecikalski, J.R.; Sumner, D.M.; Pathak, C.S.; Wu, Q.; Islam, S.; Sangoyomi, T.

    2009-01-01

    Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m-2/day (13%). Calibration reduced errors to 1.7 MJ m -2/day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.

  13. Visualization tools for extremely high resolution DEM from the LRO and other orbiter satellites

    Science.gov (United States)

    Montgomery, J.; McDonald, John

    2012-10-01

    Recent space missions have included laser altimetry instrumentation that provides precise high-resolution global topographic data products. These products are critical in analyzing geomorphological surface processes of planets and moons. Although highly valued, the high-resolution data is often overlooked by researchers due to the high level of IT sophistication necessary to use the high-resolution data products, which can be as large as several hundred gigabytes. Researchers have developed software tools to assist in viewing and manipulating data products derived from altimetry data, however current software tools require substantial off-line processing, provide rudimentary visualization or are not suited for viewing the new high-resolution data. We have adapted mVTK, a novel software visualization tool, to work with NASA's recently acquired Lunar Reconnaissance Orbiter data. mVTK is a software visualization package that dynamically creates cylindrical cartographic map projections from gridded high-resolution altimetry data in real-time. The projections are interactive 2D shade relief, false color maps that allow the user to make simple slope and distance measurements on the actual underlying high-resolution data. We have tested mVTK on several laser altimetry data sets including binned gridded record data from NASA's Mars Global Surveyor and Lunar Reconnaissance Orbiter space missions.

  14. Global mesospheric tidal winds observed by the high resolution Doppler imager on board the upper atmosphere research satellite

    Energy Technology Data Exchange (ETDEWEB)

    Morton, Y.T.; Lieberman, R.S.; Hays, P.B.; Ortland, D.A.; Marshall, A.R.; Wu, D.; Skinner, W.R.; Burrage, M.D.; Gell, D.A.; Yee, J.H.

    1993-06-18

    This paper presents results of mesospheric and lower thermospheric wind tides. The observations come from the high resolution doppler imager (HRDI) on board the upper atmosphere research satellite. From these observations, the authors report the observation of tidal effects on top of the meridonal winds observed in this region. Previous measurements have been mainly limited to radar measurements from fixed ground stations, which do not give consistent results, and do not provide a global picture of the wave structure.

  15. Estimates of changes of structural parameters of forest ecosystems in decoding high resolution satellite images

    Directory of Open Access Journals (Sweden)

    Yuri F. Rozhkov

    2016-05-01

    Full Text Available Aim of this study was to assess the possibility of using of the parameter of symmetry of pixel distribution in the forest condition monitoring. Multispectral satellite imagery and their fragments of high and medium resolution (Landsat TM/ЕТМ+, Aster, Spot, IRS, which have been made in 1995–2011, were processed in two stages. At the first stage, uncontrolled classification has been carried out using the method ISODATA (Iterative Self-Organizing Data Analysis Technigue. At the second stage, parameter of symmetry of pixel distribution was calculated. The results of classification were divided into two halves. Classes with lower optical density of the reflected light were concentrated in the upper half while classes with higher optical density of the reflected light were concentrated in the bottom half. The prospects for using the parameter symmetry of pixel distribution aim to assess the degree of forest disturbance after the fire impact was demonstrated. Disturbed forest areas a have larger sum of pixels in the bottom half of the classification results compared with the upper half. In contrast, undisturbed forest areas have a larger or equal sum of pixels in the upper half of the classification results compared with the bottom half. The prospects for using the parameter symmetry of pixel distribution in monitoring of seasonal changes of forest status were demonstrated. Comparison of two forest fragments with dominance of larch and Siberian pine showed that during the autumn months (September, October after needle fall and leaf fall, there is a sharp decrease of the parameter "symmetry of pixel distribution" within the fragment with dominance of larch due to the increase of the proportion of pixels with high optical density. Seasonal changes in the parameter of symmetry of pixels distribution were less pronounced for the forest fragment with dominance of Siberian pine. We considered the prospect to use the parameter of symmetry of pixel

  16. Inferring urban household socio-economic conditions in Mafikeng, South Africa, using high spatial resolution satellite imagery

    Directory of Open Access Journals (Sweden)

    Christopher Munyati

    2014-01-01

    Full Text Available Updated household socio-economic information is necessary for planning the delivery of municipal services, particularly for cities in third world countries. The repetitive coverage of satellite imagery provides a possibility for sourcing and frequently updating information on household socio-economic conditions in urban landscapes. This paper examines the potential use of satellite imagery in inferring urban household socio-economic variables, using two high-resolution images of 2001 and 2010. Manual image interpretation was employed in deducing selected socio-economic variables that are utilised in census enumerations in South Africa, at four suburbs in Mafikeng. Of the three socio-economic variables that were examined (type of main dwelling, toilet facilities, and energy source for cooking, type of dwelling could more readily be deduced from the high-resolution imagery. Identified change in number of formal and informal houses indicated potential of satellite imagery in monitoring third world setting urban sprawl and the associated growth in informal settlements due to migration, among other factors. Satellite imagery appears useful as a supplementary source of socio-economic data to municipal authorities, for periods between regular censuses.

  17. High resolution surface solar radiation patterns over Eastern Mediterranean: Satellite, ground-based, reanalysis data and radiative transfer simulations

    Science.gov (United States)

    Alexandri, G.; Georgoulias, A.; Meleti, C.; Balis, D.

    2013-12-01

    Surface solar radiation (SSR) and its long and short term variations play a critical role in the modification of climate and by extent of the social and financial life of humans. Thus, SSR measurements are of primary importance. SSR is measured for decades from ground-based stations for specific spots around the planet. During the last decades, satellite observations allowed for the assessment of the spatial variability of SSR at a global as well as regional scale. In this study, a detailed spatiotemporal view of the SSR over Eastern Mediterranean is presented at a high spatial resolution. Eastern Mediterranean is affected by various aerosol types (continental, sea, dust and biomass burning particles) and encloses countries with significant socioeconomical changes during the last decades. For the aims of this study, SSR data from satellites (Climate Monitoring Satellite Application Facility - CM SAF) and our ground station in Thessaloniki, a coastal city of ~1 million inhabitants in northern Greece, situated in the heart of Eastern Mediterranean (Eppley Precision pyranometer and Kipp & Zonen CM-11 pyranometer) are used in conjunction with radiative transfer simulations (Santa Barbara DISORT Atmospheric Radiative Transfer - SBDART). The CM SAF dataset used here includes monthly mean SSR observations at a high spatial resolution of 0.03x0.03 degrees for the period 1983-2005. Our ground-based SSR observations span from 1983 until today. SBDART radiative transfer simulations were implemented for a number of spots in the area of study in order to calculate the SSR. High resolution (level-2) aerosol and cloud data from MODIS TERRA and AQUA satellite sensors were used as input, as well as ground-based data from the AERONET. Data from other satellites (Earth Probe TOMS, OMI, etc) and reanalysis projects (ECMWF) were used where needed. The satellite observations, the ground-based measurements and the model estimates are validated against each other. The good agreement

  18. Smoke Dispersion Modeling Over Complex Terrain Using High-Resolution Meteorological Data and Satellite Observations: The FireHub Platform

    Science.gov (United States)

    Solomos, S.; Amiridis, V.; Zanis, P.; Gerasopoulos, E.; Sofiou, F. I.; Herekakis, T.; Brioude, J.; Stohl, A.; Kahn, R. A.; Kontoes, C.

    2015-01-01

    A total number of 20,212 fire hot spots were recorded by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument over Greece during the period 2002e2013. The Fire Radiative Power (FRP) of these events ranged from 10 up to 6000 MW at 1 km resolution, and many of these fire episodes resulted in long-range transport of smoke over distances up to several hundred kilometers. Three different smoke episodes over Greece are analyzed here using real time hot-spot observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite instrument as well as from MODIS hot-spots. Simulations of smoke dispersion are performed with the FLEXPART-WRF model and particulate matter emissions are calculated directly from the observed FRP. The modeled smoke plumes are compared with smoke stereo-heights from the Multiangle Imaging Spectroradiometer (MISR) instrument and the sensitivities to atmospheric and modeling parameters are examined. Driving the simulations with high resolution meteorology (4 4 km) and using geostationary satellite data to identify the hot spots allows the description of local scale features that govern smoke dispersion. The long-range transport of smoke is found to be favored over the complex coastline environment of Greece due to the abrupt changes between land and marine planetary boundary layers (PBL) and the decoupling of smoke layers from the surface.

  19. Smoke dispersion modeling over complex terrain using high resolution meteorological data and satellite observations - The FireHub platform

    Science.gov (United States)

    Solomos, S.; Amiridis, V.; Zanis, P.; Gerasopoulos, E.; Sofiou, F. I.; Herekakis, T.; Brioude, J.; Stohl, A.; Kahn, R. A.; Kontoes, C.

    2015-10-01

    A total number of 20,212 fire hot spots were recorded by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument over Greece during the period 2002-2013. The Fire Radiative Power (FRP) of these events ranged from 10 up to 6000 MW at 1 km resolution, and many of these fire episodes resulted in long-range transport of smoke over distances up to several hundred kilometers. Three different smoke episodes over Greece are analyzed here using real time hot-spot observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite instrument as well as from MODIS hot-spots. Simulations of smoke dispersion are performed with the FLEXPART-WRF model and particulate matter emissions are calculated directly from the observed FRP. The modeled smoke plumes are compared with smoke stereo-heights from the Multiangle Imaging Spectroradiometer (MISR) instrument and the sensitivities to atmospheric and modeling parameters are examined. Driving the simulations with high resolution meteorology (4 × 4 km) and using geostationary satellite data to identify the hot spots allows the description of local scale features that govern smoke dispersion. The long-range transport of smoke is found to be favored over the complex coastline environment of Greece due to the abrupt changes between land and marine planetary boundary layers (PBL) and the decoupling of smoke layers from the surface.

  20. Smoke Dispersion Modeling Over Complex Terrain Using High-Resolution Meteorological Data and Satellite Observations: The FireHub Platform

    Science.gov (United States)

    Solomos, S.; Amiridis, V.; Zanis, P.; Gerasopoulos, E.; Sofiou, F. I.; Herekakis, T.; Brioude, J.; Stohl, A.; Kahn, R. A.; Kontoes, C.

    2015-01-01

    A total number of 20,212 fire hot spots were recorded by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument over Greece during the period 2002e2013. The Fire Radiative Power (FRP) of these events ranged from 10 up to 6000 MW at 1 km resolution, and many of these fire episodes resulted in long-range transport of smoke over distances up to several hundred kilometers. Three different smoke episodes over Greece are analyzed here using real time hot-spot observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite instrument as well as from MODIS hot-spots. Simulations of smoke dispersion are performed with the FLEXPART-WRF model and particulate matter emissions are calculated directly from the observed FRP. The modeled smoke plumes are compared with smoke stereo-heights from the Multiangle Imaging Spectroradiometer (MISR) instrument and the sensitivities to atmospheric and modeling parameters are examined. Driving the simulations with high resolution meteorology (4 4 km) and using geostationary satellite data to identify the hot spots allows the description of local scale features that govern smoke dispersion. The long-range transport of smoke is found to be favored over the complex coastline environment of Greece due to the abrupt changes between land and marine planetary boundary layers (PBL) and the decoupling of smoke layers from the surface.

  1. An Alternative Approach for Registration of High-Resolution Satellite Optical Imagery and ICESat Laser Altimetry Data

    Directory of Open Access Journals (Sweden)

    Shijie Liu

    2016-11-01

    Full Text Available Satellite optical images and altimetry data are two major data sources used in Antarctic research. The integration use of these two datasets is expected to provide more accurate and higher quality products, during which data registration is the first issue that needs to be solved. This paper presents an alternative approach for the registration of high-resolution satellite optical images and ICESat (Ice, Cloud, and land Elevation Satellite laser altimetry data. Due to the sparse distribution characteristic of the ICESat laser point data, it is difficult and even impossible to find same-type conjugate features between ICESat data and satellite optical images. The method is implemented in a direct way to correct the point-to-line inconsistency in image space through 2D transformation between the projected terrain feature points and the corresponding 2D image lines, which is simpler than discrepancy correction in object space that requires stereo images for 3D model construction, and easier than the indirect way of image orientation correction via photogrammetric bundle adjustment. The correction parameters are further incorporated into imaging model through RPCs (Rational Polynomial Coefficients generation/regeneration for the convenience of photogrammetric applications. The experimental results by using the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer images and ZY-3 (Ziyuan-3 satellite images for registration with ICESat data showed that sub-pixel level registration accuracies were achieved after registration, which have validated the feasibility and effectiveness of the presented approach.

  2. Monitoring the Total Suspended Solids (TSS) using High Spatial Resolution Satellite of THEOS

    Science.gov (United States)

    Syahreza, S.; Lim, H. S.; Mat Jafri, M. Z.; Abdullah, K.

    2010-12-01

    Environmental monitoring through the method of traditional ship sampling is time consuming and requires a high survey cost. Our study uses an empirical model, based on actual water quality of total suspended solids (TSS) measurements from the Penang Island, Malaysia to predict TSS based on optical properties of Thailand Earth Observation Satellite (THEOS) digital imagery. The objective of this study is to examine the performance of the proposed algorithm for retrieving TSS concentration by using THEOS satellite image over Penang Island, Malaysia. Water samples were collected simultaneously with the airborne image acquisition and later analyzed in the laboratory. Water sample locations were determined by using a Global Positioning System (GPS). The collected water samples were combined for algorithm calibration. The algorithm used was based on the reflectance model, which is a function of the inherent optical properties of water, and these in turn can be related to the concentration of the pollutants. Digital numbers for each band corresponding to the sea-truth data collected simultaneously with the digital image acquisition were determined for later use in the algorithm calibration analysis. The accuracy of each algorithm was determined based on the values of the correlation coefficient (R) and Root-Mean-Square deviation (RMS). This algorithm was then used to map the TSS concentration over Penang, Malaysia. The TSS map was color-coded and geometrically corrected for visual interpretation. This study indicates that TSS mapping can be carried out using remote sensing technique of the satellite digital photography system over Penang, Malaysia.

  3. Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

    Science.gov (United States)

    Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

    2014-11-01

    , including skyscrapers and bridges, which were confounded and extracted as buildings. This can be attributed to low point density at building edges and on flat roofs or occlusions due to which LiDAR cannot give as much precise planimetric accuracy as photogrammetric techniques (in segmentation) and lack of optimum use of textural information as well as contextual information (especially at walls which are away from roof) in automatic extraction algorithm. In addition, there were no separate classes for bridges or the features lying inside the water and multiple water height levels were also not considered. Based on these inferences, we conclude that the LiDAR-based 3D feature extraction supplemented by high resolution satellite data is a potential application which can be used for understanding and characterization of urban setup.

  4. Mapping sub-antarctic cushion plants using random forests to combine very high resolution satellite imagery and terrain modelling.

    Directory of Open Access Journals (Sweden)

    Phillippa K Bricher

    Full Text Available Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6-96.3%, κ = 0.849-0.924. Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments.

  5. Modelling high arctic percent vegetation cover using field digital images and high resolution satellite data

    Science.gov (United States)

    Liu, Nanfeng; Treitz, Paul

    2016-10-01

    In this study, digital images collected at a study site in the Canadian High Arctic were processed and classified to examine the spatial-temporal patterns of percent vegetation cover (PVC). To obtain the PVC of different plant functional groups (i.e., forbs, graminoids/sedges and mosses), field near infrared-green-blue (NGB) digital images were classified using an object-based image analysis (OBIA) approach. The PVC analyses comparing different vegetation types confirmed: (i) the polar semi-desert exhibited the lowest PVC with a large proportion of bare soil/rock cover; (ii) the mesic tundra cover consisted of approximately 60% mosses; and (iii) the wet sedge consisted almost exclusively of graminoids and sedges. As expected, the PVC and green normalized difference vegetation index (GNDVI; (RNIR - RGreen)/(RNIR + RGreen)), derived from field NGB digital images, increased during the summer growing season for each vegetation type: i.e., ∼5% (0.01) for polar semi-desert; ∼10% (0.04) for mesic tundra; and ∼12% (0.03) for wet sedge respectively. PVC derived from field images was found to be strongly correlated with WorldView-2 derived normalized difference spectral indices (NDSI; (Rx - Ry)/(Rx + Ry)), where Rx is the reflectance of the red edge (724.1 nm) or near infrared (832.9 nm and 949.3 nm) bands; Ry is the reflectance of the yellow (607.7 nm) or red (658.8 nm) bands with R2's ranging from 0.74 to 0.81. NDSIs that incorporated the yellow band (607.7 nm) performed slightly better than the NDSIs without, indicating that this band may be more useful for investigating Arctic vegetation that often includes large proportions of senescent vegetation throughout the growing season.

  6. Bayesian Information Criterion Based Feature Filtering for the Fusion of Multiple Features in High-Spatial-Resolution Satellite Scene Classification

    Directory of Open Access Journals (Sweden)

    Da Lin

    2015-01-01

    Full Text Available This paper presents a novel classification method for high-spatial-resolution satellite scene classification introducing Bayesian information criterion (BIC-based feature filtering process to further eliminate opaque and redundant information between multiple features. Firstly, two diverse and complementary feature descriptors are extracted to characterize the satellite scene. Then, sparse canonical correlation analysis (SCCA with penalty function is employed to fuse the extracted feature descriptors and remove the ambiguities and redundancies between them simultaneously. After that, a two-phase Bayesian information criterion (BIC-based feature filtering process is designed to further filter out redundant information. In the first phase, we gradually impose a constraint via an iterative process to set a constraint on the loadings for averting sparse correlation descending below to a lower confidence limit of the approximated canonical correlation. In the second phase, Bayesian information criterion (BIC is utilized to conduct the feature filtering which sets the smallest loading in absolute value to zero in each iteration for all features. Lastly, a support vector machine with pyramid match kernel is applied to obtain the final result. Experimental results on high-spatial-resolution satellite scenes demonstrate that the suggested approach achieves satisfactory performance in classification accuracy.

  7. Detailed Maps Depicting the Shallow-Water Benthic Habitats of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Detailed, shallow-water coral reef ecosystem maps were generated by rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations...

  8. Detailed Maps Depicting the Shallow-Water Benthic Habitats of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Detailed, shallow-water coral reef ecosystem maps were generated by rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations...

  9. Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

    Science.gov (United States)

    De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.

    2009-01-01

    An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

  10. Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information

    Directory of Open Access Journals (Sweden)

    Curt H. Davis

    2005-08-01

    Full Text Available High-resolution satellite imagery provides an important new data source for building extraction. We demonstrate an integrated strategy for identifying buildings in 1-meter resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. First, a series of geodesic opening and closing operations are used to build a differential morphological profile (DMP that provides image structural information. Building hypotheses are generated and verified through shape analysis applied to the DMP. Second, shadows are extracted using the DMP to provide reliable contextual information to hypothesize position and size of adjacent buildings. Seed building rectangles are verified and grown on a finely segmented image. Next, bright buildings are extracted using spectral information. The extraction results from the different information sources are combined after independent extraction. Performance evaluation of the building extraction on an urban test site using IKONOS satellite imagery of the City of Columbia, Missouri, is reported. With the combination of structural, contextual, and spectral information, 72.7% of the building areas are extracted with a quality percentage 58.8%.

  11. Detecting tents to estimate the displaced populations for post-disaster relief using high resolution satellite imagery

    Science.gov (United States)

    Wang, Shifeng; So, Emily; Smith, Pete

    2015-04-01

    Estimating the number of refugees and internally displaced persons is important for planning and managing an efficient relief operation following disasters and conflicts. Accurate estimates of refugee numbers can be inferred from the number of tents. Extracting tents from high-resolution satellite imagery has recently been suggested. However, it is still a significant challenge to extract tents automatically and reliably from remote sensing imagery. This paper describes a novel automated method, which is based on mathematical morphology, to generate a camp map to estimate the refugee numbers by counting tents on the camp map. The method is especially useful in detecting objects with a clear shape, size, and significant spectral contrast with their surroundings. Results for two study sites with different satellite sensors and different spatial resolutions demonstrate that the method achieves good performance in detecting tents. The overall accuracy can be up to 81% in this study. Further improvements should be possible if over-identified isolated single pixel objects can be filtered. The performance of the method is impacted by spectral characteristics of satellite sensors and image scenes, such as the extent of area of interest and the spatial arrangement of tents. It is expected that the image scene would have a much higher influence on the performance of the method than the sensor characteristics.

  12. Urban landscape classification using Chinese advanced high-resolution satellite imagery and an object-oriented multi-variable model

    Institute of Scientific and Technical Information of China (English)

    Li-gang MA; Jin-song DENG; Huai YANG; Yang HONG; Ke WANG

    2015-01-01

    The Chinese ZY-1 02C satellite is one of the most advanced high-resolution earth observation systems designed for terrestrial resource monitoring. Its capability for comprehensive landscape classification, especially in urban areas, has been under constant study. In view of the limited spectral resolution of the ZY-1 02C satellite (three bands), and the complexity and hetero-geneity across urban environments, we attempt to test its performance of urban landscape classification by combining a multi-variable model with an object-oriented approach. The multiple variables including spectral reflection, texture, spatial autocorre-lation, impervious surface fraction, vegetation, and geometry indexes were first calculated and selected using forward stepwise linear discriminant analysis and applied in the following object-oriented classification process. Comprehensive accuracy as-sessment which adopts traditional error matrices with stratified random samples and polygon area consistency (PAC) indexes was then conducted to examine the real area agreement between a classified polygon and its references. Results indicated an overall classification accuracy of 92.63%and a kappa statistic of 0.9124. Furthermore, the proposed PAC index showed that more than 82%of all polygons were correctly classified. Misclassification occurred mostly between residential area and barren/farmland. The presented method and the Chinese ZY-1 02C satellite imagery are robust and effective for urban landscape classification.

  13. Scaling properties of Arctic sea ice deformation in high-resolution viscous-plastic sea ice models and satellite observations

    Science.gov (United States)

    Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

    2017-04-01

    Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

  14. Use of shadow for enhancing mapping of perennial desert plants from high-spatial resolution multispectral and panchromatic satellite imagery

    Science.gov (United States)

    Alsharrah, Saad A.; Bouabid, Rachid; Bruce, David A.; Somenahalli, Sekhar; Corcoran, Paul A.

    2016-07-01

    Satellite remote-sensing techniques face challenges in extracting vegetation-cover information in desert environments. The limitations in detection are attributed to three major factors: (1) soil background effect, (2) distribution and structure of perennial desert vegetation, and (3) tradeoff between spatial and spectral resolutions of the satellite sensor. In this study, a modified vegetation shadow model (VSM-2) is proposed, which utilizes vegetation shadow as a contextual classifier to counter the limiting factors. Pleiades high spatial resolution, multispectral (2 m), and panchromatic (0.5 m) images were utilized to map small and scattered perennial arid shrubs and trees. We investigated the VSM-2 method in addition to conventional techniques, such as vegetation indices and prebuilt object-based image analysis. The success of each approach was evaluated using a root sum square error metric, which incorporated field data as control and three error metrics related to commission, omission, and percent cover. Results of the VSM-2 revealed significant improvements in perennial vegetation cover and distribution accuracy compared with the other techniques and its predecessor VSM-1. Findings demonstrated that the VSM-2 approach, using high-spatial resolution imagery, can be employed to provide a more accurate representation of perennial arid vegetation and, consequently, should be considered in assessments of desertification.

  15. SACRA – global data sets of satellite-derived crop calendars for agricultural simulations: an estimation of a high-resolution crop calendar using satellite-sensed NDVI

    Directory of Open Access Journals (Sweden)

    S. Kotsuki

    2015-01-01

    Full Text Available To date, many studies have performed numerical estimations of food production and agricultural water demand to understand the present and future supply–demand relationship. A crop calendar (CC is an essential input datum to estimate food production and agricultural water demand accurately with the numerical estimations. CC defines the date or month when farmers plant and harvest in cropland. This study aims to develop a new global data set of a satellite-derived crop calendar for agricultural simulations (SACRA and reveal advantages and disadvantages of the satellite-derived CC compared to other global products. We estimate global CC at a spatial resolution of 5 min (≈10 km using the satellite-sensed NDVI data, which corresponds well to vegetation growth and death on the land surface. We first demonstrate that SACRA shows similar spatial pattern in planting date compared to a census-based product. Moreover, SACRA reflects a variety of CC in the same administrative unit, since it uses high-resolution satellite data. However, a disadvantage is that the mixture of several crops in a grid is not considered in SACRA. We also address that the cultivation period of SACRA clearly corresponds to the time series of NDVI. Therefore, accuracy of SACRA depends on the accuracy of NDVI used for the CC estimation. Although SACRA shows different CC from a census-based product in some regions, multiple usages of the two products are useful to take into consideration the uncertainty of the CC. An advantage of SACRA compared to the census-based products is that SACRA provides not only planting/harvesting dates but also a peak date from the time series of NDVI data.

  16. Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery

    Science.gov (United States)

    Grimm, Amanda G.; Brooks, Colin N.; Binder, Thomas R.; Riley, Stephen C.; Farha, Steve A.; Shuchman, Robert A.; Krueger, Charles C.

    2016-01-01

    The availability and quality of spawning habitat may limit lake trout recovery in the Great Lakes, but little is known about the location and characteristics of current spawning habitats. Current methods used to identify lake trout spawning locations are time- and labor-intensive and spatially limited. Due to the observation that some lake trout spawning sites are relatively clean of overlaying algae compared to areas not used for spawning, we suspected that spawning sites could be identified using satellite imagery. Satellite imagery collected just before and after the spawning season in 2013 was used to assess whether lake trout spawning habitat could be identified based on its spectral characteristics. Results indicated that Pléiades high-resolution multispectral satellite imagery can be successfully used to estimate algal coverage of substrates and temporal changes in algal coverage, and that models developed from processed imagery can be used to identify potential lake trout spawning sites based on comparison of sites where lake trout eggs were and were not observed after spawning. Satellite imagery is a potential new tool for identifying lake trout spawning habitat at large scales in shallow nearshore areas of the Great Lakes.

  17. High spatial resolution mapping of malaria transmission risk in the Gambia, west Africa, using LANDSAT TM satellite imagery.

    Science.gov (United States)

    Bøgh, Claus; Lindsay, Steven W; Clarke, Siân E; Dean, Andy; Jawara, Musa; Pinder, Margaret; Thomas, Christopher J

    2007-05-01

    Understanding local variability in malaria transmission risk is critically important when designing intervention or vaccine trials. Using a combination of field data, satellite image analysis, and GIS modeling, we developed a high-resolution map of malaria entomological inoculation rates (EIR) in The Gambia, West Africa. The analyses are based on the variation in exposure to malaria parasites experienced in 48 villages in 1996 and 21 villages in 1997. The entomological inoculation rate (EIR) varied from 0 to 166 infective bites per person per rainy season. Detailed field surveys identified the major Anopheles gambiae s.l. breeding habitats. These habitats were mapped by classification of a LANDSAT TM satellite image with an overall accuracy of 85%. Village EIRs decreased as a power function based on the breeding areas size and proximity. We use this relationship and the breeding habitats to map the variation in EIR over the entire 2500-km(2) study area.

  18. Crop Investigation Using High-Resolution Worldview-1 and Quickbird-2 Satellite Images on a Test Site in Bulgaria

    Science.gov (United States)

    Vassilev, Vassil

    2013-12-01

    The paper aims to investigate the capabilities of using high-resolution satellite images: panchromatic WorldView-1 satellite image acquired on 30/11/2011 and multispectral QuickBird-2 satellite image acquired on 31/05/2009 for crop analysis, which includes crop identification, crop condition assessment and crop area estimates applications in Bulgaria using the power and flexibility of ERDAS IMAGINE tools. The crop identification was accomplished using unsupervised and supervised classification processing techniques using as reference ground data. After the supervised classification, fuzzy convolution filter was applied to reduce the mixed pixels using ERDAS Imagine software. Accuracy totals, error matrix and kappa statistics were calculated using accuracy assessment tool in ERDAS Imagine to assess the quality of the classification process. Crop condition assessment was accomplished using the derived Normalized Difference Vegetation Index (NDVI) image from the QuickBird-2 image, which was reclassified and was given meaningful estimations on the crop condition. Crop area was estimated using pixel counting approach. Pixel counting methods are known for introducing bias to the crop area estimates but using the high Overall Accuracy of 90.86% and overall Kappa Statistics of 0.8538 for the classified QuickBird-2 image and Overall Accuracy of 86.71% and overall Kappa Statistics of 0.7721% for the classified WorldView-1 allows that option to be utilized according to (Gallego, 2004). As a conclusion it can be stated that using the benefits that high-resolution satellite images gives in combination with the power and flexibility of ERDAS Imagine tools, crop identification can be achieved more accurately by increasing the identification accuracy and also by having the necessary ground information for selecting appropriate training samples. Crop identification by applying an arable mask is better practice, because it is reducing the mixed pixels problem i.e. also known as

  19. Assessing Leaf Area Index from High Resolution Satellite Datasets for Maize in Trans Nzoia County, Kenya

    Science.gov (United States)

    Bartolomew Thiongo, Kuria; Menz, Gunter; Thonfeld, Frank

    2016-08-01

    The Normalized Differenced Vegetation Index (NDVI) and the two band Enhanced vegetation Index (EVI2) derived from RapidEye and Landsat 8 satellite images were evaluated against the empirically derived terrestrial Leaf Area Index (LAI) acquired during the maize growth season April to November, 2015 and covering the phenological growth stages prescribed in the BBCH code. The results indicate a high correlation of the vegetation indices plotted over the entire maize season with R2 values of 88% and 83% for NDVI and EVI2 respectively. The maximum values were found to occur during the maize vegetative phase in the months of July and August. The correlation between the vegetation indices and the LAI had R2 values of 50% and 49% for NDVI and EVI2 respectively. Alternative methods of estimating and calculating the LAI values may improve the achieved results.

  20. Estimating Agricultural Land Use Change in Karamoja, NE. Uganda Using Very High Resolution Satellite Data

    Science.gov (United States)

    Nakalembe, C. L.

    2013-12-01

    Land use information is useful for deriving biophysical variables for effective planning and management of natural resources. Land use information is also needed to understand negative environmental impacts of land use while maintaining economic and social benefits. Recent maps of land cover and land use have been generated for Africa at the continental scale from coarse resolution data (e.g. MODIS, Spot Vegetation, MERIS, and Landsat). In these map products, croplands and rangelands are generally poorly represented, particularly in semi-arid regions like Karamoja. Products derived from coarse resolution data also fail at mapping subsistence croplands and are limited in their use for extraction of land-cover specific temporal profiles for agricultural monitoring in the study area (Fritz, See, & Rembold, 2010). Given the subsistence nature of agriculture, most fields in Karamoja are very small that care not discernible from other land uses in coarse resolution data and data products such as FAO Africover2000. product derived from 30m Landsat data is one such product. There is a high level of disagreement and large errors of omission and omission due to the coarse resolution of the data used to derive the product. In addition population growth and policy changes in the region have resulted in a shift to agro-pastoralism and systematic expansion of cropland area since 2000. This research will produce an updated agricultural land use map for Karamoja. The land cover map will be used to estimate agricultural land use change in the region and as a filter to extract agricultural land use specific temporal profiles specific to agriculture to compare to crop statistics.

  1. Feature extraction and classification of clouds in high resolution panchromatic satellite imagery

    Science.gov (United States)

    Sharghi, Elan

    The development of sophisticated remote sensing sensors is rapidly increasing, and the vast amount of satellite imagery collected is too much to be analyzed manually by a human image analyst. It has become necessary for a tool to be developed to automate the job of an image analyst. This tool would need to intelligently detect and classify objects of interest through computer vision algorithms. Existing software called the Rapid Image Exploitation Resource (RAPIER®) was designed by engineers at Space and Naval Warfare Systems Center Pacific (SSC PAC) to perform exactly this function. This software automatically searches for anomalies in the ocean and reports the detections as a possible ship object. However, if the image contains a high percentage of cloud coverage, a high number of false positives are triggered by the clouds. The focus of this thesis is to explore various feature extraction and classification methods to accurately distinguish clouds from ship objects. An examination of a texture analysis method, line detection using the Hough transform, and edge detection using wavelets are explored as possible feature extraction methods. The features are then supplied to a K-Nearest Neighbors (KNN) or Support Vector Machine (SVM) classifier. Parameter options for these classifiers are explored and the optimal parameters are determined.

  2. Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

    Science.gov (United States)

    Alshehhi, Rasha; Marpu, Prashanth Reddy

    2017-04-01

    Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

  3. New optical sensor systems for high-resolution satellite, airborne and terrestrial imaging systems

    Science.gov (United States)

    Eckardt, Andreas; Börner, Anko; Lehmann, Frank

    2007-10-01

    The department of Optical Information Systems (OS) at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR) has more than 25 years experience with high-resolution imaging technology. The technology changes in the development of detectors, as well as the significant change of the manufacturing accuracy in combination with the engineering research define the next generation of spaceborne sensor systems focusing on Earth observation and remote sensing. The combination of large TDI lines, intelligent synchronization control, fast-readable sensors and new focal-plane concepts open the door to new remote-sensing instruments. This class of instruments is feasible for high-resolution sensor systems regarding geometry and radiometry and their data products like 3D virtual reality. Systemic approaches are essential for such designs of complex sensor systems for dedicated tasks. The system theory of the instrument inside a simulated environment is the beginning of the optimization process for the optical, mechanical and electrical designs. Single modules and the entire system have to be calibrated and verified. Suitable procedures must be defined on component, module and system level for the assembly test and verification process. This kind of development strategy allows the hardware-in-the-loop design. The paper gives an overview about the current activities at DLR in the field of innovative sensor systems for photogrammetric and remote sensing purposes.

  4. Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

    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.

  5. Object-based locust habitat mapping using high-resolution multispectral satellite data in the southern Aral Sea basin

    Science.gov (United States)

    Navratil, Peter; Wilps, Hans

    2013-01-01

    Three different object-based image classification techniques are applied to high-resolution satellite data for the mapping of the habitats of Asian migratory locust (Locusta migratoria migratoria) in the southern Aral Sea basin, Uzbekistan. A set of panchromatic and multispectral Système Pour l'Observation de la Terre-5 satellite images was spectrally enhanced by normalized difference vegetation index and tasseled cap transformation and segmented into image objects, which were then classified by three different classification approaches: a rule-based hierarchical fuzzy threshold (HFT) classification method was compared to a supervised nearest neighbor classifier and classification tree analysis by the quick, unbiased, efficient statistical trees algorithm. Special emphasis was laid on the discrimination of locust feeding and breeding habitats due to the significance of this discrimination for practical locust control. Field data on vegetation and land cover, collected at the time of satellite image acquisition, was used to evaluate classification accuracy. The results show that a robust HFT classifier outperformed the two automated procedures by 13% overall accuracy. The classification method allowed a reliable discrimination of locust feeding and breeding habitats, which is of significant importance for the application of the resulting data for an economically and environmentally sound control of locust pests because exact spatial knowledge on the habitat types allows a more effective surveying and use of pesticides.

  6. High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

    Science.gov (United States)

    Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment

  7. The role of high-resolution geomagnetic field models for investigating ionospheric currents at low Earth orbit satellites

    Science.gov (United States)

    Stolle, Claudia; Michaelis, Ingo; Rauberg, Jan

    2016-07-01

    Low Earth orbiting geomagnetic satellite missions, such as the Swarm satellite mission, are the only means to monitor and investigate ionospheric currents on a global scale and to make in situ measurements of F region currents. High-precision geomagnetic satellite missions are also able to detect ionospheric currents during quiet-time geomagnetic conditions that only have few nanotesla amplitudes in the magnetic field. An efficient method to isolate the ionospheric signals from satellite magnetic field measurements has been the use of residuals between the observations and predictions from empirical geomagnetic models for other geomagnetic sources, such as the core and lithospheric field or signals from the quiet-time magnetospheric currents. This study aims at highlighting the importance of high-resolution magnetic field models that are able to predict the lithospheric field and that consider the quiet-time magnetosphere for reliably isolating signatures from ionospheric currents during geomagnetically quiet times. The effects on the detection of ionospheric currents arising from neglecting the lithospheric and magnetospheric sources are discussed on the example of four Swarm orbits during very quiet times. The respective orbits show a broad range of typical scenarios, such as strong and weak ionospheric signal (during day- and nighttime, respectively) superimposed over strong and weak lithospheric signals. If predictions from the lithosphere or magnetosphere are not properly considered, the amplitude of the ionospheric currents, such as the midlatitude Sq currents or the equatorial electrojet (EEJ), is modulated by 10-15 % in the examples shown. An analysis from several orbits above the African sector, where the lithospheric field is significant, showed that the peak value of the signatures of the EEJ is in error by 5 % in average when lithospheric contributions are not considered, which is in the range of uncertainties of present empirical models of the EEJ.

  8. Using high resolution satellite multi-temporal interferometry for landslide hazard detection in tropical environments: the case of Haiti

    Science.gov (United States)

    Wasowski, Janusz; Nutricato, Raffaele; Nitti, Davide Oscar; Bovenga, Fabio; Chiaradia, Maria Teresa; Piard, Boby Emmanuel; Mondesir, Philemon

    2015-04-01

    Synthetic aperture radar (SAR) multi-temporal interferometry (MTI) is one of the most promising satellite-based remote sensing techniques for fostering new opportunities in landslide hazard detection and assessment. MTI is attractive because it can provide very precise quantitative information on slow slope displacements of the ground surface over huge areas with limited vegetation cover. Although MTI is a mature technique, we are only beginning to realize the benefits of the high-resolution imagery that is currently acquired by the new generation radar satellites (e.g., COSMO-SkyMed, TerraSAR-X). In this work we demonstrate the potential of high resolution X-band MTI for wide-area detection of slope instability hazards even in tropical environments that are typically very harsh (eg. coherence loss) for differential interferometry applications. This is done by presenting an example from the island of Haiti, a tropical region characterized by dense and rapidly growing vegetation, as well as by significant climatic variability (two rainy seasons) with intense precipitation events. Despite the unfavorable setting, MTI processing of nearly 100 COSMO-SkyMed (CSK) mages (2011-2013) resulted in the identification of numerous radar targets even in some rural (inhabited) areas thanks to the high resolution (3 m) of CSK radar imagery, the adoption of a patch wise processing SPINUA approach and the presence of many man-made structures dispersed in heavily vegetated terrain. In particular, the density of the targets resulted suitable for the detection of some deep-seated and shallower landslides, as well as localized, very slow slope deformations. The interpretation and widespread exploitation of high resolution MTI data was facilitated by Google EarthTM tools with the associated high resolution optical imagery. Furthermore, our reconnaissance in situ checks confirmed that MTI results provided useful information on landslides and marginally stable slopes that can represent a

  9. Estimating babassu palm density using automatic palm tree detection with very high spatial resolution satellite images.

    Science.gov (United States)

    Dos Santos, Alessio Moreira; Mitja, Danielle; Delaître, Eric; Demagistri, Laurent; de Souza Miranda, Izildinha; Libourel, Thérèse; Petit, Michel

    2017-05-15

    High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale.

  10. Application of High Resolution Satellite Imagery to Characterize Individual-Based Environmental Heterogeneity in a Wild Blue Tit Population

    Directory of Open Access Journals (Sweden)

    Marta Szulkin

    2015-10-01

    Full Text Available Environmental heterogeneity in space and time plays a key role in influencing trait variability in animals, and can be particularly relevant to animal phenology. Until recently, the use of remotely sensed imagery in understanding animal variation was limited to analyses at the population level, largely because of a lack of high-resolution data that would allow inference at the individual level. We evaluated the potential of SPOT 4 (Take 5 satellite imagery data (with observations every fifth day at 20 m resolution and equivalent to acquisition parameters of Sentinel-2 in animal ecology research. We focused on blue tit Cyanistes caeruleus reproduction in a study site containing 227 nestboxes scattered in a Mediterranean forest dominated by deciduous downy oaks Quercus pubescens with a secondary cover of evergreen holm oaks Quercus ilex. We observed high congruence between ground data collected in a 50 m radius around each nestbox and NDVI values averaged across a 5 by 5 pixel grid centered around each nestbox of the study site. The number of deciduous and evergreen oaks around nestboxes explained up to 66% of variance in nestbox-centered, SPOT-derived NDVI values. We also found highly equivalent patterns of spatial autocorrelation for both ground- and satellite-derived indexes of environmental heterogeneity. For deciduous and evergreen oaks, the derived NDVI signal was highly distinctive in winter and early spring. June NDVI values for deciduous and evergreen oaks were higher by 58% and 8% relative to February values, respectively. The number of evergreen oaks was positively associated with later timing of breeding in blue tits. SPOT-derived, Sentinel-2 like imagery thus provided highly reliable, ground-validated information on habitat heterogeneity of direct relevance to a long-term field study of a free-living passerine bird. Given that the logistical demands of gathering ground data often limit our understanding of variation in animal

  11. 3D high resolution tracking of ice flow using mutli-temporal stereo satellite imagery, Franz Josef Glacier, New Zealand

    Science.gov (United States)

    Leprince, S.; Lin, J.; Ayoub, F.; Herman, F.; Avouac, J.

    2013-12-01

    We present the latest capabilities added to the Co-Registration of Optically Sensed Images and Correlation (COSI-Corr) software, which aim at analyzing time-series of stereoscopic imagery to document 3D variations of the ground surface. We review the processing chain and present the new and improved modules for satellite pushbroom imagery, in particular the N-image bundle block adjustment to jointly optimize the viewing geometry of multiple acquisitions, the improved multi-scale image matching based on Semi-Global Matching (SGM) to extract high resolution topography, and the triangulation of multi-temporal disparity maps to derive 3D ground motion. In particular, processes are optimized to run on a cluster computing environment. This new suite of algorithms is applied to the study of Worldview stereo imagery above the Franz Josef, Fox, and Tasman Glaciers, New Zealand, acquired on 01/30/2013, 02/09/2013, and 02/28/2013. We derive high resolution (1m post-spacing) maps of ice flow in three dimensions, where ice velocities of up to 4 m/day are recorded. Images were collected in early summer during a dry and sunny period, which followed two weeks of unsettled weather with several heavy rainfall events across the Southern Alps. The 3D tracking of ice flow highlights the surface response of the glaciers to changes in effective pressure at the ice-bedrock interface due to heavy rainfall, at an unprecedented spatial resolution.

  12. Advances In very high resolution satellite imagery analysis for Monitoring human settlements

    Energy Technology Data Exchange (ETDEWEB)

    Vatsavai, Raju [ORNL; Cheriyadat, Anil M [ORNL; Bhaduri, Budhendra L [ORNL

    2014-01-01

    The high rate of urbanization, political conflicts and ensuing internal displacement of population, and increased poverty in the 20th century has resulted in rapid increase of informal settlements. These unplanned, unauthorized, and/or unstructured homes, known as informal settlements, shantytowns, barrios, or slums, pose several challenges to the nations, as these settlements are often located in most hazardous regions and lack basic services. Though several World Bank and United Nations sponsored studies stress the importance of poverty maps in designing better policies and interventions, mapping slums of the world is a daunting and challenging task. In this paper, we summarize our ongoing research on settlement mapping through the utilization of Very high resolution (VHR) remote sensing imagery. Most existing approaches used to classify VHR images are single instance (or pixel-based) learning algorithms, which are inadequate for analyzing VHR imagery, as single pixels do not contain sufficient contextual information (see Figure 1). However, much needed spatial contextual information can be captured via feature extraction and/or through newer machine learning algorithms in order to extract complex spatial patterns that distinguish informal settlements from formal ones. In recent years, we made significant progress in advancing the state of art in both directions. This paper summarizes these results.

  13. Robust Change Vector Analysis (RCVA) for multi-sensor very high resolution optical satellite data

    Science.gov (United States)

    Thonfeld, Frank; Feilhauer, Hannes; Braun, Matthias; Menz, Gunter

    2016-08-01

    The analysis of rapid land cover/land use changes by means of remote sensing is often based on data acquired under varying and occasionally unfavorable conditions. In addition, such analyses frequently use data acquired by different sensor systems. These acquisitions often differ with respect to sun position and sensor viewing geometry which lead to characteristic effects in each image. These differences may have a negative impact on reliable change detection. Here, we propose an approach called Robust Change Vector Analysis (RCVA), aiming to mitigate these effects. RCVA is an improvement of the widely-used Change Vector Analysis (CVA), developed to account for pixel neighborhood effects. We used a RapidEye and Kompsat-2 cross-sensor change detection test to demonstrate the efficiency of RCVA. Our analysis showed that RCVA results in fewer false negatives as well as false positives when compared to CVA under similar test conditions. We conclude that RCVA is a powerful technique which can be utilized to reduce spurious changes in bi-temporal change detection analyses based on high- or very-high spatial resolution imagery.

  14. Irrigation water use monitoring at watershed scale using series of high-resolution satellite images

    Science.gov (United States)

    Díaz, A.; González-Dugo, M. P.; Escuin, S.; Mateos, L.; Cano, F.; Cifuentes, V.; Tirado, J. L.; Oyonarte, N.

    2009-09-01

    The integration of time series of high-resolution remote sensing images in the FAO crop evapotranspiration (ET) model is receiving growing interest in the last years, specially for operational applications in irrigated areas. In this study, a simplified methodology to estimate actual ET for these areas in large watersheds was developed. Then it was applied to the Guadalquivir river watershed (Southern Spain) in the 2007 and 2008 irrigation seasons. The evolution of vegetation indices, obtained from 10 Landsat and IRS images per season, was used for two purposes. Firstly, it was used for identifying crop types based on a classification algorithm. This algorithm used training data from a screened subset of the information declared by farmers for EU agriculture subsidies purposes. Secondly, the vegetation indices were used to obtain basal crop coefficients (Kcb, the component of the crop coefficient that represents transpiration). The last step was the parameterization of the influence of evaporation from the soil surface, considering the averaged effect of a given rain distribution and irrigation schedule. The results showed only small discrepancies between the crop coefficients calculated using the simplified model and those calculated based on a soil water balance and the dual approach proposed by FAO. Therefore, it was concluded that the simplified method can be applied to large irrigation areas where detailed information about soils and/or water applied by farmers lacks..

  15. Operational High Resolution Land Cover Map Production at the Country Scale Using Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    Jordi Inglada

    2017-01-01

    Full Text Available A detailed and accurate knowledge of land cover is crucial for many scientific and operational applications, and as such, it has been identified as an Essential Climate Variable. This accurate knowledge needs frequent updates. This paper presents a methodology for the fully automatic production of land cover maps at country scale using high resolution optical image time series which is based on supervised classification and uses existing databases as reference data for training and validation. The originality of the approach resides in the use of all available image data, a simple pre-processing step leading to a homogeneous set of acquisition dates over the whole area and the use of a supervised classifier which is robust to errors in the reference data. The produced maps have a kappa coefficient of 0.86 with 17 land cover classes. The processing is efficient, allowing a fast delivery of the maps after the acquisition of the image data, does not need expensive field surveys for model calibration and validation, nor human operators for decision making, and uses open and freely available imagery. The land cover maps are provided with a confidence map which gives information at the pixel level about the expected quality of the result.

  16. Rotation-and-scale-invariant airplane detection in high-resolution satellite images based on deep-Hough-forests

    Science.gov (United States)

    Yu, Yongtao; Guan, Haiyan; Zai, Dawei; Ji, Zheng

    2016-02-01

    This paper proposes a rotation-and-scale-invariant method for detecting airplanes from high-resolution satellite images. To improve feature representation capability, a multi-layer feature generation model is created to produce high-order feature representations for local image patches through deep learning techniques. To effectively estimate airplane centroids, a Hough forest model is trained to learn mappings from high-order patch features to the probabilities of an airplane being present at specific locations. To handle airplanes with varying orientations, patch orientation is defined and integrated into the Hough forest to augment Hough voting. The scale invariance is achieved by using a set of scale factors embedded in the Hough forest. Quantitative evaluations on the images collected from Google Earth service show that the proposed method achieves a completeness, correctness, quality, and F1-measure of 0.968, 0.972, 0.942, and 0.970, respectively, in detecting airplanes with arbitrary orientations and sizes. Comparative studies also demonstrate that the proposed method outperforms the other three existing methods in accurately and completely detecting airplanes in high-resolution remotely sensed images.

  17. Monitoring Changes in Water Resources Systems Using High Resolution Satellite Observations: Application to Lake Urmia

    Science.gov (United States)

    Norouzi, H.; AghaKouchak, A.; Madani, K.; Mirchi, A.; Farahmand, A.; Conway, C.

    2013-12-01

    Lake Urmia with its unique ecosystem in northwestern Iran is the second largest saltwater lake in the world. It is home of more than 300 species of birds, reptiles, and mammals with high salinity level of more than 300 g/l. In recent years, a significant water retreat has occurred in this lake. In this study, we tried to monitor the desiccation of the lake over more than four decades using remote sensing observations. Multi-spectral high-resolution LandSat images of the Lake Urmia region from 1972 to 2012 were acquired to derive the lake area. The composite maps of the lake were created, and a Bayesian Maximum Likelihood classification technique was used to classify land and water in the composite maps. The time series of the lake area reveals that it has shrunk by more than 40% in the past ten years. Moreover, water budget related components such as precipitation, soil moisture, and drought indices from remote sensing of the lake basin were utilized to investigate if droughts or climate change are the primary driving forces behind this phenomenon. These analyses show that the retreat of the lake is not related to droughts or global climate change as it has survived several drought events before year 2000. Similar analyses conducted on Lake Van located about 400 km west of Lake Urmia with very similar climate pattern revealed no significant areal change despite the lake's exposure to similar drought events. These results raise serious concern about the destructive role of unbridled development coupled with supply-oriented water management scheme driven by a classic upstream-downstream competition for water in the Lake Urmia region. There is an urgent need to investigate sustainable restoration initiatives for Lake Urmia in order to prevent an environmental disaster comparable to catastrophic death of Aral Sea.

  18. Utilizing Chinese high-resolution satellite images for inspection of unauthorized constructions in Beijing

    Institute of Scientific and Technical Information of China (English)

    LI DeRen; WANG Mi; HU Fen

    2009-01-01

    After Beijing wins the bit to host the 29th Olympic Games, in order to manifest the technical support advantages and capabilities of the autonomously-developed RS and GIS based change detection techniques in 2008 Beijing Olympic Games, and from the standpoints of executing new city planning, relieving the traffic congestion as well as maintaining the historic features, an automatic satellite monitoring system has been studied and established to accomplish the mission of unauthorized construction inspection within the Sixth Ring Road of Beijing city quarterly, by adopting the CBERS-2 satellite images and combining technologies of GIS, GPS, etc. This article discusses the applicable procedures and key issues when utilizing such Chinese satellite images and relevant techniques to discover the illegal constructions, and introduces the monitoring system from both the design and implementation aspects; additionally, some typical application cases in the practice of the system are also illustrated. The monitoring system can timely supply abundant information to facilitate the policy-making of relevant planning departments, thus providing consolidate technical support to eliminate the illegal constructing behaviors in the blossom. During the five years' excellent performance, it has helped China save large amounts of expenditures for processing of unauthorized constructed buildings.

  19. Local high-resolution crustal magnetic field analysis from satellite data

    Science.gov (United States)

    Plattner, Alain; Simons, Frederik J.

    2016-04-01

    Planetary crustal magnetic fields are key to understanding a planet or moon's structure and history. Due to satellite orbit parameters such as aerobraking (Mars) or only partial coverage (Mercury), or simply because of the strongly heterogeneous crustal field strength, satellite data of planetary magnetic fields vary regionally in their signal-to noise ratio and data coverage. To take full advantage of data quality within one region of a planet or moon without diluting the data with lower quality measurements outside of that region we resort to local methods. Slepian functions are linear combinations of spherical harmonics that provide local sensitivity to structure. Here we present a selection of crustal magnetic field models obtained from vector-valued variable-altitude satellite observations using an altitude-cognizant gradient-vector Slepian approach. This method is based on locally maximizing energy concentration within the region of data availability while simultaneously bandlimiting the model in terms of its spherical-harmonic degree and minimizing noise amplification due to downward continuation. For simple regions such as spherical caps, our method is computationally efficient and allows us to calculate local crustal magnetic field solutions beyond spherical harmonic degree 800, if the data permit. We furthermore discuss extensions of the method that are optimized for the analysis and separation of internal and external magnetic fields.

  20. A NEW OBJECT-BASED FRAMEWORK TO DETECT SHODOWS IN HIGH-RESOLUTION SATELLITE IMAGERY OVER URBAN AREAS

    Directory of Open Access Journals (Sweden)

    N. Tatar

    2015-12-01

    Full Text Available In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

  1. Assimilation of satellite NO2 observations at high spatial resolution using OSSEs

    Science.gov (United States)

    Liu, Xueling; Mizzi, Arthur P.; Anderson, Jeffrey L.; Fung, Inez Y.; Cohen, Ronald C.

    2017-06-01

    Observations of trace gases from space-based instruments offer the opportunity to constrain chemical and weather forecast and reanalysis models using the tools of data assimilation. In this study, observing system simulation experiments (OSSEs) are performed to investigate the potential of high space- and time-resolution column measurements as constraints on urban NOx emissions. The regional chemistry-meteorology assimilation system where meteorology and chemical variables are simultaneously assimilated is comprised of a chemical transport model, WRF-Chem, the Data Assimilation Research Testbed, and a geostationary observation simulator. We design OSSEs to investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission updating scheme. We describe the overall model framework and some initial experiments that point out the first steps toward an optimal configuration for improving our understanding of NOx emissions by combining space-based measurements and data assimilation. Among the findings we describe is the dependence of errors in the estimated NOx emissions on the wind forecast errors, showing that wind vectors with a RMSE below 1 m s-1 allow inference of NOx emissions with a RMSE of less than 30 mol/(km2 × h) at the 3 km scale of the model we use. We demonstrate that our inference of emissions is more accurate when we simultaneously update both NOx emissions and NOx concentrations instead of solely updating emissions. Furthermore, based on our analyses, we recommend carrying out meteorology assimilations to stabilize NO2 transport from the initial wind errors before starting the emission assimilation. We show that wind uncertainties (calculated as a spread around a mean wind) are not important for estimating NOx emissions when the wind uncertainties are reduced below 1.5 m s-1. Finally, we present results assessing the role of separate vs. simultaneous chemical and meteorological assimilation in a model

  2. Exploring New Challenges of High-Resolution SWOT Satellite Altimetry with a Regional Model of the Solomon Sea

    Science.gov (United States)

    Brasseur, P.; Verron, J. A.; Djath, B.; Duran, M.; Gaultier, L.; Gourdeau, L.; Melet, A.; Molines, J. M.; Ubelmann, C.

    2014-12-01

    The upcoming high-resolution SWOT altimetry satellite will provide an unprecedented description of the ocean dynamic topography for studying sub- and meso-scale processes in the ocean. But there is still much uncertainty on the signal that will be observed. There are many scientific questions that are unresolved about the observability of altimetry at vhigh resolution and on the dynamical role of the ocean meso- and submesoscales. In addition, SWOT data will raise specific problems due to the size of the data flows. These issues will probably impact the data assimilation approaches for future scientific or operational oceanography applications. In this work, we propose to use a high-resolution numerical model of the Western Pacific Solomon Sea as a regional laboratory to explore such observability and dynamical issues, as well as new data assimilation challenges raised by SWOT. The Solomon Sea connects subtropical water masses to the equatorial ones through the low latitude western boundary currents and could potentially modulate the tropical Pacific climate. In the South Western Pacific, the Solomon Sea exhibits very intense eddy kinetic energy levels, while relatively little is known about the mesoscale and submesoscale activities in this region. The complex bathymetry of the region, complicated by the presence of narrow straits and numerous islands, raises specific challenges. So far, a Solomon sea model configuration has been set up at 1/36° resolution. Numerical simulations have been performed to explore the meso- and submesoscales dynamics. The numerical solutions which have been validated against available in situ data, show the development of small scale features, eddies, fronts and filaments. Spectral analysis reveals a behavior that is consistent with the SQG theory. There is a clear evidence of energy cascade from the small scales including the submesoscales, although those submesoscales are only partially resolved by the model. In parallel

  3. Mapping Urban Tree Canopy Coverage and Structure using Data Fusion of High Resolution Satellite Imagery and Aerial Lidar

    Science.gov (United States)

    Elmes, A.; Rogan, J.; Williams, C. A.; Martin, D. G.; Ratick, S.; Nowak, D.

    2015-12-01

    Urban tree canopy (UTC) coverage is a critical component of sustainable urban areas. Trees provide a number of important ecosystem services, including air pollution mitigation, water runoff control, and aesthetic and cultural values. Critically, urban trees also act to mitigate the urban heat island (UHI) effect by shading impervious surfaces and via evaporative cooling. The cooling effect of urban trees can be seen locally, with individual trees reducing home HVAC costs, and at a citywide scale, reducing the extent and magnitude of an urban areas UHI. In order to accurately model the ecosystem services of a given urban forest, it is essential to map in detail the condition and composition of these trees at a fine scale, capturing individual tree crowns and their vertical structure. This paper presents methods for delineating UTC and measuring canopy structure at fine spatial resolution (HVAC benefits from UTC for individual homes, and for assessing the ecosystem services for entire urban areas. Such maps have previously been made using a variety of methods, typically relying on high resolution aerial or satellite imagery. This paper seeks to contribute to this growing body of methods, relying on a data fusion method to combine the information contained in high resolution WorldView-3 satellite imagery and aerial lidar data using an object-based image classification approach. The study area, Worcester, MA, has recently undergone a large-scale tree removal and reforestation program, following a pest eradication effort. Therefore, the urban canopy in this location provides a wide mix of tree age class and functional type, ideal for illustrating the effectiveness of the proposed methods. Early results show that the object-based classifier is indeed capable of identifying individual tree crowns, while continued research will focus on extracting crown structural characteristics using lidar-derived metrics. Ultimately, the resulting fine resolution UTC map will be

  4. Forest Condition Monitoring Using Very-High-Resolution Satellite Imagery in a Remote Mountain Watershed in Nepal

    Directory of Open Access Journals (Sweden)

    Kabir Uddin

    2015-08-01

    Full Text Available Satellite imagery has proven extremely useful for repetitive timeline-based data collection, because it offers a synoptic view and enables fast processing of large quantities of data. The changes in tree crown number and land cover in a very remote watershed (area 1305 ha in Nepal were analyzed using a QuickBird image from 2006 and an IKONOS image from 2011. A geographic object-based image analysis (GEOBIA was carried out using the region-growing technique for tree crown detection, delineation, and change assessment, and a multiresolution technique was used for land cover mapping and change analysis. The coefficient of determination for tree crown detection and delineation was 0.97 for QuickBird and 0.99 for IKONOS, calculated using a line-intercept transect method with 10 randomly selected windows (1×1 ha. The number of tree crowns decreased from 47,121 in 2006 to 41,689 in 2011, a loss of approximately 90 trees per month on average; the area of needle-leaved forest was reduced by 140 ha (23% over the same period. Analysis of widely available very-high-resolution satellite images using GEOBIA techniques offers a cost-effective method for detecting changes in tree crown number and land cover in remote mountain valleys; the results provide the information needed to support improved local-level planning and forest management in such areas.

  5. Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

    Science.gov (United States)

    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

  6. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    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.

  7. Rapid, High-Resolution Detection of Environmental Change over Continental Scales from Satellite Data - the Earth Observation Data Cube

    Science.gov (United States)

    Lewis, Adam; Lymburner, Leo; Purss, Matthew B. J.; Brooke, Brendan; Evans, Ben; Ip, Alex; Dekker, Arnold G.; Irons, James R.; Minchin, Stuart; Mueller, Norman

    2015-01-01

    The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations - the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.

  8. Vegetation mapping from high-resolution satellite images in the heterogeneous arid environments of Socotra Island (Yemen)

    Science.gov (United States)

    Malatesta, Luca; Attorre, Fabio; Altobelli, Alfredo; Adeeb, Ahmed; De Sanctis, Michele; Taleb, Nadim M.; Scholte, Paul T.; Vitale, Marcello

    2013-01-01

    Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geomorphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum likelihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.

  9. Research on the classification result and accuracy of building windows in high resolution satellite images: take the typical rural buildings in Guangxi, China, as an example

    Science.gov (United States)

    Li, Baishou; Gao, Yujiu

    2015-12-01

    The information extracted from the high spatial resolution remote sensing images has become one of the important data sources of the GIS large scale spatial database updating. The realization of the building information monitoring using the high resolution remote sensing, building small scale information extracting and its quality analyzing has become an important precondition for the applying of the high-resolution satellite image information, because of the large amount of regional high spatial resolution satellite image data. In this paper, a clustering segmentation classification evaluation method for the high resolution satellite images of the typical rural buildings is proposed based on the traditional KMeans clustering algorithm. The factors of separability and building density were used for describing image classification characteristics of clustering window. The sensitivity of the factors influenced the clustering result was studied from the perspective of the separability between high image itself target and background spectrum. This study showed that the number of the sample contents is the important influencing factor to the clustering accuracy and performance, the pixel ratio of the objects in images and the separation factor can be used to determine the specific impact of cluster-window subsets on the clustering accuracy, and the count of window target pixels (Nw) does not alone affect clustering accuracy. The result can provide effective research reference for the quality assessment of the segmentation and classification of high spatial resolution remote sensing images.

  10. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

  11. Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2010-12-01

    Full Text Available Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.

  12. Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

    Directory of Open Access Journals (Sweden)

    Mou Leong Tan

    2015-01-01

    Full Text Available Satellite precipitation products (SPPs potentially constitute an alternative to sparse rain gauge networks for assessing the spatial distribution of precipitation. However, applications of these products are still limited due to the lack of robust quality assessment. This study compares daily, monthly, seasonal, and annual rainfall amount at 342 rain gauges over Malaysia to estimations using five SPPs (3B42RT, 3B42V7, GPCP-1DD, PERSIANN-CDR, and CMORPH and a ground-based precipitation product (APHRODITE. The performance of the precipitation products was evaluated from 2003 to 2007 using continuous (RMSE, R2, ME, MAE, and RB and categorical (ACC, POD, FAR, CSI, and HSS statistical approaches. Overall, 3B42V7 and APHRODITE performed the best, while the worst performance was shown by GPCP-1DD. 3B42RT, 3B42V7, and PERSIANN-CDR slightly overestimated observed precipitation by 2%, 4.7%, and 2.1%, respectively. By contrast, APHRODITE and CMORPH significantly underestimated precipitations by 19.7% and 13.2%, respectively, whereas GPCP-1DD only slightly underestimated by 2.8%. All six precipitation products performed better in the northeast monsoon than in the southwest monsoon. The better performances occurred in eastern and southern Peninsular Malaysia and in the north of East Malaysia, which receives higher rainfall during the northeast monsoon, whereas poor performances occurred in the western and dryer Peninsular Malaysia. All precipitation products underestimated the no/tiny (<1 mm/day and extreme (≥20 mm/day rainfall events, while they overestimated low (1–20 mm/day rainfall events. 3B42RT and 3B42V7 showed the best ability to detect precipitation amounts with the highest HSS value (0.36. Precipitations during flood events such as those which occurred in late 2006 and early 2007 were estimated the best by 3B42RT and 3B42V7, as shown by an R2 value ranging from 0.49 to 0.88 and 0.52 to 0.86, respectively. These results on SPPs’ uncertainties

  13. 3-Dimentional Mapping Coastal Zone using High Resolution Satellite Stereo Imageries

    Science.gov (United States)

    Hong, Zhonghua; Liu, Fengling; Zhang, Yun

    2014-03-01

    The metropolitan coastal zone mapping is critical for coastal resource management, coastal environmental protection, and coastal sustainable development and planning. The results of geometric processing of a Shanghai coastal zone from 0.7-m-resolution QuickBird Geo stereo images are presented firstly. The geo-positioning accuracy of ground point determination with vendor-provided rigorous physical model (RPM) parameters is evaluated and systematic errors are found when compared with ground control points surveyed by GPS real-time kinematic (GPS-RTK) with 5cm accuracy. A bias-compensation process in image space that applies a RPM bundle adjustment to the RPM-calculated 3D ground points to correct the systematic errors is used to improve the geo-positioning accuracy. And then, a area-based matching (ABM) method is used to generated the densely corresponding points of left and right QuickBird images. With the densely matching points, the 3-dimentinal coordinates of ground points can be calculated by using the refined geometric relationship between image and ground points. At last step, digital surface model (DSM) can be achieved automatically using interpolation method. Accuracies of the DSM as assessed from independent checkpoints (ICPs) are approximately 1.2 m in height.

  14. High Resolution Topography of Polar Regions from Commercial Satellite Imagery, Petascale Computing and Open Source Software

    Science.gov (United States)

    Morin, Paul; Porter, Claire; Cloutier, Michael; Howat, Ian; Noh, Myoung-Jong; Willis, Michael; Kramer, WIlliam; Bauer, Greg; Bates, Brian; Williamson, Cathleen

    2017-04-01

    Surface topography is among the most fundamental data sets for geosciences, essential for disciplines ranging from glaciology to geodynamics. Two new projects are using sub-meter, commercial imagery licensed by the National Geospatial-Intelligence Agency and open source photogrammetry software to produce a time-tagged 2m posting elevation model of the Arctic and an 8m posting reference elevation model for the Antarctic. When complete, this publically available data will be at higher resolution than any elevation models that cover the entirety of the Western United States. These two polar projects are made possible due to three equally important factors: 1) open-source photogrammetry software, 2) petascale computing, and 3) sub-meter imagery licensed to the United States Government. Our talk will detail the technical challenges of using automated photogrammetry software; the rapid workflow evolution to allow DEM production; the task of deploying the workflow on one of the world's largest supercomputers; the trials of moving massive amounts of data, and the management strategies the team needed to solve in order to meet deadlines. Finally, we will discuss the implications of this type of collaboration for future multi-team use of leadership-class systems such as Blue Waters, and for further elevation mapping.

  15. Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

    Science.gov (United States)

    Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

    2017-05-01

    Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

  16. Discrimination of tree species using random forests from the Chinese high-resolution remote sensing satellite GF-1

    Science.gov (United States)

    Lv, Jie; Ma, Ting

    2016-10-01

    Tree species distribution is an important issue for sustainable forest resource management. However, the accuracy of tree species discrimination using remote-sensing data needs to be improved to support operational forestry-monitoring tasks. This study aimed to classify tree species in the Liangshui Nature Reserve of Heilongjiang Province, China using spectral and structural remote sensing information in an auto-mated Random Forest modelling approach. This study evaluates and compares the performance of two machine learning classifiers, random forests (RF), support vector machine (SVM) to classify the Chinese high-resolution remote sensing satellite GF-1 images. Texture factor was extracted from GF-1 image with grey-level co-occurrence matrix method. Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Enhanced Vegetation Index (EVI), Difference Vegetation Index (DVI) were calculated and coupled into the model. The result show that the Random Forest model yielded the highest classification accuracy and prediction success for the tree species with an overall classification accuracy of 81.07% and Kappa coefficient value of 0.77. The proposed random forests method was able to achieve highly satisfactory tree species discrimination results. And aerial LiDAR data should be further explored in future research activities.

  17. Geometric/radiometric calibration from ordinary images for high resolution satellite systems

    Science.gov (United States)

    Latry, Christophe

    2011-10-01

    This paper presents two techniques respectively devoted to noise and geometric characteristics assessment from standard images instead of dedicated ones. The noise computation technique assumes that high spatial frequencies are sufficiently weakened by MTF so that only noise remains near Nyquist frequency. It uses Fourier Transform or wavelet packet decomposition. The second technique is based upon matching processing between spectral bands assuming the imaging system focal plane has staggered arrays. It yields very accurate information on focal plane layout as well as high frequency attitude disturbances. Results obtained on simulated images as well as Worldview-2 real products are detailed

  18. Deriving the DTU15 Global high resolution marine gravity field from satellite altimetry

    DEFF Research Database (Denmark)

    Andersen, Ole Baltazar; Knudsen, Per

    Data from the Cryosat-2 (369 days repeat mission) as well as Jason-1 end-of-life mission are the first new “geodetic mission” data sets released in nearly 2 decades since the ERS-1 and Geosat geodetic missions were conducted in the early 90’th and late 80’th. Besides providing high quality sea...... surface height observations, the Cryosat-2 has now completed its fifth cycle of 369 days. This opens for new ways of using “pseudo” repeat Geodetic mission data, by averaging or other means of analysisOne further advantage of the Cryosat-2 is its ability of provide new accurate sea surface height...... data using a reduced parameter system in combination with empirical retracking of the SAR and SAR-In data in particularly high latitude regions....

  19. High-Resolution Mapping of Sea Ice, Icebergs and Growlers in Kongsfjorden, Svalbard, using Ground Based Radar, Satellite, and UAV

    Science.gov (United States)

    Lauknes, T. R.; Rouyet, L.; Solbø, S. A.; Sivertsen, A.; Storvold, R.; Akbari, V.; Negrel, J.; Gerland, S.

    2016-12-01

    The dynamics of sea ­ice has a well­ recognized role in the climate system and its extent and evolution is impacted by the global warming. In addition, calving of icebergs and growlers at the tidewater glacier fronts is a component of the mass loss in polar regions. Understanding of calving and ice ­ocean interaction, in particular at tidewater glacier front remains elusive, and a problematic uncertainty in climate change projections. Studying the distribution, volumetry and motion of sea ­ice, icebergs and growlers is thus essential to understand their interactions with the environment in order to be able to predict at short­term their drifts, e.g. to mitigate the risk for shipping, and at longer term the multiple relations with climate changes. Here, we present the results from an arctic fieldwork campaign conducted in Kongsfjorden, Svalbard in April 2016, where we used different remote sensing instruments to observe dynamics of sea ice, icebergs, and growlers. We used a terrestrial radar system, imaging the study area every second minute during the observation period. At the front of the Kronebreen glacier, calving events can be detected and the drift of the generated icebergs and growlers tracked with unprecedented spatial and temporal resolution. During the field campaign, we collected four Radarsat-2 quad-pol images, that will be used to classify the different types of sea ice. In addition, we used small unmanned aircraft (UAS) instrumented with high resolution cameras capturing HD video and still pictures. This allows to map and measure the size of icebergs and ice floes. Such information is essential to validate sensitivity and detection limits from the ground and satellite based measurements.

  20. Quasi-Epipolar Resampling of High Resolution Satellite Stereo Imagery for Semi Global Matching

    Science.gov (United States)

    Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

    2015-12-01

    Semi-global matching is a well-known stereo matching algorithm in photogrammetric and computer vision society. Epipolar images are supposed as input of this algorithm. Epipolar geometry of linear array scanners is not a straight line as in case of frame camera. Traditional epipolar resampling algorithms demands for rational polynomial coefficients (RPCs), physical sensor model or ground control points. In this paper we propose a new solution for epipolar resampling method which works without the need for these information. In proposed method, automatic feature extraction algorithms are employed to generate corresponding features for registering stereo pairs. Also original images are divided into small tiles. In this way by omitting the need for extra information, the speed of matching algorithm increased and the need for high temporal memory decreased. Our experiments on GeoEye-1 stereo pair captured over Qom city in Iran demonstrates that the epipolar images are generated with sub-pixel accuracy.

  1. Object-oriented feature extraction approach for mapping supraglacial debris in Schirmacher Oasis using very high-resolution satellite data

    Science.gov (United States)

    Jawak, Shridhar D.; Jadhav, Ajay; Luis, Alvarinho J.

    2016-05-01

    Supraglacial debris was mapped in the Schirmacher Oasis, east Antarctica, by using WorldView-2 (WV-2) high resolution optical remote sensing data consisting of 8-band calibrated Gram Schmidt (GS)-sharpened and atmospherically corrected WV-2 imagery. This study is a preliminary attempt to develop an object-oriented rule set to extract supraglacial debris for Antarctic region using 8-spectral band imagery. Supraglacial debris was manually digitized from the satellite imagery to generate the ground reference data. Several trials were performed using few existing traditional pixel-based classification techniques and color-texture based object-oriented classification methods to extract supraglacial debris over a small domain of the study area. Multi-level segmentation and attributes such as scale, shape, size, compactness along with spectral information from the data were used for developing the rule set. The quantitative analysis of error was carried out against the manually digitized reference data to test the practicability of our approach over the traditional pixel-based methods. Our results indicate that OBIA-based approach (overall accuracy: 93%) for extracting supraglacial debris performed better than all the traditional pixel-based methods (overall accuracy: 80-85%). The present attempt provides a comprehensive improved method for semiautomatic feature extraction in supraglacial environment and a new direction in the cryospheric research.

  2. Semi-automatic verification of cropland and grassland using very high resolution mono-temporal satellite images

    Science.gov (United States)

    Helmholz, Petra; Rottensteiner, Franz; Heipke, Christian

    2014-11-01

    Many public and private decisions rely on geospatial information stored in a GIS database. For good decision making this information has to be complete, consistent, accurate and up-to-date. In this paper we introduce a new approach for the semi-automatic verification of a specific part of the, possibly outdated GIS database, namely cropland and grassland objects, using mono-temporal very high resolution (VHR) multispectral satellite images. The approach consists of two steps: first, a supervised pixel-based classification based on a Markov Random Field is employed to extract image regions which contain agricultural areas (without distinction between cropland and grassland), and these regions are intersected with boundaries of the agricultural objects from the GIS database. Subsequently, GIS objects labelled as cropland or grassland in the database and showing agricultural areas in the image are subdivided into different homogeneous regions by means of image segmentation, followed by a classification of these segments into either cropland or grassland using a Support Vector Machine. The classification result of all segments belonging to one GIS object are finally merged and compared with the GIS database label. The developed approach was tested on a number of images. The evaluation shows that errors in the GIS database can be significantly reduced while also speeding up the whole verification task when compared to a manual process.

  3. Landuse change detection in a surface coal mine area using multi-temporal high resolution satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Demirel, N.; Duzgun, S.; Kemal Emil, M. [Middle East Technical Univ., Ankara (Turkey). Dept. of Mining Engineering

    2010-07-01

    Changes in the landcover and landuse of a mine area can be caused by surface mining activities, exploitation of ore and stripping and dumping overburden. In order to identify the long-term impacts of mining on the environment and land cover, these changes must be continuously monitored. A facility to regularly observe the progress of surface mining and reclamation is important for effective enforcement of mining and environmental regulations. Remote sensing provides a powerful tool to obtain rigorous data and reduce the need for time-consuming and expensive field measurements. The purpose of this study was to conduct post classification change detection for identifying, quantifying, and analyzing the spatial response of landscape due to surface lignite coal mining activities in Goynuk, Bolu, Turkey, from 2004 to 2008. The paper presented the research algorithm which involved acquiring multi temporal high resolution satellite data; preprocessing the data; performing image classification using maximum likelihood classification algorithm and performing accuracy assessment on the classification results; performing post classification change detection algorithm; and analyzing the results. Specifically, the paper discussed the study area, data and methodology, and image preprocessing using radiometric correction. Image classification and change detection were also discussed. It was concluded that the mine and dump area decreased by 192.5 ha from 2004 to 2008 and was caused by the diminishing reserves in the area and decline in the required production. 5 refs., 2 tabs., 4 figs.

  4. Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

    Science.gov (United States)

    Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

    2016-09-01

    Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

  5. Long-term evolution of Wink sinkholes in West Texas observed by high-resolution satellite imagery

    Science.gov (United States)

    Kim, J. W.; Lu, Z.

    2016-12-01

    Sinkhole is ground depression and/or collapse over the subsurface cavity in the karst terrain underlain by the carbonates, evaporites, and other soluble soils and rocks. The geohazards have been considered as a "hidden threat" to human life, infrastructures, and properties. The Delaware Basin of West Texas in the southwest part of the Permian Basin contains one of the greatest accumulations of evaporites in the United States. Sinkholes in West Texas have been developed by the dissolution of the subsurface evaporite deposits that come in contact with groundwater. Two Wink sinkholes in Wink, Texas, were developed in 1980 and 2002, respectively. However, monitoring the sinkholes in no man's lands has been challenging due to the lack of availability of high-resolution and temporally dense acquisitions. We employ aerial photography and radar satellite imagery to measure the long-term deformation from early 2000 and characterize the inherent hydrogeology that is closely related to sinkhole collapse and subsidence. Furthermore, data on oil/gas production and water injection into the subsurface as well as ground water level are analyzed to study their effects on the concurrent unstable ground surface in Wink sinkholes. Our study will provide invaluable information to understand the mechanism of sinkhole development and mitigate the catastrophic outcomes of the geohazards.

  6. Geospatial mapping of Antarctic coastal oasis using geographic object-based image analysis and high resolution satellite imagery

    Science.gov (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-04-01

    An accurate spatial mapping and characterization of land cover features in cryospheric regions is an essential procedure for many geoscientific studies. A novel semi-automated method was devised by coupling spectral index ratios (SIRs) and geographic object-based image analysis (OBIA) to extract cryospheric geospatial information from very high resolution WorldView 2 (WV-2) satellite imagery. The present study addresses development of multiple rule sets for OBIA-based classification of WV-2 imagery to accurately extract land cover features in the Larsemann Hills, east Antarctica. Multilevel segmentation process was applied to WV-2 image to generate different sizes of geographic image objects corresponding to various land cover features with respect to scale parameter. Several SIRs were applied to geographic objects at different segmentation levels to classify land mass, man-made features, snow/ice, and water bodies. We focus on water body class to identify water areas at the image level, considering their uneven appearance on landmass and ice. The results illustrated that synergetic usage of SIRs and OBIA can provide accurate means to identify land cover classes with an overall classification accuracy of ≍97%. In conclusion, our results suggest that OBIA is a powerful tool for carrying out automatic and semiautomatic analysis for most cryospheric remote-sensing applications, and the synergetic coupling with pixel-based SIRs is found to be a superior method for mining geospatial information.

  7. Geographic Object-based Image Analysis for Developing Cryospheric Surface Mapping Application using Remotely Sensed High-Resolution Satellite Imagery

    Science.gov (United States)

    Jawak, S. D.; Luis, A. J.

    2015-12-01

    A novel semi-automated method was devised by coupling spectral index ratios (SIRs) and geographic object-based image analysis (GEOBIA) to extract cryospheric geoinformation from very high resolution WorldView 2 (WV-2) satellite imagery. The present study addresses development of multiple rule sets for GEOBIA-based classification of WV-2 imagery to accurately extract land cover features in the Larsemann Hills, Antarctica. Multi-level segmentation process was applied to WV-2 image to generate different sizes of geographic image objects corresponding to various land cover features w.r.t scale parameter. Several SIRs were applied to geographic objects at different segmentation levels to classify landmass, man-made features, snow/ice, and water bodies. A specific attention was paid to water body class to identify water areas at the image level, considering their uneven appearance on landmass and ice. The results illustrated that synergetic usage of SIRs and GEOBIA can provide accurate means to identify land cover classes with an overall classification accuracy of ≈97%. In conclusion, the results suggest that GEOBIA is a powerful tool for carrying out automatic and semiautomatic analysis for most cryospheric remote-sensing applications, and the synergetic coupling with pixel-based SIRs is found to be a superior method for mining geoinformation.

  8. Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

    Science.gov (United States)

    Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

  9. Mapping Sub-Saharan African Agriculture in High-Resolution Satellite Imagery with Computer Vision & Machine Learning

    Science.gov (United States)

    Debats, Stephanie Renee

    Smallholder farms dominate in many parts of the world, including Sub-Saharan Africa. These systems are characterized by small, heterogeneous, and often indistinct field patterns, requiring a specialized methodology to map agricultural landcover. In this thesis, we developed a benchmark labeled data set of high-resolution satellite imagery of agricultural fields in South Africa. We presented a new approach to mapping agricultural fields, based on efficient extraction of a vast set of simple, highly correlated, and interdependent features, followed by a random forest classifier. The algorithm achieved similar high performance across agricultural types, including spectrally indistinct smallholder fields, and demonstrated the ability to generalize across large geographic areas. In sensitivity analyses, we determined multi-temporal images provided greater performance gains than the addition of multi-spectral bands. We also demonstrated how active learning can be incorporated in the algorithm to create smaller, more efficient training data sets, which reduced computational resources, minimized the need for humans to hand-label data, and boosted performance. We designed a patch-based uncertainty metric to drive the active learning framework, based on the regular grid of a crowdsourcing platform, and demonstrated how subject matter experts can be replaced with fleets of crowdsourcing workers. Our active learning algorithm achieved similar performance as an algorithm trained with randomly selected data, but with 62% less data samples. This thesis furthers the goal of providing accurate agricultural landcover maps, at a scale that is relevant for the dominant smallholder class. Accurate maps are crucial for monitoring and promoting agricultural production. Furthermore, improved agricultural landcover maps will aid a host of other applications, including landcover change assessments, cadastral surveys to strengthen smallholder land rights, and constraints for crop modeling

  10. Fast terrain modelling for hydrogeological risk mapping and emergency management: the contribution of high-resolution satellite SAR imagery

    Directory of Open Access Journals (Sweden)

    A. Nascetti

    2015-07-01

    Full Text Available Geomatic tools fast terrain modelling play a relevant role in hydrogeological risk mapping and emergency management. Given their complete independence from logistic constraints on the ground (as for airborne data collection, illumination (daylight, and weather (clouds conditions, synthetic aperture radar (SAR satellite systems may provide important contributions in terms of digital surface models (DSMs and digital elevation models (DEMs. For this work we focused on the potential of high-resolution SAR satellite imagery for DSM generation using an interferometric (InSAR technique and using a revitalized radargrammetric stereomapping approach. The goal of this work was just methodological. Our goal was to illustrate both the fundamental advantages and drawbacks of the radargrammetric approach with respect to the InSAR technique for DSM generation, and to outline their possible joint role in hydrogeological risk mapping and emergency management. Here, it is worth mentioning that radargrammetry procedures are independent of image coherence (unlike the interferometric approach and phase unwrapping, as well as of parsimony (only a few images are necessary. Therefore, a short time is required for image collection (from tens of minutes to a few hours, thanks to the independence from illumination and weather. The most relevant obstacles of the technique are speckle and the lack of texture impact on image matching, as well as the well-known deformations of SAR imagery (layover and foreshortening, which may produce remarkable difficulties with complex morphologies and that must be accounted for during acquisition planning. Here, we discuss results obtained with InSAR and radargrammetry applied to a COSMO-SkyMed SpotLight triplet (two stereopairs suited for radargrammetry and InSAR, sharing one common image acquired over suburbs of San Francisco (United States, which are characterized by mixed morphology and land cover. We mainly focused on urban areas and

  11. Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

    Science.gov (United States)

    Limaye, Ashutosh S.; Molthan, Andrew L.; Srikishen, Jayanthi

    2010-01-01

    The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

  12. Developing an Ice Volume Estimate of Jarvis Glacier, Alaska, using Ground-Penetrating Radar and High Resolution Satellite Imagery

    Science.gov (United States)

    Wu, N. L.; Campbell, S. W.; Douglas, T. A.; Osterberg, E. C.

    2013-12-01

    Jarvis Glacier is an important water source for Fort Greely and Delta Junction, Alaska. Yet with warming summer temperatures caused by climate change, the glacier is melting rapidly. Growing concern of a dwindling water supply has caused significant research efforts towards determining future water resources from spring melt and glacier runoff which feeds the community on a yearly basis. The main objective of this project was to determine the total volume of the Jarvis Glacier. In April 2012, a centerline profile of the Jarvis Glacier and 15 km of 100 MHz ground-penetrating radar (GPR) profiles were collected in cross sections to provide ice depth measurements. These depth measurements were combined with an interpreted glacier boundary (depth = 0 m) from recently collected high resolution WorldView satellite imagery to estimate total ice volume. Ice volume was calculated at 0.62 km3 over a surface area of 8.82 km2. However, it is likely that more glacier-ice exists within Jarvis Glacier watershed considering the value calculated with GPR profiles accounts for only the glacier ice within the valley and not for the valley side wall ice. The GLIMS glacier area database suggests that the valley accounts for approximately 50% of the total ice covered watershed. Hence, we are currently working to improve total ice volume estimates which incorporate the surrounding valley walls. Results from this project will be used in conjunction with climate change estimates and hydrological properties downstream of the glacier to estimate future water resources available to Fort Greely and Delta Junction.

  13. On-orbit geometric calibration and geometric quality assessment for the high-resolution geostationary optical satellite GaoFen4

    Science.gov (United States)

    Wang, Mi; Cheng, Yufeng; Chang, Xueli; Jin, Shuying; Zhu, Ying

    2017-03-01

    The Chinese GaoFen4 (GF4) remote sensing satellite, launched at the end of December 2015, is China's first civilian high-resolution geostationary optical satellite and has the world's highest resolution from geostationary orbit. High accuracy geometric calibration is the key factor in the geometrical quality of satellite imagery. This paper proposes an on-orbit geometric calibration approach for the high-resolution geostationary optical satellite GF4 in which a stepwise calibration is performed, external parameters are estimated, and internal parameters are then estimated in a generalized camera frame determined by external parameters. First, the correlation of the imaging error sources and the rigorous imaging model of GF4 are introduced. Second, the geometric calibration model based on the two-dimensional detector directional angle and the parameters estimation method for the planar array camera are presented. LandSat 8 digital orthophoto maps (DOM) and GDEM2 digital elevation models (DEM) are used to validate the efficiency of the proposed method and to make a geometric quality assessment of GF4. The results indicate that changing imaging time and imaging area will dramatically affect the absolute positioning accuracy because of the change of the camera's installation angles caused by thermal environment changes around the satellite in a high orbit. After calibration, the internal distortion is well-compensated, and the positioning accuracy with relatively few ground control points (GCPs) is demonstrated to be better than 1.0 pixels for both the panchromatic and near-infrared sensor and the intermediate infrared sensor.

  14. A novel method to retrieve Aerosol Optical Thickness from high-resolution optical satellite images using an extended version of the Haze Optimized Transform (HOTBAR)

    Science.gov (United States)

    Wilson, Robin; Milton, Edward; Nield, Joanna

    2016-04-01

    Aerosol Optical Thickness (AOT) data has many important applications including atmospheric correction of satellite imagery and monitoring of particulate matter air pollution. Current data products are generally available at a kilometre-scale resolution, but many applications require far higher resolutions. For example, particulate matter concentrations vary on a metre-scale, and thus data products at a similar scale are required to provide accurate assessments of particle densities and allow effective monitoring of air quality and analysis of local air quality effects on health. A novel method has been developed which retrieves per-pixel AOT values from high-resolution (~30m) satellite data. This method is designed to work over a wide range of land covers - including both bright and dark surfaces - and requires only standard visible and near-infrared data, making it applicable to a range of data from sensors such as Landsat, SPOT and Sentinel-2. The method is based upon an extension of the Haze Optimized Transform (HOT). The HOT was originally designed for assessing areas of thick haze in satellite imagery by calculating a 'haziness' value for each pixel in an image as the distance from a 'Clear Line' in feature space, defined by the high correlation between visible bands. Here, we adapt the HOT method and use it to provide AOT data instead. Significant extensions include Monte Carlo estimation of the 'Clear Line', object-based correction for land cover, and estimation of AOT from the haziness values through radiative transfer modelling. This novel method will enable many new applications of AOT data that were impossible with previously available low-resolution data, and has the potential to contribute significantly to our understanding of the air quality on health, the accuracy of satellite image atmospheric correction and the role of aerosols in the climate system.

  15. SACRA - a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI

    Science.gov (United States)

    Kotsuki, S.; Tanaka, K.

    2015-11-01

    To date, many studies have performed numerical estimations of biomass production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC), which defines the date or month when farmers sow and harvest crops, is an essential input for the numerical estimations. This study aims to present a new global data set, the SAtellite-derived CRop calendar for Agricultural simulations (SACRA), and to discuss advantages and disadvantages compared to existing census-based and model-derived products. We estimate global CC at a spatial resolution of 5 arcmin using satellite-sensed normalized difference vegetation index (NDVI) data, which corresponds to vegetation vitality and senescence on the land surface. Using the time series of the NDVI averaged from three consecutive years (2004-2006), sowing/harvesting dates are estimated for six crops (temperate-wheat, snow-wheat, maize, rice, soybean and cotton). We assume time series of the NDVI represent the phenology of one dominant crop and estimate CCs of the dominant crop in each grid. The dominant crops are determined using harvested areas based on census-based data. The cultivation period of SACRA is identified from the time series of the NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (disadvantage of our method is that the mixture of several crops in a grid is not considered in SACRA. The assumption of one dominant crop in each grid is a major source of discrepancy in crop calendars between SACRA and other products. The disadvantages of our approach may be reduced with future improvements based on finer satellite sensors and crop-type classification studies to consider several dominant crops in each grid. The comparison of the CC also demonstrates that identification of wheat type (sowing in spring or fall) is a major source of

  16. Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery

    Science.gov (United States)

    Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha

    2017-04-01

    A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.

  17. A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

    Directory of Open Access Journals (Sweden)

    Byongjun Hwang

    2017-07-01

    Full Text Available In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover

  18. Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

    Directory of Open Access Journals (Sweden)

    Timothy Shields

    2016-05-01

    Full Text Available Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase. Comparison of the images indicated that 971 (25.4% structures were added and 536 (14.0% removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

  19. Improvement of satellite-based gross primary production through incorporation of high resolution input data over east asia

    Science.gov (United States)

    Park, Haemi; Im, Jungho; Kim, Miae

    2016-04-01

    Photosynthesis of plants is the main mechanism of carbon absorption from the atmosphere into the terrestrial ecosystem and it contributes to remove greenhouse gases such as carbon dioxide. Annually, 120 Gt of C is supposed to be assimilated through photosynthetic activity of plants as the gross primary production (GPP) over global land area. In terms of climate change, GPP modelling is essential to understand carbon cycle and the balance of carbon budget over various ecosystems. One of the GPP modelling approaches uses light use efficiency that each vegetation type has a specific efficiency for consuming solar radiation related with temperature and humidity. Satellite data can be used to measure various meteorological and biophysical factors over vast areas, which can be used to quantify GPP. NASA Earth Observing System (EOS) program provides Moderate Resolution Imaging Spectroradiometer (MODIS)-derived global GPP product, namely MOD17A2H, on a daily basis. However, significant underestimation of MOD17A2H has been reported in Eastern Asia due to its dense forest distribution and humid condition during monsoon rainy season in summer. The objective of this study was to improve underestimation of MODIS GPP (MOD17A2H) by incorporating meteorological data-temperature, relative humidity, and solar radiation-of higher spatial resolution than data used in MOD17A2H. Landsat-based land cover maps of finer resolution observation and monitoring - global land cover (FROM-GLC) at 30m resolution were used for selection of light use efficiency (LUE). GPP (eq1. GPP = APAR×LUE) is computed by multiplication of APAR (IPAR×fPAR) and LUE (ɛ= ɛmax×T(°C)scalar×VPD(Pa)scalar, where, T is temperature, VPD is vapour pressure deficit) in this study. Meteorological data of Japanese 55-year Reanalysis (JRA-55, 0.56° grid, 3hr) were used for calculation of GPP in East Asia, including Eastern part of China, Korean peninsula, and Japan. Results were validated using flux tower-observed GPP

  20. Towards stochastically downscaled precipitation in the Tropics based on a robust 1DD combined satellite product and a high resolution IR-based rain mask

    Science.gov (United States)

    Guilloteau, Clement; Roca, Rémy; Gosset, Marielle

    2015-04-01

    In the Tropics where the ground-based rain gauges network is very sparse, satellite rainfall estimates are becoming a compulsory source of information for various applications: hydrological modeling, water resources management or vegetation-monitoring. The tropical Tropical Amount of Precipitation with Estimate of Error (TAPEER) algorithm, developed within the framework of Megha-Tropiques satellite mission is a robust estimate of surface rainfall accumulations at the daily, one degree resolution. TAPEER validation in West Africa has proven its accuracy. Nevertheless applications that involve non-linear processes (such as surface runoff) require finer space / time resolution than one degree one day, or at least the statistical characterization of the sub-grid rainfall variability. TAPEER is based on a Universally Adjusted Global Precipitation Index (UAGPI) technique. The one degree, one day estimation relies on the combination of observations from microwave radiometers embarked on the 7 platforms forming the GPM constellation of low earth orbit satellites together with geostationary infra-red (GEO-IR) imagery. TAPEER provides as an intermediate product a high-resolution rain-mask based on the GEO-IR information (2.8 km, 15 min in Africa). The main question of this work is, how to use this high-resolution mask information as a constraint for downscaling ? This work first presents the multi-scale evaluation of TAPEER's rain detection mask against ground X-band polarimetric radar data and TRMM precipitation radar data in West Africa, through wavelet transform. Other algorithms (climate prediction center morphing technique CMORPH, global satellite mapping of precipitation GSMaP, multi-sensor precipitation estimate MPE) detection capabilities are also evaluated. Spatio-temporal wavelet filtering of the detection mask is then used to compute precipitation probability at the GEO-IR resolution. The wavelet tool is finally used to stochastically generate rain / no rain field

  1. High-Resolution NDVI from Planet's Constellation of Earth Observing Nano-Satellites: A New Data Source for Precision Agriculture

    KAUST Repository

    Houborg, Rasmus

    2016-09-19

    Planet Labs ("Planet") operate the largest fleet of active nano-satellites in orbit, offering an unprecedented monitoring capacity of daily and global RGB image capture at 3-5 m resolution. However, limitations in spectral resolution and lack of accurate radiometric sensor calibration impact the utility of this rich information source. In this study, Planet\\'s RGB imagery was translated into a Normalized Difference Vegetation Index (NDVI): a common metric for vegetation growth and condition. Our framework employs a data mining approach to build a set of rule-based regression models that relate RGB data to atmospherically corrected Landsat-8 NDVI. The approach was evaluated over a desert agricultural landscape in Saudi Arabia where the use of near-coincident (within five days) Planet and Landsat-8 acquisitions in the training of the regression models resulted in NDVI predictabilities with an r2 of approximately 0.97 and a Mean Absolute Deviation (MAD) on the order of 0.014 (~9%). The MAD increased to 0.021 (~14%) when the Landsat NDVI training image was further away (i.e., 11-16 days) from the corrected Planet image. In these cases, the use of MODIS observations to inform on the change in NDVI occurring between overpasses was shown to significantly improve prediction accuracies. MAD levels ranged from 0.002 to 0.011 (3.9% to 9.1%) for the best performing 80% of the data. The technique is generic and extendable to any region of interest, increasing the utility of Planet\\'s dense time-series of RGB imagery.

  2. Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?

    DEFF Research Database (Denmark)

    Schumacher, Paul; Mislimshoeva, Bunafsha; Brenning, Alexander;

    2016-01-01

    Remote sensing-based woody biomass quantification in sparsely-vegetated areas is often limited when using only common broadband vegetation indices as input data for correlation with ground-based measured biomass information. Red edge indices and texture attributes are often suggested as a means...... to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically...... red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data...

  3. MISTiC Winds: A micro-satellite constellation approach to high resolution observations of the atmosphere using infrared sounding and 3D winds measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-09-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  4. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere using Infrared Sounding and 3D Winds Measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Susskind, J.; Aumann, H. H.

    2015-12-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sun-synchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's Atmospheric Infrared Sounder that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  5. Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering.

    Science.gov (United States)

    Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

    2015-09-10

    In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments.

  6. Using high-resolution satellite imagery to engage students in classroom experiences which meld research, the nature of science, and inquiry-based instruction

    Science.gov (United States)

    Pennycook, J.; LaRue, M.; Herried, B.; Morin, P. J.

    2013-12-01

    Recognizing the need to bridge the gap between scientific research and the classroom, we have developed an exciting activity which engages students in grades 5-12 using high-resolution satellite imagery to observe Weddell seal populations in Antarctica. Going beyond the scope of the textbook, students experience the challenge researchers face in counting and monitoring animal populations in the field. The activity is presented in a non-expert, non-technical exercise enriched for students, with background information, tutorials, and satellite imagery included. Teachers instruct their class in how to use satellite imagery analysis techniques to collect data on seal populations in the McMurdo Sound region of the Ross Sea, Antarctica. Students participate in this inquiry-based, open-ended exercise to evaluate changes in the seal population within and between seasons. The activity meets the New Generation Science Standards (NGSS) through inquiry-based, real-world application and supports seven Performance Expectations (PE) for grade 5-12. In addition, it offers students a glimpse into the work of a field biologist, promoting interest in entering the STEM career pipeline. As every new Antarctica season unfolds, new imagery will be uploaded to the website allowing each year of students to add their counts to a growing long-term dataset for the classroom. The activity files provide 1) a tutorial in how to use the images to count the populations, 2) background information about Weddell seals in the McMurdo Sound region of the Ross Sea for the students and the teachers, and 3) collections of satellite imagery for spatial and temporal analysis of population fluctuations. Teachers can find all activity files to conduct the activity, including student instructions, on the Polar Geospatial Center's website (http://z.umn.edu/seals). Satellite image, Big Razorback Island, Antarctica Weddell seals,Tent Island, Antarctica

  7. Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery

    Directory of Open Access Journals (Sweden)

    Jordi Inglada

    2015-09-01

    Full Text Available Crop area extent estimates and crop type maps provide crucial information for agricultural monitoring and management. Remote sensing imagery in general and, more specifically, high temporal and high spatial resolution data as the ones which will be available with upcoming systems, such as Sentinel-2, constitute a major asset for this kind of application. The goal of this paper is to assess to what extent state-of-the-art supervised classification methods can be applied to high resolution multi-temporal optical imagery to produce accurate crop type maps at the global scale. Five concurrent strategies for automatic crop type map production have been selected and benchmarked using SPOT4 (Take5 and Landsat 8 data over 12 test sites spread all over the globe (four in Europe, four in Africa, two in America and two in Asia. This variety of tests sites allows one to draw conclusions applicable to a wide variety of landscapes and crop systems. The results show that a random forest classifier operating on linearly temporally gap-filled images can achieve overall accuracies above 80% for most sites. Only two sites showed low performances: Madagascar due to the presence of fields smaller than the pixel size and Burkina Faso due to a mix of trees and crops in the fields. The approach is based on supervised machine learning techniques, which need in situ data collection for the training step, but the map production is fully automatic.

  8. Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011

    Science.gov (United States)

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-01-01

    Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

  9. A High-Resolution Two-Stage Satellite Model to Estimate PM2.5 Concentrations in China

    Science.gov (United States)

    Liu, Y.; Ma, Z.; Hu, X.; Yang, K.

    2014-12-01

    With the rapid economic development and urbanization, severe and widespread PM2.5 pollution in China has attracted nationwide attention. Study of the health impact of PM2.5 exposure has been hindered, however, by the limited coverage of ground measurements from recently established regulatory monitoring networks. Estimating ground-level PM2.5 from satellite remote sensing is a promising new method to evaluate the spatial and temporal patterns of PM2.5 exposure. We developed a two-stage spatial statistical model to estimate daily mean PM2.5 concentrations at 10 km resolution in 2013 in China using MODIS Collection 6 AOD, assimilated meteorology, population density, and land use parameters. A custom inverse variance weighting approach was developed to combine MODIS Dark Target (DT) and Deep Blue (DB) AOD to optimize coverage. Compared with the AERONET AOD measurements, our combined AOD (R2=0.80, mean bias = 0.07) performs similarly to MODIS' combined AOD (R2=0.81, mean bias =0.07), but has 90% greater coverage. We used the first-stage linear mixed effect model to represent the temporal variability of PM2.5 and the second-stage generalized additive model to represent its spatial contrast. The overall model cross-validation R2 and relative prediction error are 0.80 and 30%, respectively. PM2.5 levels exhibit strong seasonal patterns, with the highest national mean concentrations in winter (75 µg/m3) and the lowest in summer (30 µg/m3). Elevated annual mean PM2.5 levels are predicted in North China Plain and Sichuan Basin, with the maximum annual PM2.5 concentrations higher than 130 µg/m3 and 110 µg/m3, respectively. Our results also indicates that over 94% of the Chinese population lives in areas that exceed the WHO Air Quality Interim Target-1 standard (35 μg/m3). The exceptions include Taiwan, Hainan, Yunnan, Tibet, and North Inner Mongolia.

  10. Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR), P. R. China

    Science.gov (United States)

    Leempoel, K.; Satyaranayana, B.; Bourgeois, C.; Zhang, J.; Chen, M.; Wang, J.; Bogaert, J.; Dahdouh-Guebas, F.

    2013-08-01

    Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc.) to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China) were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively). Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (-36%) was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%), the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements) (August-September, 2009) as well as spectral reflectance values (obtained from pansharpened GeoEye-1), both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73-100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%). In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m) for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e.g. Kandelia obovata

  11. Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR, P. R. China

    Directory of Open Access Journals (Sweden)

    K. Leempoel

    2013-08-01

    Full Text Available Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc. to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively. Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (−36% was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%, the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements (August–September, 2009 as well as spectral reflectance values (obtained from pansharpened GeoEye-1, both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73–100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%. In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e

  12. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    Science.gov (United States)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  13. An improved high-resolution hybrid stepper motor for solar-array drive of Indian remote-sensing satellite

    Energy Technology Data Exchange (ETDEWEB)

    Rajagopal, K.R.; Krishnaswamy, M. [Indian Space Research Organization, Trivandrum (India). ISRO Inertial Systems Unit; Singh, B.; Singh, B.P. [Indian Inst. of Tech., New Delhi (India). Dept. of Electrical Engineering

    1997-07-01

    This paper presents the computer-aided design and development of an improved 720-steps hybrid stepper motor used as the drive motor for the solar array of the Indian remote-sensing (IRS) satellite in the polar sun-synchronous orbit. The motor is of pancake type with coil redundancy, and the step angle is 0.5{degree}. It is designed to deliver a constant holding torque of 1 N{center_dot}m against a varying dc supply voltage of 28--42 V and in an operating temperature range from {minus}10 C to +60 C. The authors introduce a phenomenon named as torque saturation, achievable in a hybrid stepper motor by properly choosing the operating point of the rotor permanent magnet and the stator winding configuration. Apart from the computer-aided design procedure, relevant details regarding fabrication and testing are also provided. The test results of the developed motor match fairly with the computed values and confirm the high performance of the developed hybrid stepper motor.

  14. Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

    Science.gov (United States)

    Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

    2015-12-01

    A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each

  15. Validation of Suomi-NPP VIIRS sea ice concentration with very high-resolution satellite and airborne camera imagery

    Science.gov (United States)

    Baldwin, Daniel; Tschudi, Mark; Pacifici, Fabio; Liu, Yinghui

    2017-08-01

    Two independent VIIRS-based Sea Ice Concentration (SIC) products are validated against SIC as estimated from Very High Spatial Resolution Imagery for several VIIRS overpasses. The 375 m resolution VIIRS SIC from the Interface Data Processing Segment (IDPS) SIC algorithm is compared against estimates made from 2 m DigitalGlobe (DG) WorldView-2 imagery and also against estimates created from 10 cm Digital Mapping System (DMS) camera imagery. The 750 m VIIRS SIC from the Enterprise SIC algorithm is compared against DG imagery. The IDPS vs. DG comparisons reveal that, due to algorithm issues, many of the IDPS SIC retrievals were falsely assigned ice-free values when the pixel was clearly over ice. These false values increased the validation bias and RMS statistics. The IDPS vs. DMS comparisons were largely over ice-covered regions and did not demonstrate the false retrieval issue. The validation results show that products from both the IDPS and Enterprise algorithms were within or very close to the 10% accuracy (bias) specifications in both the non-melting and melting conditions, but only products from the Enterprise algorithm met the 25% specifications for the uncertainty (RMS).

  16. Global high-resolution simulations of CO2 and CH4 using a NIES transport model to produce a priori concentrations for use in satellite data retrievals

    Directory of Open Access Journals (Sweden)

    S. Maksyutov

    2013-01-01

    Full Text Available The Greenhouse gases Observing SATellite (GOSAT measures column-averaged dry air mole fractions of carbon dioxide and methane (XCO2 and XCH4, respectively. Since the launch of GOSAT, model-simulated three-dimensional concentrations from a National Institute for Environmental Studies offline tracer Transport Model (NIES TM have been used as a priori concentration data for operational near real-time retrievals of XCO2 and XCH4 from GOSAT short-wavelength infrared spectra at NIES. Although the choice of a priori profile has only a minor effect on retrieved XCO2 or XCH4, a realistic simulation with minimal deviation from observed data is desirable. In this paper, we describe the newly developed version of NIES TM that has been adapted to provide global and near real-time concentrations of CO2 and CH4 using a high-resolution meteorological dataset, the Grid Point Value (GPV prepared by the Japan Meteorological Agency. The spatial resolution of the NIES TM is set to 0.5° × 0.5° in the horizontal in order to utilise GPV data, which have a resolution of 0.5° × 0.5°, 21 pressure levels and a time interval of 3 h. GPV data are provided to the GOSAT processing system with a delay of several hours, and the near real-time model simulation produces a priori concentrations driven by diurnally varying meteorology. A priori variance–covariance matrices of CO2 and CH4 are also derived from the simulation outputs and observation-based reference data for each month of the year at a resolution of 0.5° × 0.5° and 21 pressure levels. Model performance is assessed by comparing simulation results with the GLOBALVIEW dataset and other observational data. The overall root-mean-square differences between model predictions and GLOBALVIEW analysis are estimated to be 1.45 ppm and 12.52 ppb for CO2 and CH4, respectively, and the seasonal correlation coefficients are 0.87 for CO2 and 0.53 for CH4. The model showed good performance particularly at oceanic and free

  17. Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

    Science.gov (United States)

    Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

    2017-01-01

    As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and

  18. Monitoring of the Spatial Distribution and Temporal Dynamics of the Green Vegetation Fraction of Croplands in Southwest Germany Using High-Resolution RapidEye Satellite Images

    Science.gov (United States)

    Imukova, Kristina; Ingwersen, Joachim; Streck, Thilo

    2014-05-01

    The green vegetation fraction (GVF) is a key input variable to the evapotranspiration scheme applied in the widely used NOAH land surface model (LSM). In standard applications of the NOAH LSM, the GVF is taken from a global map with a 15 km×15 km resolution. The central objective of the present study was (a) to derive gridded GVF data in a high spatial and temporal resolution from RapidEye images for a region in Southwest Germany, and (b) to improve the representation of the GVF dynamics of croplands in the NOAH LSM for a better simulation of water and energy exchange between land surface and atmosphere. For the region under study we obtained monthly RapidEye satellite images with a resolution 5 m×5 m by the German Aerospace Center (DLR). The images hold five spectral bands: blue, green, red, red-edge and near infrared (NIR). The GVF dynamics were determined based on the Normalized Difference Vegetation Index (NDVI) calculated from the red and near-infrared bands of the satellite images. The satellite GVF data were calibrated and validated against ground truth measurements. Digital colour photographs above the canopy were taken with a boom-mounted digital camera at fifteen permanently marked plots (1 m×1 m). Crops under study were winter wheat, winter rape and silage maize. The GVF was computed based on the red and the green band of the photographs according to Rundquist's method (2002). Based on the obtained calibration scheme GVF maps were derived in a monthly resolution for the region. Our results confirm a linear relationship between GVF and NDVI and demonstrate that it is possible to determine the GVF of croplands from RapidEye images based on a simple two end-member mixing model. Our data highlight the high variability of the GVF in time and space. At the field scale, the GVF was normally distributed with a coefficient of variation of about 32%. Variability was mainly caused by soil heterogeneities and management differences. At the regional scale the GVF

  19. High-resolution satellite-derived ocean surface winds in the Nordic-Barents seas region: Implications for ocean modeling (Invited)

    Science.gov (United States)

    Dukhovskoy, D. S.; Bourassa, M. A.; Hughes, P. J.

    2010-12-01

    High-resolution (0.25°) ocean surface wind velocity data derived from satellite observations are used to analyze winds in the Nordic-Barents seas during 2007-2008. For the analysis, a Cross-Calibrated, Multi-Platform (CCMP), multi-instrument ocean surface wind velocity data set is utilized. The product has been developed by National Aeronautics and Space Administration (NASA) within Making Earth Science data records for Use in Research Environments (MEaSUREs) Program. A variational method was used to combine wind measurements derived from satellite-born active and passive remote sensing instruments. In the objective procedure, winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) Operational Analysis (DS111.1) were used as the background fields. The ocean surface wind fields are compared with those derived from the National Centers for Environmental Protection/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. The NCEP/NCAR fields are commonly used to provide atmospheric forcing for Arctic Ocean models. The utility of using high-resolution winds in the ocean modeling is discussed. In particular, air-sea heat fluxes estimated from the two wind data sets are compared. It is anticipated that wind fields with higher spatial and temporal resolution will better resolve small-scale, short-lived atmospheric systems. As an example, the ice free region in the Nordic and Barents seas is frequently impacted by very intense cyclones known as “polar lows” with wind speeds near to or above gale force. A polar low forms over the sea and predominantly during the winter months. The size of these cyclones varies greatly from 100 to 1000 km. Presumably small-scale cyclones are misrepresented or not resolved in the NCAR fields leading to biases in the air-sea flux calculations in the ocean models. Inaccurate estimates of the air-sea fluxes eventually lead to biases in the Arctic Ocean model solutions.

  20. Radial distribution and strong lensing statistics of satellite galaxies and substructure using high resolution LCDM hydrodynamical simulations

    CERN Document Server

    Maccio, A V; Stadel, J; Diemand, J; Maccio', Andrea V.; Moore, Ben; Stadel, Joachim; Diemand, Juerg

    2006-01-01

    We analyse the number density and radial distribution of substructures and satellite galaxies using cosmological simulations that follow the gas dynamics of a baryonic component, including shock heating, radiative cooling and star formation within the hierarchical concordance LCDM model. We find that the dissipation of the baryons greatly enhances the survival of subhaloes, expecially in the galaxy core, resulting in a radial distribution of satellite galaxies that closely follows the overall mass distribution. Hydrodynamical simulations are necessary to resolve the adiabatic contraction and dense cores of galaxies, resulting in a total number of satellites a factor of two larger than found in pure dark matter simulation. Convergence tests show that the cored distribution found by previous authors was due to physical overmerging of dark matter only structures. We proceed to use a ray-shooting technique in order to study the impact of these additional substructures on the number of violations of the cusp caust...

  1. Integration of carbon conservation into sustainable forest management using high resolution satellite imagery: A case study in Sabah, Malaysian Borneo

    Science.gov (United States)

    Langner, Andreas; Samejima, Hiromitsu; Ong, Robert C.; Titin, Jupiri; Kitayama, Kanehiro

    2012-08-01

    Conservation of tropical forests is of outstanding importance for mitigation of climate change effects and preserving biodiversity. In Borneo most of the forests are classified as permanent forest estates and are selectively logged using conventional logging techniques causing high damage to the forest ecosystems. Incorporation of sustainable forest management into climate change mitigation measures such as Reducing Emissions from Deforestation and Forest Degradation (REDD+) can help to avert further forest degradation by synergizing sustainable timber production with the conservation of biodiversity. In order to evaluate the efficiency of such initiatives, monitoring methods for forest degradation and above-ground biomass in tropical forests are urgently needed. In this study we developed an index using Landsat satellite data to describe the crown cover condition of lowland mixed dipterocarp forests. We showed that this index combined with field data can be used to estimate above-ground biomass using a regression model in two permanent forest estates in Sabah, Malaysian Borneo. Tangkulap represented a conventionally logged forest estate while Deramakot has been managed in accordance with sustainable forestry principles. The results revealed that conventional logging techniques used in Tangkulap during 1991 and 2000 decreased the above-ground biomass by an annual amount of average -6.0 t C/ha (-5.2 to -7.0 t C/ha, 95% confidential interval) whereas the biomass in Deramakot increased by 6.1 t C/ha per year (5.3-7.2 t C/ha, 95% confidential interval) between 2000 and 2007 while under sustainable forest management. This indicates that sustainable forest management with reduced-impact logging helps to protect above-ground biomass. In absolute terms, a conservative amount of 10.5 t C/ha per year, as documented using the methodology developed in this study, can be attributed to the different management systems, which will be of interest when implementing REDD+ that

  2. BUILT-UP AREA AND LAND COVER EXTRACTION USING HIGH RESOLUTION PLEIADES SATELLITE IMAGERY FOR MIDRAND, IN GAUTENG PROVINCE, SOUTH AFRICA

    Directory of Open Access Journals (Sweden)

    E. Fundisi

    2017-09-01

    Full Text Available Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.

  3. Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

    Science.gov (United States)

    Drzewiecki, Wojciech; Wężyk, Piotr; Pierzchalski, Marcin; Szafrańska, Beata

    2014-06-01

    In 2011 the Marshal Office of Małopolska Voivodeship decided to evaluate the vulnerability of soils to water erosion for the entire region. The quantitative and qualitative assessment of the erosion risk for the soils of the Małopolska region was done based on the USLE approach. The special work-flow of geoinformation technologies was used to fulfil this goal. A high-resolution soil map, together with rainfall data, a detailed digital elevation model and statistical information about areas sown with particular crops created the input information for erosion modelling in GIS environment. The satellite remote sensing technology and the object-based image analysis (OBIA) approach gave valuable support to this study. RapidEye satellite images were used to obtain the essential up-to-date data about land use and vegetation cover for the entire region (15,000 km2). The application of OBIA also led to defining the direction of field cultivation and the mapping of contour tillage areas. As a result, the spatially differentiated values of erosion control practice factor were used. Both, the potential and the actual soil erosion risk were assessed quantificatively and qualitatively. The results of the erosion assessment in the Małopolska Voivodeship reveal the fact that a majority of its agricultural lands is characterized by moderate or low erosion risk levels. However, high-resolution erosion risk maps show its substantial spatial diversity. According to our study, average or higher actual erosion intensity levels occur for 10.6 % of agricultural land, i.e. 3.6 % of the entire voivodeship area. In 20 % of the municipalities there is a very urgent demand for erosion control. In the next 23 % an urgent erosion control is needed. Our study showed that even a slight improvement of P-factor estimation may have an influence on modeling results. In our case, despite a marginal change of erosion assessment figures on a regional scale, the influence on the final prioritization of

  4. Instantaneous Shoreline Extraction Utilizing Integrated Spectrum and Shadow Analysis From LiDAR Data and High-resolution Satellite Imagery

    Science.gov (United States)

    Lee, I.-Chieh

    Shoreline delineation and shoreline change detection are expensive processes in data source acquisition and manual shoreline delineation. These costs confine the frequency and interval of shoreline mapping periods. In this dissertation, a new shoreline delineation approach was developed targeting on lowering the data source cost and reducing human labor. To lower the cost of data sources, we used the public domain LiDAR data sets and satellite images to delineate shorelines without the requirement of data sets being acquired simultaneously, which is a new concept in this field. To reduce the labor cost, we made improvements in classifying LiDAR points and satellite images. Analyzing shadow relations with topography to improve the satellite image classification performance is also a brand-new concept. The extracted shoreline of the proposed approach could achieve an accuracy of 1.495 m RMSE, or 4.452m at the 95% confidence level. Consequently, the proposed approach could successfully lower the cost and shorten the processing time, in other words, to increase the shoreline mapping frequency with a reasonable accuracy. However, the extracted shoreline may not compete with the shoreline extracted by aerial photogrammetric procedures in the aspect of accuracy. Hence, this is a trade-off between cost and accuracy. This approach consists of three phases, first, a shoreline extraction procedure based mainly on LiDAR point cloud data with multispectral information from satellite images. Second, an object oriented shoreline extraction procedure to delineate shoreline solely from satellite images; in this case WorldView-2 images were used. Third, a shoreline integration procedure combining these two shorelines based on actual shoreline changes and physical terrain properties. The actual data source cost would only be from the acquisition of satellite images. On the other hand, only two processes needed human attention. First, the shoreline within harbor areas needed to be

  5. Bi-Temporal Analysis of High-Resolution Satellite Imagery in Support of a Forest Conservation Program in Western Uganda

    Science.gov (United States)

    Thomas, N.; Lambin, E.; Audy, R.; Biryahwaho, B.; de Laat, J.; Jayachandran, S.

    2014-12-01

    Recent studies in land use sustainability have shown the conservation value of even small forest fragments in tropical smallholder agricultural regions. Forest patches provide important ecosystem services, wildlife habitat, and support human livelihoods. Our study incorporates multiple dates of high-resolution Quickbird imagery to map forest disturbance and regrowth in a smallholder agricultural landscape in western Uganda. This work is in support of a payments for ecosystem services (PES) project which uses a randomized controlled trial to assess the efficacy of PES for enhancing forest conservation. The research presented here details the remote sensing phase of this project. We developed an object-based methodology for detecting forest change from high-resolution imagery that calculates per class image reflectance and change statistics to determine persistent forest, non-forest, forest gain, and forest loss classes. The large study area (~ 2,400 km2) necessitated using a combination of 10 different image pairs of varying seasonality, sun angle, and viewing angle. We discuss the impact of these factors on mapping results. Reflectance data was used in conjunction with texture measures and knowledge-driven modeling to derive forest change maps. First, baseline Quickbird images were mapped into tree cover and non-tree categories based on segmented image objects and field inventory data, applied through a classification and regression tree (CART) classifier. Then a bi-temporal segmentation layer was generated and a series of object metrics from both image dates were extracted. A sample set of persistent forest objects that remained undisturbed was derived from the tree cover map and the red band (B3) change values. We calculated a variety of statistical indices for these persistent tree cover objects from the post- survey imagery to create maps of both forest cover loss and forest cover gain. These results are compared to visually assessed image objects in addition

  6. Ocean color measurements onboard a jet ski: consistency for calval exercise of high-resolution satellite imagery?

    Science.gov (United States)

    Martiny, Nadège; Dehouck, Aurélie; Froidefond, Jean-Marie; Sénéchal, Nadia

    2009-01-01

    An original data set has been acquired on the 5th of April 2008 during the international field experiment ECORS-Truc Vert 2008 (SW France) in the nearshore zone over a complex bathymetry and in moderate turbid waters (SPM RAMSES sensors which measure simultaneous atmospheric downwelling irradiances Ed and in-water upwelling radiances Lu in the 350-950nm range. Water samples have also been collected at different stages of the jet-ski trajectory (3-25m water depth) in order to assess the concentrations of the ocean constituents (SPM and Chl-a). In the current study we present a methodology to validate FORMOSAT-2 high-resolution ocean color data using "jetski" reflectance measurements, which first require a detailed analysis. The reflectance spectra measurements are shown to be consistent: (i) they are typical of the presence of mineral particles with light absorption at short wavelengths; (ii) their shape and magnitude depend on the depth and the water type (turbidity); (iii) some of them, especially in low turbid waters, are similar to other reflectance spectra measured northward from a ship (Gironde mouth). Thus, the use of "jet-ski" ocean color measurements appears to be adequate for remote sensing calval activities in shallow case-2 waters.

  7. Applicability of data mining algorithms in the identification of beach features/patterns on high-resolution satellite data

    Science.gov (United States)

    Teodoro, Ana C.

    2015-01-01

    The available beach classification algorithms and sediment budget models are mainly based on in situ parameters, usually unavailable for several coastal areas. A morphological analysis using remotely sensed data is a valid alternative. This study focuses on the application of data mining techniques, particularly decision trees (DTs) and artificial neural networks (ANNs) to an IKONOS-2 image in order to identify beach features/patterns in a stretch of the northwest coast of Portugal. Based on knowledge of the coastal features, five classes were defined. In the identification of beach features/patterns, the ANN algorithm presented an overall accuracy of 98.6% and a kappa coefficient of 0.97. The best DTs algorithm (with pruning) presents an overall accuracy of 98.2% and a kappa coefficient of 0.97. The results obtained through the ANN and DTs were in agreement. However, the ANN presented a classification more sensitive to rip currents. The use of ANNs and DTs for beach classification from remotely sensed data resulted in an increased classification accuracy when compared with traditional classification methods. The association of remotely sensed high-spatial resolution data and data mining algorithms is an effective methodology with which to identify beach features/patterns.

  8. Derivation and Validation of Supraglacial Lake Volumes on the Greenland Ice Sheet from High-Resolution Satellite Imagery

    Science.gov (United States)

    Moussavi, Mahsa S.; Abdalati, Waleed; Pope, Allen; Scambos, Ted; Tedesco, Marco; MacFerrin, Michael; Grigsby, Shane

    2016-01-01

    Supraglacial meltwater lakes on the western Greenland Ice Sheet (GrIS) are critical components of its surface hydrology and surface mass balance, and they also affect its ice dynamics. Estimates of lake volume, however, are limited by the availability of in situ measurements of water depth,which in turn also limits the assessment of remotely sensed lake depths. Given the logistical difficulty of collecting physical bathymetric measurements, methods relying upon in situ data are generally restricted to small areas and thus their application to largescale studies is difficult to validate. Here, we produce and validate spaceborne estimates of supraglacial lake volumes across a relatively large area (1250 km(exp 2) of west Greenland's ablation region using data acquired by the WorldView-2 (WV-2) sensor, making use of both its stereo-imaging capability and its meter-scale resolution. We employ spectrally-derived depth retrieval models, which are either based on absolute reflectance (single-channel model) or a ratio of spectral reflectances in two bands (dual-channel model). These models are calibrated by usingWV-2multispectral imagery acquired early in the melt season and depth measurements from a high resolutionWV-2 DEM over the same lake basins when devoid of water. The calibrated models are then validated with different lakes in the area, for which we determined depths. Lake depth estimates based on measurements recorded in WV-2's blue (450-510 nm), green (510-580 nm), and red (630-690 nm) bands and dual-channel modes (blue/green, blue/red, and green/red band combinations) had near-zero bias, an average root-mean-squared deviation of 0.4 m (relative to post-drainage DEMs), and an average volumetric error of b1%. The approach outlined in this study - image-based calibration of depth-retrieval models - significantly improves spaceborne supraglacial bathymetry retrievals, which are completely independent from in situ measurements.

  9. Derivation and Validation of Supraglacial Lake Volumes on the Greenland Ice Sheet from High-Resolution Satellite Imagery

    Science.gov (United States)

    Moussavi, Mahsa S.; Abdalati, Waleed; Pope, Allen; Scambos, Ted; Tedesco, Marco; MacFerrin, Michael; Grigsby, Shane

    2016-01-01

    Supraglacial meltwater lakes on the western Greenland Ice Sheet (GrIS) are critical components of its surface hydrology and surface mass balance, and they also affect its ice dynamics. Estimates of lake volume, however, are limited by the availability of in situ measurements of water depth,which in turn also limits the assessment of remotely sensed lake depths. Given the logistical difficulty of collecting physical bathymetric measurements, methods relying upon in situ data are generally restricted to small areas and thus their application to largescale studies is difficult to validate. Here, we produce and validate spaceborne estimates of supraglacial lake volumes across a relatively large area (1250 km(exp 2) of west Greenland's ablation region using data acquired by the WorldView-2 (WV-2) sensor, making use of both its stereo-imaging capability and its meter-scale resolution. We employ spectrally-derived depth retrieval models, which are either based on absolute reflectance (single-channel model) or a ratio of spectral reflectances in two bands (dual-channel model). These models are calibrated by usingWV-2multispectral imagery acquired early in the melt season and depth measurements from a high resolutionWV-2 DEM over the same lake basins when devoid of water. The calibrated models are then validated with different lakes in the area, for which we determined depths. Lake depth estimates based on measurements recorded in WV-2's blue (450-510 nm), green (510-580 nm), and red (630-690 nm) bands and dual-channel modes (blue/green, blue/red, and green/red band combinations) had near-zero bias, an average root-mean-squared deviation of 0.4 m (relative to post-drainage DEMs), and an average volumetric error of b1%. The approach outlined in this study - image-based calibration of depth-retrieval models - significantly improves spaceborne supraglacial bathymetry retrievals, which are completely independent from in situ measurements.

  10. Combining structure-from-motion derived point clouds from satellites and unmanned aircraft systems images with ground-truth data to create high-resolution digital elevation models

    Science.gov (United States)

    Palaseanu, M.; Thatcher, C.; Danielson, J.; Gesch, D. B.; Poppenga, S.; Kottermair, M.; Jalandoni, A.; Carlson, E.

    2016-12-01

    Coastal topographic and bathymetric (topobathymetric) data with high spatial resolution (1-meter or better) and high vertical accuracy are needed to assess the vulnerability of Pacific Islands to climate change impacts, including sea level rise. According to the Intergovernmental Panel on Climate Change reports, low-lying atolls in the Pacific Ocean are extremely vulnerable to king tide events, storm surge, tsunamis, and sea-level rise. The lack of coastal topobathymetric data has been identified as a critical data gap for climate vulnerability and adaptation efforts in the Republic of the Marshall Islands (RMI). For Majuro Atoll, home to the largest city of RMI, the only elevation dataset currently available is the Shuttle Radar Topography Mission data which has a 30-meter spatial resolution and 16-meter vertical accuracy (expressed as linear error at 90%). To generate high-resolution digital elevation models (DEMs) in the RMI, elevation information and photographic imagery have been collected from field surveys using GNSS/total station and unmanned aerial vehicles for Structure-from-Motion (SfM) point cloud generation. Digital Globe WorldView II imagery was processed to create SfM point clouds to fill in gaps in the point cloud derived from the higher resolution UAS photos. The combined point cloud data is filtered and classified to bare-earth and georeferenced using the GNSS data acquired on roads and along survey transects perpendicular to the coast. A total station was used to collect elevation data under tree canopies where heavy vegetation cover blocked the view of GNSS satellites. A subset of the GPS / total station data was set aside for error assessment of the resulting DEM.

  11. Tidal inundation (“Rob”) investigation using time series of high resolution satellite image data and from institu measurements along northern coast of Java (Pantura)

    Science.gov (United States)

    Andreas, Heri; Usriyah; Zainal Abidin, Hasanuddin; Anggreni Sarsito, Dina

    2017-06-01

    Tidal inundation (in Javanese they call it “Rob”) is now becoming a well known phenomenon along northern coast of Java Indonesia (Pantura). The occurrence of tidal inundation was recognized at least in the early 2000 and even earlier. In the recent years the tidal inundation comes not only at a high tide but even at the regular tide in some area across Pantura. In fact in location such as Pondok Bali, north of Blanakan, north of Pekalongan, north of Semarang and north west of Demak, seems those areas are sinking to the sea through times. Sea level rise and land subsidence are considered as main factors deriving the occurrence of this tidal inundation. We were using time series of high resolution satellite image data and insitu data measurements to mapping the tidal inundation along northern coast of Java. All available data from google data satellite archives (year 2000- recent years) and any available sources being analyze together with field surveys tagging and also from media information. As a result we can see the tidal inundation are taking place in Tanggerang, Jakarta, Bekasi, Cilamaya, Pondok Bali, Blanakan, Indramayu, Cirebon, Brebes, Tegal, Pemalang, Pekalongan, Kendal, Semarang, Demak, Gresik, Surabaya, Sidoarjo and Pasuruan.

  12. A compact thermal infrared imaging radiometer with high spatial resolution and wide swath for a small satellite using a large format uncooled infrared focal plane array

    Science.gov (United States)

    Tatsumi, Kenji; Sakuma, Fumihiro; Kikuchi, Masakuni; Tanii, Jun; Kawanishi, Toneo; Ueno, Shinichi; Kuga, Hideki

    2014-10-01

    In this paper, we present a feasibility study for the potential of a high spatial resolution and wide swath thermal infrared (TIR) imaging radiometer for a small satellite using a large format uncooled infrared focal plane array (IR-FPA). The preliminary TIR imaging radiometer designs were performed. One is a panchromatic (mono-band) imaging radiometer (8-12μm) with a large format 2000 x 1000 pixels uncooled IR-FPA with a pixel pitch of 15 μm. The other is a multiband imaging radiometer (8.8μm, 10.8μm, 11.4μm). This radiometer is employed separate optics and detectors for each wave band. It is based on the use of a 640 x 480 pixels uncooled IR-FPA with a pixel pitch of 25 μm. The thermal time constant of an uncooled IR-FPA is approximately 10-16ms, and introduces a constraint to the satellite operation to achieve better signal-to-noise ratio, MTF and linearity performances. The study addressed both on-ground time-delayintegration binning and staring imaging solutions, although a staring imaging was preferred after trade-off. The staring imaging requires that the line of sight of the TIR imaging radiometer gazes at a target area during the acquisition time of the image, which can be obtained by rotating the satellite or a steering mirror around the pitch axis. The single band radiometer has been designed to yield a 30m ground sample distance over a 30km swath width from a satellite altitude of 500km. The radiometric performance, enhanced with staring imaging, is expected to yield a NETD less than 0.5K for a 300K ground scene. The multi-band radiometer has three spectral bands with spatial resolution of 50m and swath width of 24km. The radiometric performance is expected to yield a NETD less than 0.85K. We also showed some preliminary simulation results on volcano, desert/urban scenes, and wildfire.

  13. Mapping Above-Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions

    Directory of Open Access Journals (Sweden)

    Jiahui Han

    2017-03-01

    Full Text Available Oilseed rape (Brassica napus L. is one of the three most important oil crops in China, and is regarded as a drought-tolerant oilseed crop. However, it is commonly sensitive to waterlogging, which usually refers to an adverse environment that limits crop development. Moreover, crop growth and soil irrigation can be monitored at a regional level using remote sensing data. High spatial resolution optical satellite sensors are very useful to capture and resist unfavorable field conditions at the sub-field scale. In this study, four different optical sensors, i.e., Pleiades-1A, Worldview-2, Worldview-3, and SPOT-6, were used to estimate the dry above-ground biomass (AGB of oilseed rape and track the seasonal growth dynamics. In addition, three different soil water content field experiments were carried out at different oilseed rape growth stages from November 2014 to May 2015 in Northern Zhejiang province, China. As a significant indicator of crop productivity, AGB was measured during the seasonal growth stages of the oilseed rape at the experimental plots. Several representative vegetation indices (VIs obtained from multiple satellite sensors were compared with the simultaneously-collected oilseed rape AGB. Results showed that the estimation model using the normalized difference vegetation index (NDVI with a power regression model performed best through the seasonal growth dynamics, with the highest coefficient of determination (R2 = 0.77, the smallest root mean square error (RMSE = 104.64 g/m2, and the relative RMSE (rRMSE = 21%. It is concluded that the use of selected VIs and high spatial multiple satellite data can significantly estimate AGB during the winter oilseed rape growth stages, and can be applied to map the variability of winter oilseed rape at the sub-field level under different waterlogging conditions, which is very promising in the application of agricultural irrigation and precision agriculture.

  14. Using High Resolution Satellite Precipitation fields to Assess the Impacts of Climate Change on the Santa Cruz and San Pedro River Basins

    Science.gov (United States)

    Robles-Morua, A.; Vivoni, E.; Rivera-Fernandez, E. R.; Dominguez, F.; Meixner, T.

    2013-05-01

    Hydrologic modeling using high spatiotemporal resolution satellite precipitation products in the southwestern United States and northwest Mexico is important given the sparse nature of available rain gauges. In addition, the bimodal distribution of annual precipitation also presents a challenge as differential climate impacts during the winter and summer seasons are not currently well understood. In this work, we focus on hydrological comparisons using rainfall forcing from a satellite-based product, downscaled GCM precipitation estimates and available ground observations. The simulations are being conducted in the Santa Cruz and San Pedro river basins along the Arizona-Sonora border at high spatiotemporal resolutions (~100 m and ~1 hour). We use a distributed hydrologic model, known as the TIN-based Real-time Integrated Basin Simulator (tRIBS), to generate simulated hydrological fields under historical (1991-2000) and climate change (2031-2040) scenarios obtained from an application of the Weather Research and Forecast (WRF) model. Using the distributed model, we transform the meteorological scenarios at 10-km, hourly resolution into predictions of the annual water budget, seasonal land surface fluxes and individual hydrographs of flood and recharge events. We compare the model outputs and rainfall fields of the WRF products against the forcing from the North American Land Data Assimilation System (NLDAS) and available ground observations from the National Climatic Data Center (NCDC) and Arizona Meteorological Network (AZMET). For this contribution, we selected two full years in the historical period and in the future scenario that represent wet and dry conditions for each decade. Given the size of the two basins, we rely on a high performance computing platform and a parallel domain discretization with higher resolutions maintained at experimental catchments in each river basin. Model simulations utilize best-available data across the Arizona-Sonora border on

  15. A characterization of intermediate-scale spread F structure from four years of high-resolution C/NOFS satellite data

    Science.gov (United States)

    Rino, Charles L.; Carrano, Charles S.; Groves, Keith M.; Roddy, Patrick A.

    2016-06-01

    Power law spectra have been invoked to interpret equatorial scintillation data for decades. Published analyses of intensity and phase scintillation data typically report power law spectra of the form q-p with 2.4 power law components. Strong scatter simulations and recent theoretical results have shown that two-component power law spectra can reconcile simultaneous equatorial scintillation observations from VHF to S-Band. The Communication/Navigation Outage Forecasting System (C/NOFS) satellite Planar Langmuir Probe generated a multiyear high-resolution sampling of equatorial spread F, but published analyses to date have reported only single-component power laws over scales from tens of kilometers to 70 m. This paper summarizes the analysis of high-resolution C/NOFS data collected over the four year period 2011 to 2014. Following an earlier investigation of several months of C/NOFS data by the authors of this paper, the extended data set revealed a pattern of occurrence of two-component spectra in the most highly disturbed data sets. The results confirm a known inverse correlation between turbulent strength and spectral index. The new results are interpreted as an equatorial spread F life cycle pattern with two-component spectra in the early development phase giving way to single-component spectra in the decay phase.

  16. An object-based approach to delineate wetlands across landscapes of varied disturbance with high spatial resolution satellite imagery

    Science.gov (United States)

    Mui, Amy; He, Yuhong; Weng, Qihao

    2015-11-01

    Mapping wetlands across both natural and human-altered landscapes is important for the management of these ecosystems. Though they are considered important landscape elements providing both ecological and socioeconomic benefits, accurate wetland inventories do not exist in many areas. In this study, a multi-scale geographic object-based image analysis (GEOBIA) approach was employed to segment three high spatial resolution images acquired over landscapes of varying heterogeneity due to human-disturbance to determine the robustness of this method to changing scene variability. Multispectral layers, a digital elevation layer, normalized-difference vegetation index (NDVI) layer, and a first-order texture layer were used to segment images across three segmentation scales with a focus on accurate delineation of wetland boundaries and wetland components. Each ancillary input layer contributed to improving segmentation at different scales. Wetlands were classified using a nearest neighbor approach across a relatively undisturbed park site and an agricultural site using GeoEye1 imagery, and an urban site using WorldView2 data. Successful wetland classification was achieved across all study sites with an accuracy above 80%, though results suggest that overall a higher degree of landscape heterogeneity may negatively affect both segmentation and classification. The agricultural site suffered from the greatest amount of over and under segmentation, and lowest map accuracy (kappa: 0.78) which was partially attributed to confusion among a greater proportion of mixed vegetated classes from both wetlands and uplands. Accuracy of individual wetland classes based on the Canadian Wetland Classification system varied between each site, with kappa values ranging from 0.64 for the swamp class and 0.89 for the marsh class. This research developed a unique approach to mapping wetlands of various degrees of disturbance using GEOBIA, which can be applied to study other wetlands of similar

  17. Multitemporal High-Resolution Satellite Images for the Study and Monitoring of an Ancient Mesopotamian City and its Surrounding Landscape: The Case of Ur

    Directory of Open Access Journals (Sweden)

    Giacomo Di Giacomo

    2012-01-01

    Full Text Available The paper concerns the use of multitemporal high-resolution satellite images for the study of the ancient city of Ur, in southern Mesopotamia, inaccessible to scholars from 2003. The acquired dataset is composed by two Gambit KH-7 (1966 and one Corona KH-4B (1968 declassified spy space photos and by few images taken by the recent satellites for civilian use QuickBird-2 (2002, 2004, 2007, Ikonos-2 (2008, and WorldView-1 (2008. The processing of all these images and the integration with ASTER and SRTM DEMs allowed the acquisition of new data about the topographical layout of the city and its monuments and ancient roads; the georeferencing of all archaeological remains and traces visible on the images allowed the upgrade of the archaeological map of Ur. The research also provided important data concerning the reconstruction of the surrounding landscape, where a lot of traces of old channels and riverbeds of the Euphrates were identified in areas much modified and altered during the last decades by urbanization and agricultural works. Moreover, the multitemporal images allowed the monitoring of the conservation of the archaeological area, particularly before and after second Gulf War.

  18. CLASSIFIER FUSION OF HIGH-RESOLUTION OPTICAL AND SYNTHETIC APERTURE RADAR (SAR SATELLITE IMAGERY FOR CLASSIFICATION IN URBAN AREA

    Directory of Open Access Journals (Sweden)

    T. Alipour Fard

    2014-10-01

    Full Text Available This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular application. In this paper, two category of features are generate and six classifier fusion operators implemented and evaluated. Implementation results show significant improvement in the classification accuracy.

  19. A high-resolution global inventory of fossil fuel CO2 emission derived using a global power plant database and satellite-observed nightlight data

    Science.gov (United States)

    Oda, Tomohiro; Maksyutov, Shamil

    2010-05-01

    We developed the Open-source Data Inventory of Anthropogenic CO2 emissions (ODIAC), a global high-resolution fossil fuel CO2 emission inventory for the years 1980-2007, by applying a combination of country-level fuel consumption statistics, a global point source database, and satellite-observed nightlight data. The primary goal of ODIAC is to provide a-priori information of fossil fuel CO2 emission to the flux inversions using observational data of the Japanese Greenhouse Gas Observing Satellite (GOSAT). Fossil fuel CO2 emissions are a critical quantity required by the established flux inversion framework, as it is assumed to be a known quantity. Recent studies have suggested the feasibility of regional flux inversions using satellite-observed CO2 beyond the established global inversion, and thus spatiotemporally detailed information of fossil fuel CO2 emissions will be needed for emerging regional flux inversions. National emissions are often available in the gridded form, and the disaggregation of national emissions have been done using a common surrogate such as population and nightlight data; however, these approaches correlate poorly with sources at a resolution beyond country and city level. In this study, national total emissions were derived from country-level fuel consumption statistics and emissions from point sources were separately calculated. We utilized point source emission and geographic location data available in the global power plant database CARMA (Carbon Monitoring and Action). The individual point source emissions were placed at the exact locations specified by CARMA. Emissions from other sources, the residual of national total emissions minus point source emissions, were distributed using nightlight data obtained by the US Air Force Defense Meteorological Satellite Project-Operational Line Scan (DMSP-OSL) instruments. As DMSP-OSL instruments often meet instrumental saturation over bright regions such as city cores, the single use of normal

  20. Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST Using an Ensemble Kalman Filter

    Directory of Open Access Journals (Sweden)

    Takuji Waseda

    2013-06-01

    Full Text Available We develop an assimilation method of high horizontal resolution sea surface temperature data, provided from the Moderate Resolution Imaging Spectroradiometer (MODIS-SST sensors boarded on the Aqua and Terra satellites operated by National Aeronautics and Space Administration (NASA, focusing on the reproducibility of the Kuroshio front variations south of Japan in February 2010. Major concerns associated with the development are (1 negative temperature bias due to the cloud effects, and (2 the representation of error covariance for detection of highly variable phenomena. We treat them by utilizing an advanced data assimilation method allowing use of spatiotemporally varying error covariance: the Local Ensemble Transformation Kalman Filter (LETKF. It is found that the quality control, by comparing the model forecast variable with the MODIS-SST data, is useful to remove the negative temperature bias and results in the mean negative bias within −0.4 °C. The additional assimilation of MODIS-SST enhances spatial variability of analysis SST over 50 km to 25 km scales. The ensemble spread variance is effectively utilized for excluding the erroneous temperature data from the assimilation process.

  1. Discrete Topology Based Hierarchical Segmentation for Efficient Object-Based Image Analyis: Application to Object Detection in High Resolution Satellite Images

    Science.gov (United States)

    Syed, A. H.; Saber, E.; Messinger, D.

    2013-05-01

    With rapid developments in satellite and sensor technologies, there has been a dramatic increase in the availability of high resolution (HR) remotely sensed images. Hence, the ability to collect images remotely is expected to far exceed our capacity to analyse these images manually. Consequently, techniques that can handle large volumes of data are urgently needed. In many of today's multiscale techniques the underlying representation of objects is still pixel-based, i.e. object entities are still described/accessed via pixelbased descriptors, thereby creating a bottleneck when processing large volumes of data. Also, these techniques do not yet leverage the topological and contextual information present in the image. We propose a framework for Discrete Topology based hierarchical segmentation, addressing both the algorithms and data structures that will be required. The framework consists of three components: 1) Conversion to dart-based representation, 2) Size-Constrained-Region Merging to generate multiple segmentations, and 3) Update of two sparse arrays SIGMA and LAMBDA which together encode the topology of each region in the hierarchy. The results of our representation are demonstrated both on a synthetic and a real high resolution images. Application of this representation to objectdetection is also discussed.

  2. Roof Type Selection Based on Patch-Based Classification Using Deep Learning for High Resolution Satellite Imagery

    Science.gov (United States)

    Partovi, T.; Fraundorfer, F.; Azimi, S.; Marmanis, D.; Reinartz, P.

    2017-05-01

    3D building reconstruction from remote sensing image data from satellites is still an active research topic and very valuable for 3D city modelling. The roof model is the most important component to reconstruct the Level of Details 2 (LoD2) for a building in 3D modelling. While the general solution for roof modelling relies on the detailed cues (such as lines, corners and planes) extracted from a Digital Surface Model (DSM), the correct detection of the roof type and its modelling can fail due to low quality of the DSM generated by dense stereo matching. To reduce dependencies of roof modelling on DSMs, the pansharpened satellite images as a rich resource of information are used in addition. In this paper, two strategies are employed for roof type classification. In the first one, building roof types are classified in a state-of-the-art supervised pre-trained convolutional neural network (CNN) framework. In the second strategy, deep features from deep layers of different pre-trained CNN model are extracted and then an RBF kernel using SVM is employed to classify the building roof type. Based on roof complexity of the scene, a roof library including seven types of roofs is defined. A new semi-automatic method is proposed to generate training and test patches of each roof type in the library. Using the pre-trained CNN model does not only decrease the computation time for training significantly but also increases the classification accuracy.

  3. A stochastic ensemble-based model to predict crop water requirements from numerical weather forecasts and VIS-NIR high resolution satellite images in Southern Italy

    Science.gov (United States)

    Pelosi, Anna; Falanga Bolognesi, Salvatore; De Michele, Carlo; Medina Gonzalez, Hanoi; Villani, Paolo; D'Urso, Guido; Battista Chirico, Giovanni

    2015-04-01

    Irrigation agriculture is one the biggest consumer of water in Europe, especially in southern regions, where it accounts for up to 70% of the total water consumption. The EU Common Agricultural Policy, combined with the Water Framework Directive, imposes to farmers and irrigation managers a substantial increase of the efficiency in the use of water in agriculture for the next decade. Ensemble numerical weather predictions can be valuable data for developing operational advisory irrigation services. We propose a stochastic ensemble-based model providing spatial and temporal estimates of crop water requirements, implemented within an advisory service offering detailed maps of irrigation water requirements and crop water consumption estimates, to be used by water irrigation managers and farmers. The stochastic model combines estimates of crop potential evapotranspiration retrieved from ensemble numerical weather forecasts (COSMO-LEPS, 16 members, 7 km resolution) and canopy parameters (LAI, albedo, fractional vegetation cover) derived from high resolution satellite images in the visible and near infrared wavelengths. The service provides users with daily estimates of crop water requirements for lead times up to five days. The temporal evolution of the crop potential evapotranspiration is simulated with autoregressive models. An ensemble Kalman filter is employed for updating model states by assimilating both ground based meteorological variables (where available) and numerical weather forecasts. The model has been applied in Campania region (Southern Italy), where a satellite assisted irrigation advisory service has been operating since 2006. This work presents the results of the system performance for one year of experimental service. The results suggest that the proposed model can be an effective support for a sustainable use and management of irrigation water, under conditions of water scarcity and drought. Since the evapotranspiration term represents a staple

  4. Utilization of high resolution satellite geoid data for estimation of lithospheric thickness in the Bay of Bengal

    Digital Repository Service at National Institute of Oceanography (India)

    Majumdar, T.J.; Bhattacharyya, R.; Chatterjee, S.; Krishna, K.S.

    height anomalies have been analyzed across the Ninetyeast and 85 degrees E Ridges within the Bay of Bengal. Present data sets are more accurate and detailed (off-track resolution: about 3.33 km and grid size: about 3.5 km). Observed geoid height - age...

  5. Estimating Invasion Success by Non-Native Trees in a National Park Combining WorldView-2 Very High Resolution Satellite Data and Species Distribution Models

    Directory of Open Access Journals (Sweden)

    Antonio T. Monteiro

    2017-01-01

    Full Text Available Invasion by non-native tree species is an environmental and societal challenge requiring predictive tools to assess invasion dynamics. The frequent scale mismatch between such tools and on-ground conservation is currently limiting invasion management. This study aimed to reduce these scale mismatches, assess the success of non-native tree invasion and determine the environmental factors associated to it. A hierarchical scaling approach combining species distribution models (SDMs and satellite mapping at very high resolution (VHR was developed to assess invasion by Acacia dealbata in Peneda-Gerês National Park, the only national park in Portugal. SDMs were first used to predict the climatically suitable areas for A. dealdata and satellite mapping with the random-forests classifier was then applied to WorldView-2 very-high resolution imagery to determine whether A. dealdata had actually colonized the predicted areas (invasion success. Environmental attributes (topographic, disturbance and canopy-related differing between invaded and non-invaded vegetated areas were then analyzed. The SDM results indicated that most (67% of the study area was climatically suitable for A. dealbata invasion. The onset of invasion was documented to 1905 and satellite mapping highlighted that 12.6% of study area was colonized. However, this species had only colonized 62.5% of the maximum potential range, although was registered within 55.6% of grid cells that were considerable unsuitable. Across these areas, the specific success rate of invasion was mostly below 40%, indicating that A. dealbata invasion was not dominant and effective management may still be possible. Environmental attributes related to topography (slope, canopy (normalized difference vegetation index (ndvi, land surface albedo and disturbance (historical burnt area differed between invaded and non-invaded vegetated area, suggesting that landscape attributes may alter at specific locations with Acacia

  6. Extracting Soil Water Holding Capacity Parameters of a Distributed Agro-Hydrological Model from High Resolution Optical Satellite Observations Series

    Directory of Open Access Journals (Sweden)

    Sylvain Ferrant

    2016-02-01

    Full Text Available Sentinel-2 (S2 earth observation satellite mission, launched in 2015, is foreseen to promote within-field decisions in Precision Agriculture (PA for both: (1 optimizing crop production; and (2 regulating environmental impacts. In this second scope, a set of Leaf Area Index (LAI derived from S2 type time-series (2006–2010, using Formosat-2 satellite is used to spatially constrain the within-field crop growth and the related nitrogen contamination of surface water simulated at a small experimental catchment scale with the distributed agro-hydrological model Topography Nitrogen Transfer and Transformation (TNT2. The Soil Water Holding Capacity (SWHC, represented by two parameters, soil depth and retention porosity, is used to fit the yearly maximum of LAI (LAX at each pixel of the satellite image. Possible combinations of soil parameters, defining 154 realistic SWHC found on the study site are used to force spatially homogeneous SWHC. LAX simulated at the pixel level for the 154 SWHC, for each of the five years of the study period, are recorded and hereafter referred to as synthetic LAX. Optimal SWHCyear_I,pixel_j, corresponding to minimal difference between observed and synthetic LAXyear_I,pixel_j, is selected for each pixel, independent of the value at neighboring pixels. Each re-estimated soil maps are used to re-simulate LAXyear_I. Results show that simulated and synthetic LAXyear_I,allpixels obtained from SWHCyear_I,allpixels are close and accurately fit the observed LAXyear_I,allpixels (RMSE = 0.05 m2/m2 to 0.2 and R2 = 0.99 to 0.94, except for the year 2008 (RMSE = 0.8 m2/m2 and R2 = 0.8. These results show that optimal SWHC can be derived from remote sensing series for one year. Unique SWHC solutions for each pixel that limit the LAX error for the five years to less than 0.2 m2/m2 are found for only 10% of the pixels. Selection of unique soil parameters using multi-year LAX and neighborhood solution is expected to deliver more robust soil

  7. A co-training, mutual learning approach towards mapping snow cover from multi-temporal high-spatial resolution satellite imagery

    Science.gov (United States)

    Zhu, Liujun; Xiao, Pengfeng; Feng, Xuezhi; Zhang, Xueliang; Huang, Yinyou; Li, Chengxi

    2016-12-01

    High-spatial and -temporal resolution snow cover maps for mountain areas are needed for hydrological applications and snow hazard monitoring. The Chinese GF-1 satellite is potential to provide such information with a spatial resolution of 8 m and a revisit of 4 days. The main challenge for the extraction of multi-temporal snow cover from high-spatial resolution images is that the observed spectral signature of snow and snow-free areas is non-stationary in both spatial and temporal domains. As a result, successful extraction requires adequate labelled samples for each image, which is difficult to be achieved. To solve this problem, a semi-supervised multi-temporal classification method for snow cover extraction (MSCE) is proposed. This method extends the co-training based algorithms from single image classification to multi-temporal ones. Multi-temporal images in MSCE are treated as different descriptions of the same land surface, and consequently, each pixel has multiple sets of features. Independent classifiers are trained on each feature set using a few labelled samples, and then, they are iteratively re-trained in a mutual learning way using a great number of unlabelled samples. The main principle behind MSCE is that the multi-temporal difference of land surface in spectral space can be the source of mutual learning inspired by the co-training paradigm, providing a new strategy to deal with multi-temporal image classification. The experimental findings of multi-temporal GF-1 images confirm the effectiveness of the proposed method.

  8. Detecting Rock Glacier Dynamics in Southern Carpathians Mountains Using High-Resolution Optical and Multi-Temporal SAR Satellite Imagery .....

    Science.gov (United States)

    Necsoiu, M.; Onaca, A.

    2015-12-01

    This research provided the first documented assessment of the dynamics of rock glaciers in Southern Carpathian Mountains over almost half a century (1968-2014). The dynamics of four representative rock glaciers were assessed using complementary satellite-based optical and radar remote sensing techniques. We investigated the dynamics of the area using co-rectification of paired optical satellite datasets acquired by SPOT5, WV-1, Pléiades, and Corona to estimate short term (7 years) and longer term changes (44 years). Accurately rectifying and co-registering Corona KH-4B imagery allowed us to expand the time horizon over which changes in this alpine environment could be analyzed. The displacements revealed by this analysis correlate with variations in local slope of the rock glaciers, and presence or absence of permafrost. For radar analysis, nine ascending ALOS-1 PALSAR images were used based clear sky and absence of snow groundcover (i.e. June-October). Although decorrelation limits the ability to perform quantitative InSAR analyses, loss of coherence was useful in detecting subtle changes in active rock glacier environments, as well as other mass movements including rock falls, rock avalanches, debris flows, creep of permafrost, and solifluction. Small Baseline Subset (SBAS) InSAR analysis successfully quantified rates of change for unstable areas. The results of this investigation, although based on limited archived imagery, demonstrate that correlation analysis, coherence analysis, and multitemporal InSAR techniques can yield useful information for detecting creeping permafrost in a complex mountain environment, such as Retezat Mountains. Our analyses showed that rock glaciers in the Southern Carpathian Mountains are experiencing very slow annual movement of only a few cm per year. Results of the remote sensing analyses are consistent with field observations of permafrost occurrence at these sites (for more, please see Abstract ID# 68413). The combined optical

  9. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  10. GHRSST Level 3P Global Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 3 Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A platform...

  11. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  12. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  13. Automatic Classification of High Resolution Satellite Imagery - a Case Study for Urban Areas in the Kingdom of Saudi Arabia

    Science.gov (United States)

    Maas, A.; Alrajhi, M.; Alobeid, A.; Heipke, C.

    2017-05-01

    Updating topographic geospatial databases is often performed based on current remotely sensed images. To automatically extract the object information (labels) from the images, supervised classifiers are being employed. Decisions to be taken in this process concern the definition of the classes which should be recognised, the features to describe each class and the training data necessary in the learning part of classification. With a view to large scale topographic databases for fast developing urban areas in the Kingdom of Saudi Arabia we conducted a case study, which investigated the following two questions: (a) which set of features is best suitable for the classification?; (b) what is the added value of height information, e.g. derived from stereo imagery? Using stereoscopic GeoEye and Ikonos satellite data we investigate these two questions based on our research on label tolerant classification using logistic regression and partly incorrect training data. We show that in between five and ten features can be recommended to obtain a stable solution, that height information consistently yields an improved overall classification accuracy of about 5%, and that label noise can be successfully modelled and thus only marginally influences the classification results.

  14. Automatic urban debris zone extraction from post-hurricane very high-resolution satellite and aerial imagery

    Directory of Open Access Journals (Sweden)

    Shasha Jiang

    2016-05-01

    Full Text Available Automated remote sensing methods have not gained widespread usage for damage assessment after hurricane events, especially for low-rise buildings, such as individual houses and small businesses. Hurricane wind, storm surge with waves, and inland flooding have unique damage signatures, further complicating the development of robust automated assessment methodologies. As a step toward realizing automated damage assessment for multi-hazard hurricane events, this paper presents a mono-temporal image classification methodology that quickly and accurately differentiates urban debris from non-debris areas using post-event images. Three classification approaches are presented: spectral, textural, and combined spectral–textural. The methodology is demonstrated for Gulfport, Mississippi, using IKONOS panchromatic satellite and NOAA aerial colour imagery collected after 2005 Hurricane Katrina. The results show that multivariate texture information significantly improves debris class detection performance by decreasing the confusion between debris and other land cover types, and the extracted debris zone accurately captures debris distribution. Additionally, the extracted debris boundary is approximately equivalent regardless of imagery type, demonstrating the flexibility and robustness of the debris mapping methodology. While the test case presents results for hurricane hazards, the proposed methodology is generally developed and expected to be effective in delineating debris zones for other natural hazards, including tsunamis, tornadoes, and earthquakes.

  15. Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes

    CERN Document Server

    Arellano-Baeza, A A; 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. "The Lineament Extraction and Stripes Statistic Analysis" (LESSA) software package, developed by Zlatopolsy (1992, 1997). We assume that the lineaments allow to detect, at least partially, the presence ruptures in the Earths crust, and therefore enable one to follow the changes in the system of faults and fractures associated with strong earthquakes. We analysed 6 earthquakes occurred in the Pacific coast of the South America and XXX with the Richter scale magnitude >4.5. They were located in the regions with small season...

  16. The high resolution topographic evolution of an active retrogressive thaw slump compiled from a decade of photography, ground surveys, laser scans and satellite imagery

    Science.gov (United States)

    Crosby, B. T.; Barnhart, T. B.; Rowland, J. C.

    2015-12-01

    Remote sensing imagery has enables the temporal reconstruction of thermal erosion features including lakes, shorelines and hillslope failures in remote Arctic locations, yet these planar data limit analysis to lines and areas. This study explores the application of varying techniques to reconstruct the three dimensional evolution of a single thermal erosion feature using a mixture of opportunistic oblique photos, ground surveys and satellite imagery. At the Selawik River retrogressive thaw slump in northwest Alaska, a bush plane collected oblique aerial photos when the feature was first discovered in 2004 and in subsequent years. These images were recently processed via Structure from Motion to generate georeferenced point clouds for the years prior to the initiation of our research. High resolution ground surveys in 2007, 2009 and 2010 were completed using robotic total station. Terrestrial laser scans (TLS) were collected in the summers of 2011 and 2012. Analysis of stereo satellite imagery from 2012 and 2015 enable continued monitoring of the feature after ground campaigns ended. As accurate coregistraion between point clouds is vital to topographic change detection, all prior and subsequent datasets were georeferenced to stable features observed in the 2012 TLS scan. Though this coregistration introduces uncertainty into each image, the magnitudes of uncertainty are significantly smaller than the topographic changes detected. Upslope retreat of the slump headwall generally decreases over time as the slump floor progresses from a highly dissected gully topography to a low relief, earthflow dominated depositional plane. The decreasing slope of the slump floor diminishes transport capacity, resulting in the progressive burial of the slump headwall, thus decreasing headwall retreat rates. This self-regulation of slump size based on feature relief and transport capacity suggests a capacity to predict the maximum size a given feature can expand to before

  17. Potential of high resolution satellite imagery, remote weather data and 1D hydraulic modeling to evaluate flood areas in Gonaives, Haiti

    Science.gov (United States)

    Bozza, Andrea; Durand, Arnaud; Allenbach, Bernard; Confortola, Gabriele; Bocchiola, Daniele

    2013-04-01

    We present a feasibility study to explore potential of high-resolution imagery, coupled with hydraulic flood modeling to predict flooding risks, applied to the case study of Gonaives basins (585 km²), Haiti. We propose a methodology working at different scales, providing accurate results and a faster intervention during extreme flood events. The 'Hispaniola' island, in the Caribbean tropical zone, is often affected by extreme floods events. Floods are caused by tropical springs and hurricanes, and may lead to several damages, including cholera epidemics, as recently occurred, in the wake of the earthquake upon January 12th 2010 (magnitude 7.0). Floods studies based upon hydrological and hydraulic modeling are hampered by almost complete lack of ground data. Thenceforth, and given the noticeable cost involved in the organization of field measurement campaigns, the need for exploitation of remote sensing images data. HEC-RAS 1D modeling is carried out under different scenarios of available Digital Elevation Models. The DEMs are generated using optical remote sensing satellite (WorldView-1) and SRTM, combined with information from an open source database (Open Street Map). We study two recent flood episodes, where flood maps from remote sensing were available. Flood extent and land use have been assessed by way of data from SPOT-5 satellite, after hurricane Jeanne in 2004 and hurricane Hanna in 2008. A semi-distributed, DEM based hydrological model is used to simulate flood flows during the hurricanes. Precipitation input is taken from daily rainfall data derived from TRMM satellite, plus proper downscaling. The hydraulic model is calibrated using floodplain friction as tuning parameters against the observed flooded area. We compare different scenarios of flood simulation, and the predictive power of model calibration. The method provide acceptable results in depicting flooded areas, especially considering the tremendous lack of ground data, and show the potential of

  18. Measurement-based perturbation theory and differential equation parameter estimation for high-precision high-resolution reconstruction of the Earth's gravitational field from satellite tracking measurements

    CERN Document Server

    Xu, Peiliang

    2016-01-01

    The numerical integration method has been routinely used to produce global standard gravitational models from satellite tracking measurements of CHAMP/GRACE types. It is implemented by solving the differential equations of the partial derivatives of a satellite orbit with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical point of view, satellite gravimetry from satellite tracking is the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in satellite gravimetry and statistics, is groundless. We use three different methods to derive new local solutions to the Newton's nonlinear governing differential equations of motion with a nominal reference orbit. Bearing in mind that satellite orbits ...

  19. THE OLKHON GEODYNAMIC PROVING GROUND (LAKE BAIKAL: HIGH RESOLUTION SATELLITE DATA AND GEOLOGICAL MAPS OF NEW GENERATION

    Directory of Open Access Journals (Sweden)

    Valentin S. Fedorovsky

    2015-09-01

    Full Text Available The Olkhon region of the Western Pribaikalie is highly attractive for geologists due to the presence of diverse metamorphic complexes and highly complicated combinations of folded structures in this region. The Olkhon region is located within the area of the Pribaikalsky National Park of Russia. At abundant outcrops in the subject area, various geological aspects resulting from the Early Palaeozoic collision system can be studied in detail. By its parameters, the subject area can be considered a «geodynamic proving ground». In recent years, abundant aerospace materials on the area have been accumulated, and long-term field studies resulted in many discoveries and findings which encourage critical revision of the initial conceptions. The material available allows compilation of a new package of geological maps in hard and electronic versions.

  20. 10 Yr Spatial and Temporal Trends of PM2.5 Concentrations in the Southeastern US Estimated Using High-resolution Satellite Data

    Science.gov (United States)

    Hu, X.; Waller, L. A.; Lyapustin, A.; Wang, Y.; Liu, Y.

    2013-01-01

    Long-term PM2.5 exposure has been reported to be associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of the true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of spatiotemporally continuous distribution of PM2.5 concentrations are essential. Satellite-retrieved aerosol optical depth (AOD) has been widely used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, an inherent disadvantage of current AOD products is their coarse spatial resolutions. For instance, the spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) are 10 km and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5-AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US, centered at the Atlanta Metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted for each year individually, and we obtained model fitting R2 ranging from 0.71 to 0.85, MPE from 1.73 to 2.50 g m3, and RMSPE from 2.75 to 4.10 g m3. In addition, we found cross validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 g m3, and RMSPE from 3.12 to 5.00 g m3, indicating a good agreement between the estimated and observed values. Spatial trends show that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. A time series analysis was conducted to examine temporal trends of PM2.5 concentrations in the study area from 2001 to 2010. The results showed

  1. Toward a High-Resolution Monitoring of Continental Surface Water Extent and Dynamics, at Global Scale: from GIEMS (Global Inundation Extent from Multi-Satellites) to SWOT (Surface Water Ocean Topography)

    Science.gov (United States)

    Prigent, Catherine; Lettenmaier, Dennis P.; Aires, Filipe; Papa, Fabrice

    2016-03-01

    Up to now, high-resolution mapping of surface water extent from satellites has only been available for a few regions, over limited time periods. The extension of the temporal and spatial coverage was difficult, due to the limitation of the remote sensing technique [e.g., the interaction of the radiation with vegetation or cloud for visible observations or the temporal sampling with the synthetic aperture radar (SAR)]. The advantages and the limitations of the various satellite techniques are reviewed. The need to have a global and consistent estimate of the water surfaces over long time periods triggered the development of a multi-satellite methodology to obtain consistent surface water all over the globe, regardless of the environments. The Global Inundation Extent from Multi-satellites (GIEMS) combines the complementary strengths of satellite observations from the visible to the microwave, to produce a low-resolution monthly dataset (0.25^circ × 0.25^circ) of surface water extent and dynamics. Downscaling algorithms are now developed and applied to GIEMS, using high-spatial-resolution information from visible, near-infrared, and synthetic aperture radar (SAR) satellite images, or from digital elevation models. Preliminary products are available down to 500-m spatial resolution. This work bridges the gaps and prepares for the future NASA/CNES Surface Water Ocean Topography (SWOT) mission to be launched in 2020. SWOT will delineate surface water extent estimates and their water storage with an unprecedented spatial resolution and accuracy, thanks to a SAR in an interferometry mode. When available, the SWOT data will be adopted to downscale GIEMS, to produce a long time series of water surfaces at global scale, consistent with the SWOT observations.

  2. Land cover trajectory in the Caatinga biome: analysing trends, drivers and consequences with high resolution satellite time series in Paraiba, Brazil

    Science.gov (United States)

    Rufino, Iana; Cunha, John; Carlos, Galvão; Nailson, Silva

    2017-04-01

    The Caatinga Biome is a unique Earth ecosystem with only 1% of conserved and protected areas (Oliveira et al, 2012). Human activities pressures high threaten Caatinga Biodiversity. Along the last decades, native green areas are changed by crops, livestock or those areas are reached by urban areas (Oliveira et al 2012; Fiaschi e Pianni, 2009; Sivakumar, 2007; Castelleti et al, 2004; Pereira et al, 2013; le Polain de Waroux & Lambin, 2012; Apgaua et al, 2013). Precipitation rates have high variability in space and time. High temperatures with small inter annual variability drives evapotranspiration up and turns the water scarcity the main challenge for sustainable life in rural areas. Sánchez-Azofeifa et al., (2005) try establishing research priorities for tropical dry forests and they recommend Scientific Community to focus on ecology and social aspects and possibilities of remote sensing techniques in those studies. Specific algorithms to produce estimates of energy balance and evapotranspiration of water to the atmosphere can process satellite images derived from several sensors. These estimates, combined with the analysis of historical time-series, allow the detection of changes in the terrestrial plant systems and can be used to discriminate the influences from human occupation and those from climate variability and/or change on energy fluxes and land cover. The algorithms have to be calibrated and validated using ground-based data. Thus, a large multiple source set of satellite and ground data has to be processed and comparatively analyzed. However, the high computational cost for image processing introduce further processing challenges. In order to face those challenges, this research explores the possibilities of using these medium resolution remote sensing products (30 meters), presenting a multitemporal long term analysis (24 months) to identify the land trajectory of one Semi-arid area (pilot) in the Caatinga biome. All processing steps use the

  3. Measurement of Surface Displacement and Deformation of Mass Movements Using Least Squares Matching of Repeat High Resolution Satellite and Aerial Images

    Directory of Open Access Journals (Sweden)

    Misganu Debella-Gilo

    2012-01-01

    Full Text Available Displacement and deformation are fundamental measures of Earth surface mass movements such as glacier flow, rockglacier creep and rockslides. Ground-based methods of monitoring such mass movements can be costly, time consuming and limited in spatial and temporal coverage. Remote sensing techniques, here matching of repeat optical images, are increasingly used to obtain displacement and deformation fields. Strain rates are usually computed in a post-processing step based on the gradients of the measured velocity field. This study explores the potential of automatically and directly computing velocity, rotation and strain rates on Earth surface mass movements simultaneously from the matching positions and the parameters of the geometric transformation models using the least squares matching (LSM approach. The procedures are exemplified using bi-temporal high resolution satellite and aerial images of glacier flow, rockglacier creep and land sliding. The results show that LSM matches the images and computes longitudinal strain rates, transverse strain rates and shear strain rates reliably with mean absolute deviations in the order of 10−4 (one level of significance below the measured values as evaluated on stable grounds. The LSM also improves the accuracy of displacement estimation of the pixel-precision normalized cross-correlation by over 90% under ideal (simulated circumstances and by about 25% for real multi-temporal images of mass movements.

  4. High spatial resolution radiation budget for Europe: derived from satellite data, validation of a regional model; Raeumlich hochaufgeloeste Strahlungsbilanz ueber Europa: Ableitung aus Satellitendaten, Validation eines regionalen Modells

    Energy Technology Data Exchange (ETDEWEB)

    Hollmann, R. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Atmosphaerenphysik

    2000-07-01

    Since forty years instruments onboard satellites have been demonstrated their usefulness for many applications in the field of meteorology and oceanography. Several experiments, like ERBE, are dedicated to establish a climatology of the global Earth radiation budget at the top of the atmosphere. Now the focus has been changed to the regional scale, e.g. GEWEX with its regional sub-experiments like BALTEX. To obtain a regional radiation budget for Europe in the first part of the work the well calibrated measurements from ScaRaB (scanner for radiation budget) are used to derive a narrow-to-broadband conversion, which is applicable to the AVHRR (advanced very high resolution radiometer). It is shown, that the accuracy of the method is in the order of that from SCaRaB itself. In the second part of the work, results of REMO have been compared with measurements of ScaRaB and AVHRR for March 1994. The model reproduces the measurements overall well, but it is overestimating the cold areas and underestimating the warm areas in the longwave spectral domain. Similarly it is overestimating the dark areas and underestimating the bright areas in the solar spectral domain. (orig.)

  5. Investigating Within-Field Variability of Rice from High Resolution Satellite Imagery in Qixing Farm County, Northeast China

    Directory of Open Access Journals (Sweden)

    Quanying Zhao

    2015-02-01

    Full Text Available Rice is a primary staple food for the world population and there is a strong need to map its cultivation area and monitor its crop status on regional scales. This study was conducted in the Qixing Farm County of the Sanjiang Plain, Northeast China. First, the rice cultivation areas were identified by integrating the remote sensing (RS classification maps from three dates and the Geographic Information System (GIS data obtained from a local agency. Specifically, three FORMOSAT-2 (FS-2 images captured during the growing season in 2009 and a GIS topographic map were combined using a knowledge-based classification method. A highly accurate classification map (overall accuracy = 91.6% was generated based on this Multi-Data-Approach (MDA. Secondly, measured agronomic variables that include biomass, leaf area index (LAI, plant nitrogen (N concentration and plant N uptake were correlated with the date-specific FS-2 image spectra using stepwise multiple linear regression models. The best model validation results with a relative error (RE of 8.9% were found in the biomass regression model at the phenological stage of heading. The best index of agreement (IA value of 0.85 with an RE of 13.6% was found in the LAI model, also at the heading stage. For plant N uptake estimation, the most accurate model was again achieved at the heading stage with an RE of 11% and an IA value of 0.77; however, for plant N concentration estimation, the model performance was best at the booting stage. Finally, the regression models were applied to the identified rice areas to map the within-field variability of the four agronomic variables at different growth stages for the Qixing Farm County. The results provide detailed spatial information on the within-field variability on a regional scale, which is critical for effective field management in precision agriculture.

  6. Development of high accuracy and resolution geoid and gravity maps

    Science.gov (United States)

    Gaposchkin, E. M.

    1986-01-01

    Precision satellite to satellite tracking can be used to obtain high precision and resolution maps of the geoid. A method is demonstrated to use data in a limited region to map the geopotential at the satellite altitude. An inverse method is used to downward continue the potential to the Earth surface. The method is designed for both satellites in the same low orbit.

  7. Satellite-derived high resolution PM2.5 concentrations in Yangtze River Delta Region of China using improved linear mixed effects model

    Science.gov (United States)

    Ma, Zongwei; Liu, Yang; Zhao, Qiuyue; Liu, Miaomiao; Zhou, Yuanchun; Bi, Jun

    2016-05-01

    Satellite remotely sensed aerosol optical depth (AOD) provides an effective way to fill the spatial and temporal gaps left by ground PM2.5 monitoring network. Previous studies have established robust advanced statistical models to estimate PM2.5 using AOD data in China. However, their coarse resolutions (˜10 km or greater) of PM2.5 estimations are not enough to support the health effect studies at urban scales. In this study, 3 km AOD data from Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 products were used to estimate the high resolution PM2.5 concentrations in Yangtze Delta Region of China. We proposed a nested linear mixed effects (LME) model including nested month-, week-, and day-specific random effects of PM2.5-AOD relationships. Validation results show that the LME model only with day-specific random effects (non-nested model) used in previous studies has poor performance in the days without PM2.5-AOD matchups (the R2 of day-of-year-based cross validation (DOY-based CV) is 0.148). The results also show that our nested model cannot improve the performance of non-nested model in the days with PM2.5-AOD matchups (sample-based CV R2 = 0.671 for nested model vs. 0.661 for non-nested model), but can greatly improve the model performance beyond those days (DOY-based CV R2 = 0.339 for nested model vs. 0.148 for non-nested model). To further improve the model performance, we applied the "buffer models" (i.e., models fitted from datasets which ground PM2.5 were matched with the average AOD values within certain radius buffer zones of gridded PM2.5 data) on the 3 km AOD data since the "buffer models" has more days with PM2.5-AOD matchups and can provide more day-specific relationships. The results of this study show that 3 km MODIS C6 AOD data can be used to estimate PM2.5 concentrations and can provide more detailed spatial information for urban scale studies. The application of our nested LME model can greatly improve the accuracy of 3 km PM2

  8. Design and Implementation of a Real-time Processing System of Full Resolution Quick-look Image of HJ-1 Environmental Satellite C SAR Based on High Performance Cluster

    Directory of Open Access Journals (Sweden)

    Li Jing-shan

    2014-06-01

    Full Text Available This study is concerned with the design and implementation of a real-time processing system of full resolution quick-look image of HJ-1 environmental satellite C SAR based on high-performance clusters. The system processes the first quick-look SAR image on December 9, 2012. The results show that the design and implementation of the quick-look processing system satisfies the real-time SAR image processing performance requirements at full resolution. Moreover, this system is the first real-time business system of full-resolution quick-look spaceborne SAR images in China.

  9. High Resolution Elevation Contours

    Data.gov (United States)

    Minnesota Department of Natural Resources — This dataset contains contours generated from high resolution data sources such as LiDAR. Generally speaking this data is 2 foot or less contour interval.

  10. 100-Meter Resolution Satellite View of Alaska - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View of Alaska map layer is a 100-meter resolution simulated natural-color image of Alaska. Vegetation is generally green, with forests in darker green...

  11. 100-Meter Resolution Satellite View of Hawaii - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View of Hawaii map layer is a 100-meter resolution simulated natural-color image of Hawaii. Vegetation is generally green, with forests in darker green...

  12. Geology, tectonics, and the 2002-2003 eruption of the Semeru volcano, Indonesia: Interpreted from high-spatial resolution satellite imagery

    Science.gov (United States)

    Solikhin, Akhmad; Thouret, Jean-Claude; Gupta, Avijit; Harris, Andy J. L.; Liew, Soo Chin

    2012-02-01

    The paper illustrates the application of high-spatial resolution satellite images in interpreting volcanic structures and eruption impacts in the Tengger-Semeru massif in east Java, Indonesia. We use high-spatial resolution images (IKONOS and SPOT 5) and aerial photos in order to analyze the structures of Semeru volcano and map the deposits. Geological and tectonic mapping is based on two DEMs and on the interpretation of aerial photos and four SPOT and IKONOS optical satellite images acquired between 1996 and 2002. We also compared two thermal Surface Kinetic Temperature ASTER images before and after the 2002-2003 eruption in order to delineate and evaluate the impacts of the pyroclastic density currents. Semeru's principal structural features are probably due to the tectonic setting of the volcano. A structural map of the Tengger-Semeru massif shows four groups of faults orientated N40, N160, N75, and N105 to N140. Conspicuous structures, such as the SE-trending horseshoe-shaped scar on Semeru's summit cone, coincide with the N160-trending faults. The direction of minor scars on the east flank parallels the first and second groups of faults. The Semeru composite cone hosts the currently active Jonggring-Seloko vent. This is located on, and buttressed against, the Mahameru edifice at the head of a large scar that may reflect a failure plane at shallow depth. Dipping 35° towards the SE, this failure plane may correspond to a weak basal layer of weathered volcaniclastic rocks of Tertiary age. We suggest that the deformation pattern of Semeru and its large scar may be induced by flank spreading over the weak basal layer of the volcano. It is therefore necessary to consider the potential for flank and summit collapse in the future. The last major eruption took place in December 2002-January 2003, and involved emplacement of block-and-ash flows. We have used the 2003 ASTER Surface Kinetic Temperature image to map the 2002-2003 pyroclastic density current deposits. We

  13. ASTER Urgent Response to the 2006 Eruption of Augustine Volcano, Alaska: Science and Decision Support Gained From Frequent High-resolution, Satellite Thermal Infrared Imaging of Volcanic Events

    Science.gov (United States)

    Wessels, R. L.; Ramsey, M. S.; Schneider, D. S.; Coombs, M.; Dehn, J.; Realmuto, V. J.

    2006-12-01

    Augustine Volcano, Alaska explosively erupted on January 11, 2006 after nearly eight months of increasing seismicity, deformation, gas emission, and small phreatic explosions. The volcano produced a total of 13 explosive eruptions during the last three weeks of January 2006. A new summit lava dome and two short, blocky lava flows grew during February and March 2006. A series of 7 daytime and 15 nighttime Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes were acquired in response to this new activity. This response was facilitated by a new ASTER Urgent Request Protocol system. The ASTER data provided several significant observations as a part of a much larger suite of real-time or near-real-time data from other satellite (AVHRR, MODIS), airborne (FLIR, visual, gas), and ground-based (seismometers, radiometers) sensors used at the Alaska Volcano Observatory (AVO). ASTER is well-suited to volcanic observations because of its 15-m to 90-m spatial resolution, its ability to be scheduled and point off-nadir, and its ability to collect visible-near infrared (VNIR) to thermal infrared (TIR) data during both the day and night. Aided by the volcano's high latitude (59.4°N) ASTER was able to provide frequent repeat imaging as short as one day between scenes with an average 6-day repeat during the height of activity. These data provided a time series of high-resolution VNIR, shortwave infrared (SWIR - detects temperatures from about 200°C to > 600°C averaged over a 30-m pixel), and TIR (detects temperatures up to about 100°C averaged over a 90-m pixel) data of the volcano and its eruptive products. Frequent satellite imaging of volcanoes is necessary to record rapid changes in activity and to avoid recurring cloud cover. Of the 22 ASTER scenes acquired between October 30, 2005 and May 30, 2006, the volcano was clear to partly cloudy in 13 scenes. The most useful pre-eruption ASTER Urgent Request image was acquired on December 20. These data

  14. [Landscape pattern changes at village scale using high resolution satellite images: A case study in low-slope hilly area of Dali City, Northwestern Yunnan Province].

    Science.gov (United States)

    Zhao, Ming-yue; Peng, Jian; Liu, Yan-xu; Zhang, Tian

    2015-12-01

    Human activity is the main driving force of the change of land cover and landscape patterns. However, there are few studies focusing on the mechanism of human-induced change of land cover and landscape patterns at village scale. In this study, taking low-slope hilly area of Dali City, Northwestern Yunnan Province as a case study area, high resolution satellite images were introduced to find out the rules of land cover and landscape pattern changes, i.e. GeoEye-1 of 2009 and World- View-3 of 2014. The object-oriented and human-computer-interaction approaches were applied to interpret the images using ArcGIS 10.2 and ENVI 5.2. The results showed that, the main land cover types in the study area were forest land, paddy field and dry land in 2009, with forest, bulldozed unbuilt ground and paddy field in 2014, accounting for 82.8% and 70.9% of the total area, respectively. The land cover transition showed that, during 2009-2014, the main land cover change flows were from forest land, paddy field and dry land, to bulldozed unbuilt ground and construction land. Furthermore, the area of bulldozed but unbuilt land had increased to be 531.57 hm² in 2014, which mainly came from forest land (42.8%), dry land (21.7%), and paddy field (14.2%). Landscape pattern change was characterized as the increase of patch quantity and density, the decrease of mean patch size, the complication of patch shape, the fragmentation of landscape patches, and the diversification of landscape patterns.

  15. Ultra high resolution tomography

    Energy Technology Data Exchange (ETDEWEB)

    Haddad, W.S.

    1994-11-15

    Recent work and results on ultra high resolution three dimensional imaging with soft x-rays will be presented. This work is aimed at determining microscopic three dimensional structure of biological and material specimens. Three dimensional reconstructed images of a microscopic test object will be presented; the reconstruction has a resolution on the order of 1000 A in all three dimensions. Preliminary work with biological samples will also be shown, and the experimental and numerical methods used will be discussed.

  16. GEO中高分辨率民用光学对地观测卫星发展研究%Development Analysis on GEO Civil Optical Earth Observation Satellites with Mid-high Resolution

    Institute of Scientific and Technical Information of China (English)

    于龙江; 刘云鹤

    2013-01-01

    The development of state-of-art GEO civil optical earth observation satellites with mid-high resolution is investigated, including COMS, GEO-Africa, GEO-Oculus, etc. The mission and main functions of these satellites are analyzed. The system level design and main technology approach of these satellites are summarized and compared. Finally, several issues that are important in GEO mid-high resolution civil optical earth observation satellites technology are discussed, such as selection of focal detector, high stability attitude control, jitter rejection, heat management in the night, etc. The research results could be instructions to the development of China's GEO civil optical earth observation satellites with mid-high resolution.%调研了国外地球静止轨道(GEO)中高分辨率民用光学对地观测卫星的发展情况,其中包括“通信海洋-气象卫星”(COMS)、GEO-Africa和GEO-Oculus等卫星;分析了卫星的任务范围和主要功能;对卫星总体设计方案和采用的主要技术途径进行了归纳和对比.对发展GEO中高分辨率民用光学对地观测卫星需要注意的探测器选型、高稳定度姿态控制、微振动抑制、夜晚阶段的热控等相关问题进行了分析,可为中国发展同类卫星提供参考.

  17. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  18. GHRSST Level 2P Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  19. GHRSST Level 2P Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the Atlantic Ocean and nearby regions based on multi-channel sea surface...

  20. GHRSST Level 2P Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the Atlantic Ocean and nearby regions based on multi-channel sea surface...

  1. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset based on multi-channel sea surface temperature (SST) retrievals from the...

  2. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset based on multi-channel sea surface temperature (SST) retrievals from the...

  3. GHRSST Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  4. Towards high temporal and moderate spatial resolutions in the remote sensing retrieval of evapotranspiration by combining geostationary and polar orbit satellite data

    Science.gov (United States)

    Barrios, José Miguel; Ghilain, Nicolas; Arboleda, Alirio; Gellens-Meulenberghs, Françoise

    2014-05-01

    Evapotranspiration (ET) is the water flux going from the surface into the atmosphere as result of soil and surface water evaporation and plant transpiration. It constitutes a key component of the water cycle and its quantification is of crucial importance for a number of applications like water management, climatic modelling, agriculture monitoring and planning, etc. Estimating ET is not an easy task; specially if large areas are envisaged and various spatio-temporal patterns of ET are present as result of heterogeneity in land cover, land use and climatic conditions. In this respect, spaceborne remote sensing (RS) provides the only alternative to continuously measure surface parameters related to ET over large areas. The Royal Meteorological Institute (RMI) of Belgium, in the framework of EUMETSAT's "Land Surface Analysis-Satellite Application Facility" (LSA-SAF), has developed a model for the estimation of ET. The model is forced by RS data, numerical weather predictions and land cover information. The RS forcing is derived from measurements by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite. This ET model is operational and delivers ET estimations over the whole field of view of the MSG satellite (Europe, Africa and Eastern South America) (http://landsaf.meteo.pt) every 30 minutes. The spatial resolution of MSG is 3 x 3 km at subsatellite point and about 4 x 5 km in continental Europe. The spatial resolution of this product may constrain its full exploitation as the interest of potential users (farmers and natural resources scientists) may lie on smaller spatial units. This study aimed at testing methodological alternatives to combine RS imagery (geostationary and polar orbit satellites) for the estimation of ET such that the spatial resolution of the final product is improved. In particular, the study consisted in the implementation of two approaches for combining the current ET estimations with

  5. Glider and satellite high resolution monitoring of a mesoscale eddy in the Algerian basin: effects on the mixed layer depth and biochemistry

    Science.gov (United States)

    Cotroneo, Yuri; Aulicino, Giuseppe; Ruiz, Simón; Pascual, Ananda; Budillon, Giorgio; Fusco, Giannetta; Tintoré, Joaquin

    2016-04-01

    Despite of the extensive bibliography about the circulation of the Mediterranean Sea and its sub-basins, the debate on mesoscale dynamics and its impacts on biochemical processes is still open because of their intrinsic time scales and of the difficulties in sampling. In order to clarify some of these processes, the "Algerian BAsin Circulation Unmanned Survey - ABACUS" project was proposed and realized through access to JERICO Trans National Access (TNA) infrastructures between September and December 2014. In this framework, a deep glider cruise was carried out in the area between Balearic Islands and Algerian coasts to establish an endurance line for monitoring the basin circulation. During the mission, a mesoscale eddy, identified on satellite altimetry maps, was sampled at high-spatial horizontal resolution (4 km) along its main axes and from surface to 1000 m depth. Data were collected by a Slocum glider equipped with a pumped CTD and biochemical sensors that collected about 100 complete casts inside the eddy. In order to describe the structure of the eddy, in situ data were merged with new generation remotely sensed data as daily synoptic sea surface temperature (SST) and chlorophyll concentration (Chl-a) images from MODIS satellites as well as sea surface height and geostrophic velocities from AVISO. From its origin along the Algerian coast in the eastern part of the basin, the eddy propagated to north-west at a mean speed of about 4 km/day with a mean diameter of 112/130 km, a mean elevation of 15.7 cm and clearly distinguished by the surrounding waters thanks to its higher SST and Chl-a values. Temperature and salinity values along the water column confirm the origin of the eddy from the AC showing the presence of recent Atlantic water in the surface layer and Levantine Intermediate Water (LIW) in the deeper layer. Eddy footprint is clearly evident in the multiparametric vertical sections conducted along its main axes. Deepening of temperature, salinity and

  6. Enabling High Spectral Resolution Thermal Imaging from CubeSat and MicroSatellite Platforms Using Uncooled Microbolometers and a Fabry-Perot interferometer

    Science.gov (United States)

    Wright, R.; Lucey, P. G.; Crites, S.; Garbeil, H.; Wood, M.; Pilger, E. J.; Honniball, C.; Gabrieli, A.

    2016-12-01

    Measurements of reflectance or emittance in tens of narrow, contiguous wavebands, allow for the derivation of laboratory quality spectra remotely, from which the chemical composition and physical properties of targets can be determined. Although spaceborne (e.g. EO-1 Hyperion) hyperspectral data in the 0.4-2.5 micron (VSWIR) region are available, the provision of equivalent data in the log-wave infrared has lagged behind, there being no currently operational high spatial resolution LWIR imaging spectrometer on orbit. This is attributable to two factors. Firstly, earth emits less light than it reflects, reducing the signal available to measure in the TIR, and secondly, instruments designed to measure (and spectrally decompose) this signal are more complex, massive, and expensive than their VSWIR counterparts, largely due to the need to cryogenically cool the detector and optics. However, this measurement gap needs to be filled, as LWIR data provide fundamentally different information than VSWIR measurements. The TIRCIS instrument (Thermal Infra-Red Compact Imaging Spectrometer), developed at the Hawaii Institute of Geophysics and Planetology, uses a Fabry-Perot interferometer, an uncooled microbolometer array, and push-broom scanning to acquire hyperspectral image data in the 8-14 micron spectral range. Radiometric calibration is provided by blackbody targets while spectral calibration is achieved using monochromatic light sources. The instrument has a mass of <15 kg and dimensions of 53 cm × 25 cm × 22 cm, and has been designed to be compatible with integration into a micro-satellite platform. (A precursor to this instrument was launched onboard a 55 kg microsatellite as part of the ORS-4 mission in October 2015). The optical design yields a 120 m ground sample size given an orbit of 500 km. Over the wavelength interval of 7.5 to 14 microns up to 50 spectral samples are possible (the accompanying image shows a quartz spectrum composed of 17 spectral samples). Our

  7. High-resolution headlamp

    Science.gov (United States)

    Gut, Carsten; Cristea, Iulia; Neumann, Cornelius

    2016-04-01

    The following article shall describe how human vision by night can be influenced. At first, front lighting systems that are already available on the market will be described, followed by their analysis with respect to the positive effects on traffic safety. Furthermore, how traffic safety by night can be increased since the introduction of high resolution headlamps shall be discussed.

  8. Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  9. High-resolution shipboard measurements of phytoplankton: a way forward for enhancing the utility of satellite SST and chlorophyll for mapping microscale features and frontal zones in coastal waters

    Science.gov (United States)

    Jenkins, Christy A.; Goes, Joaquim I.; McKee, Kali; Gomes, Helga do R.; Arnone, Robert; Wang, Menghua; Ondrusek, Michael; Nagamani, P. V.; Preethi Latha, T.; Rao, K. H.; Dadhwal, V. K.

    2016-05-01

    Coastal eddies, frontal zones and microscale oceanographic features are now easily observable from satellite measurements of SST and Chl a. Enhancing the utility of these space-borne measurements for biological productivity, biogeochemical cycling and fisheries investigations will require novel bio-optical methods capable of providing information on the community structure, biomass and photo-physiology of phytoplankton associated on spatial scales that match these features. This study showcases high-resolution in-situ measurements of sea water hydrography (SeaBird CTD®), CDOM (WetLabs ALF®), phytoplankton functional types (PFTs, FlowCAM®), biomass (bbe Moldaenke AlgaeOnlineAnalyzer® and WetLabs ALF®) and phytoplankton photosynthetic competency (mini-FIRe) across microscale features encountered during a recent (Nov. 2014) cruise in support of NOAA's VIIRS ocean color satellite calibration and validation activities. When mapped against binned daily, Level 2 satellite images of Chl a, Kd490 and SST over the cruise period, these high-resolution in-situ data showed great correspondence with the satellite data, but more importantly allowed for identification of PFTs and water types associated with microscale features. Large assemblages of phytoplankton communities comprising of diatoms and diatom-diazotroph associations (DDAs), were found in mesohaline frontal zones. Despite their high biomass, these populations were characterized by low photosynthetic competency, indicative of a bloom at the end of its active growth possibly due to nitrogen depletion in the water. Other prominent PFTs such as Trichodesmium spp., Synechococcus spp. and cryptophytes, were also associated with specific water masses offering the promise and potential that ocean remote sensing reflectance bands when examined in the context of water types also measurable from space, could greatly enhance the utility of satellite measurements for biological oceanographic, carbon cycling and fisheries

  10. Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  11. High Resolution Acoustical Imaging

    Science.gov (United States)

    1989-05-01

    1028 (September 1982). 26 G. Arfken , Mathematical Methods for Physicists (Academic Press, New York, 1971), 2nd printing, pp.662-666. 27 W. R. Hahn...difference in the approach used by the two methods , as noted in the previous paragraph, forming a direct mathematical com- parison may be impossible...examines high resolution methods which use a linear array to locate stationary objects which have scattered the fressure waves. Several;- new methods

  12. High resolution differential thermometer

    Directory of Open Access Journals (Sweden)

    Gotra Z. Yu.

    2009-11-01

    Full Text Available Main schematic solutions of differential thermometers with measurement resolution about 0.001°C are considered. Differential temperature primary transducer realized on a transistor differential circuit in microampere mode. Analytic calculation and schematic mathematic simulation of primary transducer are fulfilled. Signal transducer is realized on a high precision Zero-Drift Single-Supply Rail-to-Rail operation amplifier AD8552 and 24-Bit S-D microconverter ADuC834.

  13. Evaluation of the impact of the 2010 pyroclastic density currents at Merapi volcano from high-resolution satellite imagery, field investigations and numerical simulations

    Science.gov (United States)

    Charbonnier, S. J.; Germa, A.; Connor, C. B.; Gertisser, R.; Preece, K.; Komorowski, J.-C.; Lavigne, F.; Dixon, T.; Connor, L.

    2013-07-01

    The 2010 pyroclastic density currents (PDC) at Merapi have presented a rare opportunity to collect a uniquely detailed dataset of the source, extent, lateral variations and impact of various PDC deposits on a densely populated area. Using traditional volcanological field-based methods and a multi-temporal dataset of high-resolution satellite imagery, a total of 23 PDC events have been recognized, including 5 main channeled flows, 15 overbank flows derived from overspill and re-channelization of the main PDCs into adjacent tributaries and two main surge events. The 2010 PDC deposits covered an area of ~ 22.3 km2, unequally distributed between valley-filling (6.9%), overbank (22.4%) and surge and associated fallout deposits (71.7%). Their total estimated non-DRE volume is ~ 36.3 × 106 m3, with 50.2% of this volume accounting for valley-filling deposits, 39.3% for overbank deposits and 10.5% for surge and associated fallout deposits. More than 70% of the total volume was deposited during the third eruptive phase (4-5 November), and only 16.6%, 11.5% and 0.9% during the first (26-29 October), second (30 October - 3 November) and fourth phase (6-23 November), respectively. The internal architecture and lithofacies variations of the 2010 PDC deposits were investigated using data collected from 30 stratigraphic sections measured after one rainy season of erosion. The results show that complex, local-scale variations in flow dynamics and deposit architectures are apparent and that the major factors controlling the propagation of the main flows and their potential hazards for overbanking were driven by: (1) the rapid emplacement of several voluminous PDCs, associated with the steady infilling of the receiving landscape after the two first phases of the eruption; (2) longitudinal changes in channel capacity following increased sinuosity in the valley and decreased containment space; and (3) the effects of varying source mechanisms (gravitational dome collapse, vertical or

  14. Integrating satellite imagery-derived data and GIS-based solar radiation algorithms to map solar radiation in high temporal and spatial resolutions for the province of Salta, Argentina

    Science.gov (United States)

    Ramirez Camargo, Luis; Dorner, Wolfgang

    2016-10-01

    An accurate estimation of solar radiation availability is vital for planning solar energy generation systems. Classically, this type of estimation is made by cumulating data for periods of one year and serves to determine locations with the highest solar radiation availability. However, the integration of high shares of technologies such as photovoltaics in the energy matrix and the evaluation of the economic viability of these systems under time-dependent promotion mechanisms, also requires estimations in a high temporal resolution. When looking at the yearly solar resource availability, the north-west of Argentina is one of the regions of the world with the highest solar radiation potential. Yet estimations are available mainly in low spatial resolutions and there are only few studies that try to characterize the temporal variability of the solar resource in this part of the world. This paper presents a methodology to integrate satellite imagery derived data and a GIS-based solar radiation algorithm in order to generate a high resolution solar irradiance spatiotemporal data set for the province of Salta, north-west Argentina. This data set describes in a better way the differences in solar resource availability between flat and mountainous regions in the province, serves to accurately identify locations with the highest global solar radiation and to characterize its variability on time. Furthermore, the presented methodology can be easily replicated for the rest of South America that is covered by Down-welling Surface Shortwave Flux (DSSF) product provided by the Land Surface Analysis Satellite Applications Facility.

  15. High-Resolution NDVI from Planet’s Constellation of Earth Observing Nano-Satellites: A New Data Source for Precision Agriculture

    Directory of Open Access Journals (Sweden)

    Rasmus Houborg

    2016-09-01

    Full Text Available Planet Labs (“Planet” operate the largest fleet of active nano-satellites in orbit, offering an unprecedented monitoring capacity of daily and global RGB image capture at 3–5 m resolution. However, limitations in spectral resolution and lack of accurate radiometric sensor calibration impact the utility of this rich information source. In this study, Planet’s RGB imagery was translated into a Normalized Difference Vegetation Index (NDVI: a common metric for vegetation growth and condition. Our framework employs a data mining approach to build a set of rule-based regression models that relate RGB data to atmospherically corrected Landsat-8 NDVI. The approach was evaluated over a desert agricultural landscape in Saudi Arabia where the use of near-coincident (within five days Planet and Landsat-8 acquisitions in the training of the regression models resulted in NDVI predictabilities with an r2 of approximately 0.97 and a Mean Absolute Deviation (MAD on the order of 0.014 (~9%. The MAD increased to 0.021 (~14% when the Landsat NDVI training image was further away (i.e., 11–16 days from the corrected Planet image. In these cases, the use of MODIS observations to inform on the change in NDVI occurring between overpasses was shown to significantly improve prediction accuracies. MAD levels ranged from 0.002 to 0.011 (3.9% to 9.1% for the best performing 80% of the data. The technique is generic and extendable to any region of interest, increasing the utility of Planet’s dense time-series of RGB imagery.

  16. Saturn's rings - high resolution

    Science.gov (United States)

    1981-01-01

    Voyager 2 obtained this high-resolution picture of Saturn's rings Aug. 22, when the spacecraft was 4 million kilometers (2.5 million miles) away. Evident here are the numerous 'spoke' features, in the B-ring; their very sharp, narrow appearance suggests short formation times. Scientists think electromagnetic forces are responsible in some way for these features, but no detailed theory has been worked out. Pictures such as this and analyses of Voyager 2's spoke movies may reveal more clues about the origins of these complex structures. The Voyager project is managed for NASA by the Jet Propulsion Laboratory, Pasadena, Calif.

  17. Geostatistics and remote sensing as predictive tools of tick distribution: a cokriging system to estimate Ixodes scapularis (Acari: Ixodidae) habitat suitability in the United States and Canada from advanced very high resolution radiometer satellite imagery.

    Science.gov (United States)

    Estrada-Peña, A

    1998-11-01

    Geostatistics (cokriging) was used to model the cross-correlated information between satellite-derived vegetation and climate variables and the distribution of the tick Ixodes scapularis (Say) in the Nearctic. Output was used to map the habitat suitability for I. scapularis on a continental scale. A data base of the localities where I. scapularis was collected in the United States and Canada was developed from a total of 346 published and geocoded records. This data base was cross-correlated with satellite pictures from the advanced very high resolution radiometer sensor obtained from 1984 to 1994 on the Nearctic at 10-d intervals, with a resolution of 8 km per pixel. Eight climate and vegetation variables were tabulated from this imagery. A cokriging system was generated to exploit satellite-derived data and to estimate the distribution of I. scapularis. Results obtained using 2 vegetation (standard NDVI) and 4 temperature variables closely agreed with actual records of the tick, with a sensitivity of 0.97 and a specificity of 0.89, with 6 and 4% of false-positive and false-negative sites, respectively. Such statistical analysis can be used to guide field work toward the correct interpretation of the distribution limits of I. scapularis and can also be used to make predictions about the impact of global change on tick range.

  18. High Resolution Laboratory Spectroscopy

    CERN Document Server

    Brünken, Sandra

    2016-01-01

    In this short review we will highlight some of the recent advancements in the field of high-resolution laboratory spectroscopy that meet the needs dictated by the advent of highly sensitive and broadband telescopes like ALMA and SOFIA. Among these is the development of broadband techniques for the study of complex organic molecules, like fast scanning conventional absorption spectroscopy based on multiplier chains, chirped pulse instrumentation, or the use of synchrotron facilities. Of similar importance is the extension of the accessible frequency range to THz frequencies, where many light hydrides have their ground state rotational transitions. Another key experimental challenge is the production of sufficiently high number densities of refractory and transient species in the laboratory, where discharges have proven to be efficient sources that can also be coupled to molecular jets. For ionic molecular species sensitive action spectroscopic schemes have recently been developed to overcome some of the limita...

  19. High resolution SAR applications and instrument design

    Science.gov (United States)

    Dionisio, C.; Torre, A.

    1993-01-01

    The Synthetic Aperture Radar (SAR) has viewed, in the last two years, a huge increment of interest from many preset and potential users. The good spatial resolution associated to the all weather capability lead to considering SAR not only a scientific instrument but a tool for verifying and controlling the daily human relationships with the Earth Environment. New missions were identified for SAR as spatial resolution became lower than three meters: disasters, pollution, ships traffic, volcanic eruptions, earthquake effect are only a few of the possible objects which can be effectively detected, controlled and monitored by SAR mounted on satellites. High resolution radar design constraints and dimensioning are discussed.

  20. High Time Resolution Astrophysics

    CERN Document Server

    Phelan, Don; Shearer, Andrew

    2008-01-01

    High Time Resolution Astrophysics (HTRA) is an important new window to the universe and a vital tool in understanding a range of phenomena from diverse objects and radiative processes. This importance is demonstrated in this volume with the description of a number of topics in astrophysics, including quantum optics, cataclysmic variables, pulsars, X-ray binaries and stellar pulsations to name a few. Underlining this science foundation, technological developments in both instrumentation and detectors are described. These instruments and detectors combined cover a wide range of timescales and can measure fluxes, spectra and polarisation. These advances make it possible for HTRA to make a big contribution to our understanding of the Universe in the next decade.

  1. Assessing Wildfire Risk in Cultural Heritage Properties Using High Spatial and Temporal Resolution Satellite Imagery and Spatially Explicit Fire Simulations: The Case of Holy Mount Athos, Greece

    Directory of Open Access Journals (Sweden)

    Giorgos Mallinis

    2016-02-01

    Full Text Available Fire management implications and the design of conservation strategies on fire prone landscapes within the UNESCO World Heritage Properties require the application of wildfire risk assessment at landscape level. The objective of this study was to analyze the spatial variation of wildfire risk on Holy Mount Athos in Greece. Mt. Athos includes 20 monasteries and other structures that are threatened by increasing frequency of wildfires. Site-specific fuel models were created by measuring in the field several fuel parameters in representative natural fuel complexes, while the spatial extent of the fuel types was determined using a synergy of high-resolution imagery and high temporal information from medium spatial resolution imagery classified through object-based analysis and a machine learning classifier. The Minimum Travel Time (MTT algorithm, as it is embedded in FlamMap software, was applied in order to evaluate Burn Probability (BP, Conditional Flame Length (CFL, Fire Size (FS, and Source-Sink Ratio (SSR. The results revealed low burn probabilities for the monasteries; however, nine out of the 20 monasteries have high fire potential in terms of fire intensity, which means that if an ignition occurs, an intense fire is expected. The outputs of this study may be used for decision-making for short-term predictions of wildfire risk at an operational level, contributing to fire suppression and management of UNESCO World Heritage Properties.

  2. Monitoring the Impacts of Wildfires on Forest Ecosystems and Public Health in the Exo-Urban Environment Using High-Resolution Satellite Aerosol Products from the Visible Infrared Imaging Radiometer Suite (VIIRS).

    Science.gov (United States)

    Huff, Amy K; Kondragunta, Shobha; Zhang, Hai; Hoff, Raymond M

    2015-01-01

    Increasing development of exo-urban environments and the spread of urbanization into forested areas is making humans and forest ecosystems more susceptible to the risks associated with wildfires. Larger and more damaging wildfires are having a negative impact on forest ecosystem services, and smoke from wildfires adversely affects the public health of people living in exo-urban environments. Satellite aerosol measurements are valuable tools that can track the evolution of wildfires and monitor the transport of smoke plumes. Operational users, such as air quality forecasters and fire management officials, can use satellite observations to complement ground-based and aircraft measurements of wildfire activity. To date, wildfire applications of satellite aerosol products, such as aerosol optical depth (AOD), have been limited by the relatively coarse resolution of available AOD data. However, the new Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi National Polar-orbiting Partnership (S-NPP) satellite has high-resolution AOD that is ideally suited to monitoring wildfire impacts on the exo-urban scale. Two AOD products are available from VIIRS: the 750-m × 750-m nadir resolution Intermediate Product (IP) and the 6-km × 6-km resolution Environmental Data Record product, which is aggregated from IP measurements. True color (red, green, and blue [RGB]) imagery and a smoke mask at 750-m × 750-m resolution are also available from VIIRS as decision aids for wildfire applications; they serve as counterparts to AOD measurements by providing visible information about areas of smoke in the atmosphere. To meet the needs of operational users, who do not have time to process raw data files and need access to VIIRS products in near-real time (NRT), VIIRS AOD and RGB NRT imagery are available from the Infusing satellite Data into Environmental Applications (IDEA) web site. A key feature of IDEA is an interactive visualization tool that allows users to

  3. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?

    Science.gov (United States)

    Tan, Zeli; Zhuang, Qianlai; Henze, Daven K.; Frankenberg, Christian; Dlugokencky, Ed; Sweeney, Colm; Turner, Alexander J.; Sasakawa, Motoki; Machida, Toshinobu

    2016-10-01

    Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range of 496.4-511.5 Tg yr-1, and pan-Arctic methane emissions were in the range of 11.9-28.5 Tg yr-1. Methane emissions from pan-Arctic wetlands and lakes were 5.5-14.2 and 2.4-14.2 Tg yr-1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.

  4. Level study on fractal characteristics of tidal creeks and information of seashell habitats in the Gaizhou Beach based on high-resolution satellite images

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiufa; YANG Xiaomei; LI Yunju; LIU Baoyin; WANG Jinggui; ZHANG Zichuan

    2004-01-01

    The fractal characteristics of tidal creeks in the Gaizhou Beach are analyzed based on high-resolution images fusion of Landsat TM and ERS-2, and then the graphic models and characteristics of converse information tree of tidal creeks in the Gaizhou Beach are established. A calculation model is established based on the above results, and at the same time, quantitative calculation of the evolution characteristics and the diversity between the northern and the southern parts of the Gaizhou Beach is carried out. By the supervised classification of these images, distribution and areas of high tidal flats, middle tidal flats and low tidal flats in the Gaizhou Beach are studied quantitatively, and image charactistics of seashell habitats in the Gaizhou Beach and the correlation between mudflat distribution and seashell habitats are studied. At last, the engineering problems in the Gaizhou Beach are discussed.

  5. Blending Model Output with satellite-based and in-situ observations to produce high-resolution estimates of population exposure to wildfire smoke

    Science.gov (United States)

    Lassman, William

    In the western US, emissions from wildfires and prescribed fire have been associated with degradation of regional air quality. Whereas atmospheric aerosol particles with aerodynamic diameters less than 2.5 mum (PM2.5) have known impacts on human health, there is uncertainty in how particle composition, concentrations, and exposure duration impact the associated health response. Due to changes in climate and land-management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of PM2.5 in the western US. While composition and source of the aerosol is thought to be an important factor in the resulting human health-effects, this is currently not well-understood; therefore, there is a need to develop a quantitative understanding of wildfire-smoke-specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools are commonly used to assess exposure to wildfire smoke: in-situ measurements, satellite-based observations, and chemical-transport model (CTM) simulations, and each of these exposure-estimation tools have associated strengths and weakness. In this thesis, we investigate the utility of blending these tools together to produce highly accurate estimates of smoke exposure during the 2012 fire season in Washington for use in an epidemiological case study. For blending, we use a ridge regression model, as well as a geographically weighted ridge regression model. We evaluate the performance of the three individual exposure-estimate techniques and the two blended techniques using Leave-One-Out Cross-Validation. Due to the number of in-situ monitors present during this time period, we find that predictions based on in-situ monitors were more accurate for this particular fire season than the CTM simulations and

  6. Highly Enhanced Risk Management Emergency Satellite

    DEFF Research Database (Denmark)

    Dalmeir, Michael; Gataullin, Yunir; Indrajit, Agung

    HERMES (Highly Enhanced Risk Management Emergency Satellite) is potential European satellite mission for global flood management, being implemented by Technical University Munich and European Space Agency. With its main instrument - a reliable and precise Synthetic Aperture Radar (SAR) antenna...

  7. Geostatistics and remote sensing using NOAA-AVHRR satellite imagery as predictive tools in tick distribution and habitat suitability estimations for Boophilus microplus (Acari: Ixodidae) in South America. National Oceanographic and Atmosphere Administration-Advanced Very High Resolution Radiometer.

    Science.gov (United States)

    Estrada-Peña, A

    1999-02-01

    Remote sensing based on NOAA (National Oceanographic and Atmosphere Administration) satellite imagery was used, together with geostatistics (cokriging) to model the correlation between the temperature and vegetation variables and the distribution of the cattle tick, Boophilus microplus (Canestrini), in the Neotropical region. The results were used to map the B. microplus habitat suitability on a continental scale. A database of B. microplus capture localities was used, which was tabulated with the AVHRR (Advanced Very High Resolution Radiometer) images from the NOAA satellite series. They were obtained at 10 days intervals between 1983 and 1994, with an 8 km resolution. A cokriging system was generated to extrapolate the results. The data for habitat suitability obtained through two vegetation and four temperature variables were strongly correlated with the known distribution of B. microplus (sensitivity 0.91; specificity 0.88) and provide a good estimation of the tick habitat suitability. This model could be used as a guide to the correct interpretation of the distribution limits of B. microplus. It can be also used to prepare eradication campaigns or to make predictions about the effects of global change on the distribution of the parasite.

  8. Mapping the bathymetry of supraglacial lakes and streams on the Greenland Ice Sheet using field measurements and high resolution satellite images

    Directory of Open Access Journals (Sweden)

    C. J. Legleiter

    2013-09-01

    Full Text Available Recent melt events on the Greenland Ice Sheet (GrIS accentuate the need to constrain estimates of sea level rise through improved characterization of meltwater pathways. This effort will require more precise estimates of the volume of water stored on the surface of the GrIS. We assessed the potential to obtain such information by mapping the bathymetry of supraglacial lakes and streams from WorldView2 (WV2 satellite images. Simultaneous {in situ} observations of depth and reflectance from two streams and a lake with measured depths up to 10.45 m were used to test a spectrally-based depth retrieval algorithm. We performed Optimal Band Ratio Analysis (OBRA of continuous field spectra and spectra convolved to the bands of the WV2, Landsat, MODIS, and ASTER sensors. The field spectra yielded a strong relationship with depth (R2 = 0.94, and OBRA R2 values were nearly as high (0.87–0.92 for convolved spectra, suggesting that these sensors' broader bands would be sufficient for depth retrieval. Our field measurements thus indicated that remote sensing of supraglacial bathymetry is not only feasible but potentially highly accurate. OBRA of spectra from 2 m-pixel WV2 images acquired within 3–72 h of our field observations produced an optimal R2 value of 0.92 and unbiased, precise depth estimates, with mean and root-mean square errors < 1% and 10–25% of the mean depth. Bathymetric maps produced by applying OBRA relations revealed subtle features of lake and channel morphology. In addition to providing refined storage volume estimates for lakes of various sizes, this approach can help provide estimates of the transient flux of meltwater through streams.

  9. An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery

    Science.gov (United States)

    Shean, David E.; Alexandrov, Oleg; Moratto, Zachary M.; Smith, Benjamin E.; Joughin, Ian R.; Porter, Claire; Morin, Paul

    2016-06-01

    We adapted the automated, open source NASA Ames Stereo Pipeline (ASP) to generate digital elevation models (DEMs) and orthoimages from very-high-resolution (VHR) commercial imagery of the Earth. These modifications include support for rigorous and rational polynomial coefficient (RPC) sensor models, sensor geometry correction, bundle adjustment, point cloud co-registration, and significant improvements to the ASP code base. We outline a processing workflow for ∼0.5 m ground sample distance (GSD) DigitalGlobe WorldView-1 and WorldView-2 along-track stereo image data, with an overview of ASP capabilities, an evaluation of ASP correlator options, benchmark test results, and two case studies of DEM accuracy. Output DEM products are posted at ∼2 m with direct geolocation accuracy of computing environment. We are leveraging these resources to produce dense time series and regional mosaics for the Earth's polar regions.

  10. The High Resolution Stereo Camera (HRSC) of Mars Express and its approach to science analysis and mapping for Mars and its satellites

    Science.gov (United States)

    Gwinner, K.; Jaumann, R.; Hauber, E.; Hoffmann, H.; Heipke, C.; Oberst, J.; Neukum, G.; Ansan, V.; Bostelmann, J.; Dumke, A.; Elgner, S.; Erkeling, G.; Fueten, F.; Hiesinger, H.; Hoekzema, N. M.; Kersten, E.; Loizeau, D.; Matz, K.-D.; McGuire, P. C.; Mertens, V.; Michael, G.; Pasewaldt, A.; Pinet, P.; Preusker, F.; Reiss, D.; Roatsch, T.; Schmidt, R.; Scholten, F.; Spiegel, M.; Stesky, R.; Tirsch, D.; van Gasselt, S.; Walter, S.; Wählisch, M.; Willner, K.

    2016-07-01

    The High Resolution Stereo Camera (HRSC) of ESA's Mars Express is designed to map and investigate the topography of Mars. The camera, in particular its Super Resolution Channel (SRC), also obtains images of Phobos and Deimos on a regular basis. As HRSC is a push broom scanning instrument with nine CCD line detectors mounted in parallel, its unique feature is the ability to obtain along-track stereo images and four colors during a single orbital pass. The sub-pixel accuracy of 3D points derived from stereo analysis allows producing DTMs with grid size of up to 50 m and height accuracy on the order of one image ground pixel and better, as well as corresponding orthoimages. Such data products have been produced systematically for approximately 40% of the surface of Mars so far, while global shape models and a near-global orthoimage mosaic could be produced for Phobos. HRSC is also unique because it bridges between laser altimetry and topography data derived from other stereo imaging instruments, and provides geodetic reference data and geological context to a variety of non-stereo datasets. This paper, in addition to an overview of the status and evolution of the experiment, provides a review of relevant methods applied for 3D reconstruction and mapping, and respective achievements. We will also review the methodology of specific approaches to science analysis based on joint analysis of DTM and orthoimage information, or benefitting from high accuracy of co-registration between multiple datasets, such as studies using multi-temporal or multi-angular observations, from the fields of geomorphology, structural geology, compositional mapping, and atmospheric science. Related exemplary results from analysis of HRSC data will be discussed. After 10 years of operation, HRSC covered about 70% of the surface by panchromatic images at 10-20 m/pixel, and about 97% at better than 100 m/pixel. As the areas with contiguous coverage by stereo data are increasingly abundant, we also

  11. Higher resolution satellite remote sensing and the impact on image mapping

    Science.gov (United States)

    Watkins, Allen H.; Thormodsgard, June M.

    1987-01-01

    Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented. 

  12. Higher resolution satellite remote sensing and the impact on image mapping

    Science.gov (United States)

    Watkins, Allen H.; Thormodsgard, June M.

    Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

  13. Advanced Extremely High Frequency Satellite (AEHF)

    Science.gov (United States)

    2015-12-01

    High Frequency Satellite (AEHF) is a joint service satellite communications system that provides global , survivable, secure, protected, and jam...three satellites fully integrated into the Milstar constellation. October 2014: On October 16, 2014, the program received PEO certification for the...Combined Orbital Operation, Logistics Sustainment ( COOLS ) contract, it will be completed and coordinated in CY 2016. The AEHF system being sustained

  14. Analysing the advantages of high temporal resolution geostationary MSG SEVIRI data compared to Polar operational environmental satellite data for land surface monitoring in Africa

    DEFF Research Database (Denmark)

    Fensholt, Rasmus; Anyamba, Assaf; Huber Gharib, Silvia

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth’s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which oft...

  15. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean- New constraints from high-resolution satellite-derived gravity data

    Digital Repository Service at National Institute of Oceanography (India)

    Sreejith, K.M.; Chaubey, A; Mishra, A; Kumar, S.; Rajawat, A

    is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned...

  16. High Resolution Formaldehyde Photochemistry

    Science.gov (United States)

    Ernest, C. T.; Bauer, D.; Hynes, A. J.

    2010-12-01

    Formaldehyde (HCHO) is the most abundant and most important organic carbonyl compound in the atmosphere. The sources of formaldehyde are the oxidation of methane, isoprene, acetone, and other volatile organic compounds (VOCs); fossil fuel combustion; and biomass burning. The dominant loss mechanism for formaldehyde is photolysis which occurs via two pathways: (R1) HCHO + hv → HCO + H (R2) HCHO + hv → H2 + CO The first pathway (R1) is referred to as the radical channel, while the second pathway (R2) is referred to as the molecular channel. The products of both pathways play a significant role in atmospheric chemistry. The CO that is produced in the molecular channel undergoes further oxidation to produce CO2. Under atmospheric conditions, the H atom and formyl radical that are produced in the radical channel undergo rapid reactions with O2 to produce the hydroperoxyl radical (HO2) via (R3) and (R4). (R3) HCO + O2 → HO2 + CO (R4) H + O2 → HO2 Thus, for every photon absorbed, the photolysis of formaldehyde can contribute one CO2 molecule to the global greenhouse budget or two HO2 radicals to the tropospheric HOx (OH + HO2) cycle. The HO2 radicals produced during formaldehyde photolysis have also been implicated in the formation of photochemical smog. The HO2 radicals act as radical chain carriers and convert NO to NO2, which ultimately results in the catalytic production of O3. Constraining the yield of HO2 produced via HCHO photolysis is essential for improving tropospheric chemistry models. In this study, both the absorption cross section and the quantum yield of the radical channel (R1) were measured at high resolution over the tropospherically relevant wavelength range 304-330 nm. For the cross section measurements a narrow linewidth Nd:YAG pumped dye laser was used with a multi-pass cell. Partial pressures of HCHO were kept below 0.3 torr. Simultaneous measurement of OH LIF in a flame allowed absolute calibration of the wavelength scale. Pressure

  17. Full hierarchic versus non-hierarchic classification approaches for mapping sealed surfaces at the rural-urban fringe using high-resolution satellite data.

    Science.gov (United States)

    De Roeck, Tim; Van de Voorde, Tim; Canters, Frank

    2009-01-01

    Since 2008 more than half of the world population is living in cities and urban sprawl is continuing. Because of these developments, the mapping and monitoring of urban environments and their surroundings is becoming increasingly important. In this study two object-oriented approaches for high-resolution mapping of sealed surfaces are compared: a standard non-hierarchic approach and a full hierarchic approach using both multi-layer perceptrons and decision trees as learning algorithms. Both methods outperform the standard nearest neighbour classifier, which is used as a benchmark scenario. For the multi-layer perceptron approach, applying a hierarchic classification strategy substantially increases the accuracy of the classification. For the decision tree approach a one-against-all hierarchic classification strategy does not lead to an improvement of classification accuracy compared to the standard all-against-all approach. Best results are obtained with the hierarchic multi-layer perceptron classification strategy, producing a kappa value of 0.77. A simple shadow reclassification procedure based on characteristics of neighbouring objects further increases the kappa value to 0.84.

  18. A novel super resolution scheme to acquire and process satellite images

    Science.gov (United States)

    Yin, Dong-yu; Su, Xiao-feng; Lin, Jian-chun; Wang, Gan-quan; Kuang, Ding-bo

    2013-09-01

    Geosynchronous satellite has obvious limitations for the weight and the scale of payloads, and large aperture optical system is not permitted. The optical diffraction limit of small aperture optical system has an adverse impact on the resolution of the acquired images. Therefore, how to get high resolution images using super-resolution technique with the acquired low resolution images becomes a popular problem investigated by researchers. Here, we present a novel scheme to acquire low resolution images and process them to achieve a high resolution image. Firstly, to acquire low resolution images, we adopt a special arrangement pattern of four CCD staggered arrays on the focal plane in the remote sensing satellite framework .These four CCD linear arrays are parallelized with a 0.25√2 pixel shift along the CCD direction and a 1.25 pixel shift along the scanning direction. The rotation angle between the two directions is 45 degree. The tilting sampling mode and the special arrangement pattern allow the sensor to acquire images with a smaller sampling interval which can give the resolution a greater enhancement. Secondly, to reconstruct a high resolution image of pretty good quality with a magnification factor 4, we propose a novel algorithm based on the iterative-interpolation super resolution algorithm (IISR) and the new edge-directed interpolation algorithm (NEDI). The new algorithm makes a critical improvement to NEDI and introduces it into the multi-frame interpolation in IISR. The algorithm can preserve the edges well and requires a relatively small number of low-resolution images to achieve better reconstruction accuracy .In the last part of the paper, we carry out a simulation experiment, and use MSE as the quality measure. The results demonstrate that our new scheme substantially improves the image resolution with both better quantitative quality and visual quality compared with some previous normal methods.

  19. Calibration of Angular Systematic Errors for High Resolution Satellite Imagery%高分辨率卫星遥感影像姿态角系统误差检校

    Institute of Scientific and Technical Information of China (English)

    袁修孝; 余翔

    2012-01-01

    The object positioning accuracy from high resolution satellite imagery is strongly relevant to image attitude data accuracy, but the attitude data have generally systematic errors and the object location becomes unreliable. The angular systematic error calibration model is stricter than constant angular error calibration model, based on the rigorous geometric processing model of high resolution satellite remote sensing imagery. The calibration model was tested on SPOT-5 and CBERS-02B images and both have proved its correctness. After compensating the angular systematic errors of images, the direct georeferencing accuracy can reach ±(2-3) pixels, which is much better than results of constant angular calibration.%简要介绍高分辨率卫星遥感影像的严格几何处理模型,提出较为严密的影像姿态角系统误差检校模型。通过对SPOT-5、CBERS-02B两种卫星遥感影像的试验证实模型的正确性和方法的有效性。对影像姿态角系统误差进行补偿后,可明显提高卫星遥感影像对地目标定位的精度,且优于影像姿态角常差检校的效果,目标点平面定位精度达到了±(2-~3)像素的水平。

  20. Mapping Intra-Field Yield Variation Using High Resolution Satellite Imagery to Integrate Bioenergy and Environmental Stewardship in an Agricultural Watershed

    Directory of Open Access Journals (Sweden)

    Yuki Hamada

    2015-07-01

    Full Text Available Biofuels are important alternatives for meeting our future energy needs. Successful bioenergy crop production requires maintaining environmental sustainability and minimum impacts on current net annual food, feed, and fiber production. The objectives of this study were to: (1 determine under-productive areas within an agricultural field in a watershed using a single date; high resolution remote sensing and (2 examine impacts of growing bioenergy crops in the under-productive areas using hydrologic modeling in order to facilitate sustainable landscape design. Normalized difference indices (NDIs were computed based on the ratio of all possible two-band combinations using the RapidEye and the National Agricultural Imagery Program images collected in summer 2011. A multiple regression analysis was performed using 10 NDIs and five RapidEye spectral bands. The regression analysis suggested that the red and near infrared bands and NDI using red-edge and near infrared that is known as the red-edge normalized difference vegetation index (RENDVI had the highest correlation (R2 = 0.524 with the reference yield. Although predictive yield map showed striking similarity to the reference yield map, the model had modest correlation; thus, further research is needed to improve predictive capability for absolute yields. Forecasted impact using the Soil and Water Assessment Tool model of growing switchgrass (Panicum virgatum on under-productive areas based on corn yield thresholds of 3.1, 4.7, and 6.3 Mg·ha−1 showed reduction of tile NO3-N and sediment exports by 15.9%–25.9% and 25%–39%, respectively. Corresponding reductions in water yields ranged from 0.9% to 2.5%. While further research is warranted, the study demonstrated the integration of remote sensing and hydrologic modeling to quantify the multifunctional value of projected future landscape patterns in a context of sustainable bioenergy crop production.

  1. Multi Resolution Analysis (MRA of satellite images of oil spill disasters

    Directory of Open Access Journals (Sweden)

    Rashid Hussain

    2014-09-01

    Full Text Available Oil spill disasters monitoring and mitigation requires availability of state of the art applications and tools. Conventional technology gets benefit from latest trends and research in satellite imaginary. This research highlights multi-resolution wavelet analysis of satellite images of oil spill disasters. Multi-resolution analysis is one of the powerful techniques to analyze information content of images. This analysis enables us to have a scale-invariant interpretation of the image. At each resolution level, both smooth and detailed signals carry all the necessary information to reconstruct the smooth signal at the next level. The wavelet decomposition results in detail and approximate threshold coefficients. Multi resolution wavelet decomposition is used to analyze the image in both time and frequency domain. It provides better frequency resolution and poor time resolution for lower frequency; better time resolution and poor frequency resolution for higher frequency. This condition is fortunately suited for real applications; as signals have high frequency components for very short period of the interval and low frequency components for longer durations.

  2. Intra- and Inter-Seasonal Supra-glacial Water Variability over the West Greenland Ice Sheet as Estimated from Combining High Resolution Satellite Optical Data and a Digital Elevation Model

    Science.gov (United States)

    Brown, M. G.; Tedesco, M.; Smith, L. C.; Rennermalm, A. K.; Yang, K.

    2015-12-01

    The supra-glacial hydrology of the Greenland Ice Sheet (GrIS) plays a crucial role on the surface energy and mass balance budgets of the ice sheet as a whole. The surface hydrology network variability of small streams in the ablation zone of Greenland is poorly understood both spatially and temporally. Using satellites that can spatially resolve the presence and associated properties of small streams, the scientific community is now able to be provided with accurate spatial and temporal analysis of surface hydrology on the ice sheet (that could not have been resolved with other sensors such as those on board MODIS or LANDSAT). In this study we report mapped supra-glacial water networks over a region of the West GrIS (approximately 164 km2) derived from high resolution multispectral satellite imagery from the Quickbird and WorldView - 2 satellites in tandem with a 2 meter stereographic SETSM DEM (digital elevation model). The branching complexity of the identified surface streams is computed from the available DEM as well as the intra- and inter seasonal changes observed in the hydrological system. The stream networks created during the melt season (at several different stages of melting) are compared and discussed as well as the networks mapped between consecutive years for proximate dates. Also, depth and volume estimations for the surface water features identified were extracted via band math algorithms, threshold classifications, and morphological operations. Our results indicate that the higher stream orders have the largest amount of stored surface water per km but the lower stream orders, specifically 1st order with widths of ~ 2 meters, hold more stored surface water overall. We also employ and compare runoff data from the numerical model MAR (Modèle Atmosphérique Régional) to the estimations found using imagery and the DEM.

  3. Satellite constraint for emissions of nitrogen oxides from anthropogenic, lightning and soil sources over East China on a high-resolution grid

    Directory of Open Access Journals (Sweden)

    J.-T. Lin

    2012-03-01

    Full Text Available Vertical column densities (VCDs of tropospheric nitrogen dioxide (NO2 retrieved from space provide valuable information to estimate emissions of nitrogen oxides (NOx inversely. Accurate emission attribution to individual sources, important both for understanding the global biogeochemical cycling of nitrogen and for emission control, remains difficult. This study presents a regression-based multi-step inversion approach to estimate emissions of NOx from anthropogenic, lightning and soil sources individually for 2006 over East China on a 0.25° long × 0.25° lat grid, employing the DOMINO product version 2 retrieved from the Ozone Monitoring Instrument. The inversion is done gridbox by gridbox to derive the respective emissions, taking advantage of differences in seasonality between anthropogenic and natural sources. Lightning and soil emissions are combined together for any given gridbox due to their similar seasonality; and their different spatial distributions are used implicitly for source separation to some extent. The nested GEOS-Chem model for East Asia is used to simulate the seasonal variations of different emission sources and impacts on VCDs of NO2 for the inversion purpose. Sensitivity tests are conducted to evaluate key assumptions embedded in the inversion process. The inverse estimate suggests annual budgets of about 7.1 TgN (±39%, 0.21 TgN (±61%, and 0.38 TgN (±65% for the a posteriori anthropogenic, lightning and soil emissions, respectively, about 18–23% higher than the respective a priori values. The enhancements in anthropogenic emissions are largest in cities and areas with extensive use of coal, particularly in the north in winter, as evident on the high-resolution grid. Derived soil emissions are consistent with recent bottom-up estimates. They are less than 6% of anthropogenic emissions annually, increasing to about 13% for July. Derived lightning emissions are about 3% of

  4. Influence of low spatial resolution a priori data on tropospheric NO2 satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. P. Burrows

    2011-09-01

    Full Text Available The retrieval of tropospheric columns of NO2 and other trace gases from satellite observations of backscattered solar radiation relies on the use of accurate a priori information. The spatial resolution of current space sensors is often significantly higher than that of the a priori datasets used, introducing uncertainties from spatial misrepresentation. In this study, the effect of spatial under-sampling of a priori data on the retrieval of NO2 columns was studied for a typical coastal area (around San Francisco. High-resolution (15 × 15 km2 NO2 a priori data from the WRF-Chem model in combination with high-resolution MODIS surface reflectance and aerosol data were used to investigate the uncertainty introduced by applying a priori data at typical global chemical transport model resolution. The results show that the relative uncertainties can be large (more than a factor of 2 if all a priori data used is at the coarsest resolution for individual measurements, mainly due to spatial variations in NO2 profile and surface albedo, with smaller contributions from aerosols and surface height changes. Similar sensitivities are expected for other coastal regions and localised sources such as power plants, highlighting the need for high-resolution a priori data in quantitative analysis of the spatial patterns retrieved from satellite observations of tropospheric pollution.

  5. Does the Data Resolution/origin Matter? Satellite, Airborne and Uav Imagery to Tackle Plant Invasions

    Science.gov (United States)

    Müllerová, Jana; Brůna, Josef; Dvořák, Petr; Bartaloš, Tomáš; Vítková, Michaela

    2016-06-01

    Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

  6. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  7. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  8. GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR)...

  9. GHRSST Level 3P North Atlantic Regional Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  10. GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR)...

  11. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  12. MRF-based segmentation and unsupervised classification for building and road detection in peri-urban areas of high-resolution satellite images

    Science.gov (United States)

    Grinias, Ilias; Panagiotakis, Costas; Tziritas, Georgios

    2016-12-01

    We present in this article a new method on unsupervised semantic parsing and structure recognition in peri-urban areas using satellite images. The automatic "building" and "road" detection is based on regions extracted by an unsupervised segmentation method. We propose a novel segmentation algorithm based on a Markov random field model and we give an extensive data analysis for determining relevant features for the classification problem. The novelty of the segmentation algorithm lies on the class-driven vector data quantization and clustering and the estimation of the likelihoods given the resulting clusters. We have evaluated the reachability of a good classification rate using the Random Forest method. We found that, with a limited number of features, among them some new defined in this article, we can obtain good classification performance. Our main contribution lies again on the data analysis and the estimation of likelihoods. Finally, we propose a new method for completing the road network exploiting its connectivity, and the local and global properties of the road network.

  13. Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: insights into spatial variability using high-resolution satellite data.

    Science.gov (United States)

    Alexeeff, Stacey E; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A

    2015-01-01

    Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1 km × 1 km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R(2) yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with >0.9 out-of-sample R(2) yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the SEs. Land use regression models performed better in chronic effect simulations. These results can help researchers when interpreting health effect estimates in these types of studies.

  14. Glacier Basal Sliding in Two-Dimensions Quantified from Correlation of High-Resolution Satellite Imagery: A Case Study on Kennicott Glacier, Alaska

    Science.gov (United States)

    Armstrong, W. H., Jr.; Anderson, R. S.; Allen, J.; Rajaram, H.; Anderson, L. S.

    2014-12-01

    The coupling of glacial hydrology and sliding is a source of uncertainty for both ice flow modeling and prediction of future sea level rise. As basal sliding is required for a glacier to erode its bed, the spatial pattern of glacier sliding is also important for understanding alpine landscape evolution. We use multi-temporal WorldView satellite imagery (0.5 m pixel) to monitor the seasonal progression of glacier velocity across the terminal ~50 km2of Kennicott Glacier, Alaska. We employ the free image correlation software COSI-Corr to construct multiple velocity maps, using 2013 imagery with repeat times from 15 to 38 days. These short intervals between images allow us to analyze variations in glacier velocity over weekly to monthly timescales associated with hydrologically-induced basal sliding. By assuming that spring (March-April) glacier velocity results solely from viscous deformation, we produce spatially distributed maps of glacier sliding speed by differencing summer and spring ice surface speeds. For a given time, a large portion of our study reach slides with roughly uniform speed, despite significant variation in deformation speed. This suggests that glacier flow models in which basal sliding is taken simply to scale as ice surface velocity are unfounded. The upglacier end of our study reach slides at speeds that vary through the summer, whereas the terminal reach slides at a steady speed. The proportion of glacier motion due to sliding increases dramatically moving downglacier, making basal sliding especially important in the terminal region. Many formulations express glacier sliding as a function of effective pressure (ice pressure minus water pressure). If such formulations are correct, effective pressure varies little over large areas or is averaged over lengthscales equivalent to ~10 glacier thicknesses. Also, effective pressure is steady in the terminal region through the summer. We explore existing sliding laws to find which best describes the

  15. High resolution digital delay timer

    Science.gov (United States)

    Martin, Albert D.

    1988-01-01

    Method and apparatus are provided for generating an output pulse following a trigger pulse at a time delay interval preset with a resolution which is high relative to a low resolution available from supplied clock pulses. A first lumped constant delay (20) provides a first output signal (24) at predetermined interpolation intervals corresponding to the desired high resolution time interval. Latching circuits (26, 28) latch the high resolution data (24) to form a first synchronizing data set (60). A selected time interval has been preset to internal counters (142, 146, 154) and corrected for circuit propagation delay times having the same order of magnitude as the desired high resolution. Internal system clock pulses (32, 34) count down the counters to generate an internal pulse delayed by an interval which is functionally related to the preset time interval. A second LCD (184) corrects the internal signal with the high resolution time delay. A second internal pulse is then applied to a third LCD (74) to generate a second set of synchronizing data (76) which is complementary with the first set of synchronizing data (60) for presentation to logic circuits (64). The logic circuits (64) further delay the internal output signal (72) to obtain a proper phase relationship of an output signal (80) with the internal pulses (32, 34). The final delayed output signal (80) thereafter enables the output pulse generator (82) to produce the desired output pulse (84) at the preset time delay interval following input of the trigger pulse (10, 12).

  16. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  17. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  18. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  19. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  20. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  4. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  6. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  7. An Analysis of the Loess Landslide Based on High Spatial Resolution of Satellite Images%基于高空间分辨率卫星影像的黄土滑坡灾害解译

    Institute of Scientific and Technical Information of China (English)

    邹艳琴

    2014-01-01

    The Loess Plateau is vast and vulnerable to serious and frequent geological disasters such as storms. As an advanced technology, remote sensing is playing an important role in de-tecting geological disasters. The satellite images of high spatial resolution can quickly determine the distribution, scale and affected objects and therefore is of great significance for the preven-ting and controlling of natural disasters. Based on data SPOT-5 of high spatial resolution, an analysis is made of the remote sensing and the information extraction of landslides. The outcome is supposed to serve as an example of remote sensing interpretation of geological disaster.%黄土高原地域广袤,地形破碎,暴雨集中,地质灾害频发,为地质灾害防治工作带来了诸多的困难。遥感作为一个先进技术已在区域地质灾害宏观调查中发挥了重要作用,特别是通过高分辨率卫星影像能快速、准确的分辨和了解地质灾害的分布、规模及危害对象,对黄土高原区地质灾害的防治工作具有重要的指导作用和意义。以高空间分辨率的SPOT-5数据为例,分析了对黄土滑坡灾害遥感解译标志与信息提取,为黄土高原地区的遥感解译地质灾害提供示例。

  8. 高分辨率卫星立体影像对的图割匹配算法%Stereo matching algorithm based on improved graph cuts for high spatial resolution satellite stereo pair

    Institute of Scientific and Technical Information of China (English)

    王瑞瑞; 石伟; 黄华国

    2013-01-01

    针对高分辨率卫星立体像对自动匹配中同名特征点难以选取,导致视差图较低的问题,引入在计算机领域取得成功应用的图割匹配算法,将立体匹配问题转换为全局能量函数的最小化问题,并进行改进,构建简化的网络求解最小割,实现能量函数的最小化,得到较为准确的视差图,实现卫星立体像对的匹配。该文选取EROS-B卫星立体像对进行试验,结果证明改进的图割立体匹配算法生成视差图的均方根误差是传统基于相关系数的区域匹配算法生成视差图的均方根误差的1/3,且算法运行时间比传统的图割立体匹配算法的运行时间缩短了85.2%。该研究可为基于卫星立体像对构建高精度数字高程模型提供前提条件。%Many objects have clear contour and texture in the high spatial resolution satellite stereo pair. Due to the elevation differences in many objects, and the existence of building shades, and the similar objects, and so on, the extraction of corresponding feature points from the high spatial resolution satellite stereo pair is difficult, which leads to a rough disparity map. Aiming at the problem, the graph cuts algorithm, which has a successful application in the computer vision field, was introduced and improved for the stereo matching. The core problem of stereo matching is to compute the optimal disparity value. Based on this rule, the graph cuts constructs the global energy function by using the disparity value of all the pixels, and transforms the problem of stereo matching to the problem of minimization of the global energy function. However, there are two problems existing in the process of stereo matching by using the traditional graph cuts for the high-resolution satellite stereo pair. The first one is that the time complexity is high; the other one is that the disparity map has a lower precision. Aiming to the aforementioned two problems, the graph cuts

  9. The application of very high resolution satellite image in urban vegetation cover investigation: a case study of Xiamen City%应用高精度卫星图像进行城市植被覆盖调查:以厦门市为例

    Institute of Scientific and Technical Information of China (English)

    程承旗; 李滨; 马廷

    2003-01-01

    With the technological improvements of satellite sensors, we will acquire more informationabout the earth so that we have reached a new application epoch of observation on earthenvironmental change and cartography. But with the enhancement of spatial resolution, somequestions have arisen in the application of using traditional image processing and classificationmethods. Aiming for such questions, we studied the application of IKONOS very high resolutionimage (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the differencebetween the very high resolution image and traditional low spatial resolution image at classification,information abstraction etc. It is an advantageous test for the large-scale application of very highresolution data in the future.

  10. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  11. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  12. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  13. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  14. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: Chapter DD in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  15. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: Chapter EE in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  16. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  17. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  18. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  19. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  20. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  4. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  6. Coverage Options for a Low cost, High Resolution Optical Constellation

    OpenAIRE

    Price, M E; Levett, W.; Graham, K.

    2003-01-01

    This paper presents the range of coverage options available to TopSat like small satellites, both singly and in a small constellation. TopSat is a low-cost, high resolution and image quality, optical small satellite, due for launch in October 2004. In particular, the paper considers the use of tuned, repeat ground track orbits to improve coverage for selected ground targets, at the expense of global coverage. TopSat is designed to demonstrate the capabilities of small satellites for high valu...

  7. 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 NigeriaSat...

  8. Tracing high time-resolution fluctuations in dissolved organic carbon using satellite and buoy observations: Case study in Lake Taihu, China

    Science.gov (United States)

    Huang, Changchun; Yunmei, Li; Liu, Ge; Guo, Yulong; Yang, Hao; Zhu, A.-xing; Song, Ting; Huang, Tao; Zhang, Mingli; Shi, Kun

    2017-10-01

    Field measurements of dissolved organic carbon (DOC) concentration and remote-sensing reflectance were conducted to develop a regional, empirical red-blue algorithm to retrieve surface DOC from Geostationary Ocean Color Imager (GOCI) data for Lake Taihu, China. The auxiliary data (in-situ observations of the optical properties and water quality, buoy measurements of hydrodynamic data and water chemical parameters) were used to investigate the spatial and temporal variations in DOC. GOCI was shown to be capable of successfully obtaining hourly variations in DOC, with a root mean square error percentage (RMSP) of 17.29% (RMSE = 0.69 mg/L) for the match-up data. The GOCI-derived DOC in Lake Taihu confirms that the highest DOC concentration is in northwest Lake Taihu, followed by Meiliang Bay, Gonghu Bay and northeast Lake Taihu. Hourly DOC variation is significant and presents a different trend for each lake segment due to the variety of influencing factors. Discharge of DOC from surrounding rivers is an important factor to the variation of DOC in northeast Lake Taihu. However, organic products of algae will be the primary contributor to DOC when algal bloom occurred. During the period of algal bloom, high DOC levels in Lake Taihu can lead to hypoxia when coupled with high temperatures and low disturbance.

  9. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    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

  10. High Resolution Orientation Imaging Microscopy

    Science.gov (United States)

    2012-05-02

    carbon distribution as it relates to the presence of Bainite phase (with small tetragonality) interspersed among the cubic ferrite. An example of the...preferentially segregate. The view offered by these high resolution methods differs from what has been considered before: grains thought to be Bainite

  11. High-Resolution Instrumentation Radar.

    Science.gov (United States)

    1986-09-30

    30 September 1986 Los Angeles Air Force Station 13. NUMBER OF PAGES Los Angeles, Calif. 90009-2960 36 74. MONITORING AGENCY NAME & ADDRESS(If...TREE PLMUT ",-20 -CUTLIASS DumpER SED AN... TREE TRUNK, -0 - MERC BUMPER f - 40 H!-I -50 iI Fig. 7. High-Resolution Instrumentation Radar View of

  12. Fuel type characterization based on coarse resolution MODIS satellite data

    Directory of Open Access Journals (Sweden)

    Lanorte A

    2007-01-01

    Full Text Available Fuel types is one of the most important factors that should be taken into consideration for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. In the present study, forest fuel mapping is considered from a remote sensing perspective. The purpose is to delineate forest types by exploring the use of coarse resolution satellite remote sensing MODIS imagery. In order to ascertain how well MODIS data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers and complex topography was analysed. The study area is located in the South of Italy. Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing MODIS data, were used as ground-truth dataset to assess the obtained results. The method comprised the following three steps: (I adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II model construction for the spectral characterization and mapping of fuel types based on two different approach, maximum likelihood (ML classification algorithm and spectral Mixture Analysis (MTMF; (III accuracy assessment for the performance evaluation based on the comparison of MODIS-based results with ground-truth. Results from our analyses showed that the use of remotely sensed MODIS data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 73% for ML classifier and higher than 83% for MTMF.

  13. Requirements on high resolution detectors

    Energy Technology Data Exchange (ETDEWEB)

    Koch, A. [European Synchrotron Radiation Facility, Grenoble (France)

    1997-02-01

    For a number of microtomography applications X-ray detectors with a spatial resolution of 1 {mu}m are required. This high spatial resolution will influence and degrade other parameters of secondary importance like detective quantum efficiency (DQE), dynamic range, linearity and frame rate. This note summarizes the most important arguments, for and against those detector systems which could be considered. This article discusses the mutual dependencies between the various figures which characterize a detector, and tries to give some ideas on how to proceed in order to improve present technology.

  14. Ionosphere influence on success rate of GPS ambiguity resolution in a satellite formation flying

    Science.gov (United States)

    Baroni, Leandro

    2015-10-01

    Satellite formation flying is one of the most promising technologies for future space missions. The distribution of sensors and payloads among different satellites provides more redundancy, flexibility, improved communication coverage, among other advantages. One of the fundamental issues in spacecraft formation flying is precise position and velocity determination between satellites. For missions in low Earth orbits, GPS system can meet the precision requirement in relative positioning, since the satellite dynamics is modeled properly. The key for high accuracy GPS relative positioning is to resolve the ambiguities to their integer values. Ambiguities resolved successfully can improve the positioning accuracy to decimetre or even millimetre-level. So, integer carrier phase ambiguity resolution is often a prerequisite for high precision GPS positioning. The determination of relative position was made using an extended Kalman filter. The filter must take into account imperfections in dynamic modeling of perturbations affecting the orbital flight, and changes in solar activity that affects the GPS signal propagation, for mitigating these effects on relative positioning accuracy. Thus, this work aims to evaluate the impact of ionosphere variation, caused by changes in solar activity, in success rate of ambiguity resolution. Using the Ambiguity Dilution of Precision (ADOP) concept, the ambiguity success rate is analyzed and the expected precision of the ambiguity-fixed solution is calculated. Evaluations were performed using actual data from GRACE mission and analyzed for their performance in real scenarios. Analyses were conducted in different configurations of relative position and during different levels of solar activity. Results bring the impact of various disturbances and modeling of solar activity level on the success rate of ambiguity resolution.

  15. Retrieval of HCFC-142b (CH3CClF2) from ground-based high-resolution infrared solar spectra: Atmospheric increase since 1989 and comparison with surface and satellite measurements

    Science.gov (United States)

    Mahieu, Emmanuel; Lejeune, Bernard; Bovy, Benoît; Servais, Christian; Toon, Geoffrey C.; Bernath, Peter F.; Boone, Christopher D.; Walker, Kaley A.; Reimann, Stefan; Vollmer, Martin K.; O'Doherty, Simon

    2017-01-01

    We have developed an approach for retrieving HCFC-142b (CH3CClF2) from ground-based high-resolution infrared solar spectra, using its ν7 band Q branch in the 900-906 cm-1 interval. Interferences by HNO3, CO2 and H2O have to be accounted for. Application of this approach to observations recorded within the framework of long-term monitoring activities carried out at the northern mid-latitude, high-altitude Jungfraujoch station in Switzerland (46.5°N, 8.0°E, 3580 m above sea level) has provided a total column times series spanning the 1989 to mid-2015 time period. A fit to the HCFC-142b daily mean total column time series shows a statistically-significant long-term trend of (1.23±0.08×1013 molec cm-2) per year from 2000 to 2010, at the 2-σ confidence level. This corresponds to a significant atmospheric accumulation of (0.94±0.06) ppt (1 ppt=1/1012) per year for the mean tropospheric mixing ratio, at the 2-σ confidence level. Over the subsequent time period (2010-2014), we note a significant slowing down in the HCFC-142b buildup. Our ground-based FTIR (Fourier Transform Infrared) results are compared with relevant data sets derived from surface in situ measurements at the Mace Head and Jungfraujoch sites of the AGAGE (Advanced Global Atmospheric Gases Experiment) network and from occultation measurements by the ACE-FTS (Atmospheric Chemistry Experiment-Fourier Transform Spectrometer) instrument on-board the SCISAT satellite.

  16. Spacecraft design project: High latitude communications satellite

    Science.gov (United States)

    Josefson, Carl; Myers, Jack; Cloutier, Mike; Paluszek, Steve; Michael, Gerry; Hunter, Dan; Sakoda, Dan; Walters, Wes; Johnson, Dennis; Bauer, Terry

    1989-01-01

    The spacecraft design project was part of AE-4871, Advanced Spacecraft Design. The project was intended to provide experience in the design of all major components of a satellite. Each member of the class was given primary responsibility for a subsystem or design support function. Support was requested from the Naval Research Laboratory to augment the Naval Postgraduate School faculty. Analysis and design of each subsystem was done to the extent possible within the constraints of an eleven week quarter and the design facilities (hardware and software) available. The project team chose to evaluate the design of a high latitude communications satellite as representative of the design issues and tradeoffs necessary for a wide range of satellites. The High-Latitude Communications Satellite (HILACS) will provide a continuous UHF communications link between stations located north of the region covered by geosynchronous communications satellites, i.e., the area above approximately 60 N latitude. HILACS will also provide a communications link to stations below 60 N via a relay Net Control Station (NCS), which is located with access to both the HILACS and geosynchronous communications satellites. The communications payload will operate only for that portion of the orbit necessary to provide specified coverage.

  17. High resolution tomographic instrument development

    Energy Technology Data Exchange (ETDEWEB)

    1992-08-01

    Our recent work has concentrated on the development of high-resolution PET instrumentation reflecting in part the growing importance of PET in nuclear medicine imaging. We have developed a number of positron imaging instruments and have the distinction that every instrument has been placed in operation and has had an extensive history of application for basic research and clinical study. The present program is a logical continuation of these earlier successes. PCR-I, a single ring positron tomograph was the first demonstration of analog coding using BGO. It employed 4 mm detectors and is currently being used for a wide range of biological studies. These are of immense importance in guiding the direction for future instruments. In particular, PCR-II, a volume sensitive positron tomograph with 3 mm spatial resolution has benefited greatly from the studies using PCR-I. PCR-II is currently in the final stages of assembly and testing and will shortly be placed in operation for imaging phantoms, animals and ultimately humans. Perhaps the most important finding resulting from our previous study is that resolution and sensitivity must be carefully balanced to achieve a practical high resolution system. PCR-II has been designed to have the detection characteristics required to achieve 3 mm resolution in human brain under practical imaging situations. The development of algorithms by the group headed by Dr. Chesler is based on a long history of prior study including his joint work with Drs. Pelc and Reiderer and Stearns. This body of expertise will be applied to the processing of data from PCR-II when it becomes operational.

  18. High resolution tomographic instrument development

    Energy Technology Data Exchange (ETDEWEB)

    1992-01-01

    Our recent work has concentrated on the development of high-resolution PET instrumentation reflecting in part the growing importance of PET in nuclear medicine imaging. We have developed a number of positron imaging instruments and have the distinction that every instrument has been placed in operation and has had an extensive history of application for basic research and clinical study. The present program is a logical continuation of these earlier successes. PCR-I, a single ring positron tomograph was the first demonstration of analog coding using BGO. It employed 4 mm detectors and is currently being used for a wide range of biological studies. These are of immense importance in guiding the direction for future instruments. In particular, PCR-II, a volume sensitive positron tomograph with 3 mm spatial resolution has benefited greatly from the studies using PCR-I. PCR-II is currently in the final stages of assembly and testing and will shortly be placed in operation for imaging phantoms, animals and ultimately humans. Perhaps the most important finding resulting from our previous study is that resolution and sensitivity must be carefully balanced to achieve a practical high resolution system. PCR-II has been designed to have the detection characteristics required to achieve 3 mm resolution in human brain under practical imaging situations. The development of algorithms by the group headed by Dr. Chesler is based on a long history of prior study including his joint work with Drs. Pelc and Reiderer and Stearns. This body of expertise will be applied to the processing of data from PCR-II when it becomes operational.

  19. HRSC: High resolution stereo camera

    Science.gov (United States)

    Neukum, G.; Jaumann, R.; Basilevsky, A.T.; Dumke, A.; Van Gasselt, S.; Giese, B.; Hauber, E.; Head, J. W.; Heipke, C.; Hoekzema, N.; Hoffmann, H.; Greeley, R.; Gwinner, K.; Kirk, R.; Markiewicz, W.; McCord, T.B.; Michael, G.; Muller, Jan-Peter; Murray, J.B.; Oberst, J.; Pinet, P.; Pischel, R.; Roatsch, T.; Scholten, F.; Willner, K.

    2009-01-01

    The High Resolution Stereo Camera (HRSC) on Mars Express has delivered a wealth of image data, amounting to over 2.5 TB from the start of the mapping phase in January 2004 to September 2008. In that time, more than a third of Mars was covered at a resolution of 10-20 m/pixel in stereo and colour. After five years in orbit, HRSC is still in excellent shape, and it could continue to operate for many more years. HRSC has proven its ability to close the gap between the low-resolution Viking image data and the high-resolution Mars Orbiter Camera images, leading to a global picture of the geological evolution of Mars that is now much clearer than ever before. Derived highest-resolution terrain model data have closed major gaps and provided an unprecedented insight into the shape of the surface, which is paramount not only for surface analysis and geological interpretation, but also for combination with and analysis of data from other instruments, as well as in planning for future missions. This chapter presents the scientific output from data analysis and highlevel data processing, complemented by a summary of how the experiment is conducted by the HRSC team members working in geoscience, atmospheric science, photogrammetry and spectrophotometry. Many of these contributions have been or will be published in peer-reviewed journals and special issues. They form a cross-section of the scientific output, either by summarising the new geoscientific picture of Mars provided by HRSC or by detailing some of the topics of data analysis concerning photogrammetry, cartography and spectral data analysis.

  20. Section on High Resolution Optical Imaging (HROI)

    Data.gov (United States)

    Federal Laboratory Consortium — The Section on High Resolution Optical Imaging (HROI) develops novel technologies for studying biological processes at unprecedented speed and resolution. Research...

  1. Improving the Resolution of X-Ray Telescopes with Occulting Satellites

    CERN Document Server

    Copi, C J; Copi, Craig J.; Starkman, Glenn D.

    2000-01-01

    One of the challenges of X-ray astronomy is how to both collect large numbersof photons yet attain high angular resolution. Because X-ray telescopes utilizegrazing optics, to collect more photons requires a larger acceptance anglewhich in turn compromises the angular resolution. All X-ray telescopes thushave angular resolution far poorer than their diffraction limit. Althoughcollecting more photons is a desirable goal, sometimes selective collectingfewer photons may yield more information. Natural (such as lunar) occultationshave long been used to study sources on small angular scales. But naturalocculters are of limited utility because of their large angular velocitiesrelative to the telescope, and because of the serendipity of their transits. Wedescribe here how one can make use of an X-ray Big Occulting SteerableSatellite (X-BOSS) to achieve very-high resolution of X-ray sources. An X-BOSScould significantly improve the resolution of existing X-ray facilities such asthe Chandra telescope, or X-ray Multiple...

  2. Monitoring of oil pollution in the Arabian Gulf based on medium resolution satellite imagery

    Science.gov (United States)

    Zhao, J.; Ghedira, H.

    2013-12-01

    A large number of inland and offshore oil fields are located in the Arabian Gulf where about 25% of the world's oil is produced by the countries surrounding the Arabian Gulf region. Almost all of this oil production is shipped by sea worldwide through the Strait of Hormuz making the region vulnerable to environmental and ecological threats that might arise from accidental or intentional oil spills. Remote sensing technologies have the unique capability to detect and monitor oil pollutions over large temporal and spatial scales. Synoptic satellite imaging can date back to 1972 when Landsat-1 was launched. Landsat satellite missions provide long time series of imagery with a spatial resolution of 30 m. MODIS sensors onboard NASA's Terra and Aqua satellites provide a wide and frequent coverage at medium spatial resolution, i.e. 250 m and 500, twice a day. In this study, the capability of medium resolution MODIS and Landsat data in detecting and monitoring oil pollutions in the Arabian Gulf was tested. Oil spills and slicks show negative or positive contrasts in satellite derived RGB images compared with surrounding clean waters depending on the solar/viewing geometry, oil thickness and evolution, etc. Oil-contaminated areas show different spectral characteristics compared with surrounding waters. Rayleigh-corrected reflectance at the seven medium resolution bands of MODIS is lower in oil affected areas. This is caused by high light absorption of oil slicks. 30-m Landsat image indicated the occurrence of oil spill on May 26 2000 in the Arabian Gulf. The oil spill showed positive contrast and lower temperature than surrounding areas. Floating algae index (FAI) images are also used to detect oil pollution. Oil-contaminated areas were found to have lower FAI values. To track the movement of oil slicks found on October 21 2007, ocean circulations from a HYCOM model were examined and demonstrated that the oil slicks were advected toward the coastal areas of United Arab

  3. 100-Meter Resolution Satellite View with Shaded Relief of Alaska - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View with Shaded Relief of Alaska map layer is a 100-meter resolution simulated natural-color image of Alaska, with relief shading added to accentuate...

  4. 100-Meter Resolution Satellite View of the Conterminous United States - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View of the Conterminous United States map layer is a 100-meter resolution simulated natural-color image of the United States. Vegetation is generally...

  5. USGS Small-scale Dataset - 100-Meter Resolution Satellite View of Hawaii 201304 GeoTIFF

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View of Hawaii map layer is a 100-meter resolution simulated natural-color image of Hawaii. Vegetation is generally green, with forests in darker green...

  6. 100-Meter Resolution Satellite View with Shaded Relief of the Conterminous United States - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View with Shaded Relief of the Conterminous United States map layer is a 100-meter resolution simulated natural-color image of the United States, with...

  7. USGS Small-scale Dataset - 100-Meter Resolution Satellite View of Alaska 201304 GeoTIFF

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View of Alaska map layer is a 100-meter resolution simulated natural-color image of Alaska. Vegetation is generally green, with forests in darker green...

  8. 100-Meter Resolution Satellite View with Shaded Relief of Hawaii - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View with Shaded Relief of Hawaii map layer is a 100-meter resolution simulated natural-color image of Hawaii, with relief shading added to accentuate...

  9. The Impact of Horizontal and Temporal Resolution on Convection and Precipitation with High-Resolution GEOS-5

    Science.gov (United States)

    Putman, William P.

    2012-01-01

    Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.

  10. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  11. GHRSST Level 2P Regional 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  12. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  13. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite produced by NAVO (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  14. GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-B satellite produced by NAVO (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  15. GHRSST Level 2P Global Skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite produced by EUMETSAT (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated...

  16. GHRSST Level 2P sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated...

  17. GHRSST Level 2P sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated...

  18. 1962 Satellite High Altitude Radiation Belt Database

    Science.gov (United States)

    2014-03-01

    TR-14-18 1962 Satellite High Altitude Radiation Belt Database Approved for public release; distribution is unlimited. March...the Status of the High Altitude Nuclear Explosion (HANE) Trapped Radiation Belt Database”, AFRL-VS-PS-TR- 2006-1079, Air Force Research Laboratory...Roth, B., “Blue Ribbon Panel and Support Work Assessing the Status of the High Altitude Nuclear Explosion (HANE) Trapped Radiation Belt Database

  19. High-resolution intravital microscopy.

    Directory of Open Access Journals (Sweden)

    Volker Andresen

    Full Text Available Cellular communication constitutes a fundamental mechanism of life, for instance by permitting transfer of information through synapses in the nervous system and by leading to activation of cells during the course of immune responses. Monitoring cell-cell interactions within living adult organisms is crucial in order to draw conclusions on their behavior with respect to the fate of cells, tissues and organs. Until now, there is no technology available that enables dynamic imaging deep within the tissue of living adult organisms at sub-cellular resolution, i.e. detection at the level of few protein molecules. Here we present a novel approach called multi-beam striped-illumination which applies for the first time the principle and advantages of structured-illumination, spatial modulation of the excitation pattern, to laser-scanning-microscopy. We use this approach in two-photon-microscopy--the most adequate optical deep-tissue imaging-technique. As compared to standard two-photon-microscopy, it achieves significant contrast enhancement and up to 3-fold improved axial resolution (optical sectioning while photobleaching, photodamage and acquisition speed are similar. Its imaging depth is comparable to multifocal two-photon-microscopy and only slightly less than in standard single-beam two-photon-microscopy. Precisely, our studies within mouse lymph nodes demonstrated 216% improved axial and 23% improved lateral resolutions at a depth of 80 µm below the surface. Thus, we are for the first time able to visualize the dynamic interactions between B cells and immune complex deposits on follicular dendritic cells within germinal centers (GCs of live mice. These interactions play a decisive role in the process of clonal selection, leading to affinity maturation of the humoral immune response. This novel high-resolution intravital microscopy method has a huge potential for numerous applications in neurosciences, immunology, cancer research and

  20. High-resolution image analysis.

    Science.gov (United States)

    Preston, K

    1986-01-01

    In many departments of cytology, cytogenetics, hematology, and pathology, research projects using high-resolution computerized microscopy are now being mounted for computation of morphometric measurements on various structural components, as well as for determination of cellular DNA content. The majority of these measurements are made in a partially automated, computer-assisted mode, wherein there is strong interaction between the user and the computerized microscope. At the same time, full automation has been accomplished for both sample preparation and sample examination for clinical determination of the white blood cell differential count. At the time of writing, approximately 1,000 robot differential counting microscopes are in the field, analyzing images of human white blood cells, red blood cells, and platelets at the overall rate of about 100,000 slides per day. This mammoth through-put represents a major accomplishment in the application of machine vision to automated microscopy for hematology. In other areas of automated high-resolution microscopy, such as cytology and cytogenetics, no commercial instruments are available (although a few metaphase-finding machines are available and other new machines have been announced during the past year). This is a disappointing product, considering the nearly half century of research effort in these areas. This paper provides examples of the state of the art in automation of cell analysis for blood smears, cervical smears, and chromosome preparations. Also treated are new developments in multi-resolution automated microscopy, where images are now being generated and analyzed by a single machine over a range of 64:1 magnification and from 10,000 X 20,000 to 500 X 500 in total picture elements (pixels). Examples of images of human lymph node and liver tissue are presented. Semi-automated systems are not treated, although there is mention of recent research in the automation of tissue analysis.

  1. GNSS Carrier Phase Integer Ambiguity Resolution with Camera and Satellite images

    Science.gov (United States)

    Henkel, Patrick

    2015-04-01

    Ambiguity Resolution is the key to high precision position and attitude determination with GNSS. However, ambiguity resolution of kinematic receivers becomes challenging in environments with substantial multipath, limited satellite availability and erroneous cycle slip corrections. There is a need for other sensors, e.g. inertial sensors that allow an independent prediction of the position. The change of the predicted position over time can then be used for cycle slip detection and correction. In this paper, we provide a method to improve the initial ambiguity resolution for RTK and PPP with vision-based position information. Camera images are correlated with geo-referenced aerial/ satellite images to obtain an independent absolute position information. This absolute position information is then coupled with the GNSS and INS measurements in an extended Kalman filter to estimate the position, velocity, acceleration, attitude, angular rates, code multipath and biases of the accelerometers and gyroscopes. The camera and satellite images are matched based on some characteristic image points (e.g. corners of street markers). We extract these characteristic image points from the camera images by performing the following steps: An inverse mapping (homogenous projection) is applied to transform the camera images from the driver's perspective to bird view. Subsequently, we detect the street markers by performing (a) a color transformation and reduction with adaptive brightness correction to focus on relevant features, (b) a subsequent morphological operation to enhance the structure recognition, (c) an edge and corner detection to extract feature points, and (d) a point matching of the corner points with a template to recognize the street markers. We verified the proposed method with two low-cost u-blox LEA 6T GPS receivers, the MPU9150 from Invensense, the ASCOS RTK corrections and a PointGrey camera. The results show very precise and seamless position and attitude

  2. Developing an efficient technique for satellite image denoising and resolution enhancement for improving classification accuracy

    Science.gov (United States)

    Thangaswamy, Sree Sharmila; Kadarkarai, Ramar; Thangaswamy, Sree Renga Raja

    2013-01-01

    Satellite images are corrupted by noise during image acquisition and transmission. The removal of noise from the image by attenuating the high-frequency image components removes important details as well. In order to retain the useful information, improve the visual appearance, and accurately classify an image, an effective denoising technique is required. We discuss three important steps such as image denoising, resolution enhancement, and classification for improving accuracy in a noisy image. An effective denoising technique, hybrid directional lifting, is proposed to retain the important details of the images and improve visual appearance. The discrete wavelet transform based interpolation is developed for enhancing the resolution of the denoised image. The image is then classified using a support vector machine, which is superior to other neural network classifiers. The quantitative performance measures such as peak signal to noise ratio and classification accuracy show the significance of the proposed techniques.

  3. High-Resolution Mass Spectrometers

    Science.gov (United States)

    Marshall, Alan G.; Hendrickson, Christopher L.

    2008-07-01

    Over the past decade, mass spectrometry has been revolutionized by access to instruments of increasingly high mass-resolving power. For small molecules up to ˜400 Da (e.g., drugs, metabolites, and various natural organic mixtures ranging from foods to petroleum), it is possible to determine elemental compositions (CcHhNnOoSsPp…) of thousands of chemical components simultaneously from accurate mass measurements (the same can be done up to 1000 Da if additional information is included). At higher mass, it becomes possible to identify proteins (including posttranslational modifications) from proteolytic peptides, as well as lipids, glycoconjugates, and other biological components. At even higher mass (˜100,000 Da or higher), it is possible to characterize posttranslational modifications of intact proteins and to map the binding surfaces of large biomolecule complexes. Here we review the principles and techniques of the highest-resolution analytical mass spectrometers (time-of-flight and Fourier transform ion cyclotron resonance and orbitrap mass analyzers) and describe some representative high-resolution applications.

  4. Seasonal variabilty of surface velocities and ice discharge of Columbia Glacier, Alaska using high-resolution TanDEM-X satellite time series and NASA IceBridge data

    Science.gov (United States)

    Vijay, Saurabh; Braun, Matthias

    2014-05-01

    Columbia Glacier is a grounded tidewater glacier located on the south coast of Alaska. It has lost half of its volume during 1957-2007, more rapidly after 1980. It is now split into two branches, known as Main/East and West branch due to the dramatic retreat of ~ 23 km and calving of iceberg from its terminus in past few decades. In Alaska, a majority of the mass loss from glaciers is due to rapid ice flow and calving icebergs into tidewater and lacustrine environments. In addition, submarine melting and change in the frontal position can accelerate the ice flow and calving rate. We use time series of high-resolution TanDEM-X stripmap satellite imagery during 2011-2013. The active image of the bistatic TanDEM-X acquisitions, acquired over 11 or 22 day repeat intervals, are utilized to derive surface velocity fields using SAR intensity offset tracking. Due to the short temporal baselines, the precise orbit control and the high-resolution of the data, the accuracies of the velocity products are high. We observe a pronounce seasonal signal in flow velocities close to the glacier front of East/Main branch of Columbia Glacier. Maximum values at the glacier front reach up to 14 m/day were recorded in May 2012 and 12 m/day in June 2013. Minimum velocities at the glacier front are generally observed in September and October with lowest values below 2 m/day in October 2012. Months in between those dates show corresponding increase or deceleration resulting a kind of sinusoidal annual course of the surface velocity at the glacier front. The seasonal signal is consistently decreasing with the distance from the glacier front. At a distance of 17.5 km from the ice front, velocities are reduced to 2 m/day and almost no seasonal variability can be observed. We attribute these temporal and spatial variability to changes in the basal hydrology and lubrification of the glacier bed. Closure of the basal drainage system in early winter leads to maximum speeds while during a fully

  5. Ultra-high resolution AMOLED

    Science.gov (United States)

    Wacyk, Ihor; Prache, Olivier; Ghosh, Amal

    2011-06-01

    AMOLED microdisplays continue to show improvement in resolution and optical performance, enhancing their appeal for a broad range of near-eye applications such as night vision, simulation and training, situational awareness, augmented reality, medical imaging, and mobile video entertainment and gaming. eMagin's latest development of an HDTV+ resolution technology integrates an OLED pixel of 3.2 × 9.6 microns in size on a 0.18 micron CMOS backplane to deliver significant new functionality as well as the capability to implement a 1920×1200 microdisplay in a 0.86" diagonal area. In addition to the conventional matrix addressing circuitry, the HDTV+ display includes a very lowpower, low-voltage-differential-signaling (LVDS) serialized interface to minimize cable and connector size as well as electromagnetic emissions (EMI), an on-chip set of look-up-tables for digital gamma correction, and a novel pulsewidth- modulation (PWM) scheme that together with the standard analog control provides a total dimming range of 0.05cd/m2 to 2000cd/m2 in the monochrome version. The PWM function also enables an impulse drive mode of operation that significantly reduces motion artifacts in high speed scene changes. An internal 10-bit DAC ensures that a full 256 gamma-corrected gray levels are available across the entire dimming range, resulting in a measured dynamic range exceeding 20-bits. This device has been successfully tested for operation at frame rates ranging from 30Hz up to 85Hz. This paper describes the operational features and detailed optical and electrical test results for the new AMOLED WUXGA resolution microdisplay.

  6. Applying high-resolution satellite images to estimate tree diversity of mixed broadleaf-Korean pine forest%应用高分辨率卫星数据估算阔叶红松林乔木多样性

    Institute of Scientific and Technical Information of China (English)

    解潍嘉; 黄侃; 李瑞平; 孙浩; 扈晶晶; 黄华国

    2015-01-01

    应用遥感技术估算生物多样性是森林生态学的研究热点和难点。为探索高分辨率卫星数据在估算森林植被多样性上的应用潜力,以吉林蛟河市阔叶红松林大样地数据为支撑,提取了红松树冠的空间分布格局,并估算了乔木物种多样性。首先,基于冬季GeoEye-1影像提取红松树冠分布图,与样地每木调查数据吻合较好。然后,使用景观生态学和地统计学指数,分析红松种群空间分布规律,发现了最大自相关尺度30~40 m。最后,选择拥有红边波段的秋季RapidEye卫星图像,建立遥感影像5 m光谱值和30 m窗口大小纹理参数与生物多样性指数的多元线性回归模型。结果表明,红边信息并未显著改善多光谱数据估算植被生物多样性的能力,但所获大区域制图结果与林分龄级吻合较好。%The application of remote sensing technology to estimate forest biodiversity is a research hotspot and challenge in forest ecology. To explore the potential of high-resolution satellite data in estimating forest vegetation diversity, we extracted the spatial pattern of Korean pine ( Pinus koraiensis) canopies, and estimated the arbor species diversity, supported by field large plot data in Jiaohe, Jilin Province. First, we extracted the Korean pine canopy distribution based on a GeoEye-1 winter image, which agreed well with individual tree position measured in situ. Then, we analyzed the spatial population distribution of Korean pine using landscape ecology and geostatistics index, which was found to have a maximum autocorrelation scale of 30--40 m. Finally, we used a RapidEye satellite image with a special red edge band in autumn to establish multiple linear regression model with plot diversity data. The model linked remote sensing image spectral values ( 5 m ) and texture parameters ( 30 m window size ) with species diversity. Results showed that red edge information did not significantly

  7. High-resolution slug testing.

    Science.gov (United States)

    Zemansky, G M; McElwee, C D

    2005-01-01

    The hydraulic conductivity (K) variation has important ramifications for ground water flow and the transport of contaminants in ground water. The delineation of the nature of that variation can be critical to complete characterization of a site and the planning of effective and efficient remedial measures. Site-specific features (such as high-conductivity zones) need to be quantified. Our alluvial field site in the Kansas River valley exhibits spatial variability, very high conductivities, and nonlinear behavior for slug tests in the sand and gravel aquifer. High-resolution, multilevel slug tests have been performed in a number of wells that are fully screened. A general nonlinear model based on the Navier-Stokes equation, nonlinear frictional loss, non-Darcian flow, acceleration effects, radius changes in the wellbore, and a Hvorslev model for the aquifer has been used to analyze the data, employing an automated processing system that runs within the Excel spreadsheet program. It is concluded that slug tests can provide the necessary data to identify the nature of both horizontal and vertical K variation in an aquifer and that improved delineation or higher resolution of K structure is possible with shorter test intervals. The gradation into zones of higher conductivity is sharper than seen previously, and the maximum conductivity observed is greater than previously measured. However, data from this project indicate that well development, the presence of fines, and the antecedent history of the well are important interrelated factors in regard to slug-test response and can prevent obtaining consistent results in some cases.

  8. Visibility conflict resolution for multiple antennae and multi-satellites via genetic algorithm

    Science.gov (United States)

    Lee, Junghyun; Hyun, Chung; Ahn, Hyosung; Wang, Semyung; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

    Satellite mission control systems typically are operated by scheduling missions to the visibility between ground stations and satellites. The communication for the mission is achieved by interacting with satellite visibility and ground station support. Specifically, the satellite forms a cone-type visibility passing over a ground station, and the antennas of ground stations support the satellite. When two or more satellites pass by at the same time or consecutively, the satellites may generate a visibility conflict. As the number of satellites increases, solving visibility conflict becomes important issue. In this study, we propose a visibility conflict resolution algorithm of multi-satellites by using a genetic algorithm (GA). The problem is converted to scheduling optimization modeling. The visibility of satellites and the supports of antennas are considered as tasks and resources individually. The visibility of satellites is allocated to the total support time of antennas as much as possible for users to obtain the maximum benefit. We focus on a genetic algorithm approach because the problem is complex and not defined explicitly. The genetic algorithm can be applied to such a complex model since it only needs an objective function and can approach a global optimum. However, the mathematical proof of global optimality for the genetic algorithm is very challenging. Therefore, we apply a greedy algorithm and show that our genetic approach is reasonable by comparing with the performance of greedy algorithm application.

  9. High-resolution land topography

    Science.gov (United States)

    Massonnet, Didier; Elachi, Charles

    2006-11-01

    After a description of the background, methods of production and some scientific uses of high-resolution land topography, we present the current status and the prospect of radar interferometry, regarded as one of the best techniques for obtaining the most global and the most accurate topographic maps. After introducing briefly the theoretical aspects of radar interferometry - principles, limits of operation and various capabilities -, we will focus on the topographic applications that resulted in an almost global topographic map of the earth: the SRTM map. After introducing the Interferometric Cartwheel system, we will build on its expected performances to discuss the scientific prospects of refining a global topographic map to sub-metric accuracy. We also show how other fields of sciences such as hydrology may benefit from the products generated by interferometric radar systems. To cite this article: D. Massonnet, C. Elachi, C. R. Geoscience 338 (2006).

  10. Physical Explanation on Designing Three Axes as Different Resolution Indexes from GRACE Satellite-Borne Accelerometer

    Institute of Scientific and Technical Information of China (English)

    ZHENG Wei; XU Hou-Ze; ZHONG Min; YUN Mei-Juan

    2008-01-01

    @@ The GRACE Earth's gravitational field complete up to degree and order 120 is recovered based on the same and different three-axis resolution indexes from satellite-borne accelerometer using the improved energy conservation principle. The results show that designing XA1(2) as low-sensitivity axis (3 × 10-9 m/s2) of accelerometer and designing YA1(2) and ZA1(2) as high-sensitivity axes (3 × 10-10m/s2) are reasonable. The physical reason why the resolution of XA1(2) is one order of magnitude lower than YA1(2) and ZA1(2) is that non-conservative forces acting on GRACE satellites axe mainly decomposed into YA1(2) and ZA1(2) in the orbital plane.Since X A1(2) is not orthogonal accurately to orbital plane during the development of accelerometer, the measurement of X A1(2) can not be thrown off entirely, but be reduced properly.

  11. Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

    Directory of Open Access Journals (Sweden)

    Jochen Zschau

    2012-05-01

    Full Text Available Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types. At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free- and open-source basis and aim at being transparent, usable and transferable.

  12. High resolution emission tomography; Tomographie d`emission haute resolution

    Energy Technology Data Exchange (ETDEWEB)

    Charon, Y.; Laniece, P.; Mastrippolito, R.; Pinot, L.; Ploux, L.; Valda Ochoa, A.; Valentin, L. [Groupe I.P.B., Experimental Research Division, Inst. de Physique Nucleaire, Paris-11 Univ., 91 - Orsay (France)

    1999-11-01

    We have developed an original high resolution tomograph for in-vivo small animal imaging. A first prototype is under evaluation. Initial results of its characterisation are presented. (authors) 3 figs.

  13. VT Hydrography Dataset - High Resolution NHD

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The Vermont Hydrography Dataset (VHD) is compliant with the local resolution (also known as High Resolution) National Hydrography Dataset (NHD)...

  14. High-resolution infrared imaging

    Science.gov (United States)

    Falco, Charles M.

    2010-08-01

    The hands and mind of an artist are intimately involved in the creative process of image formation, intrinsically making paintings significantly more complex than photographs to analyze. In spite of this difficulty, several years ago the artist David Hockney and I identified optical evidence within a number of paintings that demonstrated artists began using optical projections as early as c1425 - nearly 175 years before Galileo - as aids for producing portions of their images. In the course of our work, Hockney and I developed insights that I have been applying to a new approach to computerized image analysis. Recently I developed and characterized a portable high resolution infrared for capturing additional information from paintings. Because many pigments are semi-transparent in the IR, in a number of cases IR photographs ("reflectograms") have revealed marks made by the artists that had been hidden under paint ever since they were made. I have used this IR camera to capture photographs ("reflectograms") of hundreds of paintings in over a dozen museums on three continents and, in some cases, these reflectograms have provided new insights into decisions the artists made in creating the final images that we see in the visible.

  15. Change detection studies in and around Kolleru Lake using high resolution data

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, M.V.; Rao. K.H.; Ramana, I.V.; Sasamal, S.K.; Choudhury, S.B.; Bhan, S.K.

    under fish pond culture within the lake area using high resolution data from satellites. The changes that are occurred during the last ten years in Kolleru lake area have been studied. The digital base map covering the lake and surroundings...

  16. Ground mapping resolution accuracy of a scanning radiometer from a geostationary satellite.

    Science.gov (United States)

    Stremler, F G; Khalil, M A; Parent, R J

    1977-06-01

    Measures of the spatial and spatial rate (frequency) mapping of scanned visual imagery from an earth reference system to a spin-scan geostationary satellite are examined. Mapping distortions and coordinate inversions to correct for these distortions are formulated in terms of geometric transformations between earth and satellite frames of reference. Probabilistic methods are used to develop relations for obtainable mapping resolution when coordinate inversions are employed.

  17. High-resolution neutron tomography

    Energy Technology Data Exchange (ETDEWEB)

    Mikerov, V.I. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Zhitnik, I.A. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Ignat`ev, A.P. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Isakov, A.I. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Korneev, V.V. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Krutov, V.V. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Kuzin, S.V. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Oparin, S.N. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Pertsov, A.A. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Podolyak, E.R. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Sobel`man, I.I. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Tindo, I.P. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation); Tukarev, B.A. [P.N. Lebedev Physical Inst., RAN, Moscow (Russian Federation)

    1995-12-31

    A neutron tomography technique with a coordinate resolution of several tens of micrometers has been developed. Our results indicate that the technique resolves details with dimensions less than 100 {mu}m and measures a linear attenuation of less than {approx} 0.1 cm{sup -1}. Tomograms can be reconstructed using incomplete data. Limits on the resolution of the restored pattern are analyzed, and ways to improve the sensitivity of the technique are discussed. (orig.).

  18. Monitoring Yellow River ice disaster based on Chinese high-resolution satellite data%国产高分辨率卫星数据在黄河防凌监测中应用

    Institute of Scientific and Technical Information of China (English)

    陈琳; 杨中华; 马浩录; 陈杨

    2012-01-01

    自2002~2003年度首次启用遥感技术监测黄河凌情以来,到目前已连续进行了10个年度.10个年度的生产实践表明:国产高分辨率卫星遥感数据能够有效跟踪黄河凌情的发展过程,实现黄河凌情的日动态监测、重点时段的精细监测和突发凌汛灾害时的实时监测.黄河凌情尤其在封开河阶段,日变化非常显著,中巴资源卫星作为国产高分辨率可见光民用遥感卫星的代表,以其大视场、高空间、高时间分辨率的特点,动态监测凌情,基本做到每天实现一次全覆盖监测的能力,配合其他如中国遥感卫星等高分辨率可见光、雷达数据,初步实现了凌情发展预估、开河前的河道槽蓄水量计算、封开河期间冰凌险情监测以及发生凌汛灾害时灾情信息采集与评估,为黄河防凌调度、决策会商提供了有力的技术支持.%In the paper, the following conclusions were made based on the remote sensing monitoring results during 2002 and 2003; combination of multi-source remote sensing data could show the advantages of remote sensing, more effectively monitor the Yellow River ice disaster, and achieve real-time, dynamic and precision monitoring. Ice disaster of Yellow River obviously changes each day. Being a representative of Chinese remote sensing satellites in the visible, CBERS-02 /02B has achieved positive results in the previous monitoring. In the past two years, it has been fully utilized in environmental disaster reduction. CBERS-02/02B with high spatial and spectral resolution, achieving a full coverage every day, and its dynamic monitoring capability has significantly improved. Together with radar data, it can quickly monitor the emergency disaster, the location of entrances to the bursts, calculation of water storage, ice danger monitoring at beginning, and disaster information collection and assessment in process, assisting scheduling for the Yellow River ice and providing technical support

  19. High resolution solar soft X-ray spectrometer

    Institute of Scientific and Technical Information of China (English)

    ZHANG Fei; WANG Huan-Yu; PENG Wen-Xi; LIANG Xiao-Hua; ZHANG Chun-Lei; CAO Xue-Lei; JIANG Wei-Chun; ZHANG Jia-Yu; CUI Xing-Zhu

    2012-01-01

    A high resolution solar soft X-ray spectrometer (SOX) payload onboard a satellite is developed.A silicon drift detector (SDD) is adopted as the detector of the SOX spectrometer.The spectrometer consists of the detectors and their readout electronics,a data acquisition unit and a payload data handling unit.A ground test system is also developed to test SOX.The test results show that the design goals of the spectrometer system have been achieved.

  20. AIRBORNE HIGH-RESOLUTION DIGITAL IMAGING SYSTEM

    Directory of Open Access Journals (Sweden)

    Prado-Molina, J.

    2006-04-01

    Full Text Available A low-cost airborne digital imaging system capable to perform aerial surveys with small-format cameras isintroduced. The equipment is intended to obtain high-resolution multispectral digital photographs constituting so aviable alternative to conventional aerial photography and satellite imagery. Monitoring software handles all theprocedures involved in image acquisition, including flight planning, real-time graphics for aircraft position updatingin a mobile map, and supervises the main variables engaged in the imaging process. This software also creates fileswith the geographical position of the central point of every image, and the flight path followed by the aircraftduring the entire survey. The cameras are mounted on a three-axis stabilized platform. A set of inertial sensorsdetermines platform's deviations independently from the aircraft and an automatic control system keeps thecameras at a continuous nadir pointing and heading, with a precision better than ± 1 arc-degree in three-axis. Thecontrol system is also in charge of saving the platform’s orientation angles when the monitoring software triggersthe camera. These external orientation parameters, together with a procedure for camera calibration give theessential elements for image orthocorrection. Orthomosaics are constructed using commercial GIS software.This system demonstrates the feasibility of large area coverage in a practical and economical way using smallformatcameras. Monitoring and automatization reduce the work while increasing the quality and the amount ofuseful images.

  1. DUACS: Toward High Resolution Sea Level Products

    Science.gov (United States)

    Faugere, Y.; Gerald, D.; Ubelmann, C.; Claire, D.; Pujol, M. I.; Antoine, D.; Desjonqueres, J. D.; Picot, N.

    2016-12-01

    The DUACS system produces, as part of the CNES/SALP project, and the Copernicus Marine Environment and Monitoring Service, high quality multimission altimetry Sea Level products for oceanographic applications, climate forecasting centers, geophysic and biology communities... These products consist in directly usable and easy to manipulate Level 3 (along-track cross-calibrated SLA) and Level 4 products (multiple sensors merged as maps or time series) and are available in global and regional version (Mediterranean Sea, Arctic, European Shelves …).The quality of the products is today limited by the altimeter technology "Low Resolution Mode" (LRM), and the lack of available observations. The launch of 2 new satellites in 2016, Jason-3 and Sentinel-3A, opens new perspectives. Using the global Synthetic Aperture Radar mode (SARM) coverage of S3A and optimizing the LRM altimeter processing (retracking, editing, ...) will allow us to fully exploit the fine-scale content of the altimetric missions. Thanks to this increase of real time altimetry observations we will also be able to improve Level-4 products by combining these new Level-3 products and new mapping methodology, such as dynamic interpolation. Finally these improvements will benefit to downstream products : geostrophic currents, Lagrangian products, eddy atlas… Overcoming all these challenges will provide major upgrades of Sea Level products to better fulfill user needs.

  2. Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

    Science.gov (United States)

    Fearns, Peter

    2017-01-01

    The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

  3. Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

    Science.gov (United States)

    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

  4. High-resolution structure of viruses from random diffraction snapshots

    CERN Document Server

    Hosseinizadeh, A; Dashti, A; Fung, R; D'Souza, R M; Ourmazd, A

    2014-01-01

    The advent of the X-ray Free Electron Laser (XFEL) has made it possible to record diffraction snapshots of biological entities injected into the X-ray beam before the onset of radiation damage. Algorithmic means must then be used to determine the snapshot orientations and thence the three-dimensional structure of the object. Existing Bayesian approaches are limited in reconstruction resolution typically to 1/10 of the object diameter, with the computational expense increasing as the eighth power of the ratio of diameter to resolution. We present an approach capable of exploiting object symmetries to recover three-dimensional structure to high resolution, and thus reconstruct the structure of the satellite tobacco necrosis virus to atomic level. Our approach offers the highest reconstruction resolution for XFEL snapshots to date, and provides a potentially powerful alternative route for analysis of data from crystalline and nanocrystalline objects.

  5. Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

    Science.gov (United States)

    Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

    2010-09-01

    ground cover. Thermal-based energy balance models are more suitable than the FAO-Kc model for estimating crop ET, especially under moisture stress conditions, but they require many inputs and detailed theoretical background knowledge; so they can be only used in regions where high quality, hourly agricultural weather data are readily available providing instantaneous values of heat fluxes corresponding to the time of the satellite overpass. Thus, FAO-Kc approach is widely used in research activities and real-time irrigation scheduling for several water applications since it does not require temporal upscaling for obtaining daily values and satellite imagery in the reflective bands used for vegetation index computation are more readily available at higher spatial resolution than thermal band data. There is no simple way to compute crop coefficients because they depend on climate, soil type, crop and its varieties, irrigation method, soil water, nutrient content and plant phenology. Consequently, specific calibrations of crop coefficient are required in various climatic regions. Many authors suggested a linear relationship between Kc and vegetation indices, but non-linear relationships have been proposed too. However, according to the radiative transfer theory, the nature of such relationships depends on the crop architecture and the definition of the adopted vegetation index, but the linear assumption can be adopted as first. Such studies, mainly investigated the possibility to use high resolution satellite data, such as Quickbird, Ikonos, TM, which are not suitable for operational purposes since in spite of the high spatial sampling they have an inadequate revisiting time over a given area. To obtain adequate temporal sampling, some authors proposed the use of a virtual constellation made by all currently available high-resolution satellites (e.g., DEMETER project). However the joint use of data from different satellites requires a carefully inter-satellite cross

  6. Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

    Directory of Open Access Journals (Sweden)

    Xueke Li

    2016-05-01

    Full Text Available The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1 opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m to EO-1 Hyperion (with a spatial resolution of 30 m. The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC, pixel-based support vector machine (PSVM, hybrid maximum likelihood classifier (HMLC, and hybrid support vector machine (HSVM were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the

  7. High-resolution electron microscopy

    CERN Document Server

    Spence, John C H

    2013-01-01

    This new fourth edition of the standard text on atomic-resolution transmission electron microscopy (TEM) retains previous material on the fundamentals of electron optics and aberration correction, linear imaging theory (including wave aberrations to fifth order) with partial coherence, and multiple-scattering theory. Also preserved are updated earlier sections on practical methods, with detailed step-by-step accounts of the procedures needed to obtain the highest quality images of atoms and molecules using a modern TEM or STEM electron microscope. Applications sections have been updated - these include the semiconductor industry, superconductor research, solid state chemistry and nanoscience, and metallurgy, mineralogy, condensed matter physics, materials science and material on cryo-electron microscopy for structural biology. New or expanded sections have been added on electron holography, aberration correction, field-emission guns, imaging filters, super-resolution methods, Ptychography, Ronchigrams, tomogr...

  8. DESIR high resolution separator at GANIL, France

    Directory of Open Access Journals (Sweden)

    Toprek Dragan

    2012-01-01

    Full Text Available A high-resolution separator for the SPIRAL2/DESIR project at GANIL has been designed. The extracted isotopes from SPIRAL2 will be transported to and cooled in a RFQ cooler yielding beams with very low transverse emittance and energy spread. These beams will then be accelerated to 60 keV and sent to a high-resolution mass separator where a specific isotope will be selected. The good beam properties extracted from the RFQ cooler will allow one to obtain a mass resolution of č26000 with the high-resolution mass separator.

  9. Impact of Atmospheric Attenuations Time Resolutions in Solar Radiation Derived from Satellite Imagery

    Science.gov (United States)

    Cony, Marco; Liria, Juan; Weisenberg, Ralf; Serrano, Enrique

    2014-05-01

    Accurate knowledge of solar irradiance components at the earth surface is of highly interest in many scientific and technology branches concerning meteorology, climate, agriculture and solar energy applications. In the specific case of solar energy systems the solar resource analysis with accuracy is a first step in every project since it is a required data for design, power output estimations, systems simulations and risk assessments. Solar radiation measurement availability is increasing both in spatial density and in historical archiving. However, it is still quite limited and most of the situations cannot make use of a long term ground database of high quality since solar irradiance is not generally measured where users need data. Satellite-derived solar radiation estimations are a powerful and valuable tool for solar resource assessment studies that have achieved a relatively high maturity due to years of developments and improvements. However, several sources of uncertainty are still present in satellite-derived methods. In particular, the strong influence of atmospheric attenuation information as input to the method is one of the main topics of improvement. Since solar radiation attenuation by atmospheric aerosols, and water vapor in a second place, is, after clouds, the second most important factor determining solar radiation, and particularly direct normal irradiance, the accurate knowledge of aerosol optical depth and water vapor content is relevant in the final output of satellite-derived methods. This present work, two different datasets we are used for extract atmospheric attenuation information. On the one hand the monthly mean values of the Linke turbidity factor from Meteotest database, which are twelve unique values of the Linke turbidity worldwide with a spatial resolution of 1/12º. On the other hand, daily values of AOD (Aerosol Optical Depth) at 550 nm, Angstrom alpha exponent and water vapor column were taken from a gridded database that

  10. Spatial resolution effects on the assessment of evapotranspiration in olive orchards using high resolution thermal imagery

    Science.gov (United States)

    Santos, Cristina; Zarco-Tejada, Pablo J.; Lorite, Ignacio J.; Allen, Richard G.

    2013-04-01

    The use of remote sensing techniques for estimating surface energy balance and water consumption has significantly improved the characterization of the agricultural systems by determining accurate information about crop evapotranspiration and stress, mainly for extensive crops. However the use of these methodologies for woody crops has been low due to the difficulty in the accurate characterization of these crops, mainly caused by a coarse resolution of the imagery provided by the most widely used satellites (such as Landsat 5 and 7). The coarse spatial resolution provided by these satellite sensors aggregates into a single pixel the tree crown, sunlit and shaded soil components. These surfaces can each exhibit huge differences in temperature, albedo and vegetation indexes calculated in the visible, near infrared and short-wave infrared regions. Recent studies have found that the use of energy balance approaches can provide useful results for non-homogeneous crops (Santos et al., 2012) but detailed analysis is required to determine the effect of the spatial resolution and the aggregation of the scene components in these heterogeneous canopies. In this study a comparison between different spatial resolutions has been conducted using images from Landsat 7 (with thermal resolution of 60m) and from an airborne thermal (with resolution of 80 cm) flown over olive orchards at different dates coincident with the Landsat overpass. The high resolution thermal imagery was resampled at different scales to generate images with spatial resolution ranging from 0.8 m up to 120m (thermal resolution for Landsat 5 images). The selection of the study area was made to avoid those areas with missing Landsat 7 data caused by SLC-off gaps. The selected area has a total area of around 2500 ha and is located in Southern Spain, in the province of Malaga. The selected area is mainly cultivated with olive orchards with different crop practices (rainfed, irrigated, high density, young and adult

  11. High Resolution Silicon Deformable Mirrors Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal describes a plan to build a prototype small stroke, high precision deformable mirror suitable for space-based operation in systems for high-resolution...

  12. High-Resolution Data for a Low-Resolution World

    Energy Technology Data Exchange (ETDEWEB)

    Brady, Brendan Williams [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-10

    In the past 15 years, the upper section of Cañon de Valle has been severely altered by wildfires and subsequent runoff events. Loss of root structures on high-angle slopes results in debris flow and sediment accumulation in the narrow canyon bottom. The original intent of the study described here was to better understand the changes occurring in watershed soil elevations over the course of several post-fire years. An elevation dataset from 5 years post-Cerro Grande fire was compared to high-resolution LiDAR data from 14 years post-Cerro Grande fire (also 3 years post-Las Conchas fire). The following analysis was motivated by a problematic comparison of these datasets of unlike resolution, and therefore focuses on what the data reveals of itself. The objective of this study is to highlight the effects vegetation can have on remote sensing data that intends to read ground surface elevation.

  13. A Block Adjustment Method of High-resolution Satellite Imagery with Straight Line Constraints%直线特征约束的高分辨率卫星影像区域网平差方法

    Institute of Scientific and Technical Information of China (English)

    曹金山; 龚健雅; 袁修孝

    2015-01-01

    Taking “observed straight lines and predicted straight lines in image space being bound to coincide” as a geometric constraint and the rational function model (RFM) as the imaging geometric model of high‐resolution satellite imagery (HRSI ) , a block adjustment method of HRSI with straight line constraintsis proposed .For the proposed method ,the control straight line (CSL) in image space should be correspondent with the one in object space while the image point and the ground point on the lines are not necessarily correspondent .Two IKONOS images covering San Diego area ,two QuickBird images covering Spokane area and two SPOT‐5 images covering Provence area ,respectively ,were used .The experimental results showed that the proposed method can take full advantage of the control information in the form of linear features .Systematic errors in the rational polynomial coefficients (RPCs) can be compensated effectively .After block adjustment ,both the planimetric and height accuracies of the IKONOS ,QuickBird and SPOT‐5 images reach better than 1 pixel .%以“像方观测直线与像方预测直线必须重合”作为几何约束条件,以有理函数模型(RFM)作为高分辨率卫星影像的几何处理模型,提出了一种直线特征约束的高分辨率卫星影像区域网平差方法。本文方法仅需像方直线与物方直线相对应,无须像方直线上的像点与物方直线上的地面点一一对应。通过对圣迭戈试验区的两景IKONOS影像、斯波坎试验区的两景QuickBird影像和普罗旺斯试验区的两景SPOT‐5影像进行试验,结果表明:本文方法可以充分利用直线特征作为控制条件,有效补偿RPC参数中的系统误差,获得的IKONOS、QuickBird和SPOT‐5影像区域网平差的平面与高程精度均优于1个像素。

  14. The High-ORbit Ultraviolet-visible Satellite, HORUS

    Science.gov (United States)

    Scowen, Paul A.; Cooke, Brian; Beasley, Matthew; Siegmund, Oswald

    2013-09-01

    The High-ORbit Ultraviolet-visible Satellite (HORUS) is a 2.4-meter class space telescope that will conduct a comprehensive and systematic study of the astrophysical processes and environments relevant for the births and life cycles of stars and their planetary systems, to investigate and understand the range of environments, feedback mechanisms, and other factors that most affect the outcome of the star and planet formation process. HORUS will provide 100× greater imaging efficiency and combines the resolution of STIS with the throughput of COS. The HORUS mission will contribute vital information on how solar systems form and whether habitable planets should be common or rare. It also will investigate the structure, evolution, and destiny of galaxies and the universe. This program relies on focused capabilities unique to space that no other planned NASA mission will provide: near-ultraviolet (UV)/visible (200-1100nm) wide-field (14' square), diffraction-limited imaging; and high-sensitivity, high-resolution FUV (100- 320nm) spectroscopy. From its baseline orbit at L2 HORUS will enjoy a stable environment for thermal and pointing control, and long-duration target visibility. The core HORUS design will provide wide field of view imagery and high efficiency point source far-ultraviolet (FUV) spectroscopy using a combination of spectral selection and field sharing.

  15. The calculation of satellite line structures in highly stripped plasmas

    Energy Technology Data Exchange (ETDEWEB)

    Abdallah, J. Jr.; Kilcrease, D.P. [Los Alamos National Lab., NM (United States); Faenov, A.Ya.; Pikuz, T.A. [Multicharged Ion Spectra Data Center, Moscow (Russian Federation)

    1998-11-01

    This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). Recently developed high-resolution x-ray spectrographs have made it possible to measure satellite structures from various plasma sources with great detail. These lines are weak optically thin lines caused by the decay of dielectronic states and generally accompany the resonance lines of H-like and He-like ions. The Los Alamos atomic physics and kinetics codes provide a unique capability for calculating the position and intensities of such lines. These programs have been used to interpret such highly resolved spectral measurements from pulsed power devices and laser produced plasmas. Some of these experiments were performed at the LANL Bright Source and Trident laser facilities. The satellite structures are compared with calculations to diagnose temperatures and densities. The effect of non-thermal electron distributions of electrons on calculated spectra was also considered. Collaborations with Russian scientists have added tremendous value to this research die to their vast experience in x-ray spectroscopy.

  16. High resolution studies of massive primordial haloes

    CERN Document Server

    Latif, M A; Schmidt, W; Niemeyer, J

    2012-01-01

    Atomic cooling haloes with T_vir > 10^4 K are the most plausible sites for the formation of the first galaxies. In this article, we aim to study the implications of gravity driven turbulence in protogalactic haloes. By varying the resolution per Jeans length, we explore whether the turbulent cascade is resolved well enough to obtain converged results. We have performed high resolution cosmological simulations using the adaptive mesh refinement code Enzo including a subgrid-scale turbulence model to study the role of unresolved turbulence. We compared the results of three different Jeans resolutions from 16 to 64 cells. While radially averaged profiles roughly agree at different resolutions, differences in the morphology reveal that even the highest resolution employed provides no convergence. Moreover, taking into account unresolved turbulence significantly influences the morphology of a halo. We have quantified the properties of the high-density clumps in the halo. These clumps are gravitationally unbound wi...

  17. The High Energy Particle Detector (HEPD) for the CSES satellite

    Science.gov (United States)

    Sparvoli, Roberta

    2016-04-01

    We present the advanced High Energy Particle Detector (HEPD) developed to be installed on the China Seismo-Electromagnetic Satellite (CSES), launch scheduled by the end of 2016. The HEPD instrument aims at studying the temporal stability of the inner Van Allen radiation belts and at investigating precipitation of trapped particles induced by magnetospheric, ionosferic and tropospheric EM emissions, as well as by the seismo-electromagnetic and anthropogenic disturbances. In occasion of many earthquakes and volcanic eruptions, several measurements, on ground and by experiments on LEO satellites revealed: electromagnetic and plasma perturbations, and anomalous increases of high-energy Van Allen charged particle flux. The precipitation of trapped electrons and protons (from a few MeV to several tens of MeV) could be induced by diffusion of particles pitch-angle possibly caused by the seismo-electromagnetic emissions generated before (a few hours) earthquakes. Due to the longitudinal drift along a same L-shell, anomalous particle bursts of precipitating particles could be detected by satellites not only on the epicentral area of the incoming earthquake, but along the drift path. Moreover, the opposite drift directions of positive and negative particles could allow reconstructing the longitude of the earthquake focal area. Although, the earthquake prediction is not within the reach of current knowledge, however the study of the precursors aims at collecting all relevant information that can infer the spatial and temporal coordinates of the seismic events from measurements. At this purposes, it is essential to detect particles in a wide range of energies (because particles of different energies are sensitive to different frequencies of seismo-electromagnetic emissions), with a good angular resolution (in order to separate fluxes of trapped and precipitating particles), and excellent ability to recognize the charge (that determines the direction of the longitudinal drift

  18. High Resolution Silicon Deformable Mirrors Project

    Data.gov (United States)

    National Aeronautics and Space Administration — In this proposal we describe a plan to build a deformable mirror suitable for space-based operation in systems for high-resolution imaging. The prototype DM will be...

  19. High range resolution micro-Doppler analysis

    Science.gov (United States)

    Cammenga, Zachary A.; Smith, Graeme E.; Baker, Christopher J.

    2015-05-01

    This paper addresses use of the micro-Doppler effect and the use of high range-resolution profiles to observe complex targets in complex target scenes. The combination of micro-Doppler and high range-resolution provides the ability to separate the motion of complex targets from one another. This ability leads to the differentiation of targets based on their micro-Doppler signatures. Without the high-range resolution, this would not be possible because the individual signatures would not be separable. This paper also addresses the use of the micro-Doppler information and high range-resolution profiles to generate an approximation of the scattering properties of a complex target. This approximation gives insight into the structure of the complex target and, critically, is created without using a pre-determined target model.

  20. Structure of high-resolution NMR spectra

    CERN Document Server

    Corio, PL

    2012-01-01

    Structure of High-Resolution NMR Spectra provides the principles, theories, and mathematical and physical concepts of high-resolution nuclear magnetic resonance spectra.The book presents the elementary theory of magnetic resonance; the quantum mechanical theory of angular momentum; the general theory of steady state spectra; and multiple quantum transitions, double resonance and spin echo experiments.Physicists, chemists, and researchers will find the book a valuable reference text.

  1. High Precision Orbit Determination of CHAMP Satellite

    Institute of Scientific and Technical Information of China (English)

    ZHAO Qile; LIU Jingnan; GE Maorong

    2006-01-01

    The precision orbit determination of challenging minisatellite payload(CHAMP) satellite was done based on position and navigation data analyst(PANDA) software which is developed in Wuhan University, using the onboard GPS data of year 2002 from day 126 to 131. The orbit accuracy was assessed by analyzing the difference from GFZ post-processed science orbits (PSO), the GPS carrier and pseudo-range data residuals and the satellite laser ranging (SLR) residuals.

  2. High resolution numerical weather prediction over the Indian subcontinent

    Indian Academy of Sciences (India)

    T S V Vijaya Kumar; T N Krishnamurti

    2006-10-01

    In this study, the Florida State University Global Spectral Model (FSUGSM), in association with a high-resolution nested regional spectral model (FSUNRSM), is used for short-range weather forecasts over the Indian domain. Three-day forecasts for each day of August 1998 were performed using different versions of the FSUGSM and FSUNRSM and were compared with the observed fields (analysis) obtained from the European Center for Medium Range Weather Forecasts (ECMWF). The impact of physical initialization (a procedure that assimilates observed rain rates into the model atmosphere through a set of reverse algorithms) on rainfall forecasts was examined in detail. A very high nowcasting skill for precipitation is obtained through the use of high-resolution physical initialization applied at the regional model level. Higher skills in wind and precipitation forecasts over the Indian summer monsoon region are achieved using this version of the regional model with physical initialization. A relatively new concept, called the ‘multimodel/multianalysis superensemble’ is described in this paper and is applied for the wind and precipitation forecasts over the Indian subcontinent. Large improvement in forecast skills of wind at 850 hPa level over the Indian subcontinent is shown possible through the use of the multimodel superensemble. The multianalysis superensemble approach that uses the latest satellite data from the Tropical Rainfall Measuring Mission (TRMM) and the Defense Meteorological Satellite Program (DMSP) has shown significant improvement in the skills of precipitation forecasts over the Indian monsoon region.

  3. Spatial Resolution of Core Surface Flow Models Derived From Satellite Data

    Science.gov (United States)

    Eymin, C.; Hulot, G.

    Core surface flows are usually computed from observations of the internal magnetic field and its secular variation. With observatory based secular variation models, the spatial resolution of core surface flows was mainly limited by the resolution of the secular variation model itself. This resolution dramatically improved with magnetic satellite data and for the first time the main limitation on core surface flow compu- tations comes from the hiding of the smallest length scale of the internal magnetic field by the crust. Indeed, the invisible small scale magnetic field may interact with core flows to produce large scale secular variation. This interaction cannot be taken into account during the flow computation process and may alter the computed flow models, even for large length scales. We investigate here the effects of the truncation of the internal magnetic field with known flow models using two different and inde- pendent core surface flow computation methods. In particular, we try to estimate the amplitude of the error introduced by this truncation and the spatial resolution that can be obtained with the new satellite data for core surface flows.

  4. 4MOST: the high-resolution spectrograph

    Science.gov (United States)

    Seifert, W.; Xu, W.; Buschkamp, P.; Feiz, C.; Saviauk, A.; Barden, S.; Quirrenbach, A.; Mandel, H.

    2016-08-01

    4MOST (4-meter Multi-Object Spectroscopic Telescope) is a wide-field, fiber-feed, high-multiplex spectroscopic survey facility to be installed on the 4-meter ESO telescope VISTA in Chile. It consists of two identical low resolution spectrographs and one high resolution spectrograph. The instrument is presently in the preliminary design phase and expected to get operational end of 2022. The high resolution spectrograph will afford simultaneous observations of up to 812 targets - over a hexagonal field of view of 4.1 sq.degrees on sky - with a spectral resolution R>18,000 covering a wavelength range from 393 to 679nm in three channels. In this paper we present the optical and mechanical design of the high resolution spectrograph (HRS) as prepared for the review at ESO, Garching. The expected performance including the highly multiplexed fiber slit concept is simulated and its impact on the optical performance given. We show the thermal and finite element analyses and the resulting stability of the spectrograph under operational conditions.

  5. 622 Mbps High-speed satellite communication system for WINDS

    Science.gov (United States)

    Ogawa, Yasuo; Hashimoto, Yukio; Yoshimura, Naoko; Suzuki, Ryutaro; Gedney, Richard T.; Dollard, Mike

    2006-07-01

    WINDS is the experimental communications satellite currently under joint development by Japanese Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT). The high-speed satellite communication system is very effective for quick deployment of high-speed networks economically. The WINDS will realize ultra high-speed networking and demonstrate operability of satellite communication systems in high-speed internet. NICT is now developing high-speed satellite communication system for WINDS. High-speed TDMA burst modem with high performance TPC error correction is underdevelopment. Up to the DAC on the transmitter and from the ADC on the receiver, all modem functions are performed in the digital processing technology. Burst modem has been designed for a user data rate up to 1244 Mbps. NICT is developing the digital terminal as a user interface and a network controller for this earth station. High compatibility with the Internet will be provided.

  6. USGS Small-scale Dataset - 100-Meter Resolution Satellite View of the Conterminous United States 201304 GeoTIFF

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View of the Conterminous United States map layer is a 100-meter resolution simulated natural-color image of the United States. Vegetation is generally...

  7. USGS Small-scale Dataset - 100-Meter Resolution Satellite View with Shaded Relief of Alaska 201304 GeoTIFF

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View with Shaded Relief of Alaska map layer is a 100-meter resolution simulated natural-color image of Alaska, with relief shading added to accentuate...

  8. USGS Small-scale Dataset - 100-Meter Resolution Satellite View with Shaded Relief of Hawaii 201304 GeoTIFF

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Satellite View with Shaded Relief of Hawaii map layer is a 100-meter resolution simulated natural-color image of Hawaii, with relief shading added to accentuate...

  9. High-Resolution PET Detector. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Karp, Joel

    2014-03-26

    The objective of this project was to develop an understanding of the limits of performance for a high resolution PET detector using an approach based on continuous scintillation crystals rather than pixelated crystals. The overall goal was to design a high-resolution detector, which requires both high spatial resolution and high sensitivity for 511 keV gammas. Continuous scintillation detectors (Anger cameras) have been used extensively for both single-photon and PET scanners, however, these instruments were based on NaI(Tl) scintillators using relatively large, individual photo-multipliers. In this project we investigated the potential of this type of detector technology to achieve higher spatial resolution through the use of improved scintillator materials and photo-sensors, and modification of the detector surface to optimize the light response function.We achieved an average spatial resolution of 3-mm for a 25-mm thick, LYSO continuous detector using a maximum likelihood position algorithm and shallow slots cut into the entrance surface.

  10. OMI NO2 column densities over North American urban cities: the effect of satellite footprint resolution

    Directory of Open Access Journals (Sweden)

    H. C. Kim

    2015-10-01

    Full Text Available Nitrogen dioxide vertical column density (NO2 VCD measurements via satellite are compared with a fine-scale regional chemistry transport model, using a new approach that considers varying satellite footprint sizes. Space-borne NO2 VCD measu