WorldWideScience

Sample records for spot satellite images

  1. Lineament systems indentification in Banten site using Spot 5 satellite image

    International Nuclear Information System (INIS)

    Yuliastuti; Heni Susiati; Yunus Daud; A-Sarwiyana Sastratenaya

    2013-01-01

    Lineament systems identification in Banten site using SPOT 5 satellite image has been performed. Based on regional site survey in Java Island, Banten is one of the potential candidate sites. The objective of this study was to determine direction and chronology of regional lineament morphology which was consider as fault or faulting in Banten site. The methodology used this study covered satellite image cropping, band selection, edge enhancement filtering, lineament extraction and lineament analysis. Result of the study showed that there were three dominant lineament groups, namely N-S, NW-SE, and E-W. Based on the forming chronology of the lineament, N-S group was the oldest one, followed by E-W group and NW-SE as the youngest group. These lineament groups have been confirmed as a manifestation of fault system structure. (author)

  2. An intercomparison of Satellite Burned Area Maps derived from MODIS, MERIS, SPOT-VEGETATION, and ATSR images. An application to the August 2006 Galicia (Spain forest fires

    Directory of Open Access Journals (Sweden)

    M. Huesca

    2013-07-01

    : Earth Observation System; ESA: European Space Agency; GBA2000: Global Burnt Area 2000; GLOBCARBON-BAE: GLOBCARBON Burnt Area Estimate Product; L3JRC: Terrestrial Ecosystem Monitoring Global Burnt Area Product; MCD45A1: MODIS Burned Area Product; MERIS: MEdium Resolution Imaging Spectrometer; MOD09GA: Terra MODIS Surface Reflectance Daily L2G Global 500 m; MOD09GQ: Terra MODIS Surface Reflectance Daily L2G Global 250 m; MODIS: MODerate resolution Imaging Spectrometer; NBR: Normalized Burn Ratio; NDVI: Normalized Difference Vegetation Index; NIR: near-infrared; SPOT: Satellite Pour l’Observation de la Terre; SWIR: short-wave infrared; UTM: Universal Transverse Mercator.

  3. Real-time satellite monitoring of volcanic hot spots

    Science.gov (United States)

    Harris, Andrew J. L.; Flynn, Luke P.; Dean, Ken; Pilger, Eric; Wooster, Martin; Okubo, Chris; Mouginis-Mark, Peter; Garbeil, Harold; Thornber, Carl; De la Cruz-Reyna, Servando; Rothery, Dave; Wright, Robert

    Direct satellite data reception at high temporal frequencies and automated processing enable near-real-time, near-continuous thermal monitoring of volcanoes. We review what has been achieved in terms of turning this capability into real-time tools of use to volcano monitoring agencies. Current capabilities focus on 2 instruments: the advanced very high resolution radiometer (AVHRR) and the Geostationary Operational Environmental Satellite (GOES) imager. Collection of lO AVHRR images per day covering Alaska, the Aleutians, and Kamchatka allows routine, on-reception analysis of volcanic hot spots across this region. Data collected between 1996 and 1998 detected 302 hot spots due to lava flows, lava domes, pyroclastic flows, fumaroles, and geothermally heated lakes at 12 different volcanoes. Information was used for hazard mitigation by the Alaskan Volcano Observatory. GOES provides data for North and South American volcanoes every 15-30 minutes. Automated processing allows eruption information and alerts to be posted on the Internet within 15-60 minutes of reception. We use June 1998 to demonstrate the frequency of data acquisition. During this month 2879 GOES images were collected from which 14,832 sub-images of 6 active volcanoes were processed. Although 82% (12,200) of these sub-images were cloud covered, hot spots were still evident on 11% (1634) of the sub-images. Analysis of GOES data for 1998 identified hot spots due to (1) lava flows at Kilauea and Cerro Azul, (2) dome extrusion and explosive activity at Lascar, Popocatepetl, Colima and Pacaya, and (3) dome cooling and collapse at Soufriere Hills. We were also able to suggest that reports of lava flow activity at Cerro Negro were false. This information was supplied to, and used by, various agencies whose task it is to monitor these volcanoes. Global thermal monitoring will become a reality with the launch of the Earth Observing System's moderate resolution imaging spectrometer (MODIS). An automated thermal

  4. Thermal Wave Imaging: Flying SPOT Camera.

    Science.gov (United States)

    Wang, Yiqian

    1993-01-01

    A novel "Flying Spot" infrared camera for nondestructive evaluation (NDE) and nondestructive characterization is presented. The camera scans the focal point of an unmodulated heating laser beam across the sample in a raster. The detector of the camera tracks the heating spot in the same raster, but with a time delay. The detector is thus looking at the "thermal wake" of the heating spot. The time delay between heating and detection is determined by the speed of the laser spot and the distance between it and the detector image. Since this time delay can be made arbitrarily small, the camera is capable of making thermal wave images of phenomena which occur on a very short time scale. In addition, because the heat source is a very small spot, the heat flow is fully three-dimensional. This makes the camera system sensitive to features, like tightly closed vertical cracks, which are invisible to imaging systems which employ full-field heating. A detailed theory which relates the temperature profile around the heating spot to the sample thermal properties is also described. The camera represents a potentially useful tool for measuring thermal diffusivities of materials by means of fitting the recorded temperature profiles to the theoretical curves with the diffusivity as a fitting parameter.

  5. The High Visible Resolution (HVR) instrument of the spot ground observation satellite

    Science.gov (United States)

    Otrio, G.

    1980-01-01

    Two identical high resolution cameras, capable of attaining a track width of 116 km in an almost vertical line of sight from the two 60 km images of each instrument, will be carried on the initial mission of the space observation of Earth satellite (SPOT). Specifications for the instrument, including the telescope and CCD devices are summarized. The present status of development is described including the optical characteristics, structure and thermal control, detector assembly, electronic equipment, and calibration. SPOT mission objectives include the developments relating to soil use, the exploration of EART Earth resources, the discrimination of plant species, and cartography.

  6. Interferometry to Image Surface Spots

    Science.gov (United States)

    Perrin, Guy

    2016-04-01

    I present in this lecture the technique of interferometric imaging at optical/infrared wavelengths. The technique has matured since the pioneering work of Michelson at the end of the XIXth—beginning of the XXth when he first resolved the surface of a star, Betelgeuse, with his colleague Pease. Images were obtained for the first time 20 years ago with the COAST instrument and interferometers have made constant progress to reach the minimum level where blind image reconstruction can be achieved. I briefly introduce the topic to recall why studying the surface and close environment of stars is important in some fields of stellar physics. I introduce the theory of imaging with telescopes and interferometers. I discuss the nature of interferometric data in this wavelength domain and give a few insights on the importance of getting access to visibility phases to obtain information on asymmetries of stellar surfaces. I then present the issue of aperture synthesis with a small number of telescopes, a signature of optical/infrared interferometers compared to the radio domain. Despite the impossibility to measure the phase of visibilities because of turbulence I show that useful information can be recovered from the closure phase. I eventually introduce the principles of image reconstruction and I discuss some recent results on several types of stars.

  7. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  8. Analysis of multiple access techniques in multi-satellite and multi-spot mobile satellite systems

    Science.gov (United States)

    Corazza, Giovanni E.; Ferrarelli, Carlo; Vatalaro, Francesco

    1995-01-01

    In this paper the analysis of mobile satellite systems adopting constellations of multi-spot satellites over non-geostationary orbits is addressed. A link design procedure is outlined, taking into account system spectrum efficiency, probability of bit error and outage probability. A semi-analytic approach to the evaluation of outage probability in the presence of fading and imperfect power control is described, and applied to single channel per carrier (SCPC) and code division multiple access (CDMA) techniques. Some results are shown for the Globalstar, Iridium and Odyssey orbital configurations.

  9. Shadow imaging of geosynchronous satellites

    Science.gov (United States)

    Douglas, Dennis Michael

    Geosynchronous (GEO) satellites are essential for modern communication networks. If communication to a GEO satellite is lost and a malfunction occurs upon orbit insertion such as a solar panel not deploying there is no direct way to observe it from Earth. Due to the GEO orbit distance of ~36,000 km from Earth's surface, the Rayleigh criteria dictates that a 14 m telescope is required to conventionally image a satellite with spatial resolution down to 1 m using visible light. Furthermore, a telescope larger than 30 m is required under ideal conditions to obtain spatial resolution down to 0.4 m. This dissertation evaluates a method for obtaining high spatial resolution images of GEO satellites from an Earth based system by measuring the irradiance distribution on the ground resulting from the occultation of the satellite passing in front of a star. The representative size of a GEO satellite combined with the orbital distance results in the ground shadow being consistent with a Fresnel diffraction pattern when observed at visible wavelengths. A measurement of the ground shadow irradiance is used as an amplitude constraint in a Gerchberg-Saxton phase retrieval algorithm that produces a reconstruction of the satellite's 2D transmission function which is analogous to a reverse contrast image of the satellite. The advantage of shadow imaging is that a terrestrial based redundant set of linearly distributed inexpensive small telescopes, each coupled to high speed detectors, is a more effective resolved imaging system for GEO satellites than a very large telescope under ideal conditions. Modeling and simulation efforts indicate sub-meter spatial resolution can be readily achieved using collection apertures of less than 1 meter in diameter. A mathematical basis is established for the treatment of the physical phenomena involved in the shadow imaging process. This includes the source star brightness and angular extent, and the diffraction of starlight from the satellite

  10. Significance of satellite sign and spot sign in predicting hematoma expansion in spontaneous intracerebral hemorrhage.

    Science.gov (United States)

    Yu, Zhiyuan; Zheng, Jun; Ali, Hasan; Guo, Rui; Li, Mou; Wang, Xiaoze; Ma, Lu; Li, Hao; You, Chao

    2017-11-01

    Hematoma expansion is related to poor outcome in spontaneous intracerebral hemorrhage (ICH). Recently, a non-enhanced computed tomography (CT) based finding, termed the 'satellite sign', was reported to be a novel predictor for poor outcome in spontaneous ICH. However, it is still unclear whether the presence of the satellite sign is related to hematoma expansion. Initial computed tomography angiography (CTA) was conducted within 6h after ictus. Satellite sign on non-enhanced CT and spot sign on CTA were detected by two independent reviewers. The sensitivity and specificity of both satellite sign and spot sign were calculated. Receiver-operator analysis was conducted to evaluate their predictive accuracy for hematoma expansion. This study included 153 patients. Satellite sign was detected in 58 (37.91%) patients and spot sign was detected in 38 (24.84%) patients. Among 37 patients with hematoma expansion, 22 (59.46%) had satellite sign and 23 (62.16%) had spot sign. The sensitivity and specificity of satellite sign for prediction of hematoma expansion were 59.46% and 68.97%, respectively. The sensitivity and specificity of spot sign were 62.16% and 87.07%, respectively. The area under the curve (AUC) of satellite sign was 0.642 and the AUC of spot sign was 0.746. (P=0.157) CONCLUSION: Our results suggest that the satellite sign is an independent predictor for hematoma expansion in spontaneous ICH. Although spot sign has the higher predictive accuracy, satellite sign is still an acceptable predictor for hematoma expansion when CTA is unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. SPOT Tandem completed: A unique constellation of optical satellites from Europe

    OpenAIRE

    Lemmens, M.J.P.M.

    2014-01-01

    The launch of SPOT 7 on 30 June 2014 at 6:22 a.m. CET completed the constellation of four optical spacecraft operating in the same orbit. The constellation further consists of twin sister SPOT 6 and Pléiades 1A and 1B. To mark the occasion, the author discusses the features of the extended family of 7 SPOT satellites here.

  12. Satellite spot defect reduction on 193-nm contact hole lithography using photo cell monitor methodology

    Science.gov (United States)

    Boulenger, Caroline; Caze, Jean-Luc; Mihet, Mihaela

    2006-03-01

    The goal of overall process and yield improvement requires a litho defect management and reduction strategy, which includes several layers of tactical methods. Defects may be identified through a number of schemes, including After-Develop Inspection (ADI), which was the primary tool in this study in our 0,13μ fab. Defects on 193nm contact hole lithography were identified using a KLA-Tencor 2351 High Resolution Imaging Patterned Wafer Inspection System, coupled with in-line Automatic Defect Classification (iADC). The optimized inspection was used at the core of the Photo Cell Monitor (PCM) to isolate critical defect types. PCM uses the fab's standard production resist coat, exposure, develop, and rinse process, with the focus and exposure optimized for resist on silicon test wafers. Through Pareto analysis of 193nm defects, one defect type, called satellite spot, was targeted for immediate improvement and monitoring. This paper describes the work done in improving the litho defectivity. The work includes optimization of inspection and classification parameters and the Design of Experiments (DOE) to identify the source (including the interaction between the resist and developer) and contributing factors. Several process modifications were identified which resulted in lowered defectivity up to complete suppression of satellite spot defects, although at higher process complexity and cost. This work was also done in conjunction with resist suppliers, which used the same inspection to confirm the problem at their facilities. The work with the suppliers continues with the goal of identifying a less expensive permanent solution.

  13. Smoothing of Fused Spectral Consistent Satellite Images

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2006-01-01

    on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. (2005) proposed a method of fusion of satellite images that is based on the properties of imaging physics...

  14. Performance evaluation of spot detection algorithms in fluorescence microscopy images

    CSIR Research Space (South Africa)

    Mabaso, M

    2012-10-01

    Full Text Available Detection of messenger Ribonucleic Acid (mRNA) spots in fluorescence microscopy images is of great importance for biologists seeking better understanding of cell functionality. Fluorescence microscopy and specific staining methods make biological...

  15. The best printing methods to print satellite images

    Directory of Open Access Journals (Sweden)

    G.A. Yousif

    2011-12-01

    In this paper different printing systems were used to print an image of SPOT-4 satellite, caver part of Sharm Elshekh area, Sinai, Egypt, on the same type of paper as much as possible, especially in the photography. This step is followed by measuring the experimental data, and analyzed colors to determine the best printing systems for satellite image printing data. The laser system is the more printing system where produce a wider range of color and highest densities of ink and access much color detail. Followed by the offset system which it recorded the best dot gain. Moreover, the study shows that it can use the advantages of each method according to the satellite image color and quantity to be produced.

  16. AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

    Directory of Open Access Journals (Sweden)

    V.G. Biju

    2015-11-01

    Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

  17. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  18. High resolution mapping of urban areas using SPOT-5 images and ancillary data

    Directory of Open Access Journals (Sweden)

    Elif Sertel

    2015-08-01

    Full Text Available This research aims to propose new rule sets to be used for object based classification of SPOT-5 images to accurately create detailed urban land cover/use maps. In addition to SPOT-5 satellite images, Normalized Difference Vegetation Index (NDVI and Normalized Difference Water Index (NDWI maps, cadastral maps, Openstreet maps, road maps and Land Cover maps, were also integrated into classification to increase the accuracy of resulting maps. Gaziantep city, one of the highly populated cities of Turkey with different landscape patterns was selected as the study area. Different rule sets involving spectral, spatial and geometric characteristics were developed to be used for object based classification of 2.5 m resolution Spot-5 satellite images to automatically create urban map of the region. Twenty different land cover/use classes obtained from European Urban Atlas project were applied and an automatic classification approach was suggested for high resolution urban map creation and updating. Integration of different types of data into the classification decision tree increased the performance and accuracy of the suggested approach. The accuracy assessment results illustrated that with the usage of newly proposed rule set algorithms in object-based classification, urban areas represented with seventeen different sub-classes could be mapped with 94 % or higher overall accuracy.

  19. A Comparative Accuracy Analysis of Classification Methods in Determination of Cultivated Lands with Spot 5 Satellite Imagery

    Science.gov (United States)

    kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2013-12-01

    A Comparative Accuracy Analysis of Classification Methods in Determination of Cultivated Lands with Spot 5 Satellite Imagery Ugur ALGANCI1, Sinasi KAYA1,2, Elif SERTEL1,2,Berk USTUNDAG3 1 ITU, Center for Satellite Communication and Remote Sensing, 34469, Maslak-Istanbul,Turkey 2 ITU, Department of Geomatics, 34469, Maslak-Istanbul, Turkey 3 ITU, Agricultural and Environmental Informatics Research Center,34469, Maslak-Istanbul,Turkey alganci@itu.edu.tr, kayasina@itu.edu.tr, sertele@itu.edu.tr, berk@berk.tc ABSTRACT Cultivated land determination and their area estimation are important tasks for agricultural management. Derived information is mostly used in agricultural policies and precision agriculture, in specifically; yield estimation, irrigation and fertilization management and farmers declaration verification etc. The use of satellite image in crop type identification and area estimate is common for two decades due to its capability of monitoring large areas, rapid data acquisition and spectral response to crop properties. With launch of high and very high spatial resolution optical satellites in the last decade, such kind of analysis have gained importance as they provide information at big scale. With increasing spatial resolution of satellite images, image classification methods to derive the information form them have become important with increase of the spectral heterogeneity within land objects. In this research, pixel based classification with maximum likelihood algorithm and object based classification with nearest neighbor algorithm were applied to 2012 dated 2.5 m resolution SPOT 5 satellite images in order to investigate the accuracy of these methods in determination of cotton and corn planted lands and their area estimation. Study area was selected in Sanliurfa Province located on Southeastern Turkey that contributes to Turkey's agricultural production in a major way. Classification results were compared in terms of crop type identification using

  20. Optimization of Power Allocation for Multiusers in Multi-Spot-Beam Satellite Communication Systems

    Directory of Open Access Journals (Sweden)

    Heng Wang

    2014-01-01

    Full Text Available In recent years, multi-spot-beam satellite communication systems have played a key role in global seamless communication. However, satellite power resources are scarce and expensive, due to the limitations of satellite platform. Therefore, this paper proposes optimizing the power allocation of each user in order to improve the power utilization efficiency. Initially the capacity allocated to each user is calculated according to the satellite link budget equations, which can be achieved in the practical satellite communication systems. The problem of power allocation is then formulated as a convex optimization, taking account of a trade-off between the maximization of the total system capacity and the fairness of power allocation amongst the users. Finally, an iterative algorithm based on the duality theory is proposed to obtain the optimal solution to the optimization. Compared with the traditional uniform resource allocation or proportional resource allocation algorithms, the proposed optimal power allocation algorithm improves the fairness of power allocation amongst the users. Moreover, the computational complexity of the proposed algorithm is linear with both the numbers of the spot beams and users. As a result, the proposed power allocation algorithm is easy to be implemented in practice.

  1. Satellite image classification using convolutional learning

    Science.gov (United States)

    Nguyen, Thao; Han, Jiho; Park, Dong-Chul

    2013-10-01

    A satellite image classification method using Convolutional Neural Network (CNN) architecture is proposed in this paper. As a special case of deep learning, CNN classifies classes of images without any feature extraction step while other existing classification methods utilize rather complex feature extraction processes. Experiments on a set of satellite image data and the preliminary results show that the proposed classification method can be a promising alternative over existing feature extraction-based schemes in terms of classification accuracy and classification speed.

  2. Evaluation of Total Suspended Sediment (TSS) Distribution Using ASTER, ALOS, SPOT-4 Satellite Imagery in 2005-2012

    Science.gov (United States)

    Hariyanto, T.; Krisna, T. C.; Pribadi, C. B.; Kurniawan, A.; Sukojo, B. M.; Taufik, M.

    2017-12-01

    Lapindo mud thrown to Porong River from September 27, 2006 brought an enormous impact to the environment and surrounding communities. This will exacerbate the damage Porong ecosystems, and pollute the Madura Strait and surrounding areas (Wibisono, 2006). Disposal of sludge in large quantities and continuously to Porong also indicated sedimentation resulted in Porong River, Porong River estuary and along coastal of Surabaya-Pasuruan. This is because the material sediment transport along water flow, and the influence of geographical conditions, and the waves of the sea water. Satellite image data used in this study is the ASTER in 2005-2008, ALOS/AVNIR-2 in 2010, and SPOT-4 years 2009.2011 and 2012. In the satellite image processing, for obtain the value of is used TSS algorithm of Jing Li (2008) for ASTER satellite imagery, algorithms of Hendrawan and Asai (2008) for the ALOS satellite imagery, and algorithm of Budiman (2004) for the SPOT-4 satellite imagery. TSS value of the image processing results then performed validation / test precision using reference data TSS In-Situ to obtain linear correlation (R2). R2 value was obtained is 0.854 in 2009, 0.761 in 2011, and 0712 in 2013. That indicates that the value of TSS in the field is proportional with the TSS value in image and has a very good correlation. The results show the value of TSS in the study area ranged from 25 until more than 150 mg/L and according to the results of the analysis showed an upward trend of TSS values over time. There are several locations that indicated experiencing severe sedimentation impacts such as in Porong River, Porong River Estuary, Alo River Estuary, and the surrounding area of the estuary. According to Government Regulation Number 82 in 2001, the maximum value of TSS in the river or water is must less than 50 mg/L and so the value of TSS in the study area is very improper that if allowed to continue may damage the ecosystem in the area. Results from this study is expected to be

  3. A Multivariate Model for Coastal Water Quality Mapping Using Satellite Remote Sensing Images.

    Science.gov (United States)

    Su, Yuan-Fong; Liou, Jun-Jih; Hou, Ju-Chen; Hung, Wei-Chun; Hsu, Shu-Mei; Lien, Yi-Ting; Su, Ming-Daw; Cheng, Ke-Sheng; Wang, Yeng-Fung

    2008-10-10

    his study demonstrates the feasibility of coastal water quality mapping using satellite remote sensing images. Water quality sampling campaigns were conducted over a coastal area in northern Taiwan for measurements of three water quality variables including Secchi disk depth, turbidity, and total suspended solids. SPOT satellite images nearly concurrent with the water quality sampling campaigns were also acquired. A spectral reflectance estimation scheme proposed in this study was applied to SPOT multispectral images for estimation of the sea surface reflectance. Two models, univariate and multivariate, for water quality estimation using the sea surface reflectance derived from SPOT images were established. The multivariate model takes into consideration the wavelength-dependent combined effect of individual seawater constituents on the sea surface reflectance and is superior over the univariate model. Finally, quantitative coastal water quality mapping was accomplished by substituting the pixel-specific spectral reflectance into the multivariate water quality estimation model.

  4. Spot detection in microscopy images using Convolutional Neural Network with sliding-window approach

    CSIR Research Space (South Africa)

    Mabaso, Matsilele A

    2018-01-01

    Full Text Available Robust spot detection in microscopy image analysis serves as a critical prerequisite in many biomedical applications. Various approaches that automatically detect spots have been proposed to improve the analysis of biological images. In this paper...

  5. Environmental Changes Analysis in Bucharest City Using Corona, SPOT Hrv and Ikonos Images

    Science.gov (United States)

    Noaje, I.; Sion, I. G.

    2012-08-01

    Bucharest, capital of Romania, deals with serious difficulties as a result of urban politics: influx of people due to industrialization and development of dormitory areas, lack of a modern infrastructure, absence of coherent and long term urban development politics, continuous depletion of environment. This paper presents a multisensor study relying on multiple data sets, both analogical and digital: satellite images (Corona - 1964 panchromatic, SPOT HRV - 1994 multispctral and panchromatic, IKONOS - 2007 multispectral), aerial photographs - 1994, complementary products (topographic and thematic maps). Georeferenced basis needs to be generated to highlight changes detection. The digital elevation model is generated from aerial photography 1:5,000 scaled, acquired in 1994. First a height correction is required followed by an affine transformation to the ground control points identified both in aerial photographs and IKONOS image. SPOT-HRV pansharpened satellite image has been rectified on georeferenced IKONOS image, by an affine transformation method. The Corona panoramic negative film was scanned and rubber sheeting method is used for rectification. The first 25 years of the study period (1964-1989) are characterized by growth of industrial areas, high density apartment buildings residential areas and leisure green areas by demolition of cultural heritage areas (hundred years old churches and architectural monuments). Changes between the imagery were determined partially through visual interpretation, using elements such as location, size, shape, shadow, tone, texture, and pattern (Corona image), partially using unsupervised classification (SPOT HRV and IKONOS). The second period of 18 years (1989-2007) highlighted considerable growth of residential areas in the city neighborhood, simultaneously with the diminish of green areas and massive deforestation in confiscated areas before and returned to the original owners.

  6. Satellite imager calibration and validation

    CSIR Research Space (South Africa)

    Vhengani, L

    2010-10-01

    Full Text Available The success or failure of any earth observation mission depends on the quality of its data. Data quality is assessed by determining the radiometric, spatial, spectral and geometric fidelity of the satellite sensor. The process is termed calval...

  7. Classification of high resolution satellite images

    OpenAIRE

    Karlsson, Anders

    2003-01-01

    In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

  8. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...

  9. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

    Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed and calib......Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...

  10. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.

    2006-01-01

    Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

  11. Granulometric maps from high resolution satellite images:

    OpenAIRE

    Chopin, Franck; Mering, Catherine

    2002-01-01

    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 ...

  12. Fracture mapping of lineaments and recognizing their tectonic significance using SPOT-5 satellite data: A case study from the Bajestan area, Lut Block, east of Iran

    Science.gov (United States)

    Ahmadirouhani, Reyhaneh; Rahimi, Behnam; Karimpour, Mohammad Hassan; Malekzadeh Shafaroudi, Azadeh; Afshar Najafi, Sadegh; Pour, Amin Beiranvand

    2017-10-01

    Syste'm Pour l'Observation de la Terre (SPOT) remote sensing satellite data have useful characteristics for lineament extraction and enhancement related to the tectonic evaluation of a region. In this study, lineament features in the Bajestan area associated with the tectonic significance of the Lut Block (LB), east Iran were mapped and characterized using SPOT-5 satellite data. The structure of the Bajestan area is affected by the activity of deep strike-slip faults in the boundary of the LB. Structural elements such as faults and major joints were extracted, mapped, and analyzed by the implementation of high-Pass and standard kernels (Threshold and Sobel) filters to bands 1, 2 and 3 of SPOT-5 Level 2 A scene product of the Bajestan area. Lineament map was produced by assigning resultant filter images to red-green-blue (RGB) colour combinations of three main directions such as N-S, E-W and NE-SW. Results derived from image processing technique and statistical assessment indicate that two main orientations, including NW-SE with N-110 azimuth and NE-SW with N-40 azimuth, were dominated in the Bajestan area. The NW-SE trend has a high frequency in the study area. Based on the results of remote sensing lineament analysis and fieldwork, two dextral and sinistral strike-slip components were identified as main fault trends in the Bajestan region. Two dextral faults have acted as the cause of shear in the south and north of the Bajestan granitoid mass. Furthermore, the results indicate that the most of the lineaments in this area are extensional fractures corresponding to both the dykes emplacement and hydrothermal alteration zones. The application of SPOT-5 satellite data for structural analysis in a study region has great capability to provide very useful information of a vast area with low cost and time-consuming.

  13. 4-D display of satellite cloud images

    Science.gov (United States)

    Hibbard, William L.

    1987-01-01

    A technique has been developed to display GOES satellite cloud images in perspective over a topographical map. Cloud heights are estimated using temperatures from an infrared (IR) satellite image, surface temperature observations, and a climatological model of vertical temperature profiles. Cloud levels are discriminated from each other and from the ground using a pattern recognition algorithm based on the brightness variance technique of Coakley and Bretherton. The cloud regions found by the pattern recognizer are rendered in three-dimensional perspective over a topographical map by an efficient remap of the visible image. The visible shades are mixed with an artificial shade based on the geometry of the cloud-top surface, in order to enhance the texture of the cloud top.

  14. ST Spot Detector: a web-based application for automatic spot and tissue detection for Spatial Transcriptomics image data sets.

    Science.gov (United States)

    Wong, Kim; Fernández Navarro, José; Bergenstråhle, Ludvig; Ståhl, Patrik L; Lundeberg, Joakim

    2018-01-17

    Spatial transcriptomics (ST) is a method which combines high resolution tissue imaging with high throughput transcriptome sequencing data. This data must be aligned with the images for correct visualisation, a process that involves several manual steps. Here we present ST Spot Detector, a web tool that automates and facilitates this alignment through a user friendly interface. Open source under the MIT license, available from https://github.com/SpatialTranscriptomicsResearch/st_spot_detector. jose.fernandez.navarro@scilifelab.se. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  15. Geomorphology of coastal environments from satellite images

    International Nuclear Information System (INIS)

    Da Rocha Ribeiro, R.; Velho, L.; Schossler, V.

    2010-01-01

    This study aims at recognizing coastal environments supported by data from the Landsat Thematic Mapper (TM) satellite. The digital processing of images, System Information Geographic (SIG) techniques and field observation in one section of the “Província Costeira do Rio Grande do Sul” between the Rio Grande and the São Gonçalo channels - resulted in a geomorphologic profile and mapping

  16. Satellite images for land cover monitoring - Navigating through the maze

    Science.gov (United States)

    Künzer, Claudia; Fosnight, Gene

    2001-01-01

    Policy makers, managers, scientists and the public can view the changing environment using satellite images.  More than 60 Earth observing satellites are collecting images of the Earth's surface. Remote sensing satellite systems for land cover assessment are operated by a growing number of countries including India, the United States, Japan, France, Canada and Russia.

  17. Detection of jet contrails from satellite images

    Science.gov (United States)

    Meinert, Dieter

    1994-02-01

    In order to investigate the influence of modern technology on the world climate it is important to have automatic detection methods for man-induced parameters. In this case the influence of jet contrails on the greenhouse effect shall be investigated by means of images from polar orbiting satellites. Current methods of line recognition and amplification cannot distinguish between contrails and rather sharp edges of natural cirrus or noise. They still rely on human control. Through the combination of different methods from cloud physics, image comparison, pattern recognition, and artificial intelligence we try to overcome this handicap. Here we will present the basic methods applied to each image frame, and list preliminary results derived this way.

  18. 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.

  19. Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

    Science.gov (United States)

    Verbesselt, J.; Somers, B.; Lhermitte, S.; van Aardt, J.; Jonckheere, I.; Coppin, P.

    2005-10-01

    The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

  20. Medical image transmission via communication satellite: evaluation of ultrasonographic images.

    Science.gov (United States)

    Suzuki, H; Horikoshi, H; Shiba, H; Shimamoto, S

    1996-01-01

    As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment.

  1. Using Optical Interferometry for GEO Satellites Imaging: An Update

    Science.gov (United States)

    2016-05-27

    Using Optical Interferometry for GEO satellites imaging: an update Sergio R. Restainoa,J. Thomas Armstronga, Ellyn K. Bainesa, Henrique R. Schmitta...of a geostationary satellite using the Navy Precision Optical Inter- ferometer (NPOI) during the glint season of March 2015. We succeeded in detecting...detection of a satellite . Keywords: geostationary satellites , optical interferometry, imaging, telescope arrays 1. INTRODUCTION Developing the ability to

  2. ASTER 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  3. MODIS 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  4. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete

    2009-01-01

    Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy......-based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters...

  5. Polar-Orbiting Satellite (POES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...

  6. A Novel Location-Awareness Method Using CubeSats for Locating the Spot Beam Emitters of Geostationary Communications Satellites

    Directory of Open Access Journals (Sweden)

    Weicai Yang

    2018-01-01

    Full Text Available As more spacecraft are launched into the Geostationary Earth Orbit (GEO belt, the possibility of fatal collisions or unnecessary interference between spacecraft increases. In this paper, a new location-awareness method that uses CubeSats is proposed to assist with radiofrequency (RF domain verification by means of awareness and identification of the positions of the spot beam emitters of communications satellites in geostationary orbit. By flying a CubeSat (or a constellation of CubeSats through the coverage area of a spot beam, the spot beam emitter’s position is identified and the spot beam’s pattern knowledge is characterized. The geometry, the equations of motion of the spacecraft, the measurement process, and the filtering equations in a location system are addressed with respect to the location methods investigated in this study. A realistic scenario in which a CubeSat receives signals from GEO communications satellites is simulated using the Systems Tool Kit (STK. The results of the simulation and the analysis presented in this study provide a thorough verification of the performance of the location-awareness method.

  7. Hot spot detection for breast cancer in Ki-67 stained slides: image dependent filtering approach

    Science.gov (United States)

    Niazi, M. Khalid Khan; Downs-Kelly, Erinn; Gurcan, Metin N.

    2014-03-01

    We present a new method to detect hot spots from breast cancer slides stained for Ki67 expression. It is common practice to use centroid of a nucleus as a surrogate representation of a cell. This often requires the detection of individual nuclei. Once all the nuclei are detected, the hot spots are detected by clustering the centroids. For large size images, nuclei detection is computationally demanding. Instead of detecting the individual nuclei and treating hot spot detection as a clustering problem, we considered hot spot detection as an image filtering problem where positively stained pixels are used to detect hot spots in breast cancer images. The method first segments the Ki-67 positive pixels using the visually meaningful segmentation (VMS) method that we developed earlier. Then, it automatically generates an image dependent filter to generate a density map from the segmented image. The smoothness of the density image simplifies the detection of local maxima. The number of local maxima directly corresponds to the number of hot spots in the breast cancer image. The method was tested on 23 different regions of interest images extracted from 10 different breast cancer slides stained with Ki67. To determine the intra-reader variability, each image was annotated twice for hot spots by a boardcertified pathologist with a two-week interval in between her two readings. A computer-generated hot spot region was considered a true-positive if it agrees with either one of the two annotation sets provided by the pathologist. While the intra-reader variability was 57%, our proposed method can correctly detect hot spots with 81% precision.

  8. Spot counting on fluorescence in situ hybridization in suspension images using Gaussian mixture model

    Science.gov (United States)

    Liu, Sijia; Sa, Ruhan; Maguire, Orla; Minderman, Hans; Chaudhary, Vipin

    2015-03-01

    Cytogenetic abnormalities are important diagnostic and prognostic criteria for acute myeloid leukemia (AML). A flow cytometry-based imaging approach for FISH in suspension (FISH-IS) was established that enables the automated analysis of several log-magnitude higher number of cells compared to the microscopy-based approaches. The rotational positioning can occur leading to discordance between spot count. As a solution of counting error from overlapping spots, in this study, a Gaussian Mixture Model based classification method is proposed. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) of GMM are used as global image features of this classification method. Via Random Forest classifier, the result shows that the proposed method is able to detect closely overlapping spots which cannot be separated by existing image segmentation based spot detection methods. The experiment results show that by the proposed method we can obtain a significant improvement in spot counting accuracy.

  9. AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

  10. Spot-5 multispectral image for 60-75 days of rice mapping

    International Nuclear Information System (INIS)

    Ramli, Mohd Amiruddin; Shariff, Abdul Rashid Mohamed; Bejo, Siti Khairunniza

    2014-01-01

    The objective of this study is to investigate the potential application of Spot-5 multispectral satellite data in monitoring rice cultivation areas in IADA (Integrated Agriculture Development Area) located at Kerian District, Perak Malaysia. Information of the rice cultivation areas is a global economic and environmental significance. Multi-spectral images acquired at high spatial resolution are an important tool, especially in agricultural applications. This paper addresses the relationship between normalize difference vegetation index (NDVI) and ancillary data acquired from Farmers Organization Authority (PPK) for 217 farmer's field in IADA Kerian. The results indicated that NDVI range 0.62 – 0.75 has a strong positive relationship with the ground survey area estimation with (r = 0.85; p <0.01) (r 2 = 0.722). The r 2 value of 0.722 indicated a statistically significant linear relationship between the rice area estimate using NDVI range 0.62 – 0.75 and on the ground surveyed data for 217 farmers' fields. The equation of unstandardized distribution can be described as Ŷ=0.0197+0.852x. The equation for standardized regression formula for this distribution is Ŷ= 0.850x. Thus, the results indicate that 60-75 days of rice area can be estimated from the following equation Ŷ=0.197+0.852x, where Ŷ is the predicted rice area and x is area calculated using NDVI range 0.62-0.75 in IADA Kerian Perak Malaysia. The results appear promising and rice mapping operations using SPOT-5 multispectral image data can be foreseen

  11. Spatial distribution of forest fires and controlling factors in Andhra Pradesh, India using SPOT satellite datasets.

    Science.gov (United States)

    Vadrevu, Krishna P; Eaturu, Anuradha; Badarinath, K V S

    2006-12-01

    Fires are one of the major causes of forest disturbance and destruction in several dry deciduous forests of southern India. In this study, we use remote sensing data sets in conjunction with topographic, vegetation, climate and socioeconomic factors for determining the potential causes of forest fires in Andhra Pradesh, India. Spatial patterns in fire characteristics were analyzed using SPOT satellite remote sensing datasets. We then used nineteen different metrics in concurrence with fire count datasets in a robust statistical framework to arrive at a predictive model that best explained the variation in fire counts across diverse geographical and climatic gradients. Results suggested that, of all the states in India, fires in Andhra Pradesh constituted nearly 13.53% of total fires. District wise estimates of fire counts for Andhra Pradesh suggested that, Adilabad, Cuddapah, Kurnool, Prakasham and Mehbubnagar had relatively highest number of fires compared to others. Results from statistical analysis suggested that of the nineteen parameters, population density, demand of metabolic energy (DME), compound topographic index, slope, aspect, average temperature of the warmest quarter (ATWQ) along with literacy rate explained 61.1% of total variation in fire datasets. Among these, DME and literacy rate were found to be negative predictors of forest fires. In overall, this study represents the first statewide effort that evaluated the causative factors of fire at district level using biophysical and socioeconomic datasets. Results from this study identify important biophysical and socioeconomic factors for assessing 'forest fire danger' in the study area. Our results also identify potential 'hotspots' of fire risk, where fire protection measures can be taken in advance. Further this study also demonstrate the usefulness of best-subset regression approach integrated with GIS, as an effective method to assess 'where and when' forest fires will most likely occur.

  12. Accuracy VS Performance: Finding the Sweet Spot in the Geospatial Resolution of Satellite Metadata

    Science.gov (United States)

    Baskin, W. E.; Mangosing, D. C.; Rinsland, P. L.

    2010-12-01

    NASA’s Atmospheric Science Data Center (ASDC) and the Cloud-Aerosol LIDAR and Infrared Pathfinder Satellite Observation (CALIPSO) team at the NASA Langley Research Center recently collaborated in the development of a new CALIPSO Search and Subset web application. The web application is comprised of three elements: (1) A PostGIS-enabled PostgreSQL database system, which is used to store temporal and geospatial metadata from CALIPSO’s LIDAR, Infrared, and Wide Field Camera datasets, (2) the SciFlo engine, which is a data flow engine that enables semantic, scientific data flow executions in a grid or clustered network computational environment, and (3) PHP-based web application that incorporates some Web 2.0 / AJAX technologies used in the web interface. The search portion of the web application leverages geodetic indexing and search capabilities that became available in the February 2010 release of PostGIS version1.5. This presentation highlights the lessons learned in experimenting with various geospatial resolutions of CALIPSO’s LIDAR sensor ground track metadata. Details of the various spatial resolutions, spatial database schema designs, spatial indexing strategies, and performance results will be discussed. The focus will be on illustrating our findings on the spatial resolutions for ground track metadata that optimized search time and search accuracy in the CALIPSO Search and Subset Application. The CALIPSO satellite provides new insight into the role that clouds and atmospheric aerosols (airborne particles) play in regulating Earth's weather, climate, and air quality. CALIPSO combines an active LIDAR instrument with passive infrared and visible imagers to probe the vertical structure and properties of thin clouds and aerosols over the globe. The CALIPSO satellite was launched on April 28, 2006 and is part of the A-train satellite constellation. The ASDC in Langley’s Science Directorate leads NASA’s program for the processing, archival and

  13. Space Object Detection in Video Satellite Images Using Motion Information

    Directory of Open Access Journals (Sweden)

    Xueyang Zhang

    2017-01-01

    Full Text Available Compared to ground-based observation, space-based observation is an effective approach to catalog and monitor increasing space objects. In this paper, space object detection in a video satellite image with star image background is studied. A new detection algorithm using motion information is proposed, which includes not only the known satellite attitude motion information but also the unknown object motion information. The effect of satellite attitude motion on an image is analyzed quantitatively, which can be decomposed into translation and rotation. Considering the continuity of object motion and brightness change, variable thresholding based on local image properties and detection of the previous frame is used to segment a single-frame image. Then, the algorithm uses the correlation of object motion in multiframe and satellite attitude motion information to detect the object. Experimental results with a video image from the Tiantuo-2 satellite show that this algorithm provides a good way for space object detection.

  14. Using and comparing two nonparametric methods (CART and RF and SPOT-HRG satellite data to predictive tree diversity distribution

    Directory of Open Access Journals (Sweden)

    SIAVASH KALBI

    2014-05-01

    Full Text Available Kalbi S, Fallah A, Hojjati SM. 2014. Using and comparing two nonparametric methods (CART and RF and SPOT-HRG satellite data to predictive tree diversity distribution. Nusantara Bioscience 6: 57-62. The prediction of spatial distributions of tree species by means of survey data has recently been used for conservation planning. Numerous methods have been developed for building species habitat suitability models. The present study was carried out to find the possible proper relationships between tree species diversity indices and SPOT-HRG reflectance values in Hyrcanian forests, North of Iran. Two different modeling techniques, Classification and Regression Trees (CART and Random Forest (RF, were fitted to the data in order to find the most successfully model. Simpson, Shannon diversity and the reciprocal of Simpson indices were used for estimating tree diversity. After collecting terrestrial information on trees in the 100 samples, the tree diversity indices were calculated in each plot. RF with determinate coefficient and RMSE from 56.3 to 63.9 and RMSE from 0.15 to 0.84 has better results than CART algorithms with determinate coefficient 42.3 to 63.3 and RMSE from 0.188 to 0.88. Overall the results showed that the SPOT-HRG satellite data and nonparametric regression could be useful for estimating tree diversity in Hyrcanian forests, North of Iran.

  15. Moving Target Information Extraction Based on Single Satellite Image

    Directory of Open Access Journals (Sweden)

    ZHAO Shihu

    2015-03-01

    Full Text Available The spatial and time variant effects in high resolution satellite push broom imaging are analyzed. A spatial and time variant imaging model is established. A moving target information extraction method is proposed based on a single satellite remote sensing image. The experiment computes two airplanes' flying speed using ZY-3 multispectral image and proves the validity of spatial and time variant model and moving information extracting method.

  16. THERMAL AND VISIBLE SATELLITE IMAGE FUSION USING WAVELET IN REMOTE SENSING AND SATELLITE IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    A. H. Ahrari

    2017-09-01

    Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.

  17. The edge detection enhancement on satellite image using bilateral filter

    Science.gov (United States)

    Fawwaz, I.; Zarlis, M.; Suherman; Rahmat, R. F.

    2018-02-01

    Satellite imagery is the image taken from satellites from outer space. It captures the appearance of the earth’s surface through remote sensing. Usually, satellite image’s object is hardly detected because many objects are covered with cloud shadows in the sky. Edge detection has an important role in image analysis. Edge detection aims to extract the boundary of an object contained in the image. Gaussian Filter is usually used on edge detection to smooth the image and reduce noise. However, in satellite image, we can improve it by using another filter. In this research, we compare gaussian filter with bilateral filter and analyze those two methods. We also using several operators to see the optimized process. After the experiment, by using the comparison parameter such as largest PSNR value, and the smallest MSE value, we can conclude that Bilateral Filter with Canny Operator is the most optimized edge detection for Satellite Imagery.

  18. Dual focal-spot imaging for phase extraction in phase-contrast radiography

    International Nuclear Information System (INIS)

    Donnelly, Edwin F.; Price, Ronald R.; Pickens, David R.

    2003-01-01

    The purpose of this study was to evaluate dual focal spot imaging as a method for extracting the phase component from a phase-contrast radiography image. All measurements were performed using a microfocus tungsten-target x-ray tube with an adjustable focal-spot size (0.01 mm to 0.045 mm). For each object, high-resolution digital radiographs were obtained with two different focal spot sizes to produce matched image pairs in which all other geometric variables as well as total exposure and tube kVp were held constant. For each image pair, a phase extraction was performed using pixel-wise division. The phase-extracted image resulted in an image similar to the standard image processing tool commonly referred to as 'unsharp masking' but with the additional edge-enhancement produced by phase-contrast effects. The phase-extracted image illustrates the differences between the two images whose imaging parameters differ only in focal spot size. The resulting image shows effects from both phase contrast as well as geometric unsharpness. In weakly attenuating materials the phase-contrast effect predominates, while in strongly attenuating materials the phase effects are so small that they are not detectable. The phase-extracted image in the strongly attenuating object reflects differences in geometric unsharpness. The degree of phase extraction depends strongly on the size of the smallest focal spot used. This technique of dual-focal spot phase-contrast radiography provides a simple technique for phase-component (edge) extraction in phase-contrast radiography. In strongly attenuating materials the phase-component is overwhelmed by differences in geometric unsharpness. In these cases the technique provides a form of unsharp masking which also accentuates the edges. Thus, the two effects are complimentary and may be useful in the detection of small objects

  19. Virtual Satellite Construction and Application for Image Classification

    International Nuclear Information System (INIS)

    Su, W G; Su, F Z; Zhou, C H

    2014-01-01

    Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively

  20. Thermal imaging of hot spots in nanostructured microstripes

    Energy Technology Data Exchange (ETDEWEB)

    Saidi, E; Lesueur, J; Aigouy, L [LPEM, CNRS UPR5, ESPCI, 10 rue Vauquelin, 75231 Paris Cedex 5 (France); Labeguerie-Egea, J; Mortier, M, E-mail: lionel.aigouy@espci.f [LCMCP, CNRS UMR 7574, ENSCP, 11 rue P. et M. Curie, 75005 Paris (France)

    2010-03-01

    By scanning thermal microscopy, we study the behavior of nanostructured metallic microstripes heated by Joule effect. Regularly spaced indentations have been made along the thin film stripe in order to create hot spots. For the designed stripe geometry, we observe that heat remains confined in the wire and in particular at shrinkage points within {approx}1{mu}m{sup 2}. Thermal maps have been obtained with a good lateral resolution (< 300nm) and a good temperature sensitivity ({approx}1K).

  1. Signification de linéaments sur une image SPOT dans la région liégeoise

    OpenAIRE

    Ozer, André; Marion, Jean-Marc; Roland, Christine; Tréfois, Philippe

    1988-01-01

    Under the preliminary evaluation program of the SPOT satellite (PEPS project), researches in remote sensing applied to geology of sheet 49 (SPA) have helped to identify several families of lineaments through the use of directional filters . It was mainly lineaments whose orientations reflected condrusian structures but also, other ones (NW-SE, NS and NNE-SSW) which did not correspond to any known geological structures. Dans le cadre du programme d'étude préliminaire du satellite SPOT (proj...

  2. Analysis of drought events in a Mediterranean semi-arid region, Using SPOT-VGT and TERRA-MODIS satellite products

    Science.gov (United States)

    Zribi, Mehrez; Dridi, Ghofrane; Amri, Rim; Lili-Chabaane, Zohra

    2015-04-01

    In semi-arid regions, and northern Africa in particular, the scarcity of rainfall and the occurrence of long periods of drought, represent one of the main environmental factors having a negative effect on agricultural productivity. This is the case in Central Tunisia, where the monitoring of agricultural and water resources is of prime importance. Vegetation cover is a key parameter to analyse this problem. Remote sensing has shown in the last decades a high potential to estimate these surface parameters. This study is based on two satellite products: SPOT-VGT (1998-2012) and TERRA-MODIS (2001-2012) NDVI products. They are used to study the dynamics of vegetation and land use. Different behaviors linked to drought periods have been observed. A strong agreement is observed between products proposed by the two sensors. Low spatial resolution SPOT-VGT and TERRA-MODIS NDVI images were used to map the land into three characteristic classes: olive trees, annual agriculture and pastures. An analysis of vegetation behaviour for dry years is proposed using the Windowed Fourier Transform (WTF). The Fourier Transform is able to analyze the frequency content of a signal in the time domain by decomposing the signal as the superposition of sine and cosine basis functions. Analysis for annual agricultural areas demonstrates a combined effect between climate and farmers behaviours. In these areas, bare soils show a high increasing for drought years. Highest percent of bare soil is retrieved with TERRA-MODIS than with SPOT-VGT. This could be explained by the spatial resolution of the two sensors. The temporal series of optical images are finally used to calculate a drought index, namely the VAI (Vegetation Anomaly Index), on the plain of Kairouan (Amri et al., 2011). This index shows a high correlation with precipitation statistics.

  3. Forme Fruste Keratoconus Imaging and Validation via Novel Multi-Spot Reflection Topography

    Directory of Open Access Journals (Sweden)

    Anastasios John Kanellopoulos

    2013-10-01

    Full Text Available Background/Aims: This case report aims to evaluate safety, efficacy and applicability of anterior surface imaging in a patient with forme fruste keratoconus (FFKC based on a novel multi-spot, multicolor light-emitting-diode (LED tear film-reflection imaging technology Case Description: A 45-year-old male patient, clinically diagnosed with FFKC, with highly asymmetric manifestation between his eyes, was subjected to the multicolor-spot reflection topography. We investigated elevation and sagittal curvature maps comparatively with the multicolor-spot reflection topographer, a Placido topographer and a Scheimpflug imaging system. For the right eye, steep and flat keratometry values were 41.92 and 41.05 D with the multicolor spot-reflection topographer, 42.30 and 42.08 D with the Placido, and 41.95 and 41.19 D with the Scheimpflug system. For the left eye, steep and flat keratometry values were 41.86 and 41.19 D with the multicolor spot-reflection topographer, 42.06 and 41.66 D with the Placido topographer, and 41.96 and 41.66 D with the Scheimpflug camera. Average repeatability of the keratometry measurements was ±0.35 D for the multicolor spot-reflection topographer, ±0.30 D for the Placido, and ±0.25 D for the Scheimpflug camera. Very good agreement between the instruments was demonstrated on the elevation and curvature maps. Conclusion: The ease of use and the comparable results offered by the multicolor spot-reflection topographer, in comparison to established Placido and Scheimpflug imaging, as well as the increased predictability that may be offered by the multicolor spot-reflection topographer, may hold promise for wider clinical application, such as screening of young adults for early keratoconus and, in a much wider perspective, potential candidates for laser corneal refractive surgery.

  4. Forme Fruste Keratoconus Imaging and Validation via Novel Multi-Spot Reflection Topography.

    Science.gov (United States)

    Kanellopoulos, Anastasios John; Asimellis, George

    2013-01-01

    This case report aims to evaluate safety, efficacy and applicability of anterior surface imaging in a patient with forme fruste keratoconus (FFKC) based on a novel multi-spot, multicolor light-emitting-diode (LED) tear film-reflection imaging technology. A 45-year-old male patient, clinically diagnosed with FFKC, with highly asymmetric manifestation between his eyes, was subjected to the multicolor-spot reflection topography. We investigated elevation and sagittal curvature maps comparatively with the multicolor-spot reflection topographer, a Placido topographer and a Scheimpflug imaging system. For the right eye, steep and flat keratometry values were 41.92 and 41.05 D with the multicolor spot-reflection topographer, 42.30 and 42.08 D with the Placido, and 41.95 and 41.19 D with the Scheimpflug system. For the left eye, steep and flat keratometry values were 41.86 and 41.19 D with the multicolor spot-reflection topographer, 42.06 and 41.66 D with the Placido topographer, and 41.96 and 41.66 D with the Scheimpflug camera. Average repeatability of the keratometry measurements was ±0.35 D for the multicolor spot-reflection topographer, ±0.30 D for the Placido, and ±0.25 D for the Scheimpflug camera. Very good agreement between the instruments was demonstrated on the elevation and curvature maps. The ease of use and the comparable results offered by the multicolor spot-reflection topographer, in comparison to established Placido and Scheimpflug imaging, as well as the increased predictability that may be offered by the multicolor spot-reflection topographer, may hold promise for wider clinical application, such as screening of young adults for early keratoconus and, in a much wider perspective, potential candidates for laser corneal refractive surgery.

  5. Phantom-based standardization of CT angiography images for spot sign detection

    Energy Technology Data Exchange (ETDEWEB)

    Morotti, Andrea; Rosand, Jonathan [Harvard Medical School, Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Massachusetts General Hospital, Boston, MA (United States); Harvard Medical School, J. P. Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA (United States); Romero, Javier M. [Harvard Medical School, Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Massachusetts General Hospital, Boston, MA (United States); Harvard Medical School, J. P. Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA (United States); Harvard Medical School, Neuroradiology Service, Department of Radiology, Massachusetts General Hospital, Boston, MA (United States); Jessel, Michael J.; Vashkevich, Anastasia; Schwab, Kristin; Greenberg, Steven M. [Harvard Medical School, J. P. Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA (United States); Hernandez, Andrew M.; Boone, John M. [University of California Davis, Department of Radiology, Sacramento, CA (United States); Burns, Joseph D. [Lahey Hospital and Medical Center, Department of Neurology, Burlington, MA (United States); Shah, Qaisar A. [Abington Memorial Hospital, Abington, PA (United States); Bergman, Thomas A. [Hennepin County Medical Center, Minneapolis, MN (United States); Suri, M.F.K. [St. Cloud Hospital, St. Cloud, MN (United States); Ezzeddine, Mustapha [University of Minnesota, Minneapolis, MN (United States); Kirmani, Jawad F. [JFK Medical Center, Stroke and Neurovascular Center, Edison, NJ (United States); Agarwal, Sachin [Columbia University Medical Center, New York, NY (United States); Hays Shapshak, Angela [University of Alabama at Birmingham, Birmingham, AL (United States); Messe, Steven R. [University of Pennsylvania, Philadelphia, PA (United States); Venkatasubramanian, Chitra [Stanford University, Stanford, CA (United States); Palmieri, Katherine [The University of Kansas Health System, Kansas City, KS (United States); Lewandowski, Christopher [Henry Ford Hospital, Detroit, MI (United States); Chang, Tiffany R. [University of Texas Medical School, Houston, TX (United States); Chang, Ira [Colorado Neurological Institute, Swedish Medical Center, Englewood, CO (United States); Rose, David Z. [Tampa General Hospital, University of South Florida College of Medicine, Tampa, FL (United States); Smith, Wade [UCSF Medical Center, San Francisco, CA (United States); Hsu, Chung Y.; Liu, Chun-Lin [China Medical University Hospital, Taichung (China); Lien, Li-Ming; Hsiao, Chen-Yu [Shin Kong Wu Ho-Su Memorial Hospital, Taipei (China); Iwama, Toru [Gifu University Hospital, Gifu (Japan); Afzal, Mohammad Rauf; Qureshi, Adnan I. [University of Minnesota, Zeenat Qureshi Stroke Research Center, Minneapolis, MN (United States); Cassarly, Christy; Hebert Martin, Renee [Medical University of South Carolina, Department of Public Health Sciences, Charleston, SC (United States); Goldstein, Joshua N. [Harvard Medical School, Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Massachusetts General Hospital, Boston, MA (United States); Harvard Medical School, J. P. Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA (United States); Harvard Medical School, Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA (United States); Collaboration: ATACH-II and NETT Investigators

    2017-09-15

    The CT angiography (CTA) spot sign is a strong predictor of hematoma expansion in intracerebral hemorrhage (ICH). However, CTA parameters vary widely across centers and may negatively impact spot sign accuracy in predicting ICH expansion. We developed a CT iodine calibration phantom that was scanned at different institutions in a large multicenter ICH clinical trial to determine the effect of image standardization on spot sign detection and performance. A custom phantom containing known concentrations of iodine was designed and scanned using the stroke CT protocol at each institution. Custom software was developed to read the CT volume datasets and calculate the Hounsfield unit as a function of iodine concentration for each phantom scan. CTA images obtained within 8 h from symptom onset were analyzed by two trained readers comparing the calibrated vs. uncalibrated density cutoffs for spot sign identification. ICH expansion was defined as hematoma volume growth >33%. A total of 90 subjects qualified for the study, of whom 17/83 (20.5%) experienced ICH expansion. The number of spot sign positive scans was higher in the calibrated analysis (67.8 vs 38.9% p < 0.001). All spot signs identified in the non-calibrated analysis remained positive after calibration. Calibrated CTA images had higher sensitivity for ICH expansion (76 vs 52%) but inferior specificity (35 vs 63%) compared with uncalibrated images. Normalization of CTA images using phantom data is a feasible strategy to obtain consistent image quantification for spot sign analysis across different sites and may improve sensitivity for identification of ICH expansion. (orig.)

  6. Spot restoration for GPR image post-processing

    Science.gov (United States)

    Paglieroni, David W; Beer, N. Reginald

    2014-05-20

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  7. Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

  8. Kansas Satellite Image Database (KSID) 2004-2005

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...

  9. Phantom-based standardization of CT angiography images for spot sign detection.

    Science.gov (United States)

    Morotti, Andrea; Romero, Javier M; Jessel, Michael J; Hernandez, Andrew M; Vashkevich, Anastasia; Schwab, Kristin; Burns, Joseph D; Shah, Qaisar A; Bergman, Thomas A; Suri, M Fareed K; Ezzeddine, Mustapha; Kirmani, Jawad F; Agarwal, Sachin; Shapshak, Angela Hays; Messe, Steven R; Venkatasubramanian, Chitra; Palmieri, Katherine; Lewandowski, Christopher; Chang, Tiffany R; Chang, Ira; Rose, David Z; Smith, Wade; Hsu, Chung Y; Liu, Chun-Lin; Lien, Li-Ming; Hsiao, Chen-Yu; Iwama, Toru; Afzal, Mohammad Rauf; Cassarly, Christy; Greenberg, Steven M; Martin, Renee' Hebert; Qureshi, Adnan I; Rosand, Jonathan; Boone, John M; Goldstein, Joshua N

    2017-09-01

    The CT angiography (CTA) spot sign is a strong predictor of hematoma expansion in intracerebral hemorrhage (ICH). However, CTA parameters vary widely across centers and may negatively impact spot sign accuracy in predicting ICH expansion. We developed a CT iodine calibration phantom that was scanned at different institutions in a large multicenter ICH clinical trial to determine the effect of image standardization on spot sign detection and performance. A custom phantom containing known concentrations of iodine was designed and scanned using the stroke CT protocol at each institution. Custom software was developed to read the CT volume datasets and calculate the Hounsfield unit as a function of iodine concentration for each phantom scan. CTA images obtained within 8 h from symptom onset were analyzed by two trained readers comparing the calibrated vs. uncalibrated density cutoffs for spot sign identification. ICH expansion was defined as hematoma volume growth >33%. A total of 90 subjects qualified for the study, of whom 17/83 (20.5%) experienced ICH expansion. The number of spot sign positive scans was higher in the calibrated analysis (67.8 vs 38.9% p signs identified in the non-calibrated analysis remained positive after calibration. Calibrated CTA images had higher sensitivity for ICH expansion (76 vs 52%) but inferior specificity (35 vs 63%) compared with uncalibrated images. Normalization of CTA images using phantom data is a feasible strategy to obtain consistent image quantification for spot sign analysis across different sites and may improve sensitivity for identification of ICH expansion.

  10. Effect of satellite formations and imaging modes on global albedo estimation

    Science.gov (United States)

    Nag, Sreeja; Gatebe, Charles K.; Miller, David W.; de Weck, Olivier L.

    2016-05-01

    We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static referencecase. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/m2 or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than

  11. Control of satellite imaging formations in multi-body regimes

    Science.gov (United States)

    Howell, Kathleen C.; Millard, Lindsay D.

    2009-03-01

    Libration point orbits may be ideal locations for satellite imaging formations. Therefore, control of these arrays in multi-body regimes is critical. A continuous feedback control algorithm is developed that maintains a formation of satellites in motion that is bounded relative to a halo orbit. This algorithm is derived based on the dynamic characteristics of the phase space near periodic orbits in the circular restricted three-body problem (CR3BP). By adjusting parameters of the control algorithm appropriately, satellites in the formation follow trajectories that are particularly advantageous to imaging arrays. Image reconstruction and coverage of the ( u, v) plane are simulated for interferometric satellite configurations, demonstrating potential applications of the algorithm and the resulting motion.

  12. "Calibration-on-the-spot'': How to calibrate an EMCCD camera from its images

    DEFF Research Database (Denmark)

    Mortensen, Kim; Flyvbjerg, Henrik

    In localization-based microscopy, super-resolution is obtained by analyzing isolated diffraction-limited spots imaged, typically, with EMCCD cameras. To compare experiments and calculate localization precision, the photon-to-signal amplification factor is needed but unknown without a calibration...... of the camera. Here we show how this can be done post festum from just a recorded image. We demonstrate this (i) theoretically, mathematically, (ii) by analyzing images recorded with an EMCCD camera, and (iii) by analyzing simulated EMCCD images for which we know the true values of parameters. In summary, our...... images during the measurement itself, and can at any later time be decoded with calibration-on-the-spot....

  13. Automatic Matching of High Resolution Satellite Images Based on RFM

    OpenAIRE

    JI Shunping; YUAN Xiuxiao

    2016-01-01

    A matching method for high resolution satellite images based on RFM is presented.Firstly,the RFM parameters are used to predict the initial parallax of corresponding points and the prediction accuracy is analyzed.Secondly,the approximate epipolar equation is constructed based on projection tracking and its accuracy is analyzed.Thirdly,approximate 1D image matching is executed on pyramid images and least square matching on base images.At last RANSAC is imbedded to eliminate mis-matching points...

  14. Satellite Articulation Characterization from an Image Trajectory Matrix Using Optimization

    Science.gov (United States)

    Curtis, D. H.; Cobb, R. G.

    Autonomous on-orbit satellite servicing and inspection benefits from an inspector satellite that can autonomously gain as much information as possible about the primary satellite. This includes performance of articulated objects such as solar arrays, antennas, and sensors. This paper presents a method of characterizing the articulation of a satellite using resolved monocular imagery. A simulated point cloud representing a nominal satellite with articulating solar panels and a complex articulating appendage is developed and projected to the image coordinates that would be seen from an inspector following a given inspection route. A method is developed to analyze the resulting image trajectory matrix. The developed method takes advantage of the fact that the route of the inspector satellite is known to assist in the segmentation of the points into different rigid bodies, the creation of the 3D point cloud, and the identification of the articulation parameters. Once the point cloud and the articulation parameters are calculated, they can be compared to the known truth. The error in the calculated point cloud is determined as well as the difference between the true workspace of the satellite and the calculated workspace. These metrics can be used to compare the quality of various inspection routes for characterizing the satellite and its articulation.

  15. Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

    Science.gov (United States)

    Gautam, R. S.; Singh, D.; Mittal, A.; Sajin, P.

    The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system

  16. Considerations and methods for the changes detection using satellite images in the Municipality of Paipa

    International Nuclear Information System (INIS)

    Riano M, Orlando

    2002-01-01

    In this article the considerations and methods are presented for the changes detection in the earth covering, using two images Landsat TM of different dates for an area of the municipality of Paipa, Boyaca. The changes detection has become an important application of the multi-spectral data and multi-temporal of the satellites programs for studies of natural resources Landsat, TM and Spot, in such a way that is possible to determine the types and extension of the changes that are given in the environment. To carry out this process some digital techniques they have been used for changes detection, such as: images superposition, differences between images and analysis of main components. These techniques allowed to observe and to analyze changes in the use and covering of the earth in this municipality

  17. [An experiment to estimate locations of radioisotopes producing black spots on medical images].

    Science.gov (United States)

    Nishihara, Sadamitsu; Hayashi, Hiroaki; Hanamitsu, Hiroki; Mori, Michiko

    2012-01-01

    Caused by the accident of nuclear power plants in the Fukushima at 2011, many radioisotopes (RI) were diffused to the environment. As a result, X-ray detectors were stained with RIs and black spots appeared on the medical images. Using the RI of (134)Cs and (137)Cs, black spots which appeared on the photostimulable phosphor plate (X-ray detector) were reproduced experimentally. The aim of this study is the following two points; firstly, to clarify the relationship between long-time irradiations of RI and fading effect, and secondly, to clarify the positional relationship between the RI sources and the X-ray detector based on irradiation times of RI. For the latter experiment, the samples were made by spraying water (containing the RI) in order to reproduce small point sources. Then, the sources were placed on the photostimulable phosphor plate or on the cassette, and corresponding images with different irradiation times were taken. The black spots could be reproduced with the condition, in which sources were directly adhered to the photostimulable phosphor plate. We observed the black spots when sources were placed on the cassette for one week. Based on the result, we summarized that the RI which are directly adhered on the photostimulable phosphor plate may produce the black spots.

  18. The Use of Spot Image for Mangrove Inventory in Cimanuk Delta West Java, Indonesia

    Directory of Open Access Journals (Sweden)

    Hartono .

    2013-07-01

    At least two mangrove types of mangrove could be identified from the SPOT image. Dense mangrove was found in Petak 7, Petak 8, Petak 9 and Petak 12. In the other Petaks, mangrove were less than 20% of their surface. Mangrove of Rhizophora in 26 Petaks covered 290 Ha only.

  19. Multi-image acquisition-based distance sensor using agile laser spot beam.

    Science.gov (United States)

    Riza, Nabeel A; Amin, M Junaid

    2014-09-01

    We present a novel laser-based distance measurement technique that uses multiple-image-based spatial processing to enable distance measurements. Compared with the first-generation distance sensor using spatial processing, the modified sensor is no longer hindered by the classic Rayleigh axial resolution limit for the propagating laser beam at its minimum beam waist location. The proposed high-resolution distance sensor design uses an electronically controlled variable focus lens (ECVFL) in combination with an optical imaging device, such as a charged-coupled device (CCD), to produce and capture different laser spot size images on a target with these beam spot sizes different from the minimal spot size possible at this target distance. By exploiting the unique relationship of the target located spot sizes with the varying ECVFL focal length for each target distance, the proposed distance sensor can compute the target distance with a distance measurement resolution better than the axial resolution via the Rayleigh resolution criterion. Using a 30 mW 633 nm He-Ne laser coupled with an electromagnetically actuated liquid ECVFL, along with a 20 cm focal length bias lens, and using five spot images captured per target position by a CCD-based Nikon camera, a proof-of-concept proposed distance sensor is successfully implemented in the laboratory over target ranges from 10 to 100 cm with a demonstrated sub-cm axial resolution, which is better than the axial Rayleigh resolution limit at these target distances. Applications for the proposed potentially cost-effective distance sensor are diverse and include industrial inspection and measurement and 3D object shape mapping and imaging.

  20. A CubeSat Mission for Mapping Spot Beams of Geostationary Communications Satellites

    Science.gov (United States)

    2015-03-26

    time, the concept of accomplishing space missions with smaller nanosatellite -class spacecraft becomes increasingly feasible. This research focuses... nanosatellite -class spacecraft [8]. The small satellite community has been studying various missions on nanosatellite -class spacecraft, in a similar manner to...mission seeks to fly a cluster of three nanosatellites to geolocate a cooperative RF transmitter to within 100m – using RF information from ground

  1. Medical image transmission via communication satellite. Evaluation of bone scintigraphy

    International Nuclear Information System (INIS)

    Suzuki, Hideki; Inoue, Tomio; Endo, Keigo; Shimamoto, Shigeru.

    1995-01-01

    As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT 1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical imagings by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6±2.6% via satellite, and 93.2±2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes. (author)

  2. [Medical image transmission via communication satellite: evaluation of bone scintigraphy].

    Science.gov (United States)

    Suzuki, H; Inoue, T; Endo, K; Shimamoto, S

    1995-10-01

    As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical images by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6 +/- 2.6% via satellite, and 93.2 +/- 2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes.

  3. Automatic Matching of High Resolution Satellite Images Based on RFM

    Directory of Open Access Journals (Sweden)

    JI Shunping

    2016-02-01

    Full Text Available A matching method for high resolution satellite images based on RFM is presented.Firstly,the RFM parameters are used to predict the initial parallax of corresponding points and the prediction accuracy is analyzed.Secondly,the approximate epipolar equation is constructed based on projection tracking and its accuracy is analyzed.Thirdly,approximate 1D image matching is executed on pyramid images and least square matching on base images.At last RANSAC is imbedded to eliminate mis-matching points and matching results are obtained.Test results verified the method more robust and with higher matching rate,compared to 2D gray correlation method and the popular SIFT matching method,and the method preferably solved the question of high resolution satellite image matching with different stereo model,different time and large rotation images.

  4. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

    Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

  5. Mapping Of Vegetation And Mangrove Distribution Level In Batam Island Using SPOT-5 Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Fajar Rizki

    2017-12-01

    Full Text Available Mangrove is a plant that plays a significant role in the balance of the ecosystem and coastal environment. Batam Island which is one of the island in Batam island become one of the areas rich in mangrove plants. As time goes by, mangrove forests are getting worse. This research uses SPOT-5 imagery data in analyzing mangrove density value in Batam island with MSAVI (Modified Soil Adjusted Vegetation Index method. The results of this study have mangrove density in Batam Island which is divided into four classes, which is very tenuous, tenuous, medium, and very tightly where Batam Island is dominated by a class of density. Theoretically, NDVI values range from -1 to +1 but the mangrove vegetation index values are generally in the range between +0,1 to +0,7. NDVI values greater than this range are associated with a representation of a better level of vegetation health in the islands of Batam.

  6. Remote Characterization of Forest Structure Using 5 and 10m SPOT-5 Satellite Data

    Science.gov (United States)

    Wolter, P. T.; Townsend, P. A.; Sturtevant, B. R.

    2008-12-01

    Comprehensive understanding of forest dynamics at regional or biome scales is linked to our ability to accurately characterize forest ecosystems over increasingly large areas using remote sensing. LIDAR technology, although promising, is currently not yet viable for repeated regional accounting, necessitating the development of methods which take advantage of existing spaceborne assets. As such, our objective is to estimate a comprehensive set of forest structural attributes at a finer spatial grain size (10 m) over a broader area than is currently available. We employ neighborhood statistics (standard deviation, variance, sill variance, and ratios of these metrics at 5 and 10m) calculated from SPOT-5 data and derivatives to estimate and map forest structural characteristics. A partial least squares (PLS) regression approach was used with the local statistics and field data to produce models for pixel-wise estimation and mapping of mean values, respectively, for deciduous and coniferous forest canopy diameter (R2 = 0.82 and 0.93), tree height (R2 = 0.69 and 0.92), height of live crown (R2 = 0.58 and 0.81), canopy closure (R2 = 0.52 and 0.68), bole diameter at breast height (R2 = 0.82 and 0.90), and basal area (R2 = 0.71 and 0.74) for a 3,660 km2 area in northeast Minnesota. This approach for quantifying forest structure is robust in the sense that a detailed forest cover type map is not required at any step in the process. Hence, we show that multi-resolution SPOT-5 data may be used as a practical alternative to LIDAR for regional characterization of forest biophysical parameters.

  7. Determining Surface Material Properties Using Satellite Imaging

    Science.gov (United States)

    Gloudeman, C.; Gerace, A. D.

    2017-12-01

    Knowledge of soil moisture content is necessary for drought monitoring, crop irrigation, and water runoff. Remote sensing techniques provide a more efficient alternative to traditional field measurements for determining soil moisture content. Thermal infrared sensors from Landsat, MODIS Aqua & Terra, and AVHRR MetOp A & B satellites were used to find thermal inertia, which is highly correlated with soil moisture. A diurnal cycle is converted from band effective radiance to Land Surface Temperature (LST) using Planck's Law for blackbody radiation and a modified split-window algorithm. The THERM model for finding expected LST is then used to determine the material properties. A second approach was used to calculate apparent thermal inertia and soil moisture content from day/ night pairs of LST. For this method, only the MODIS Aqua LST product was used.To this end, we have observed clear differences in moisture between areas of vegetation and sand and between different crop fields. Our results indicate that matching the observed data with the THERM model could be improved with increased satellite measurements.

  8. Image Dodging Algorithm for GF-1 Satellite WFV Imagery

    Directory of Open Access Journals (Sweden)

    HAN Jie

    2016-12-01

    Full Text Available Image dodging method is one of the important processes that determines whether the mosaicking image can be used for remote sensing quantitative application. GF-1 satellite is the first satellite in CHEOS (Chinese high-resolution earth observation system. WFV multispectral sensor is one of the instruments onboard GF-1 satellite which consist of four cameras to mosaic imaging. According to the characteristics of WFV sensor, this paper proposes an image dodging algorithm based on cross/inter-radiometric calibration method. First, the traditional cross calibration method is applied to obtain the calibration coefficients of one WFV camera. Then statistical analysis and simulation methods are adopted to build the correlation models of DN and TOA (top of atmosphere radiances between adjacent cameras. The proposed method can not only accomplish the radiation performance transfer, but also can fulfill the image dodging. The experimental results show the cross/inter-radiometric calibration coefficients in this paper can effectively eliminate the radiation inconsistency problem of the adjacent camera image which realizes the image dodging. So our proposed dodging method can provide an important reference for other similar sensor in future.

  9. Detecting aircrafts from satellite images using saliency and conical ...

    Indian Academy of Sciences (India)

    Automatic target localization in satellite images still remains as a challenging problem in the field of computer vision. The issues ... Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai 600036, India; Defence Terrain Research Laboratory, Defence Research and Development ...

  10. Class imaging of hyperspectral satellite remote sensing data using FLSOM

    OpenAIRE

    Villmann, Thomas; Schleif, Frank-Michael; Merenyi, E.; Strickert, M.; Hammer, Barbara

    2007-01-01

    We propose an extension of the self-organizing map for supervised fuzzy classification learning, whereby uncertain (fuzzy) class information is also allowed for training data. The method is able to detect class similarities, which can be used for data vizualization. Applying a special functional metric, derived from of the L_p norms, we show the application of the method for classification and visualization of hyper-spectral data in satellite image remote sensing image analysis.

  11. Efficient temporal access of satellite image data

    CSIR Research Space (South Africa)

    Bachoo, A

    2008-11-01

    Full Text Available A single tile from the gridded MODIS products, spanning a region of interest of approximately 10° by 10°, is stored as an image containing close to six million pixels, with data in multiple spectral bands for each pixel. Time series analyses...

  12. Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

    Science.gov (United States)

    Ostir, K.; Cotar, K.; Marsetic, A.; Pehani, P.; Perse, M.; Zaksek, K.; Zaletelj, J.; Rodic, T.

    2015-04-01

    In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

  13. A flying spot x-ray system for Compton backscatter imaging

    International Nuclear Information System (INIS)

    Herr, M.D.; McInerney, J.J.; Copenhaver, G.L.; Lamser, D.G.

    1994-01-01

    A Compton x-ray backscatter imaging (CBI) system using a single detector and a mechanically rastered ''flying spot'' x-ray beam has been designed, built, and tested. While retaining the essential noninvasive imaging capability of previous multiple detector CBI devices, this single detector system incorporates several advances over earlier CBI devices: more efficient detection of scattered x-rays, reduced x-ray exposure, and a simplified scan protocol more suitable for use with humans. This new CBI system also has specific design features to permit automating data acquisition from multiple two-dimensional image planes for integration into a 3-D dynamic surface image. A simulated multislice scan study of a human thorax phantom provided x-ray dosimetry data verifying a very low x-ray dose delivered by this imaging device. Validation experiments with mechanical models show that surface displacement of typical heart beam frequencies can be measured to the nearest 0.1 mm (SD)

  14. Evaluation of Multiple Kernel Learning Algorithms for Crop Mapping Using Satellite Image Time-Series Data

    Science.gov (United States)

    Niazmardi, S.; Safari, A.; Homayouni, S.

    2017-09-01

    Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.

  15. Active learning approach for detection of hard exudates, cotton wool spots, and drusen in retinal images

    Science.gov (United States)

    Sánchez, Clara I.; Niemeijer, Meindert; Kockelkorn, Thessa; Abràmoff, Michael D.; van Ginneken, Bram

    2009-02-01

    Computer-aided Diagnosis (CAD) systems for the automatic identification of abnormalities in retinal images are gaining importance in diabetic retinopathy screening programs. A huge amount of retinal images are collected during these programs and they provide a starting point for the design of machine learning algorithms. However, manual annotations of retinal images are scarce and expensive to obtain. This paper proposes a dynamic CAD system based on active learning for the automatic identification of hard exudates, cotton wool spots and drusen in retinal images. An uncertainty sampling method is applied to select samples that need to be labeled by an expert from an unlabeled set of 4000 retinal images. It reduces the number of training samples needed to obtain an optimum accuracy by dynamically selecting the most informative samples. Results show that the proposed method increases the classification accuracy compared to alternative techniques, achieving an area under the ROC curve of 0.87, 0.82 and 0.78 for the detection of hard exudates, cotton wool spots and drusen, respectively.

  16. Efficacy of 'fine' focal spot imaging in CT abdominal angiography

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Lawrence Chia Wei; Devapalasundaram, Ashwini; Ardley, Nicholas [Monash Health, Department of Diagnostic Imaging, Clayton, Victoria (Australia); Lau, Kenneth K. [Monash Health, Department of Diagnostic Imaging, Clayton, Victoria (Australia); Monash University, Department of Medicine, Faculty of Medicine, Nursing, and Health Sciences, Victoria (Australia); Buchan, Kevin [Phillips Healthcare, Clinical Science, PO Box 312, Mont Albert, Victoria (Australia); Huynh, Minh [RMIT University, School of Mathematical and Geospatial Sciences, Victoria (Australia)

    2014-12-15

    To assess the efficacy of fine focal spot imaging in calcification beam-hardening artefact reduction and vessel clarity on CT abdominal angiography (CTAA). Adult patients of any age and gender who presented for CTAA were included. Thirty-nine patients were examined with a standard focal spot size (SFSS) of 1 x 1 mm in the first 3 months while 31 consecutive patients were examined with a fine focal spot size (FFSS) of 1 x 0.5 mm in the following 3 months. Vessel clarity and calcification beam-hardening artefacts of the abdominal aorta, celiac axis, superior mesenteric artery, inferior mesenteric artery, renal arteries, and iliac arteries were assessed using a 5-point grading scale by two blinded radiologists randomly. Cohen's Kappa test indicated that on average, there was substantial agreement among reviewers for vessel wall clarity and calcification artefact grading. Mann-Whitney test showed that there was a significant difference between the two groups, with FFSS performing significantly better for vessel clarity (U, 6481.50; p < 0.001; r, 0.73) and calcification artefact reduction (U, 1916; p < 0.001; r, 0.77). Fine focus CT angiography produces images with better vessel wall clarity and less vessel calcification beam-hardening artefact. (orig.)

  17. Fibrous Dysplasia Presenting as a Cold Spot in 18F-FLT PET/CT Imaging.

    Science.gov (United States)

    Rehak, Zdenek; Bencsikova, Beatrix; Zambo, Iva; Kazda, Tomas

    2016-06-01

    Fibrous dysplasia (FD) is a benign bone lesion in which normal bone marrow is replaced by fibro-osseous tissue. The usual high fluorodeoxyglucose (F-FDG) uptake in FD may lead to the misdiagnosis of bone malignancy. Herein, we describe the case of a 42-year old man with histologically verified FD of the pubic bone, which has been subsequently examined during follow-up for rectal cancer, using both F-FDG and fluorothymidine (F-FLT) PET/CT imaging. The FD lesion was characterized by a high uptake of F-FDG (hot spot) but very low uptake of F-FLT (cold spot) as compared with the contralateral unaffected pubic bone.

  18. Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations

    Science.gov (United States)

    Jorgensen, A.; Schmitt, H.; Mozurkewich, D.; Armstrong, J.; Restaino, S.; Hindsley, R.

    2011-09-01

    Geostationary satellites are generally too small to image at high resolution with conventional single-dish telescopes. Obtaining many resolution elements across a typical geostationary satellite body requires a single-dish telescope with a diameter of 10’s of m or more, with a good adaptive optics system. An alternative is to use an optical/infrared interferometer consisting of multiple smaller telescopes in an array configuration. In this paper and companion papers1, 2 we discuss the performance of a common-mount 30-element interferometer. The instrument design is presented by Mozurkewich et al.,1 and imaging performance is presented by Schmitt et al.2 In this paper we discuss signal-to-noise ratio for both fringe-tracking and imaging. We conclude that the common-mount interferometer is sufficiently sensitive to track fringes on the majority of geostationary satellites. We also find that high-fidelity images can be obtained after a short integration time of a few minutes to a few tens of minutes.

  19. 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).

  20. Fine focal spot size improves image quality in computed tomography abdomen and pelvis

    Energy Technology Data Exchange (ETDEWEB)

    Goh, Yin P.; Low, Keat; Kuganesan, Ahilan [Monash Health, Diagnostic Imaging Department, 246, Clayton Road, Clayton, Victoria (Australia); Lau, Kenneth K. [Monash Health, Diagnostic Imaging Department, 246, Clayton Road, Clayton, Victoria (Australia); Monash University, Department of Medicine, Faculty of Medicine, Nursing and Health Sciences, Victoria (Australia); Buchan, Kevin [Philips Healthcare, Clinical Science, PO Box 312, Mont Albert, Victoria (Australia); Oh, Lawrence Chia Wei [Flinders Medical Centre, Division of Medical Imaging, Bedford Park South (Australia); Huynh, Minh [Swinburne University, Department of Statistics, Data Science and Epidemiology, School of Health Sciences, Faculty of Health, Arts and Design, Hawthorn (Australia)

    2016-12-15

    To compare the image quality between fine focal spot size (FFSS) and standard focal spot size (SFSS) in computed tomography of the abdomen and pelvis (CTAP) This retrospective review included all consecutive adult patients undergoing contrast-enhanced CTAP between June and September 2014. Two blinded radiologists assessed the margin clarity of the abdominal viscera and the detected lesions using a five-point grading scale. Cohen's kappa test was used to examine the inter-observer reliability between the two reviewers for organ margin clarity. Mann-Whitney U testing was utilised to assess the statistical difference of the organ and lesion margin clarity. 100 consecutive CTAPs were recruited. 52 CTAPs were examined with SFSS of 1.1 x 1.2 mm and 48 CTAPs were examined with FFSS of 0.6 x 0.7 mm. Results showed that there was substantial agreement for organ margin clarity (mean κ = 0.759, p < 0.001) among the reviewers. FFSS produces images with clearer organ margins (U = 76194.0, p < 0.001, r = 0.523) and clearer lesion margins (U = 239, p = 0.052, r = 0.269). FFSS CTAP improves image quality in terms of better organ and lesion margin clarity. Fine focus CT scanning is a novel technique that may be applied in routine CTAP imaging. (orig.)

  1. Targeting Villages for Rural Development Using Satellite Image Analysis.

    Science.gov (United States)

    Varshney, Kush R; Chen, George H; Abelson, Brian; Nowocin, Kendall; Sakhrani, Vivek; Xu, Ling; Spatocco, Brian L

    2015-03-01

    Satellite imagery is a form of big data that can be harnessed for many social good applications, especially those focusing on rural areas. In this article, we describe the common problem of selecting sites for and planning rural development activities as informed by remote sensing and satellite image analysis. Effective planning in poor rural areas benefits from information that is not available and is difficult to obtain at any appreciable scale by any means other than algorithms for estimation and inference from remotely sensed images. We discuss two cases in depth: the targeting of unconditional cash transfers to extremely poor villages in sub-Saharan Africa and the siting and planning of solar-powered microgrids in remote villages in India. From these cases, we draw out some common lessons broadly applicable to informed rural development.

  2. ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    H. Kim

    2012-07-01

    Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.

  3. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus

    2017-03-01

    Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU

  4. METEOROLOGICAL SATELLITE IMAGES IN GEOGRAPHY CLASSES: a didactic possibility

    Directory of Open Access Journals (Sweden)

    Diego Correia Maia

    2016-01-01

    Full Text Available ABSTRACT: The satellite images are still largely unexplored as didactic resource in geography classes, particularly about meteorology. This article aims to contribute to the development of new methodologies of interpretation and understanding, beyond the construction of pedagogical practices involving meteorological satellite images, concepts and issues related to climate issues. The aim of this paper is to present possibilities for the use of meteorological satellite images in the Teaching of Geography, aiming the promoting and the understanding of contents of air masses and fronts and climatic factors. RESUMO: As imagens de satélite ainda são pouco exploradas como recurso didático nas aulas de Geografia, principalmente aquelas relativas à meteorologia. Este artigo visa contribuir com o desenvolvimento de novas metodologias de interpretação e compreensão, além da construção de práticas pedagógicas envolvendo imagens de satélite meteorológico, conceitos e temas ligados às questões climáticas. Seu objetivo é apresentar possibilidades de utilização das imagens de satélite meteorológico no Ensino de Geografia, visando à promoção e ao entendimento dos conteúdos de massas de ar e frentes e de elementos climáticos. Palavras chave

  5. Imaging of spatially extended hot spots with coded apertures for intra-operative nuclear medicine applications

    Science.gov (United States)

    Kaissas, I.; Papadimitropoulos, C.; Potiriadis, C.; Karafasoulis, K.; Loukas, D.; Lambropoulos, C. P.

    2017-01-01

    Coded aperture imaging transcends planar imaging with conventional collimators in efficiency and Field of View (FOV). We present experimental results for the detection of 141 keV and 122 keV γ-photons emitted by uniformly extended 99mTc and 57Co hot-spots along with simulations of uniformly and normally extended 99mTc hot-spots. These results prove that the method can be used for intra-operative imaging of radio-traced sentinel nodes and thyroid remnants. The study is performed using a setup of two gamma cameras, each consisting of a coded-aperture (or mask) of Modified Uniformly Redundant Array (MURA) of rank 19 positioned on top of a CdTe detector. The detector pixel pitch is 350 μm and its active area is 4.4 × 4.4 cm2, while the mask element size is 1.7 mm. The detectable photon energy ranges from 15 keV up to 200 keV with an energy resolution of 3-4 keV FWHM. Triangulation is exploited to estimate the 3D spatial coordinates of the radioactive spots within the system FOV. Two extended sources, with uniform distributed activity (11 and 24 mm in diameter, respectively), positioned at 16 cm from the system and with 3 cm distance between their centers, can be resolved and localized with accuracy better than 5%. The results indicate that the estimated positions of spatially extended sources lay within their volume size and that neighboring sources, even with a low level of radioactivity, such as 30 MBq, can be clearly distinguished with an acquisition time about 3 seconds.

  6. TOWARD A GLOBAL BUNDLE ADJUSTMENT OF SPOT 5 – HRS IMAGES

    Directory of Open Access Journals (Sweden)

    S. Massera

    2012-07-01

    Full Text Available The HRS (High Resolution Stereoscopic instrument carried on SPOT 5 enables quasi-simultaneous acquisition of stereoscopic images on wide segments – 120 km wide – with two forward and backward-looking telescopes observing the Earth with an angle of 20° ahead and behind the vertical. For 8 years IGN (Institut Géographique National has been developing techniques to achieve spatiotriangulation of these images. During this time the capacities of bundle adjustment of SPOT 5 – HRS spatial images have largely improved. Today a global single block composed of about 20,000 images can be computed in reasonable calculation time. The progression was achieved step by step: first computed blocks were only composed of 40 images, then bigger blocks were computed. Finally only one global block is now computed. In the same time calculation tools have improved: for example the adjustment of 2,000 images of North Africa takes about 2 minutes whereas 8 hours were needed two years ago. To reach such a result a new independent software was developed to compute fast and efficient bundle adjustments. In the same time equipment – GCPs (Ground Control Points and tie points – and techniques have also evolved over the last 10 years. Studies were made to get recommendations about the equipment in order to make an accurate single block. Tie points can now be quickly and automatically computed with SURF (Speeded Up Robust Features techniques. Today the updated equipment is composed of about 500 GCPs and studies show that the ideal configuration is around 100 tie points by square degree. With such an equipment, the location of the global HRS block becomes a few meters accurate whereas non adjusted images are only 15 m accurate. This paper will describe the methods used in IGN Espace to compute a global single block composed of almost 20,000 HRS images, 500 GCPs and several million of tie points in reasonable calculation time. Many advantages can be found to use such

  7. Comparison of two detection algorithms for spot tracking in fluorescence microscopy images

    CSIR Research Space (South Africa)

    Mabaso, M

    2014-11-01

    Full Text Available in biology and biomedical fields. The issue of how to accurately process and analyze the data becomes one of the major issues in the field because manual analysis is not practical anymore [1]. This issue has drawn much attention to systems for bioimage... assignment,” Journal of structural biology, vol. 173, pp. 219–228, 2011. [5] J.-C. Olivo-Marin, “Extraction of spots in biological images using multiscale products,” Pattern Recognition, vol. 35, no. 9, pp. 1989– 1996, 2002. [6] M. Mabaso, D. Withey, N...

  8. Recurrent Neural Networks to Correct Satellite Image Classification Maps

    Science.gov (United States)

    Maggiori, Emmanuel; Charpiat, Guillaume; Tarabalka, Yuliya; Alliez, Pierre

    2017-09-01

    While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.

  9. New and Emerging Satellite Imaging Capabilities in Support of Safeguards

    International Nuclear Information System (INIS)

    Johnson, M.; Paquette, J.P.; Spyropoulos, N.; Rainville, L.; Schichor, P.; Hong, M.

    2015-01-01

    This abstract is focused on new and emerging commercial satellite imagery (CSI) capabilities. For more than a decade, experienced imagery analysts have been exploiting and analyzing CSI in support of the Department of Safeguards. As the remote sensing industry continues to evolve, additional CSI imagery types are becoming available that could enhance our ability to evaluate and verify States' declarations and to investigate the possible presence of undeclared activities. A newly available and promising CSI capability that may have a Safeguards application is Full Motion Video (FMV) imagery collection from satellites. For quite some time, FMV imagery has been collected from airborne platforms, but now FMV sensors are being deployed into space. Like its airborne counterpart, satellite FMV imagery could provide analysts with a great deal of information, including insight into the operational status of facilities and patterns of activity. From a Safeguards perspective, FMV imagery could help the Agency in the evaluation and verification of States' declared facilities and activities. There are advantages of FMV imaging capabilities that cannot be duplicated with other CSI capabilities, including the ability to loiter over areas of interest and the potential to revisit sites multiple times per day. Additional sensor capabilities applicable to the Safeguards mission include, but are not limited to, the following sensors: · Thermal Infrared imaging sensors will be launched in late 2014 to monitor operational status, e.g., heat from a transformer. · High resolution ShortWave Infrared sensors able to characterize materials that could support verification of Additional Protocol declarations under Article 2.a(v). · Unmanned Aerial Vehicles with individual sensors or specific sensor combinations. The Safeguards Symposium provides a forum to showcase and demonstrate safeguards applications for these emerging satellite imaging capabilities. (author)

  10. Satellites

    International Nuclear Information System (INIS)

    Burns, J.A.; Matthews, M.S.

    1986-01-01

    The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

  11. Dark Spots

    Science.gov (United States)

    2006-01-01

    Dark spots (left) and 'fans' appear to scribble dusty hieroglyphics on top of the Martian south polar cap in two high-resolution Mars Global Surveyor, Mars Orbiter Camera images taken in southern spring. Each image is about 3-kilometers wide (2-miles).

  12. Hot Spots Detection of Operating PV Arrays through IR Thermal Image Using Method Based on Curve Fitting of Gray Histogram

    Directory of Open Access Journals (Sweden)

    Jiang Lin

    2016-01-01

    Full Text Available The overall efficiency of PV arrays is affected by hot spots which should be detected and diagnosed by applying responsible monitoring techniques. The method using the IR thermal image to detect hot spots has been studied as a direct, noncontact, nondestructive technique. However, IR thermal images suffer from relatively high stochastic noise and non-uniformity clutter, so the conventional methods of image processing are not effective. The paper proposes a method to detect hotspots based on curve fitting of gray histogram. The result of MATLAB simulation proves the method proposed in the paper is effective to detect the hot spots suppressing the noise generated during the process of image acquisition.

  13. DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. A. Azzaoui

    2016-06-01

    Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

  14. A flying spot x-ray system for Compton backscatter imaging

    Energy Technology Data Exchange (ETDEWEB)

    Herr, M.D.; McInerney, J.J.; Copenhaver, G.L. (Pennsylvania State Univ., Hershey, PA (United States)); Lamser, D.G. (Hologic, Waltham, MA (United States))

    1994-09-01

    A Compton x-ray backscatter imaging (CBI) system using a single detector and a mechanically rastered flying spot'' x-ray beam has been designed, built, and tested. While retaining the essential noninvasive imaging capability of previous multiple detector CBI devices, this single detector system incorporates several advances over earlier CBI devices: more efficient detection of scattered x-rays, reduced x-ray exposure, and a simplified scan protocol more suitable for use with humans. This new CBI system also has specific design features to permit automating data acquisition from multiple two-dimensional image planes for integration into a 3-D dynamic surface image. A simulated multislice scan study of a human thorax phantom provided x-ray dosimetry data verifying a very low x-ray dose delivered by this imaging device. Validation experiments with mechanical models show that surface displacement of typical heart beam frequencies can be measured to the nearest 0.1 mm (SD).

  15. Stitching images of dual-cameras onboard satellite

    Science.gov (United States)

    Jiang, Yonghua; Xu, Kai; Zhao, Ruishan; Zhang, Guo; Cheng, Kan; Zhou, Ping

    2017-06-01

    The way of installing dual-cameras on one satellite is adopted to further enlarge the imaging swath, thereby improving the efficiency of data capturing. In this case, stitching images of dual-cameras with high precision is a key step in the practical application. Due to the inadequate overlapping area of dual-cameras, stitching their images by classic methods may cause internal accuracy loss of the mosaic image. The reason is that classic methods estimate the geometric transformation of dual-cameras merely by a few unevenly distributed precise tie points in overlapping area of dual-cameras, which is similar to the case of using unevenly distributed ground control points (GCPs) in block adjustment. This paper proposed a new method to precisely stitch images of dual cameras without losing internal accuracy. First, a model was built to recover the relative geometric relation of dual-cameras and eliminate Charge-Coupled Device (CCD) distortions of each camera, then a virtual camera model depending on the calibrated geometric relation was adopted to achieve a seamless mosaic image. The panchromatic images of camera A and camera B onboard Yaogan-24 were collected as the experimental data. Experiment results show that the calibration accuracies of dual-cameras are better than 0.3 pixels, and the stitching accuracies can reach the sub-pixel level, ranging from 0.3 to 0.5 pixels. On the other hand, the positioning accuracies with GCPs of the mosaic image and of individual camera are better than 0.6 pixels and 0.5 pixels respectively, so the internal accuracy loss of the mosaic image only reaches 0.1 pixels, which can be neglected. This demonstrates that the proposed method can achieve seamless mosaic images without losing internal accuracy.

  16. Chagas disease study using satellite image processing: A Bolivian case

    Science.gov (United States)

    Vargas-Cuentas, Natalia I.; Roman-Gonzalez, Avid; Mantari, Alicia Alva; Muñoz, Luis AnthonyAucapuma

    2018-03-01

    Remote sensing is the technology that has enabled us to obtain information about the Earth's surface without directly contacting it. For this reason, currently, the Bolivian state has considered a list of interesting applications of remote sensing in the country, including the following: biodiversity and environment monitoring, mining and geology, epidemiology, agriculture, water resources and land use planning. The use of satellite images has become a great tool for epidemiology because with this technological advance we can determine the environment in which transmission occurs, the distribution of the disease and its evolution over time. In that context, one of the important diseases related to public health in Bolivia is Chagas disease, also known as South American Trypanosomiasis. Chagas is caused by a blood-sucking bug or Vinchuca, which causes serious intestinal and heart long term problems and affects 33.4% of the Bolivian population. This disease affects mostly humble people, so the Bolivian state invests millions of dollars to acquire medicine and distribute it for free. Due to the above reasons, the present research aims to analyze some areas of Bolivia using satellite images for developing an epidemiology study. The primary objective is to understand the environment in which the transmission of the disease happens, and the climatic conditions under which occurs, observe the behavior of the blood-sucking bug, identify in which months occur higher outbreaks, in which months the bug leaves its eggs, and under which weather conditions this happens. All this information would be contrasted with information extracted from the satellite images and data from the Ministry of Health, and the Institute of Meteorology in Bolivia. All this data will allow us to have a more integrated understanding of this disease and promote new possibilities to prevent and control it.

  17. Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  18. Global Solar Radiation in Spain from Satellite Images

    International Nuclear Information System (INIS)

    Ramirez, L.; Mora, L.; Sidrach de Cardona, M.; Navarro, A. A.; Varela, M.; Cruz, M. de la

    2003-01-01

    In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been reevaluated to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar, impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyrano metric measures in a concrete locality, but it provides a very valid indicator in places in which it is not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs

  19. Application of infrared imaging for quality inspection in resistance spot welds

    Science.gov (United States)

    Woo, Wanchuck; Chin, Charles W.; Feng, Zhili; Wang, Hsin; Zhang, Wei; Xu, Hanbing; Sklad, Philip S.

    2009-05-01

    Infrared thermal imaging method was applied for the development of a non-destructive inspection technique to determine the quality of resistance spot welds. The current work is an initial feasibility study based on post-mortem inspection. First, resistance spot welds were fabricated on dual phase steel sheets (DP 590 steel) with carefullycontrolled welding parameters. It created welds with desirable and undesirable qualities in terms of nugget size, indentation depth, and voids and cracks. Second, five different heating and cooling methods were evaluated. The heating or cooling source was applied on one side of the weld stack while the surface temperature change on the other side of the weld was recorded using an infrared camera. Correlation between the weld quality and the "thermal signature" of each weld was established. Finally, a simplified thermal finite element analysis was developed to simulate the heat flow during inspection. The thermal model provided insight into the effect of the nugget size and indentation depth on the peak temperature and heating rate. The results reported in this work indicate that the IR thermography technique is feasible for weld quality inspection due to the distinguish temperature profiles for different welds and the repeatability and consistency in measurement.

  20. A digital image method of spot tests for determination of copper in sugar cane spirits

    Science.gov (United States)

    Pessoa, Kenia Dias; Suarez, Willian Toito; dos Reis, Marina Ferreira; de Oliveira Krambeck Franco, Mathews; Moreira, Renata Pereira Lopes; dos Santos, Vagner Bezerra

    2017-10-01

    In this work the development and validation of analytical methodology for determination of copper in sugarcane spirit samples is carried out. The digital image based (DIB) method was applied along with spot test from the colorimetric reaction employing the RGB color model. For the determination of copper concentration, it was used the cuprizone - a bidentate organic reagent - which forms with copper a blue chelate in an alkaline medium. A linear calibration curve over the concentration range from 0.75 to 5.00 mg L- 1 (r2 = 0.9988) was obtained and limits of detection and quantification of 0.078 mg L- 1 and 0.26 mg L- 1 were acquired, respectively. For the accuracy studies, recovery percentages ranged from 98 to 104% were obtained. The comparison of cooper concentration results in sugar cane spirits using the DIB method and Flame Atomic Absorption Spectrometry as reference method showed no significant differences between both methods, which were performed using the paired t-test in 95% of confidence level. Thus, the spot test method associated with DIB allows the use of devices as digital cameras and smartphones to evaluate colorimetric reaction with low waste generation, practicality, quickness, accuracy, precision, high portability and low-cost.

  1. A low cost thermal infrared hyperspectral imager for small satellites

    Science.gov (United States)

    Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.; Wood, M.

    2012-06-01

    The growth of the small satellite market and launch opportunities for these satellites is creating a new niche for earth observations that contrasts with the long mission durations, high costs, and long development times associated with traditional space-based earth observations. Low-cost, short-lived missions made possible by this new approach provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off-the-shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCoR), to demonstrate ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power-efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable use of COTS electronics and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230 meter pixels with 20 wavenumber spectral resolution from a 400 km orbit. We are currently in the laboratory and airborne testing stage in order to demonstrate the spectro-radiometric quality of data that the instrument provides.

  2. Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

    Science.gov (United States)

    Su, X.

    2017-12-01

    A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

  3. Laser Guidestar Satellite for Ground-based Adaptive Optics Imaging of Geosynchronous Satellites and Astronomical Targets

    Science.gov (United States)

    Marlow, W. A.; Cahoy, K.; Males, J.; Carlton, A.; Yoon, H.

    2015-12-01

    Real-time observation and monitoring of geostationary (GEO) satellites with ground-based imaging systems would be an attractive alternative to fielding high cost, long lead, space-based imagers, but ground-based observations are inherently limited by atmospheric turbulence. Adaptive optics (AO) systems are used to help ground telescopes achieve diffraction-limited seeing. AO systems have historically relied on the use of bright natural guide stars or laser guide stars projected on a layer of the upper atmosphere by ground laser systems. There are several challenges with this approach such as the sidereal motion of GEO objects relative to natural guide stars and limitations of ground-based laser guide stars; they cannot be used to correct tip-tilt, they are not point sources, and have finite angular sizes when detected at the receiver. There is a difference between the wavefront error measured using the guide star compared with the target due to cone effect, which also makes it difficult to use a distributed aperture system with a larger baseline to improve resolution. Inspired by previous concepts proposed by A.H. Greenaway, we present using a space-based laser guide starprojected from a satellite orbiting the Earth. We show that a nanosatellite-based guide star system meets the needs for imaging GEO objects using a low power laser even from 36,000 km altitude. Satellite guide star (SGS) systemswould be well above atmospheric turbulence and could provide a small angular size reference source. CubeSatsoffer inexpensive, frequent access to space at a fraction of the cost of traditional systems, and are now being deployed to geostationary orbits and on interplanetary trajectories. The fundamental CubeSat bus unit of 10 cm cubed can be combined in multiple units and offers a common form factor allowing for easy integration as secondary payloads on traditional launches and rapid testing of new technologies on-orbit. We describe a 6U CubeSat SGS measuring 10 cm x 20 cm x

  4. Integration of Satellite Tracking Data and Satellite Images for Detailed Characteristics of Wildlife Habitats

    Science.gov (United States)

    Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.

    2017-12-01

    Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.

  5. Development of dual imaging optical sensor (DIOS) for small satellites

    Science.gov (United States)

    Choi, Young-Wan; Kang, Myung-Seok; Jeong, Sung-Keun; Yun, Ji-Ho; Yang, Seung-Uk; Kim, Jongun; Kim, Ee-Eul

    2007-09-01

    The mission of DIOS program is to provide the function of large-swathwidth or in-track stereo imaging with compact electro-optical cameras. Optimized from its predecessor SAC (Small-sized Aperture Camera), DIOS consists of two cameras, each with an aperture of 120 mm diameter, 10 m GSD, and 50 km swath width in the spectral range of 520 ~ 890 nm. DIOS is developed to produce high quality images: MTF of more than 12 %; SNR of more than 100. DIOS can be configured to have cameras side-by-side, providing a swathwidth up to 100 km for a mission of large swathwidth. DIOS will be configured with installation of slanted two cameras for the mission of in-track stereo imaging to produce digital elevation model. In this paper, Dual Imaging Optical Sensor (DIOS) will be introduced with design approach and performance measure. Even though developed for micro satellites, the presentation of development status and test results will demonstrate the potential capability that DISO can provide for world-wide remote sensing groups: short development period, cost-effectiveness, wide application ranges, and high performance.

  6. Digital image intensifier radiography: first experiences with the DSI (Digital Spot Imaging)

    International Nuclear Information System (INIS)

    Rueckforth, J.; Wein, B.; Stargardt, A.; Guenther, R.W.

    1995-01-01

    We performed a comparative study of digitally and conventionally acquired images in gastrointestinal examinations. Radiation dose and spatial resolution were determined in a water phantom. In 676 examinations with either conventional or digital imaging (system: Diagnost 76, DSI) the number of images and the duration of the fluoroscopy time were compared. 101 examinations with digital as well as conventional documentation were evaluated by using 5 criteria describing the diagnostic performance. The entrance dose of the DSI is 12% to 36% of the film/screen system and the spatial resolution of the DSI may be better than that of a film/screen system with a speed of 200. The fluoroscopy time shows no significant difference between DSI and the film/screen technique. In 2 of 4 examination modes significantly more images were produced by the DSI. With exception of the criterion of edge sharpness, DSI yields a significantly inferior assessment compared with the film/screen technique. (orig./MG) [de

  7. Radiation dose reduction without compromise to image quality by alterations of filtration and focal spot size in cerebral angiography

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dong Joon; Park, Min Keun; Jung, Da Eun; Kang, Jung Han; Kim, Byung Moon [Dept. of Radiology, Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2017-08-01

    Different angiographic protocols may influence the radiation dose and image quality. In this study, we aimed to investigate the effects of filtration and focal spot size on radiation dose and image quality for diagnostic cerebral angiography using an in-vitro model and in-vivo patient groups. Radiation dose and image quality were analyzed by varying the filtration and focal spot size on digital subtraction angiography exposure protocols (1, inherent filtration + large focus; 2, inherent + small; 3, copper + large; 4, copper + small). For the in-vitro analysis, a phantom was used for comparison of radiation dose. For the in-vivo analysis, bilateral paired injections, and patient cohort groups were compared for radiation dose and image quality. Image quality analysis was performed in terms of contrast, sharpness, noise, and overall quality. In the in-vitro analysis, the mean air kerma (AK) and dose area product (DAP)/frame were significantly lower with added copper filtration (protocols 3 and 4). In the in-vivo bilateral paired injections, AK and DAP/frame were significantly lower with filtration, without significant difference in image quality. The patient cohort groups with added filtration (protocols 3 and 4) showed significant reduction of total AK and DAP/patient without compromise to the image quality. Variations in focal spot size showed no significant differences in radiation dose and image quality. Addition of filtration for angiographic exposure studies can result in significant total radiation dose reduction without loss of image quality. Focal spot size does not influence radiation dose and image quality. The routine angiographic protocol should be judiciously investigated and implemented.

  8. Building damage scale proposal from VHR satellite image

    Science.gov (United States)

    Sandu, Constantin; Giulio Tonolo, Fabio; Cotrufo, Silvana; Boccardo, Piero

    2017-04-01

    Natural hazards have a huge impact in terms of economic losses, affected and killed people. Current exploitation of remote sensed images play a fundamental role in the delineation of damages generated by catastrophic events. Institutions like the United Nations and the European Commission designed services that provide information about the impact of disasters rapidly. One of the approach currently used to carry out the damage assessment is based on very high resolution remote sensing imagery (including both aerial and satellite platforms). One of the main focus of the responders, especially in case of events like earthquakes, is on buildings and infrastructures. As far as the buildings are concerned, to date international standard guidelines that provide essential information on how to assess building damages using VHR images still does not exist. The aim of this study is to develop a building damage scale tailored for analyses based on VHR vertical imagery and to propose a standard for the related interpretation guidelines. The task is carried out by comparing the current scales used for damage assessment by the main satellite based emergency mapping services. The study will analyze the datasets produced after the Ecuador (April 2016) and Central Italy(August and October 2016) earthquakes. The results suggest that by using VHR remotely sensed images it is not possible to directly use damage classification scales addressing structural damages (e.g the 5 grades proposed by EMS-98). A fine-tuning of existing damage classes is therefore required and the adoption of an internationally agreed standard should be encouraged, to streamline the use of SEM products generated by different services.

  9. Accuracy assessment of topographic mapping using UAV image integrated with satellite images

    International Nuclear Information System (INIS)

    Azmi, S M; Ahmad, Baharin; Ahmad, Anuar

    2014-01-01

    Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps

  10. Accuracy assessment of topographic mapping using UAV image integrated with satellite images

    Science.gov (United States)

    Azmi, S. M.; Ahmad, Baharin; Ahmad, Anuar

    2014-02-01

    Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps.

  11. High throughput phenotyping of tomato spotted wilt disease in peanuts using unmanned aerial systems and multispectral imaging

    Science.gov (United States)

    The amount of visible and near infrared light reflected by plants varies depending on their health. In this study, multispectral images were acquired by quadcopter for detecting tomato spot wilt virus amongst twenty genetic varieties of peanuts. The plants were visually assessed to acquire ground ...

  12. Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

    Directory of Open Access Journals (Sweden)

    Maocai Wang

    2014-01-01

    Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

  13. Hyperspectral imaging and multivariate analysis in the dried blood spots investigations

    Science.gov (United States)

    Majda, Alicja; Wietecha-Posłuszny, Renata; Mendys, Agata; Wójtowicz, Anna; Łydżba-Kopczyńska, Barbara

    2018-04-01

    The aim of this study was to apply a new methodology using the combination of the hyperspectral imaging and the dry blood spot (DBS) collecting. Application of the hyperspectral imaging is fast and non-destructive. DBS method offers the advantage also on the micro-invasive blood collecting and low volume of required sample. During experimental step, the reflected light was recorded by two hyperspectral systems. The collection of 776 spectral bands in the VIS-NIR range (400-1000 nm) and 256 spectral bands in the SWIR range (970-2500 nm) was applied. Pixel has the size of 8 × 8 and 30 × 30 µm for VIS-NIR and SWIR camera, respectively. The obtained data in the form of hyperspectral cubes were treated with chemometric methods, i.e., minimum noise fraction and principal component analysis. It has been shown that the application of these methods on this type of data, by analyzing the scatter plots, allows a rapid analysis of the homogeneity of DBS, and the selection of representative areas for further analysis. It also gives the possibility of tracking the dynamics of changes occurring in biological traces applied on the surface. For the analyzed 28 blood samples, described method allowed to distinguish those blood stains because of time of apply.

  14. Satellite image analysis for surveillance, vegetation and climate change

    Energy Technology Data Exchange (ETDEWEB)

    Cai, D Michael [Los Alamos National Laboratory

    2011-01-18

    Recently, many studies have provided abundant evidence to show the trend of tree mortality is increasing in many regions, and the cause of tree mortality is associated with drought, insect outbreak, or fire. Unfortunately, there is no current capability available to monitor vegetation changes, and correlate and predict tree mortality with CO{sub 2} change, and climate change on the global scale. Different survey platforms (methods) have been used for forest management. Typical ground-based forest surveys measure tree stem diameter, species, and alive or dead. The measurements are low-tech and time consuming, but the sample sizes are large, running into millions of trees, covering large areas, and spanning many years. These field surveys provide powerful ground validation for other survey methods such as photo survey, helicopter GPS survey, and aerial overview survey. The satellite imagery has much larger coverage. It is easier to tile the different images together, and more important, the spatial resolution has been improved such that close to or even higher than aerial survey platforms. Today, the remote sensing satellite data have reached sub-meter spatial resolution for panchromatic channels (IKONOS 2: 1 m; Quickbird-2: 0.61 m; Worldview-2: 0.5 m) and meter spatial resolution for multi-spectral channels (IKONOS 2: 4 meter; Quickbird-2: 2.44 m; Worldview-2: 2 m). Therefore, high resolution satellite imagery can allow foresters to discern individual trees. This vital information should allow us to quantify physiological states of trees, e.g. healthy or dead, shape and size of tree crowns, as well as species and functional compositions of trees. This is a powerful data resource, however, due to the vast amount of the data collected daily, it is impossible for human analysts to review the imagery in detail to identify the vital biodiversity information. Thus, in this talk, we will discuss the opportunities and challenges to use high resolution satellite imagery and

  15. Automated detection and analysis of fluorescent in situ hybridization spots depicted in digital microscopic images of Pap-smear specimens

    Science.gov (United States)

    Wang, Xingwei; Zheng, Bin; Li, Shibo; Zhang, Roy; Mulvihill, John J.; Chen, Wei R.; Liu, Hong

    2009-03-01

    Fluorescence in situ hybridization (FISH) technology has been widely recognized as a promising molecular and biomedical optical imaging tool to screen and diagnose cervical cancer. However, manual FISH analysis is time-consuming and may introduce large inter-reader variability. In this study, a computerized scheme is developed and tested. It automatically detects and analyzes FISH spots depicted on microscopic fluorescence images. The scheme includes two stages: (1) a feature-based classification rule to detect useful interphase cells, and (2) a knowledge-based expert classifier to identify splitting FISH spots and improve the accuracy of counting independent FISH spots. The scheme then classifies detected analyzable cells as normal or abnormal. In this study, 150 FISH images were acquired from Pap-smear specimens and examined by both an experienced cytogeneticist and the scheme. The results showed that (1) the agreement between the cytogeneticist and the scheme was 96.9% in classifying between analyzable and unanalyzable cells (Kappa=0.917), and (2) agreements in detecting normal and abnormal cells based on FISH spots were 90.5% and 95.8% with Kappa=0.867. This study demonstrated the feasibility of automated FISH analysis, which may potentially improve detection efficiency and produce more accurate and consistent results than manual FISH analysis.

  16. Using SPOT-5 images in rice farming for detecting BPH (Brown Plant Hopper)

    International Nuclear Information System (INIS)

    Ghobadifar, F; Wayayok, A; Shattri, M; Shafri, H

    2014-01-01

    Infestation of rice plant-hopper such as Brown Plant Hopper (BPH) (Nilaparvata lugens) is one of the most notable risk in rice yield in tropical areas especially in Asia. In order to use visible and infrared images to detect stress in rice production caused by BPH infestation, several remote sensing techniques have been developed. Initial recognition of pest infestation by means of remote sensing will spreads, for precision farming practice. To address this issue, detection of sheath blight in rice farming was examined by using SPOT-5 images. Specific image indices such as Normalized decrease food production costs, limit environmental hazards, and enhance natural pest control before the problem Normalized Difference Vegetation Index (NDVI), Standard difference indices (SDI) and Ratio Vegetation Index (RVI) were used for analyses using ENVI 4.8 and SPSS software. Results showed that all the indices to recognize infected plants are significant at α = 0.01. Examination of the association between the disease indices indicated that band 3 (near infrared) and band 4 (mid infrared) have a relatively high correlation. The selected indices declared better association for detecting healthy plants from diseased ones. Consequently, these sorts of indices especially NDVI could be valued as indicators for developing techniques for detecting the sheath blight of rice by using remote sensing. This infers that they are useful for crop disease detection but the spectral resolution is probably not sufficient to distinguish plants with light infections (low severity level). Using the index as an indicator can clarify the threshold for zoning the outbreaks. Quick assessment information is very useful in precision farming to practice site specific management such as pesticide application

  17. Mapping soil heterogeneity using RapidEye satellite images

    Science.gov (United States)

    Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane

    2016-04-01

    In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

  18. Forecast of wheat yield throughout the agricultural season using optical and radar satellite images

    Science.gov (United States)

    Fieuzal, R.; Baup, F.

    2017-07-01

    The aim of this study is to estimate the capabilities of forecasting the yield of wheat using an artificial neural network combined with multi-temporal satellite data acquired at high spatial resolution throughout the agricultural season in the optical and/or microwave domains. Reflectance (acquired by Formosat-2, and Spot 4-5 in the green, red, and near infrared wavelength) and multi-configuration backscattering coefficients (acquired by TerraSAR-X and Radarsat-2 in the X- and C-bands, at co- (abbreviated HH and VV) and cross-polarization states (abbreviated HV and VH)) constitute the input variable of the artificial neural networks, which are trained and validated on the successively acquired images, providing yield forecast in near real-time conditions. The study is based on data collected over 32 fields of wheat distributed over a study area located in southwestern France, near Toulouse. Among the tested sensor configurations, several satellite data appear useful for the yield forecasting throughout the agricultural season (showing coefficient of determination (R2) larger than 0.60 and a root mean square error (RMSE) lower than 9.1 quintals by hectare (q ha-1)): CVH, CHV, or the combined used of XHH and CHH, CHH and CHV, or green reflectance and CHH. Nevertheless, the best accurate forecast (R2 = 0.76 and RMSE = 7.0 q ha-1) is obtained longtime before the harvest (on day 98, during the elongation of stems) using the combination of co- and cross-polarized backscattering coefficients acquired in the C-band (CVV and CVH). These results highlight the high interest of using synthetic aperture radar (SAR) data instead of optical ones to early forecast the yield before the harvest of wheat.

  19. Satellite Image Time Series Decomposition Based on EEMD

    Directory of Open Access Journals (Sweden)

    Yun-long Kong

    2015-11-01

    Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.

  20. Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining

    Directory of Open Access Journals (Sweden)

    Yo-Ping Huang

    2008-02-01

    Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.

  1. USING SATELLITE IMAGES FOR WIRELESS NETWORK PLANING IN BAKU CITY

    Directory of Open Access Journals (Sweden)

    M. Gojamanov

    2013-04-01

    Full Text Available It is a well known fact that the Information-Telecommunication and Space research technologies are the fields getting much more benefits from the achievements of the scientific and technical progress. In many cases, these areas supporting each other have improved the conditions for their further development. For instance, the intensive development in the field of the mobile communication has caused the rapid progress of the Space research technologies and vice versa.Today it is impossible to solve one of the most important tasks of the mobile communication as Radio Frecance planning without the 2D and 3D digital maps. The compiling of such maps is much more efficient by means of the space images. Because the quality of the space images has been improved and developed, especially at the both spectral and spatial resolution points. It has been possible to to use 8 Band images with the spatial resolution of 50 sm. At present, in relation to the function 3G of mobile communications one of the main issues facing mobile operator companies is a high-precision 3D digital maps. It should be noted that the number of mobile phone users in the Republic of Azerbaijan went forward other Community of Independent States Countries. Of course, using of aerial images for 3D mapping would be optimal. However, depending on a number of technical and administrative problems aerial photography cannot be used. Therefore, the experience of many countries shows that it will be more effective to use the space images with the higher resolution for these issues. Concerning the fact that the mobile communication within the city of Baku has included 3G function there were ordered stereo images wih the spatial resolution of 50 cm for the 150 sq.km territory occupying the central part of the city in order to compile 3D digital maps. The images collected from the WorldView-2 satellite are 4-Band Bundle(Pan+MS1 stereo images. Such kind of imagery enable to automatically

  2. Estimate Landslide Volume with Genetic Algorithms and Image Similarity Method from Single Satellite Image

    Science.gov (United States)

    Yu, Ting-To

    2013-04-01

    It is important to acquire the volume of landslide in short period of time. For hazard mitigation and also emergency response purpose, the traditional method takes much longer time than expected. Due to the weather limit, traffic accessibility and many regulations of law, it take months to handle these process before the actual carry out of filed work. Remote sensing imagery can get the data as long as the visibility allowed, which happened only few day after the event. While traditional photometry requires a stereo pairs images to produce the post event DEM for calculating the change of volume. Usually have to wait weeks or even months for gathering such data, LiDAR or ground GPS measurement might take even longer period of time with much higher cost. In this study we use one post event satellite image and pre-event DTM to compare the similarity between these by alter the DTM with genetic algorithms. The outcome of smartest guess from GAs shall remove or add exact values of height at each location, which been converted into shadow relief viewgraph to compare with satellite image. Once the similarity threshold been make then the guessing work stop. It takes only few hours to finish the entire task, the computed accuracy is around 70% by comparing to the high resolution LiDAR survey at a landslide, southern Taiwan. With extra GCPs, the estimate accuracy can improve to 85% and also within few hours after the receiving of satellite image. Data of this demonstration case is a 5 m DTM at 2005, 2M resolution FormoSat optical image at 2009 and 5M LiDAR at 2010. The GAs and image similarity code is developed on Matlab at windows PC.

  3. Children observe the Digital Earth from above: How they read aerial and satellite images

    International Nuclear Information System (INIS)

    Svatonova, H; Rybansky, M

    2014-01-01

    Digital aerial and satellite images depicting the Earth surface are not secret anymore and they are easily available for general public. Publishing of aerial and satellite images provoke the questions how the non-experts or the amateur groups can interpret these images, how they are able to cope with vertical or oblique images, with their colour, missing lettering, etc. The paper presents the results of the research of the above mentioned questions where the respondents were the Czech pupils and student at the age of about eleven, fifteen and nineteen years. These results are aimed at the effective exploitation of aerial and satellite images in teaching, they represent also information for imagery producers and distributors. A non-traditional view on the Earth surface from above using aerial or satellite images is one of the opportunities to discover the beauty of the Earth

  4. The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation

    Directory of Open Access Journals (Sweden)

    Xiao-fang Xie

    2007-05-01

    Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.

  5. Children observe the Digital Earth from above: How they read aerial and satellite images

    Science.gov (United States)

    Svatonova, H.; Rybansky, M.

    2014-02-01

    Digital aerial and satellite images depicting the Earth surface are not secret anymore and they are easily available for general public. Publishing of aerial and satellite images provoke the questions how the non-experts or the amateur groups can interpret these images, how they are able to cope with vertical or oblique images, with their colour, missing lettering, etc. The paper presents the results of the research of the above mentioned questions where the respondents were the Czech pupils and student at the age of about eleven, fifteen and nineteen years. These results are aimed at the effective exploitation of aerial and satellite images in teaching, they represent also information for imagery producers and distributors. A non-traditional view on the Earth surface from above using aerial or satellite images is one of the opportunities to discover the beauty of the Earth.

  6. Design of an Image Motion Compenstaion (IMC Algorithm for Image Registration of the Communication, Ocean, Meteorolotical Satellite (COMS-1

    Directory of Open Access Journals (Sweden)

    Taek Seo Jung

    2006-03-01

    Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.

  7. Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

    Science.gov (United States)

    Hirose, Misa; Toyota, Saori; Tsumura, Norimichi

    2018-02-01

    In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.

  8. Water extraction technique in mountainous areas from satellite images

    Science.gov (United States)

    Kaplan, Gordana; Avdan, Ugur

    2017-10-01

    Water monitoring is an important part of water resource management and has become an essential aspect of remote sensing. A number of indices have been developed for water extraction using satellite images. Even though all indices can extract the extent of a water body, none can do so without including a noise component, such as topographic shadows, cloud shadows, snow, ice, and buildup areas, all of which have spectrally similar characteristics under certain circumstances. In order to select the best index for water body extraction, several water indices have been compared. This paper proposes a method for extracting water bodies called the water extraction surface temperature index (WESTI). This method uses normalized difference water index (NDWI) and land surface temperature to eliminate the noise components, especially in mountainous and cold areas where other indices have very low accuracy. The results have shown that WESTI improves the NDWI results by removing more than 80% of topographic shadows, with an overall accuracy of 99% in all cases.

  9. Roads Data Conflation Using Update High Resolution Satellite Images

    Science.gov (United States)

    Abdollahi, A.; Riyahi Bakhtiari, H. R.

    2017-11-01

    Urbanization, industrialization and modernization are rapidly growing in developing countries. New industrial cities, with all the problems brought on by rapid population growth, need infrastructure to support the growth. This has led to the expansion and development of the road network. A great deal of road network data has made by using traditional methods in the past years. Over time, a large amount of descriptive information has assigned to these map data, but their geometric accuracy and precision is not appropriate to today's need. In this regard, the improvement of the geometric accuracy of road network data by preserving the descriptive data attributed to them and updating of the existing geo databases is necessary. Due to the size and extent of the country, updating the road network maps using traditional methods is time consuming and costly. Conversely, using remote sensing technology and geographic information systems can reduce costs, save time and increase accuracy and speed. With increasing the availability of high resolution satellite imagery and geospatial datasets there is an urgent need to combine geographic information from overlapping sources to retain accurate data, minimize redundancy, and reconcile data conflicts. In this research, an innovative method for a vector-to-imagery conflation by integrating several image-based and vector-based algorithms presented. The SVM method for image classification and Level Set method used to extract the road the different types of road intersections extracted from imagery using morphological operators. For matching the extracted points and to find the corresponding points, matching function which uses the nearest neighborhood method was applied. Finally, after identifying the matching points rubber-sheeting method used to align two datasets. Two residual and RMSE criteria used to evaluate accuracy. The results demonstrated excellent performance. The average root-mean-square error decreased from 11.8 to 4.1 m.

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

    Science.gov (United States)

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

    2017-01-01

    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. PMID:28481287

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

    Directory of Open Access Journals (Sweden)

    Lin Li

    2017-05-01

    Full Text Available 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.

  12. 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.

  13. Procedure to detect impervious surfaces using satellite images and light detection and ranging (lidar) data

    Science.gov (United States)

    Rodríguez-Cuenca, B.; Alonso-Rodríguez, M. C.; Domenech-Tofiño, E.; Valcárcel Sanz, N.; Delgado-Hernández, J.; Peces-Morera, Juan José; Arozarena-Villar, Antonio

    2014-10-01

    The detection of impervious surfaces is an important issue in the study of urban and rural environments. Imperviousness refers to water's inability to pass through a surface. Although impervious surfaces represent a small percentage of the Earth's surface, knowledge of their locations is relevant to planning and managing human activities. Impervious structures are primarily manmade (e.g., roads and rooftops). Impervious surfaces are an environmental concern because many processes that modify the normal function of land, air, and water resources are initiated during their construction. This paper presents a novel method of identifying impervious surfaces using satellite images and light detection and ranging (LIDAR) data. The inputs for the procedure are SPOT images formed by four spectral bands (corresponding to red, green, near-infrared and mid-infrared wavelengths), a digital terrain model, and an .las file. The proposed method computes five decision indexes from the input data to classify the studied area into two categories: impervious (subdivided into buildings and roads) and non-impervious surfaces. The impervious class is divided into two subclasses because the elements forming this category (mainly roads and rooftops) have different spectral and height properties, and it is difficult to combine these elements into one group. The classification is conducted using a decision tree procedure. For every decision index, a threshold is set for which every surface is considered impervious or non-impervious. The proposed method has been applied to four different regions located in the north, center, and south of Spain, providing satisfactory results for every dataset.

  14. Doppler imaging of chemical spots on magnetic Ap/Bp stars. Numerical tests and assessment of systematic errors

    Science.gov (United States)

    Kochukhov, O.

    2017-01-01

    Context. Doppler imaging (DI) is a powerful spectroscopic inversion technique that enables conversion of a line profile time series into a two-dimensional map of the stellar surface inhomogeneities. DI has been repeatedly applied to reconstruct chemical spot topologies of magnetic Ap/Bp stars with the goal of understanding variability of these objects and gaining an insight into the physical processes responsible for spot formation. Aims: In this paper we investigate the accuracy of chemical abundance DI and assess the impact of several different systematic errors on the reconstructed spot maps. Methods: We have simulated spectroscopic observational data for two different Fe spot distributions with a surface abundance contrast of 1.5 dex in the presence of a moderately strong dipolar magnetic field. We then reconstructed chemical maps using different sets of spectral lines and making different assumptions about line formation in the inversion calculations. Results: Our numerical experiments demonstrate that a modern DI code successfully recovers the input chemical spot distributions comprised of multiple circular spots at different latitudes or an element overabundance belt at the magnetic equator. For the optimal reconstruction based on half a dozen spectral intervals, the average reconstruction errors do not exceed 0.10 dex. The errors increase to about 0.15 dex when abundance distributions are recovered from a few and/or blended spectral lines. Ignoring a 2.5 kG dipolar magnetic field in chemical abundance DI leads to an average relative error of 0.2 dex and maximum errors of 0.3 dex. Similar errors are encountered if a DI inversion is carried out neglecting a non-uniform continuum brightness distribution and variation of the local atmospheric structure. None of the considered systematic effects lead to major spurious features in the recovered abundance maps. Conclusions: This series of numerical DI simulations proves that inversions based on one or two spectral

  15. Imaging-Duration Embedded Dynamic Scheduling of Earth Observation Satellites for Emergent Events

    Directory of Open Access Journals (Sweden)

    Xiaonan Niu

    2015-01-01

    Full Text Available We present novel two-stage dynamic scheduling of earth observation satellites to provide emergency response by making full use of the duration of the imaging task execution. In the first stage, the multiobjective genetic algorithm NSGA-II is used to produce an optimal satellite imaging schedule schema, which is robust to dynamic adjustment as possible emergent events occur in the future. In the second stage, when certain emergent events do occur, a dynamic adjusting heuristic algorithm (CTM-DAHA is applied to arrange new tasks into the robust imaging schedule. Different from the existing dynamic scheduling methods, the imaging duration is embedded in the two stages to make full use of current satellite resources. In the stage of robust satellite scheduling, total task execution time is used as a robust indicator to obtain a satellite schedule with less imaging time. In other words, more imaging time is preserved for future emergent events. In the stage of dynamic adjustment, a compact task merging strategy is applied to combine both of existing tasks and emergency tasks into a composite task with least imaging time. Simulated experiments indicate that the proposed method can produce a more robust and effective satellite imaging schedule.

  16. Jupiter's Great Red Spot upper cloud morphology and dynamics from JunoCam images

    Science.gov (United States)

    Sanchez-Lavega, A.; Hueso, R.; Eichstädt, G.; Orton, G.; Rogers, J.; Hansen, C. J.; Momary, T.; Tabataba-Vakili, F.

    2017-12-01

    We present an analysis of RGB color-composite images of the Great Red Spot (GRS) obtained with JunoCam during Juno's seventh close flyby (PJ7) on July 11, 2017. The images have been projected as 4 cylindrical maps with a resolution of 180 pixels per degree (about 7 km/pixel) spanning a temporal interval of 9 min 41s. The GRS shows a rich variety of cloud morphologies that reveal different dynamical processes in its interior. We consider three major regions. (1) An outer peripheral ring of homogeneous reddish clouds (width about 1,300 km) traces a laminar flow. A family of at least three packets of gravity waves with a mean wavelength of 75 km is present at the internal edge of the ring (in its northern side). They occupy an area of 2,500 km in length (East-West, EW) and 670 km in the North-South (NS) direction. Single clouds in the groups forming the wave have extents of 35 km EW and 70-135 km NS. (2) A large internal region of red clouds (width about 3,200 km) contains three morphologies: (a) fields of bright cumulus-like clusters, (b) long, dark curved filaments (about 7,000 km length with 100 km width), two of them converging into an arrowhead shape, and (c) individual anticyclonic vortices with radius of 500 km that grow due to the radial shear of the wind velocity in the GRS interior as previously measured. A cumulus cluster is conspicuous inside one such anticyclone. Each single cloud element is 50 km in size and the cluster has a 25-30 percent area coverage in cumulus-convective activity, presumably due to ammonia moist convection. (3) A central core has quasi-rectangular shape, extending about 5000 km EW and 3000 km NS, that is confined by elongated clouds distributed along its periphery. Its interior is filled with the redder clouds in the GRS that have a scale 100 km and form a turbulent pattern whose cloud orientations suggest three adjacent areas with alternating cyclonic-cyclonic-anticyclonic vorticity, each with radius 650-850 km.

  17. AN APPROACH FOR STITCHING SATELLITE IMAGES IN A BIGDATA MAPREDUCE FRAMEWORK

    Directory of Open Access Journals (Sweden)

    H. Sarı

    2017-11-01

    Full Text Available In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper and then String formats in the forms of 255s and 0s (second mapper, and finally, find the best possible matching position of the images by a reduce function.

  18. An Approach for Stitching Satellite Images in a Bigdata Mapreduce Framework

    Science.gov (United States)

    Sarı, H.; Eken, S.; Sayar, A.

    2017-11-01

    In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper) and then String formats in the forms of 255s and 0s (second mapper), and finally, find the best possible matching position of the images by a reduce function.

  19. Tectonics of the northern Venezuelan Andes from satellite images analysis

    Science.gov (United States)

    Dhont, D.; Backé, G.; Hervouët, Y.

    2003-04-01

    The northern part of the Venezuelan (or Merida) Andes is a complex area comprising a Cretaceous to Quaternary sedimentary sequence that recorded two main stages of deformation: (1) the uplifting of the Carribean belt in the Cretaceous-Eocene (Carribean stage), which is superimposed by (2) the building of the Venezuelan Andes since the Miocene (Andean stage). The study area is located at the junction between the Merida Andes and the Caribbean belt, and constitutes a key zone to understand the transition between these two orogens. Our aim is to implement the structural mapping in order to propose a new model of deformation at regional scale. The methodology is based on analysis of Landsat TM, SPOT, radarsat and DEM images, and is complemented by geological studies in the field. Integration of this complementary data set into a GIS enables a new understanding of the tectonics of the northern Venezuelan Andes during the Neogene-Quaternary. We focused on three main areas where the structures are clearly exposed. In the Mene Grande area, our structural analysis allows to precise the geometry and timing of deformations. The Cerro la Galera anticline is a fault bend fold propagating to the SW that developped along the Burro Negro fault during the Eocene-Oligocene and then eroded. The Cerro La Luna (or Cerro Misoa) is a pop-up structure that developped later during the Andean stage. In the Jirajara area, we have evidenced a releasing-bend basin at left-stepping offset of the Valera fault. To the east, this basin is surrounded by the relief of the Serrania de Jirajara which gravitationally collapses towards the lowland of the basin. In the Sierra de Barragua area, we mapped the left-lateral strike-slip Rio Diquiva fault 25 km east of the Valera fault. This fault is a major structure bounding two distincts areas of sedimentation during the Eocene. The synthesis of these observations shows that the northern Venezuelan Andes consist in a mosaic of independent crustal blocks

  20. X-ray phase imaging using a X-ray tube with a small focal spot. Improvement of image quality in mammography

    International Nuclear Information System (INIS)

    Honda, Chika; Ohara, Hiromu; Ishisaka, Akira; Shimada, Fumio

    2002-01-01

    Phase contrast X-ray imaging has been studied intensively using X-rays from synchrotron radiation and micro-focus X-ray tubes. However, these studies have revealed the difficulty of this technique's application to practical medical imaging. We have created a phase contrast imaging technique using a molybdenum X-ray tube with a small focal spot size for mammography. We identified the radiographic conditions in phase contrast magnification mammography with a screen-film system, where edge effect due to phase contrast overcomes geometrical unsharpness caused by the 0.1 mm-focal spot of a molybdenum X-ray tube. The edge enhancement due to phase imaging was observed in an image of a plastic tube, and then geometrical configuration of the X-ray tube, the object and the screen-film system was determined for phase imaging of mammography. In order to investigate a potential for medical application of this method, we conducted evaluation of the images of the American Collage of Radiology (ACR) 156 mammography phantom. We obtained higher scores for phase imaging using high speed screen-film systems without any increase of X-ray dose than the score for contract imaging using a standard speed screen-film system. (author)

  1. WEIBULL MULTIPLICATIVE MODEL AND MACHINE LEARNING MODELS FOR FULL-AUTOMATIC DARK-SPOT DETECTION FROM SAR IMAGES

    Directory of Open Access Journals (Sweden)

    A. Taravat

    2013-09-01

    Full Text Available As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method, synthetic aperture radar (SAR can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks. As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  2. Weibull Multiplicative Model and Machine Learning Models for Full-Automatic Dark-Spot Detection from SAR Images

    Science.gov (United States)

    Taravat, A.; Del Frate, F.

    2013-09-01

    As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  3. Magnetic resonance imaging of hypothalamus hypophysis axis lesions; Relationship between posterior pituitary function and posterior bright spot

    Energy Technology Data Exchange (ETDEWEB)

    Shiina, Takeki; Uno, Kimiichi; Arimizu, Noboru; Yoshida, Sho (Chiba Univ. (Japan). School of Medicine); Yamada, Kenichi

    1990-04-01

    Magnetic resonance imaging (MRI) using a 0.5T superconductive machine was performed to the thirty three cases with a variety of the sellar and parasellar tumors and with dysfunction of the hypothalamus-hypophysis axis. Posterior pituitary bright spot (PBS) on T1 weighted image was evaluated with the pituitary hormonal function. These cases were 12 cases of post-treated tumors including pituitary adenoma (9 patients), suprasellar germinoma (2 patients) and craniopharyngioma (one patient), and non-tumorous conditions including 15 cases of central diabetes insipidus (DI), Syndrome of inappropriate secretion of ADH (SIADH) (one patient), Sheehan's syndrome (3 patients) and anorexia nervosa (2 patients). Pituitary bright spot was not seen in all 19 cases with overt DI. On the other hand, PBS was not seen in 9 cases without overt DI. Three cases of these 9 cases showing Sheehan's syndrome with insufficient antidiuretic hormone (ADH) secretion was considered as the state of subclinical DI. Posterior bright spot was not seen in all 13 cases of empty sella including partial empty sella. The results suggested that disappearance of PBS represents abnormality or loss of posterior pituitary function and also it was considered to be closely related to the empty sella. (author).

  4. Image Positioning Accuracy Analysis for Super Low Altitude Remote Sensing Satellites

    Directory of Open Access Journals (Sweden)

    Ming Xu

    2012-10-01

    Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line-of-sight rebuilding of each detection element and this direction precisely intersecting with the Earth's elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.

  5. Accuracy comparison of Pléiades satellite ortho-images using GPS ...

    African Journals Online (AJOL)

    Ivan Henrico

    GCP), high- resolution ... input and reference sources used, such as the use of digital elevation models (DEMs) and ground control points ... RPC method is a coordinate transformation that converts pixel coordinates of the satellite image to.

  6. Deep Learning for Super-Resolution of Time Series Satellite Images

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to use deep learning techniques to enhance the spatial resolution of time series satellite images. This improvement, also called “super-resolution” is...

  7. NOAA Geostationary Operational Environmental Satellite (GOES) Imager Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Geostationary Operational Environmental Satellite (GOES) series provides continuous measurements of the atmosphere and surface over the Western Hemisphere....

  8. NEPR World View 2 Satellite Mosaic - NOAA TIFF Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a mosaic of World View 2 panchromatic satellite imagery of Northeast Puerto Rico that contains the shallow water area (0-35m deep) surrounding...

  9. Unsupervised Word Spotting in Historical Handwritten Document Images using Document-oriented Local Features.

    Science.gov (United States)

    Zagoris, Konstantinos; Pratikakis, Ioannis; Gatos, Basilis

    2017-05-03

    Word spotting strategies employed in historical handwritten documents face many challenges due to variation in the writing style and intense degradation. In this paper, a new method that permits effective word spotting in handwritten documents is presented that it relies upon document-oriented local features which take into account information around representative keypoints as well a matching process that incorporates spatial context in a local proximity search without using any training data. Experimental results on four historical handwritten datasets for two different scenarios (segmentation-based and segmentation-free) using standard evaluation measures show the improved performance achieved by the proposed methodology.

  10. Deforestation change detection in North Korea between 1999 and 2008 using multi temporal satellite image

    Science.gov (United States)

    KIM, K. M.

    2017-12-01

    After the mid-1990s, North Korea has gone through a hard time of shortage of food and fuel due to the large scale flood and landslide. This became a vicious circle, which has kept accelerating the deforestation in North Korea. This study aims to analyze the change of deforestation in North Korea using two different seasonal satellite images of Landsat 5-TM and SPOT-5 between 1999 and 2008. The Land cover was classified into 6 categories: forest, cropland, grassland, bare land, built area and water body. And the deforested and degraded forest area was extracted considering forest land boundary and classified into 3 categories: the cultivated, the unstocked forest land and the bare mountain. For the all classification process, unsupervised classification method was used since North Korea is inaccessible area. The results of the study showed that the stocked forest area has decreased 1,379,000 ha compared with those in 1999, whereas the deforested and degraded forest area has increased 1,207,000 ha in 2008. The increase of 880,000 ha in the unstocked forest land was the biggest expansion among 3 categories of the deforested and degraded forest area during 9 yrs. It is resulted from an increase of firewood usage, which is presumably owing to the severe shortage of fuel and food. I look forward for the outcome of this study to being used as baseline data for inter-Korean forest cooperation. Especially, it is expected to serve as important input data for the potential REDD project site selection with results of the 3rd forest monitoring(2018) of North Korea.

  11. Comparison between WorldView-2 and SPOT-5 images in mapping the bracken fern using the random forest algorithm

    Science.gov (United States)

    Odindi, John; Adam, Elhadi; Ngubane, Zinhle; Mutanga, Onisimo; Slotow, Rob

    2014-01-01

    Plant species invasion is known to be a major threat to socioeconomic and ecological systems. Due to high cost and limited extents of urban green spaces, high mapping accuracy is necessary to optimize the management of such spaces. We compare the performance of the new-generation WorldView-2 (WV-2) and SPOT-5 images in mapping the bracken fern [Pteridium aquilinum (L) kuhn] in a conserved urban landscape. Using the random forest algorithm, grid-search approaches based on out-of-bag estimate error were used to determine the optimal ntree and mtry combinations. The variable importance and backward feature elimination techniques were further used to determine the influence of the image bands on mapping accuracy. Additionally, the value of the commonly used vegetation indices in enhancing the classification accuracy was tested on the better performing image data. Results show that the performance of the new WV-2 bands was better than that of the traditional bands. Overall classification accuracies of 84.72 and 72.22% were achieved for the WV-2 and SPOT images, respectively. Use of selected indices from the WV-2 bands increased the overall classification accuracy to 91.67%. The findings in this study show the suitability of the new generation in mapping the bracken fern within the often vulnerable urban natural vegetation cover types.

  12. Storm diagnostic/predictive images derived from a combination of lightning and satellite imagery

    Science.gov (United States)

    Goodman, Steven J.; Buechler, Dennis E.; Meyer, Paul J.

    1988-01-01

    A technique is presented for generating trend or convective tendency images using a combination of GOES satellite imagery and cloud-to-ground lightning observations. The convective tendency images can be used for short term forecasting of storm development. A conceptual model of cloud electrical development and an example of the methodology used to generate lightning/satellite convective tendency imagery are given. Successive convective tendency images can be looped or animated to show the previous growth or decay of thunderstorms and their associated lighting activity. It is suggested that the convective tendency image may also be used to indicate potential microburst producing storms.

  13. Planetary geodetic control using satellite imaging. [equations for determination of control points from surface television-imagery

    Science.gov (United States)

    Duxbury, T. C.

    1979-01-01

    A new data type for planetary geodetic control using natural satellite imaging is presented. Spacecraft images of natural satellites against the planet give a direct tie between inertial space and surface features surrounding the satellite image. This technique is expected to offer a factor of 3-10 improvement in accuracy over present geodetic reduction for Mars. A specific example using Viking imaging of Phobos against Mars is given.

  14. Automatic spot preparation and image processing of paper microzone-based assays for analysis of bioactive compounds in plant extracts.

    Science.gov (United States)

    Vaher, M; Borissova, M; Seiman, A; Aid, T; Kolde, H; Kazarjan, J; Kaljurand, M

    2014-01-15

    The colorimetric determination of the concentration of phytochemicals in plant extract samples using a spotting automatic system, mobile phone camera and a computer with developed software for quantification is described. Method automation was achieved by using a robotic system for spotting. The instrument was set to disperse the appropriate aliquots of the reagents and sample on a Whatman paper sheet. Spots were photographed and analysed by ImageJ software or by applying the developed MatLab based algorithm. The developed assay was found to be effective, with a linear response at the concentration range of 0.03-0.25g/L for polyphenols. The detection limit of the proposed method is sub 0.03g/L. The paper microzone-based assays for flavonoids and amino acids/peptides were also developed and evaluated as applicable. Comparing the results with conventional PμZP methods demonstrates that both methods yield similar results. At the same time, the proposed method has an attractive advantage in analysis time and repeatability/reproducibility. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Autonomous Sub-Pixel Satellite Track Endpoint Determination for Space Based Images

    Energy Technology Data Exchange (ETDEWEB)

    Simms, L M

    2011-03-07

    An algorithm for determining satellite track endpoints with sub-pixel resolution in spaced-based images is presented. The algorithm allows for significant curvature in the imaged track due to rotation of the spacecraft capturing the image. The motivation behind the subpixel endpoint determination is first presented, followed by a description of the methodology used. Results from running the algorithm on real ground-based and simulated spaced-based images are shown to highlight its effectiveness.

  16. Remote diagnosis via a telecommunication satellite--ultrasonic tomographic image transmission experiments.

    Science.gov (United States)

    Nakajima, I; Inokuchi, S; Tajima, T; Takahashi, T

    1985-04-01

    An experiment to transmit ultrasonic tomographic section images required for remote medical diagnosis and care was conducted using the mobile telecommunication satellite OSCAR-10. The images received showed the intestinal condition of a patient incapable of verbal communication, however the image screen had a fairly coarse particle structure. On the basis of these experiments, were considered as the transmission of ultrasonic tomographic images extremely effective in remote diagnosis.

  17. DARK SPOT DETECTION USING INTENSITY AND THE DEGREE OF POLARIZATION IN FULLY POLARIMETRIC SAR IMAGES FOR OIL POLUTION MONITORING

    Directory of Open Access Journals (Sweden)

    F. Zakeri

    2015-12-01

    Full Text Available Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE 65%, Overall Accuracy 20% and correlation 40% are improved.

  18. Dark SPOT Detection Using Intensity and the Degree of Polarization in Fully Polarimetric SAR Images for Oil Polution Monitoring

    Science.gov (United States)

    Zakeri, F.; Amini, J.

    2015-12-01

    Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR) has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP) is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE) 65%, Overall Accuracy 20% and correlation 40% are improved.

  19. Spot quantification in two dimensional gel electrophoresis image analysis: comparison of different approaches and presentation of a novel compound fitting algorithm.

    Science.gov (United States)

    Brauner, Jan M; Groemer, Teja W; Stroebel, Armin; Grosse-Holz, Simon; Oberstein, Timo; Wiltfang, Jens; Kornhuber, Johannes; Maler, Juan Manuel

    2014-06-11

    Various computer-based methods exist for the detection and quantification of protein spots in two dimensional gel electrophoresis images. Area-based methods are commonly used for spot quantification: an area is assigned to each spot and the sum of the pixel intensities in that area, the so-called volume, is used a measure for spot signal. Other methods use the optical density, i.e. the intensity of the most intense pixel of a spot, or calculate the volume from the parameters of a fitted function. In this study we compare the performance of different spot quantification methods using synthetic and real data. We propose a ready-to-use algorithm for spot detection and quantification that uses fitting of two dimensional Gaussian function curves for the extraction of data from two dimensional gel electrophoresis (2-DE) images. The algorithm implements fitting using logical compounds and is computationally efficient. The applicability of the compound fitting algorithm was evaluated for various simulated data and compared with other quantification approaches. We provide evidence that even if an incorrect bell-shaped function is used, the fitting method is superior to other approaches, especially when spots overlap. Finally, we validated the method with experimental data of urea-based 2-DE of Aβ peptides andre-analyzed published data sets. Our methods showed higher precision and accuracy than other approaches when applied to exposure time series and standard gels. Compound fitting as a quantification method for 2-DE spots shows several advantages over other approaches and could be combined with various spot detection methods.The algorithm was scripted in MATLAB (Mathworks) and is available as a supplemental file.

  20. CNES studies for on-board compression of high-resolution satellite images

    Science.gov (United States)

    Thiebaut, Carole; Delaunay, Xavier; Latry, Christophe; Moury, Gilles

    2008-08-01

    Future high resolution instruments planned by CNES for space remote sensing missions will lead to higher bit rates because of the increase in resolution and dynamic range. For example, the ground resolution improvement induces a data rate multi-plied by 8 from SPOT4 to SPOT5 and by 28 to PLEIADES-HR. Lossy data compression with low complexity algorithms is then needed since compression ratio are always higher. New image compression algorithms have been used to increase their compression performance while complying with image quality requirements from the community of users and experts. Thus, DPCM algorithm used on-board SPOT4 was replaced by a DCT-based compressor on-board SPOT5. Recent compression algorithms such as PLEIADES-HR one use a wavelet-transform and a bit-plane encoder. But future compressors will have to be more powerful to reach higher compression ratios. New transforms are studied by CNES to exceed the DWT but a per-formance gap could be obtained with selective compression. This article gives an overview of CNES past and present studies of on-board compression algorithms for high-resolution images.

  1. Detecting aircrafts from satellite images using saliency and conical ...

    Indian Academy of Sciences (India)

    Samik Banerjee

    the-art method. Experimental results on real world satellite scenes exhibit the superior performance of the proposed method, over some similar attempts of aircraft localization. The rest of the paper is organized as follows: We discuss related work in section 2. Section 3 gives a detailed over- view of proposed frameworks for ...

  2. Wildfire monitoring using satellite images, ontologies and linked geospatial data

    NARCIS (Netherlands)

    K. Kyzirakos (Konstantinos); M. Karpathiotakis (Manos); G. Garbis (George); C. Nikolaou (Charalampos); K. Bereta (Konstantina); I. Papoutsis (Ioannis); T. Herekakis (Themistocles); D. Michail (Dimitrios); M. Koubarakis (Manolis); C. Kontoes (Charalampos)

    2014-01-01

    htmlabstractAdvances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation data archives have been constantly increasing in size in the last few years, and have become a valuable source of data for many

  3. RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    K. Gong

    2017-05-01

    Full Text Available High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

  4. Assessment of Off-shore Wind Energy Resource in China using QuikSCAT Satellite data and SAR Satellite Images

    DEFF Research Database (Denmark)

    Xiuzhi, Zhang; Yanbo, Shen; Jingwei, Xu

    2010-01-01

    From August 2008 to August 2009, the project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ was carried out by China Meteorological Administration (CMA), which was funded by the EU-China Energy and Environment Programme (EEP). As one ...... part of the project, off-shore wind energy resource in China was assessed with QuikSCAT Satellite data and SAR Satellite Images. In this paper, the results from these two ways were introduced.......From August 2008 to August 2009, the project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ was carried out by China Meteorological Administration (CMA), which was funded by the EU-China Energy and Environment Programme (EEP). As one...

  5. The 2017 Hurricane Season: A Revolution in Geostationary Weather Satellite Imaging and Data Processing

    Science.gov (United States)

    Weiner, A. M.; Gundy, J.; Brown-Bertold, B.; Yates, H.; Dobler, J. T.

    2017-12-01

    Since their introduction, geostationary weather satellites have enabled us to track hurricane life-cycle movement from development to dissipation. During the 2017 hurricane season, the new GOES-16 geostationary satellite demonstrated just how far we have progressed technologically in geostationary satellite imaging, with hurricane imagery showing never-before-seen detail of the hurricane eye and eyewall structure and life cycle. In addition, new ground system technology, leveraging high-performance computing, delivered imagery and data to forecasters with unprecedented speed—and with updates as often as every 30 seconds. As additional satellites and new products become operational, forecasters will be able to track hurricanes with even greater accuracy and assist in aftermath evaluations. This presentation will present glimpses into the past, a look at the present, and a prediction for the future utilization of geostationary satellites with respect to all facets of hurricane support.

  6. 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.

    or other natural landscapes. Having very high resolution digital data over a landscape will however create new challenges in the field of atmospheric correction, ground registration, image processing and finally the image interpretation itself. Even...

  7. Detecting aircrafts from satellite images using saliency and conical ...

    Indian Academy of Sciences (India)

    Samik Banerjee

    based detection framework for targets with complex shapes in high resolution remote sensing images. Results were shown on remote sensing images from Google Earth for aircraft detection. Most of the images used were of high resolution, containing clear pictures of aircrafts as targets. Several deep learning frameworks ...

  8. A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon

    Science.gov (United States)

    Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio

    2009-01-01

    Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716

  9. Moving object detection in video satellite image based on deep learning

    Science.gov (United States)

    Zhang, Xueyang; Xiang, Junhua

    2017-11-01

    Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

  10. Accuracy of stress measurement by Laue microdiffraction (Laue-DIC method): the influence of image noise, calibration errors and spot number.

    Science.gov (United States)

    Zhang, F G; Bornert, M; Petit, J; Castelnau, O

    2017-07-01

    Laue microdiffraction, available at several synchrotron radiation facilities, is well suited for measuring the intragranular stress field in deformed materials thanks to the achievable submicrometer beam size. The traditional method for extracting elastic strain (and hence stress) and lattice orientation from a microdiffraction image relies on fitting each Laue spot with an analytical function to estimate the peak position on the detector screen. The method is thus limited to spots exhibiting ellipsoidal shapes, thereby impeding the study of specimens plastically deformed. To overcome this difficulty, the so-called Laue-DIC method introduces digital image correlation (DIC) for the evaluation of the relative positions of spots, which can thus be of any shape. This paper is dedicated to evaluating the accuracy of this Laue-DIC method. First, a simple image noise model is established and verified on the data acquired at beamline BM32 of the European Synchrotron Radiation Facility. Then, the effect of image noise on errors on spot displacement measured by DIC is evaluated by Monte Carlo simulation. Finally, the combined effect of the image noise, calibration errors and the number of Laue spots used for data treatment is investigated. Results in terms of the uncertainty of stress measurement are provided, and various error regimes are identified.

  11. Monitoring the Invasion of Spartina alterniflora from 1993 to 2014 with Landsat TM and SPOT 6 Satellite Data in Yueqing Bay, China.

    Directory of Open Access Journals (Sweden)

    Anqi Wang

    Full Text Available The exotic plant Spartina alterniflora was introduced to Yueqing Bay more than 20 years ago for tidal land reclamation and as a defense against typhoons, but it has rapidly expanded and caused enormous ecological consequences. Mapping the spread and distribution of S. alterniflora is the first step toward understanding the factors that determine the population expansion patterns. Remote sensing is a promising tool to monitor the expansion of S. alterniflora. Twelve Landsat TM images and Support Vector Machine (SVM were used to delineate the invasion of S. alterniflora from 1993 to 2009, and SPOT 6 images and Object-Based Image Analysis (OBIA were used to map the distribution of S. alterniflora in 2014. In situ data and Unmanned Aerial Vehicle (UAV images were used as supplementary data. S. alterniflora spread rapidly in Yueqing Bay over the past 21 years. Between 1993 and 2009, the area of S. alterniflora increased by 608 times (from 4 to 2432 ha. The rapid expansion of S. alterniflora covered almost all of the bare mudflats around the mangrove forests and the cultivated mudflats. However, from 2009 to 2014, the rate of expansion of S. alterniflora began to slow down in Yueqing Bay, and the total area of S. alterniflora in Yantian decreased by 275 ha. These phenomena can be explained by the landscape changes and ecological niches. Through the expansion of S. alterniflora, it was found that the ecological significance and environmental impact of S. alterniflora was different in different regions in Yueqing Bay. The conservation plans for Yueqing Bay should consider both the positive and negative effects of S. alterniflora, and the governmental policy should be based on the different circumstances of the regions.

  12. Monitoring the Invasion of Spartina alterniflora from 1993 to 2014 with Landsat TM and SPOT 6 Satellite Data in Yueqing Bay, China.

    Science.gov (United States)

    Wang, Anqi; Chen, Jiadai; Jing, Changwei; Ye, Guanqiong; Wu, Jiaping; Huang, Zhixing; Zhou, Chaosheng

    2015-01-01

    The exotic plant Spartina alterniflora was introduced to Yueqing Bay more than 20 years ago for tidal land reclamation and as a defense against typhoons, but it has rapidly expanded and caused enormous ecological consequences. Mapping the spread and distribution of S. alterniflora is the first step toward understanding the factors that determine the population expansion patterns. Remote sensing is a promising tool to monitor the expansion of S. alterniflora. Twelve Landsat TM images and Support Vector Machine (SVM) were used to delineate the invasion of S. alterniflora from 1993 to 2009, and SPOT 6 images and Object-Based Image Analysis (OBIA) were used to map the distribution of S. alterniflora in 2014. In situ data and Unmanned Aerial Vehicle (UAV) images were used as supplementary data. S. alterniflora spread rapidly in Yueqing Bay over the past 21 years. Between 1993 and 2009, the area of S. alterniflora increased by 608 times (from 4 to 2432 ha). The rapid expansion of S. alterniflora covered almost all of the bare mudflats around the mangrove forests and the cultivated mudflats. However, from 2009 to 2014, the rate of expansion of S. alterniflora began to slow down in Yueqing Bay, and the total area of S. alterniflora in Yantian decreased by 275 ha. These phenomena can be explained by the landscape changes and ecological niches. Through the expansion of S. alterniflora, it was found that the ecological significance and environmental impact of S. alterniflora was different in different regions in Yueqing Bay. The conservation plans for Yueqing Bay should consider both the positive and negative effects of S. alterniflora, and the governmental policy should be based on the different circumstances of the regions.

  13. A line rate calculation method for arbitrary directional imaging of an Earth observing satellite

    Science.gov (United States)

    Jeon, Moon-Jin; Kim, Eunghyun; Lim, Seong-Bin; Choi, Seok-Weon

    2016-10-01

    For an earth observing satellite, a line rate is the number of lines which the CCD of push broom type camera scans in a second. It can be easily calculated by ground velocity divided by ground sample distance. Accurate calculation of line rate is necessary to obtain high quality image using TDI CCD. The earth observing satellite has four types of imaging missions which are strip imaging, stereo imaging, multi-point imaging, and arbitrary directional imaging. For the first three types of imaging, ground scanning direction is aligned with satellite velocity direction. Therefore, if the orbit propagation and spacecraft attitude information are available, the ground velocity and ground sample distance could be easily calculated. However, the calculation method might not be applicable to the arbitrary directional imaging. In the arbitrary directional imaging mode, the ground velocity is not fixed value which could be directly derived by orbit information. Furthermore, the ground sample distance might not be easily calculated by simple trigonometry which is possible for the other types of imaging. In this paper, we proposed a line rate calculation method for the arbitrary directional imaging. We applied spherical geometry to derive the equation of ground point which is the intersection between the line of sight vector of the camera and earth surface. The derivative of this equation for time is the ground velocity except the factor of earth rotation. By adding this equation and earth rotation factor, the true ground velocity vector could be derived. For the ground sample distance, we applied the equation of circle and ellipse for yaw angle difference. The equation of circle is used for the yaw angle representation on the plane which is orthogonal to the line of sight vector. The equation of ellipse is used for the yaw angle representation on the ground surface. We applied the proposed method to the KOMPSAT-3A (Korea Multi-Purpose Satellite 3A) mission which is the first

  14. SU-G-206-08: How Should Focal Spot Be Chosen for Optimized CT Imaging with Dose Modulation?

    International Nuclear Information System (INIS)

    Bache, S; Liu, X; Rong, J

    2016-01-01

    Purpose: To choose the preferred focal spot for achieving optimized CT image quality with balanced tube heating considerations. Methods: An anthropomorphic pelvic phantom was scanned using a GE Discovery CT750 HD at 120 and 140kVp, 0.8s rotation time, and pitch of 0.984. “Smart mA” was enabled to simulate a routine abdomen–pelvis CT scan. Permissible mA values at 120 and 140 kVp were obtained from the Serial Load Rating table (for mimicking a busy CT clinical operation) in the scanner Technical Reference Manual. At each kVp station and two Noise Index levels, the mA Upper Limit was set above/below the permissible mA values. Scanned mA values and focal spot (FS) used were obtained from the DICOM header of each image, and the FS-mA relationship was analyzed. For visual confirmation beyond recorded FS information, a CatPhan with a fat-ring attached for mimicking patient size/shape was scanned at 120kVp. A group of radiologists/physicists compared a pair of CatPhan images qualitatively. Lastly, a number of patient cases were evaluated to confirm the FS-mA relationship. Results: When preset Upper Limit values were above the permissible mA values, the Large FS (labeled 1.2) was used in scans, even if the maximum scanned mA values were much lower than the permissible values at both 120 and 140 kVp. Otherwise the Small FS (labeled 0.7) was used. Visual evaluation of the high contrast module of CatPhan and additional analysis of patient cases further confirmed that the preset Upper Limit determines which focal spot is to be used, not the actual maximum mA value to be scanned. Conclusion: Specific FS can be selected by setting up appropriate mA Upper Limit in a protocol. CT protocols could be optimized by selecting appropriate FS for improving patient image quality, especially benefiting the small size and pediatric patients.

  15. Mission planning optimization of video satellite for ground multi-object staring imaging

    Science.gov (United States)

    Cui, Kaikai; Xiang, Junhua; Zhang, Yulin

    2018-03-01

    This study investigates the emergency scheduling problem of ground multi-object staring imaging for a single video satellite. In the proposed mission scenario, the ground objects require a specified duration of staring imaging by the video satellite. The planning horizon is not long, i.e., it is usually shorter than one orbit period. A binary decision variable and the imaging order are used as the design variables, and the total observation revenue combined with the influence of the total attitude maneuvering time is regarded as the optimization objective. Based on the constraints of the observation time windows, satellite attitude adjustment time, and satellite maneuverability, a constraint satisfaction mission planning model is established for ground object staring imaging by a single video satellite. Further, a modified ant colony optimization algorithm with tabu lists (Tabu-ACO) is designed to solve this problem. The proposed algorithm can fully exploit the intelligence and local search ability of ACO. Based on full consideration of the mission characteristics, the design of the tabu lists can reduce the search range of ACO and improve the algorithm efficiency significantly. The simulation results show that the proposed algorithm outperforms the conventional algorithm in terms of optimization performance, and it can obtain satisfactory scheduling results for the mission planning problem.

  16. An attitude algorithm based on the band seamless splicing imaging for agile satellite

    Science.gov (United States)

    Wang, Ya-min; Xu, Wei; Jin, Guang; Yang, Xiu-bin; Zhang, Zhao

    2017-09-01

    In order to realize fast maneuvering imaging of the target area with high resolution agile satellite, a new attitude matching algorithm is developed. A strict mosaic imaging model of ray trace and the velocity vector mapping are built according to the strip mosaic imaging principle and the relationship between imaging target and the camera focal plane. The three-axis attitude is deduced based on the principle of optimal tracking of the maneuvering path. Finally, the geometric scaling simulation is carried out through the time delayed and integration (TDI) charge coupled device (CCD) prototype system, satellite attitude control physical simulation platform and the LED earth target simulator. The experimental results show that the algorithm could realize the matching band seamless splicing imaging of the target very well, confirming the correctness of the algorithm.

  17. SUPER RESOLUTION RECONSTRUCTION BASED ON ADAPTIVE DETAIL ENHANCEMENT FOR ZY-3 SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    H. Zhu

    2016-06-01

    Full Text Available Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

  18. NITESat: A High Resolution, Full-Color, Light Pollution Imaging Satellite Mission

    Directory of Open Access Journals (Sweden)

    Ken Walczak

    2017-06-01

    Full Text Available The NITESat (Night Imaging and Tracking Experiment Satellite mission is a 2U CubeSat satellite designed for nighttime Earth imaging to quantify and characterize light pollution across the Midwestern United States. It is accompanied and supported by an array of ground-based light pollution observing stations called GONet (Ground Observing Network. NITESat is a pilot mission testing the potential for a simple and inexpensive (<$500,000 satellite to deliver high-resolution, three-color regional data of artificial light at night. In addition, GONet will form the core of an educational outreach program by establishing an array of all-sky monitors covering the imaging region of the satellite with 20+ full sky light pollution citizen-operated stations. This will provide synchronized data coinciding with the NITESat overpasses as well as providing near continuous night sky quality monitoring. If the initial mission is a success, the potential exists to expand the program into a low cost constellation of satellites capable of delivering global coverage. NITESat is being designed, built and will be operated by the Far Horizons program at the Adler Planetarium in Chicago, Illinois. Far Horizons is a student and volunteer centered program offering hands-on engineering and scientific research opportunities for education.

  19. Information analysis of hyperspectral images from the hyperion satellite

    Science.gov (United States)

    Puzachenko, Yu. G.; Sandlersky, R. B.; Krenke, A. N.; Puzachenko, M. Yu.

    2017-07-01

    A new method of estimating the outgoing radiation spectra data obtained from the Hyperion EO-1 satellite is considered. In theoretical terms, this method is based on the nonequilibrium thermodynamics concept with corresponding estimates of the entropy and the Kullbak information. The obtained information estimates make it possible to assess the effective work of the landscape cover both in general and for its various types and to identify the spectrum ranges primarily responsible for the information increment and, accordingly, for the effective work. The information is measured in the frequency band intervals corresponding to the peaks of solar radiation absorption by different pigments, mesophyll, and water to evaluate the system operation by their synthesis and moisture accumulation. This method is assumed to be effective in investigation of ecosystem functioning by hyperspectral remote sensing.

  20. 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.

  1. Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

    Directory of Open Access Journals (Sweden)

    Shaodan Li

    2017-11-01

    Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

  2. High efficient optical remote sensing images acquisition for nano-satellite-framework

    Science.gov (United States)

    Li, Feng; Xin, Lei; Liu, Yang; Fu, Jie; Liu, Yuhong; Guo, Yi

    2017-09-01

    It is more difficult and challenging to implement Nano-satellite (NanoSat) based optical Earth observation missions than conventional satellites because of the limitation of volume, weight and power consumption. In general, an image compression unit is a necessary onboard module to save data transmission bandwidth and disk space. The image compression unit can get rid of redundant information of those captured images. In this paper, a new image acquisition framework is proposed for NanoSat based optical Earth observation applications. The entire process of image acquisition and compression unit can be integrated in the photo detector array chip, that is, the output data of the chip is already compressed. That is to say, extra image compression unit is no longer needed; therefore, the power, volume, and weight of the common onboard image compression units consumed can be largely saved. The advantages of the proposed framework are: the image acquisition and image compression are combined into a single step; it can be easily built in CMOS architecture; quick view can be provided without reconstruction in the framework; Given a certain compression ratio, the reconstructed image quality is much better than those CS based methods. The framework holds promise to be widely used in the future.

  3. Automatic archaeological feature extraction from satellite VHR images

    Science.gov (United States)

    Jahjah, Munzer; Ulivieri, Carlo

    2010-05-01

    Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were

  4. Anholt offshore wind farm winds investigated from satellite images

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Volker, Patrick

    , i.e. before the wind farm was constructed. Based on these data the wind resource is estimated. Concurrent Sentinel-1 SAR data and available SCADA and lidar data, kindly provided by DONG Energy and partners, for the period January 2013 to June 2015 account for ~70 images, while ~300 images...... are available for Sentinel-1 from July 2015 to February 2017. The Sentinel-1 wind maps are investigated for wind farm wake effects. Furthermore the results on wind resources and wakes are compared to the SCADA and model results from WRF, Park, Fuga and RANS models....

  5. The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

    Science.gov (United States)

    Ronald E. McRoberts

    2010-01-01

    Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

  6. Attitude motion compensation for imager on Fengyun-4 geostationary meteorological satellite

    Science.gov (United States)

    Lyu, Wang; Dai, Shoulun; Dong, Yaohai; Shen, Yili; Song, Xiaozheng; Wang, Tianshu

    2017-09-01

    A compensation method is used in Chinese Fengyun-4 satellite to counteracting the line-of-sight influence by attitude motion during imaging. The method is acted on-board by adding the compensation amount to the instrument scanning control circuit. The mathematics simulation and the three-axis air-bearing test results show that the method works effectively.

  7. Review On Feasibility of Using Satellite Imaging for Risk Management of Derailment Related Turnout Component Failures

    Science.gov (United States)

    Dindar, Serdar; Kaewunruen, Sakdirat; Osman, Mohd H.

    2017-10-01

    One of the emerging significant advances in engineering, satellite imaging (SI) is becoming very common in any kind of civil engineering projects e.g., bridge, canal, dam, earthworks, power plant, water works etc., to provide an accurate, economical and expeditious means of acquiring a rapid assessment. Satellite imaging services in general utilise combinations of high quality satellite imagery, image processing and interpretation to obtain specific required information, e.g. surface movement analysis. To extract, manipulate and provide such a precise knowledge, several systems, including geographic information systems (GIS) and global positioning system (GPS), are generally used for orthorectification. Although such systems are useful for mitigating risk from projects, their productiveness is arguable and operational risk after application is open to discussion. As the applicability of any novel application to the railway industry is often measured in terms of whether or not it has gained in-depth knowledge and to what degree, as a result of errors during its operation, this novel application generates risk in ongoing projects. This study reviews what can be achievable for risk management of railway turnouts thorough satellite imaging. The methodology is established on the basis of other published articles in this area and the results of applications to understand how applicable such imagining process is on railway turnouts, and how sub-systems in turnouts can be effectively traced/operated with less risk than at present. As a result of this review study, it is aimed that the railway sector better understands risk mitigation in particular applications.

  8. Effects of satellite image spatial aggregation and resolution on estimates of forest land area

    Science.gov (United States)

    M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

    2009-01-01

    Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

  9. Mapping land cover from satellite images: A basic, low cost approach

    Science.gov (United States)

    Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

    1978-01-01

    Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

  10. High-sensitive bioorthogonal SERS tag for live cancer cell imaging by self-assembling core-satellites structure gold-silver nanocomposite.

    Science.gov (United States)

    Chen, Meng; Zhang, Ling; Gao, Mingxia; Zhang, Xiangmin

    2017-09-01

    A novel, high-sensitivity, biocompatible SERS tag with core-shell structure based on gold nanoparticles containing alkynyl molecule core -silver nanoparticle satellites shell was fabricated for the first time to be used for live cancer cells Surface enhanced Raman scattering (SERS) imaging. (E)-2-((4-(phenylethynyl)benzylidene) amino) ethanethiol (PBAT) synthesized facilely in our lab is the Raman-silence region reporter which is advantage for bioorthogonal SERS cell imaging. In order to enhance the intensity of the Raman tags for live cancer cell imaging, a series of news measures have been adopted. Firstly, reporter molecules of the PBAT were added twice, which is embedded in the gold core with the reduction of tetrachloroaurate and then PBAT is conjugated again on disperse gold nanoparticles (PBAT-Au). Furthermore, numerous Ag nanoparticles self-assembly were densely arranged around PBAT-Au core surface (PBAT- Au@Ag), just like a circle of satellites cluster, which produce obvious "hot spots" effects enhancing the signal of the Raman tags enormously. Finally, Bovine serum albumin (BSA) and polydopamine (PDA) coated on the PBAT- Au@Ag successively, defined as (PBAT-Au@Ag@BSA@PDA), which make as-synthesized nanocomposites own features of bio-compatibility and facilitates antibody modification. Compared with Au@PBAT@PDA, PBAT-Au@Ag@BSA@PDA with core-shell satellites structure showed 10-fold increase in the Raman signals intensity. Moreover, PBAT-Au@Ag@BSA@PDA nanocomposites were successfully applied in the Raman imaging of human glioma cells (U251) by the recognition of the anti-epidermal growth factor receptor (EGFR). All experimental results demonstrated that the nanocomposites have high value and huge potential application in the live cancer cells imaging and biomedical diagnostics in the near future. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

    Energy Technology Data Exchange (ETDEWEB)

    Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

    2010-10-21

    The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

  12. An Improved Image Encryption Algorithm Based on Cyclic Rotations and Multiple Chaotic Sequences: Application to Satellite Images

    Directory of Open Access Journals (Sweden)

    MADANI Mohammed

    2017-10-01

    Full Text Available In this paper, a new satellite image encryption algorithm based on the combination of multiple chaotic systems and a random cyclic rotation technique is proposed. Our contribution consists in implementing three different chaotic maps (logistic, sine, and standard combined to improve the security of satellite images. Besides enhancing the encryption, the proposed algorithm also focuses on advanced efficiency of the ciphered images. Compared with classical encryption schemes based on multiple chaotic maps and the Rubik's cube rotation, our approach has not only the same merits of chaos systems like high sensitivity to initial values, unpredictability, and pseudo-randomness, but also other advantages like a higher number of permutations, better performances in Peak Signal to Noise Ratio (PSNR and a Maximum Deviation (MD.

  13. 2D-gel spot detection and segmentation based on modified image-aware grow-cut and regional intensity information.

    Science.gov (United States)

    Kostopoulou, E; Katsigiannis, S; Maroulis, D

    2015-10-01

    Proteomics, the study of proteomes, has been increasingly utilized in a wide variety of biological problems. The Two-Dimensional Gel Electrophoresis (2D-PAGE) technique is a powerful proteomics technique aiming at separation of the complex protein mixtures. Spot detection and segmentation are fundamental components of 2D-gel image analysis but remain arduous and difficult tasks. Several software packages and academic approaches are available for 2D-gel image spot detection and segmentation. Each one has its respective advantages and disadvantages and achieves a different level of success in dealing with the challenges of 2D-gel image analysis. A common characteristic of the available methods is their dependency on user intervention in order to achieve optimal results, a process that can lead to subjective and non-reproducible results. In this work, the authors propose a novel spot detection and segmentation methodology for 2D-gel images. This work introduces a novel spot detection and spot segmentation methodology that is based on a multi-thresholding scheme applied on overlapping regions of the image, a custom grow-cut algorithm, a region growing scheme and morphological operators. The performance of the proposed methodology is evaluated on real as well as synthetic 2D-gel images using well established statistical measures, including precision, sensitivity, and their weighted measure, F-measure, as well as volumetric overlap, volumetric error and volumetric overlap error. Experimental results show that the proposed methodology outperforms state-of-the-art software packages and methods proposed in the literature and results in more plausible spot boundaries and more accurate segmentation. The proposed method achieved the highest F-measure (94.8%) for spot detection and the lowest volumetric overlap error (8.3%) for the segmentation process. Evaluation against state-of-the-art 2D-gel image analysis software packages and techniques proposed in the literature

  14. V-SIPAL - A VIRTUAL LABORATORY FOR SATELLITE IMAGE PROCESSING AND ANALYSIS

    Directory of Open Access Journals (Sweden)

    K. M. Buddhiraju

    2012-09-01

    Full Text Available In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.

  15. V-Sipal - a Virtual Laboratory for Satellite Image Processing and Analysis

    Science.gov (United States)

    Buddhiraju, K. M.; Eeti, L.; Tiwari, K. K.

    2011-09-01

    In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL) being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.

  16. Study of frontal weather system using satellite images

    International Nuclear Information System (INIS)

    Qureshi, J.; Ershad, S.

    2005-01-01

    Pakistan which is situated in the south Asian sub continent, has a peculiar climatological position. It is one of the few countries in the world, which undergo a complete transformation from summer to winter season. However this project only pertains to the winter weather conditions in Pakistan. During winter, the land masses cool off rapidly as compared to the seas and so high pressure cells are developed over land causing, weak anti-cyclonic circulation over the country. In between these cells of anti-cyclonic flow of wind, there are zones of convergence, which offer a good breeding place for low-pressure waves. The low-pressure waves are similar to the extra tropical depressions and approach and approach Pakistan from west. From the same reason these are locally called the western Disturbances. Consequently the focus of study is on the extra tropical cyclones which originate along the boundary between polar continental and tropical or polar maritime and tropical maritime air masses. The extra tropical cyclones (also called western disturbances and westerly waves.) which are embedded in westerly flow of air move across north of Pakistan are usually originate from the Mediterranean sea. These systems consist of two types of fronts i.e. warm and cold fronts. In fact these systems can be traced right from the Atlantic Ocean and Mediterranean Sea. The location of frontal weather is generally associated with the surrounding synoptic situation, geographical position of the westerly wave, location of subtropical jet stream, steering wind level etc. although the satellite imageries are quite helpful for forecasting the frontal weather over our region however the weather charts (both surface and upper air ) and jet maps are also very helpful for this purpose

  17. Thermal precursors in satellite images of the 1999 eruption of Shishaldin Volcano

    Science.gov (United States)

    Dehn, Jonathan; Dean, Kenneson; Engle, Kevin; Izbekov, Pavel

    2002-07-01

    Shishaldin Volcano, Unimak Island Alaska, began showing signs of thermal unrest in satellite images on 9 February 1999. A thermal anomaly and small steam plume were detected at the summit of the volcano in short-wave thermal infrared AVHRR (advanced very high resolution radiometer) satellite data. This was followed by over 2 months of changes in the observed thermal character of the volcano. Initially, the thermal anomaly was only visible when the satellite passed nearly directly over the volcano, suggesting a hot source deep in the central crater obscured from more oblique satellite passes. The "zenith angle" needed to see the anomaly increased with time, presumably as the thermal source rose within the conduit. Based on this change, an ascent rate of ca. 14 m per day for the thermal source was estimated, until it reached the summit on around 21 March. It is thought that Strombolian activity began around this time. The precursory activity culminated in a sub-Plinian eruption on 19 April, ejecting ash to over 45,000 ft. (13,700 m). The thermal energy output through the precursory period was calculated based on geometric constraints unique to Shishaldin. These calculations show fluctuations that can be tied to changes in the eruptive character inferred from seismic records and later geologic studies. The remote location of this volcano made satellite images a necessary observation tool for this eruption. To date, this is the longest thermal precursory activity preceding a sub-Plinian eruption recorded by satellite images in the region. This type of thermal monitoring of remote volcanoes is central in the efforts of the Alaska Volcano Observatory to provide timely warnings of volcanic eruption, and mitigate their associated hazards to air-traffic and local residents.

  18. Influence of the Laser Spot Size, Focal Beam Profile, and Tissue Type on the Lipid Signals Obtained by MALDI-MS Imaging in Oversampling Mode

    Science.gov (United States)

    Wiegelmann, Marcel; Dreisewerd, Klaus; Soltwisch, Jens

    2016-12-01

    To improve the lateral resolution in matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) beyond the dimensions of the focal laser spot oversampling techniques are employed. However, few data are available on the effect of the laser spot size and its focal beam profile on the ion signals recorded in oversampling mode. To investigate these dependencies, we produced 2 times six spots with dimensions between 30 and 200 μm. By optional use of a fundamental beam shaper, square flat-top and Gaussian beam profiles were compared. MALDI-MSI data were collected using a fixed pixel size of 20 μm and both pixel-by-pixel and continuous raster oversampling modes on a QSTAR mass spectrometer. Coronal mouse brain sections coated with 2,5-dihydroxybenzoic acid matrix were used as primary test systems. Sizably higher phospholipid ion signals were produced with laser spots exceeding a dimension of 100 μm, although the same amount of material was essentially ablated from the 20 μm-wide oversampling pixel at all spot size settings. Only on white matter areas of the brain these effects were less apparent to absent. Scanning electron microscopy images showed that these findings can presumably be attributed to different matrix morphologies depending on tissue type. We propose that a transition in the material ejection mechanisms from a molecular desorption at large to ablation at smaller spot sizes and a concomitant reduction in ion yields may be responsible for the observed spot size effects. The combined results indicate a complex interplay between tissue type, matrix crystallization, and laser-derived desorption/ablation and finally analyte ionization.

  19. Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer.

    Science.gov (United States)

    Stålhammar, Gustav; Robertson, Stephanie; Wedlund, Lena; Lippert, Michael; Rantalainen, Mattias; Bergh, Jonas; Hartman, Johan

    2017-12-08

    During pathological examination of breast tumours, proliferative activity is routinely evaluated by a count of mitoses. Adding immunohistochemical stains of Ki67 provides extra prognostic and predictive information. However, the currently used methods for these evaluations suffer from imperfect reproducibility. It is still unclear whether analysis of Ki67 should be performed in hot spots, in the tumour periphery, or as an average of the whole tumour section. The aim of this study was to compare the clinical relevance of mitoses, Ki67 and phosphohistone H3 in two cohorts of primary breast cancer specimens (total n = 294). Both manual and digital image analysis scores were evaluated for sensitivity and specificity for luminal B versus A subtype as defined by PAM50 gene expression assays, for high versus low transcriptomic grade, for axillary lymph node status, and for prognostic value in terms of prediction of overall and relapse-free survival. Digital image analysis of Ki67 outperformed the other markers, especially in hot spots. Tumours with high Ki67 expression and high numbers of phosphohistone H3-positive cells had significantly increased hazard ratios for all-cause mortality within 10 years from diagnosis. Replacing manual mitotic counts with digital image analysis of Ki67 in hot spots increased the differences in overall survival between the highest and lowest histological grades, and added significant prognostic information. Digital image analysis of Ki67 in hot spots is the marker of choice for routine analysis of proliferation in breast cancer. © 2017 John Wiley & Sons Ltd.

  20. Automatic Reacquisition of Satellite Positions by Detecting Their Expected Streaks in Astronomical Images

    Science.gov (United States)

    Levesque, M.

    Artificial satellites, and particularly space junk, drift continuously from their known orbits. In the surveillance-of-space context, they must be observed frequently to ensure that the corresponding orbital parameter database entries are up-to-date. Autonomous ground-based optical systems are periodically tasked to observe these objects, calculate the difference between their predicted and real positions and update object orbital parameters. The real satellite positions are provided by the detection of the satellite streaks in the astronomical images specifically acquired for this purpose. This paper presents the image processing techniques used to detect and extract the satellite positions. The methodology includes several processing steps including: image background estimation and removal, star detection and removal, an iterative matched filter for streak detection, and finally false alarm rejection algorithms. This detection methodology is able to detect very faint objects. Simulated data were used to evaluate the methodology's performance and determine the sensitivity limits where the algorithm can perform detection without false alarm, which is essential to avoid corruption of the orbital parameter database.

  1. Improving Sediment Transport Prediction by Assimilating Satellite Images in a Tidal Bay Model of Hong Kong

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2014-03-01

    Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.

  2. Research on active imaging information transmission technology of satellite borne quantum remote sensing

    Science.gov (United States)

    Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

    2017-08-01

    According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

  3. Sun glitter imaging analysis of submarine sand waves in HJ-1A/B satellite CCD images

    Science.gov (United States)

    Zhang, Huaguo; He, Xiekai; Yang, Kang; Fu, Bin; Guan, Weibing

    2014-11-01

    Submarine sand waves are a widespread bed-form in tidal environment. Submarine sand waves induce current convergence and divergence that affect sea surface roughness thus become visible in sun glitter images. These sun glitter images have been employed for mapping sand wave topography. However, there are lots of effect factors in sun glitter imaging of the submarine sand waves, such as the imaging geometry and dynamic environment condition. In this paper, several sun glitter images from HJ-1A/B in the Taiwan Banks are selected. These satellite sun glitter images are used to discuss sun glitter imaging characteristics in different sensor parameters and dynamic environment condition. To interpret the imaging characteristics, calculating the sun glitter radiance and analyzing its spatial characteristics of the sand wave in different images is the best way. In this study, a simulated model based on sun glitter radiation transmission is adopted to certify the imaging analysis in further. Some results are drawn based on the study. Firstly, the sun glitter radiation is mainly determined by sensor view angle. Second, the current is another key factor for the sun glitter. The opposite current direction will cause exchanging of bright stripes and dark stripes. Third, brightness reversal would happen at the critical angle. Therefore, when using sun glitter image to obtain depth inversion, one is advised to take advantage of image properties of sand waves and to pay attention to key dynamic environment condition and brightness reversal.

  4. Dotlike hemosiderin spots on T2*-weighted magnetic resonance imaging as a predictor of stroke recurrence: a prospective study.

    Science.gov (United States)

    Imaizumi, Toshio; Horita, Yoshifumi; Hashimoto, Yuji; Niwa, Jun

    2004-12-01

    Microangiopathy associated with hypertension is a notable cause of cerebral small vessel disease (SVD), including deep intracerebral hemorrhage (ICH) and lacunar infarct. Dotlike low-intensity spots (dotlike hemosiderin spots: dotHSs) on T2*-weighted magnetic resonance (MR) images have been histologically diagnosed as old cerebral microbleeds associated with lipohyalinosis, amyloid angiopathy, or other microangiopathies and located in deep or subcortical regions. The aim of this study was to determine whether dotHSs indicate the severity of microangiopathy, and if so, whether large numbers of deep dotHSs are associated with SVD recurrence. The authors prospectively analyzed the number of dotHSs in 337 patients-191 men and 146 women with a mean age of 66 +/- 10.4 years (range 37-94 years)-with SVD (199 ICHs and 138 lacunar infarcts) who had been consecutively admitted to Hakodate Municipal Hospital. The follow-up period was 3.5 to 42 months (22.5 +/- 13.1 months). Patients were divided into two groups based on the recurrence. The hazard ratio (HR) for recurrence was estimated based on the Cox proportional hazard model by using the number of deep and subcortical dotHSs as well as other factors. Of 337 patients, 20 were readmitted with recurrence. Results of a multivariate analysis revealed an elevated rate of recurrence in patients with many subcortical dotHSs (> or = 5, HR 4.36, p = 0.0019) or a history of ICH (HR 3.82, p = 0.014). A trend toward a positive correlation (Pearson correlation coefficient 0.548, p < 0.0001) was found between the number of deep and subcortical dotHSs. Although a small sample size limited the power of analyses, the findings indicate that a large number of subcortical dotHSs may predict SVD recurrence.

  5. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  6. Spatial resolution enhancement of satellite image data using fusion approach

    Science.gov (United States)

    Lestiana, H.; Sukristiyanti

    2018-02-01

    Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

  7. Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images

    Science.gov (United States)

    Máttyus, G.

    2013-05-01

    Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

  8. Comparison of single-spot technique and RGB imaging for erythema index estimation.

    Science.gov (United States)

    Saknite, I; Zavorins, A; Jakovels, D; Spigulis, J; Kisis, J

    2016-03-01

    A commercially available point measurement device, the Mexameter(®), and an experimental RGB imaging prototype device were used for erythema index estimation of 50 rosacea patients by analysing the level of skin redness on the forehead, both cheeks and both sides of a nose. Results are compared with Clinician's Erythema Assessment (CEA) values given by two dermatologists. The Mexameter uses 568 nm and 660 nm LEDs and a photodetector for estimation of erythema index, while the used prototype device acquired RGB images at 460 nm, 530 nm and 665 nm LED illumination. Several erythema index estimation algorithms were compared to determine which one gives the best contrast between increased erythema and normal skin. The erythema index estimations and CEA values correlated much better for the RGB imaging data than for those obtained by the conventional Mexameter technique that is widely used by dermatologists and in clinical trials. In result, we propose an erythema index estimation approach that represents increased erythema with higher accuracy than other available methods.

  9. From SPOT 5 to Pleiades HR: evolution of the instrumental specifications

    Science.gov (United States)

    Rosak, A.; Latry, C.; Pascal, V.; Laubier, D.

    2017-11-01

    Image quality specifications should aimed to fulfil high resolution mission requirements of remote sensing satellites with a minimum cost. The most important trade-off to be taken into account is between Modulation Transfer Function, radiometric noise and sampling scheme. This compromise is the main driver during design optimisation and requirement definition in order to achieve good performances and to minimise the mission cost. For the SPOT 5 satellite, a new compromise had been chosen. The supermode principle of imagery (sampling at 2.5 meter with a pixel size of 5 meter) imp roves the resolution by a factor of four compared with the SPOT 4 satellite (10 meter resolution). This paper presents the image quality specifications of the HRG-SPOT 5 instrument. We introduce all the efforts made on the instrument to achieve good image quality and low radiometric noise, then we compare the results with the SPOT 4 instrument's performances to highlight the improvements achieved. Then, the in-orbit performance will be described. Finally, we will present the new goals of image quality specifications for the new Pleiades-HR satellite for earth observation (0.7 meter resolution) and the instrument concept.

  10. Assessing the utility of ALOS PALSAR and SPOT 4 to predict timber ...

    African Journals Online (AJOL)

    In commercial forestry, regular terrestrial enumerations of the growing stock are required for the valuation, sustainable management and planning of current and future timber supplies. In this study we examined whether the combination of synthetic aperture radar (ALOS PALSAR) and optical satellite (SPOT 4) image data ...

  11. Classification of high resolution satellite images using spatial constraints-based fuzzy clustering

    Science.gov (United States)

    Singh, Pankaj Pratap; Garg, Rahul Dev

    2014-01-01

    A spatial constraints-based fuzzy clustering technique is introduced in the paper and the target application is classification of high resolution multispectral satellite images. This fuzzy-C-means (FCM) technique enhances the classification results with the help of a weighted membership function (Wmf). Initially, spatial fuzzy clustering (FC) is used to segment the targeted vegetation areas with the surrounding low vegetation areas, which include the information of spatial constraints (SCs). The performance of the FCM image segmentation is subject to appropriate initialization of Wmf and SC. It is able to evolve directly from the initial segmentation by spatial fuzzy clustering. The controlling parameters in fuzziness of the FCM approach, Wmf and SC, help to estimate the segmented road results, then the Stentiford thinning algorithm is used to estimate the road network from the classified results. Such improvements facilitate FCM method manipulation and lead to segmentation that is more robust. The results confirm its effectiveness for satellite image classification, which extracts useful information in suburban and urban areas. The proposed approach, spatial constraint-based fuzzy clustering with a weighted membership function (SCFCWmf), has been used to extract the information of healthy trees with vegetation and shadows showing elevated features in satellite images. The performance values of quality assessment parameters show a good degree of accuracy for segmented roads using the proposed hybrid SCFCWmf-MO (morphological operations) approach which also occluded nonroad parts.

  12. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

    Science.gov (United States)

    Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2015-12-01

    Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

  13. Direct Geolocation of Satellite Images with the EO-CFI Libraries

    Science.gov (United States)

    de Miguel, Eduardo; Prado, Elena; Estebanez, Monica; Martin, Ana I.; Gonzalez, Malena

    2016-08-01

    The INTA Remote Sensing Laboratory has implemented a tool for the direct geolocation of satellite images. The core of the tool is a C code based on the "Earth Observation Mission CFI SW" from ESA. The tool accepts different types of inputs for satellite attitude (euler angles, quaternions, default attitude models). Satellite position can be provided either in ECEF or ECI coordinates. The line of sight of each individual detector is imported from an external file or is generated by the tool from camera parameters. Global DEM ACE2 is used to define ground intersection of the LOS.The tool has been already tailored for georeferencing images from the forthcoming Spanish Earth Observation mission SEOSat/Ingenio, and for the camera APIS onboard the INTA cubesat OPTOS. The next step is to configure it for the geolocation of Sentinel 2 L1b images.The tool has been internally validated by different means. This validation shows that the tool is suitable for georeferencing images from high spatial resolution missions. As part of the validation efforts, a code for simulating orbital info for LEO missions using EO-CFI has been produced.

  14. Foodstuff Survey Around a Major Nuclear Facility with Test of Satellite Image Application

    International Nuclear Information System (INIS)

    Fledderman, P.D.

    1999-01-01

    'A foodstuff survey was performed around the Savannah River Site, Aiken SC. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of SRS center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined in two ways: by the usual process of assuming uniform crop distribution in each county on the basis of agricultural statistics reported by state agencies, and by analysis of two LANDSAT TM images obtained in May and September. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the Site and by 16-km distance intervals from 16 km to 80 km. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption. For four food crops, the amounts per section based on county agricultural statistics prorated by area were compared with the amounts per section based on satellite image analysis. The median ratios of the former to the latter were 0.6 - 0.7, suggesting that the two approaches are comparable but that satellite image analysis gave consistently higher amounts. Use of satellite image analysis is recommended on the basis of these findings to obtain site-specific, as compared to area-averaged, information on crop locations in conjunction with radionuclide pathway modelling. Some improvements in technique are suggested for satellite image application to characterize additional crops.'

  15. Spatial scales of pollution from variable resolution satellite imaging.

    Science.gov (United States)

    Chudnovsky, Alexandra A; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    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 adequate 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(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. A New Physical Model to Estimate Solar Irradiance Componets on the Earth's Surface from Satellite Images

    Science.gov (United States)

    Cony, Marco, ,, Dr.; Wiesenberg, Ralf, ,, Dr.; Fernandéz, Irene; Jimenez, Marta

    2017-04-01

    The present study describes a new model designed to estimate the incident solar radiation at the Earth's surface from geostationary satellites images (AFASat). In this new physical model proposed, the effect of Rayleigh scattering, aerosols and Earth's surface topography are taken into account. Water vapor absorption is also introduced by means of its climatological effects on shortwave radiation. Cloud albedo, ground albedo and absorption are derived from brightness measurements on the assumption that they both are linearly related to the brightness. However, this simple consideration applied to individual images elements represents quite accurately the bulk effect of clouds and reflectance. AFASat model uses the Heliosat-3 method and add others environmental factors to estimate with relative precision the solar radiation that arrives at the Earth's surface. Comparisons with daily radiation measurements from ground data station located in Europe, Africa and India (BSRN) showed that the satellite estimates were, on the average, within 2% of the ground measurements for global horizontal irradiance and less than 7% for direct normal irradiance. The hourly variations monitored by the satellite also followed very closely the variations measured on the ground. This study has shown that model is sufficient for the determination of the incident solar radiation when the high spatial and temporal coverage of a geostationary satellite is used. The AFASat is highly appropriate for such those projects that required an analysis of the solar resource assessment as such as TMY report (Typical Meteorological Year).

  17. Spatial scales of pollution from variable resolution satellite imaging

    International Nuclear Information System (INIS)

    Chudnovsky, Alexandra A.; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    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 adequate 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 2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM 2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM 2.5 levels and wind speed. - Highlights: ► The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. ► High resolution MAIAC AOD 1 km retrieval can be used to investigate within-city PM 2.5 variability. ► Low pollution days exhibit higher spatial variability of AOD and PM 2.5 then moderate pollution days. ► AOD spatial variability within urban area is higher during the lower wind speed conditions. - The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. The new high-resolution MAIAC AOD retrieval has the potential to capture PM 2.5 variability at the intra-urban scale.

  18. Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

    Science.gov (United States)

    Kamangir, H.; Momeni, M.; Satari, M.

    2017-09-01

    This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

  19. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometric imaging of synthetic polymer sample spots prepared using ionic liquid matrices.

    Science.gov (United States)

    Gabriel, Stefan J; Pfeifer, Dietmar; Schwarzinger, Clemens; Panne, Ulrich; Weidner, Steffen M

    2014-03-15

    Polymer sample spots for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) prepared by the dried-droplet method often reveal ring formation accompanied by possible segregation of matrix and sample molecules as well as of the polymer homologs itself. Since the majority of sample spots are prepared by this simple and fast method, a matrix or sample preparation method that excludes such segregation has to be found. Three different ionic liquid matrices based on conventionally used aromatic compounds for MALDI-TOF MS were prepared. The formation of ionic liquids was proven by (1) H NMR spectroscopy. MALDI-Imaging mass spectrometry was applied to monitor the homogeneity. Our results show a superior sample spot homogeneity using ionic liquid matrices. Spots could be sampled several times without visible differences in the mass spectra. A frequently observed loss of matrix in the mass spectrometer vacuum was not observed. The necessary laser irradiance was reduced, which resulted in less polymer fragmentation. Ionic liquid matrices can be used to overcome segregation, a typical drawback of conventional MALDI dried-droplet preparations. Homogeneous sample spots are easy to prepare, stable in the MS vacuum and, thereby, improve the reproducibility of MALDI. Copyright © 2014 John Wiley & Sons, Ltd.

  20. Soil salinity detection from satellite image analysis: an integrated approach of salinity indices and field data.

    Science.gov (United States)

    Morshed, Md Manjur; Islam, Md Tazmul; Jamil, Raihan

    2016-02-01

    This paper attempts to detect soil salinity from satellite image analysis using remote sensing and geographic information system. Salinity intrusion is a common problem for the coastal regions of the world. Traditional salinity detection techniques by field survey and sampling are time-consuming and expensive. Remote sensing and geographic information system offer economic and efficient salinity detection, monitoring, and mapping. To predict soil salinity, an integrated approach of salinity indices and field data was used to develop a multiple regression equation. The correlations between different indices and field data of soil salinity were calculated to find out the highly correlated indices. The best regression model was selected considering the high R (2) value, low P value, and low Akaike's Information Criterion. About 20% variation was observed between the field data and predicted EC from the satellite image analysis. The precision of this salinity detection technique depends on the accuracy and uniform distribution of field data.

  1. A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink

    Directory of Open Access Journals (Sweden)

    Salemi Eric

    2008-01-01

    Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.

  2. A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink

    Directory of Open Access Journals (Sweden)

    Eric Salemi

    2008-01-01

    Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.

  3. Best Timing for Capturing Satellite Thermal Images, Asphalt, and Concrete Objects

    OpenAIRE

    Toufic Abd El-Latif Sadek

    2016-01-01

    The asphalt object represents the asphalted areas like roads, and the concrete object represents the concrete areas like concrete buildings. The efficient extraction of asphalt and concrete objects from one satellite thermal image occurred at a specific time, by preventing the gaps in times which give the close and same brightness values between asphalt and concrete, and among other objects. So that to achieve efficient extraction and then better analysis. Seven sample objects were used un th...

  4. IoSiS: a radar system for imaging of satellites in space

    Science.gov (United States)

    Jirousek, M.; Anger, S.; Dill, S.; Schreiber, E.; Peichl, M.

    2017-05-01

    Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolution radar images are helpful in analyzing a possible damage. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi-purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a highpower traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1 m RX antenna mounted on a common steerable positioner. High-resolution radar images are obtained by using Inverse Synthetic Aperture Radar (ISAR) techniques. The guided tracking of known objects during overpass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system including the basic setup of the antenna, the radar instrument with the RF error correction, and the measurement strategy. Also a short description about a simulation tool for the whole instrument and expected images is shown.

  5. Relationship between Lineament Density Extraction from Satellite Image and Earthquake Distribution of Taungtonelone Area, Myanmar

    OpenAIRE

    MYINT, Soe; WON-IN, KRIT; TAKASHIMA, lsao; CHARUSIRI, Punya

    2007-01-01

    [ABSTRACT] We studied relationship between lineament density extraction from satellite image and earthquake distribution using remote sensing applications. The result of this study aim to set up a complete earthquake hazard Map. The selected area is located in the Taungtonelone area,northern Mynmar. Myanmar is an earth-quake-prone country. It lies in a major earthquake zone of the world called Mediterranean -Himalayan belt. As the major urban areas in Myanmar lie in earthquake prone zones, ea...

  6. Do roads cause deforestation? Using satellite images in econometric analysis of land use

    OpenAIRE

    Nelson, Gerald; Hellerstein, Daniel

    1997-01-01

    In this paper we demonstrate how satellite images and other geographic data can be used to predict land use. A cross-section model of land use is estimated with data for a region in central Mexico. Parameters from the model are used to examine the effects of reduced human activity. If variables that proxy human influence are changed to reflect reduced impact, “forest” area increases and “irrigated crop” area is reduced. Copyright 1997, Oxford University Press.

  7. Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging

    Science.gov (United States)

    Nag, S.; Li, A.

    2016-12-01

    Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall

  8. TESIS experiment on XUV imaging spectroscopy of the Sun onboard the CORONAS-PHOTON satellite

    Science.gov (United States)

    Kuzin, S. V.; Zhitnik, I. A.; Bogachev, S. A.; Shestov, S. V.; Bugaenko, O. I.; Suhodrev, N. K.; Pertsov, A. A.; Mitrofanov, A. V.; Ignat'ev, A. P.; Slemzin, V. A.

    We present a brief description of new complex of space telescopes and spectrographs, TESIS, which will be placed aboard the CORONAS-PHOTON satellite. The complex is intended for high-resolution imaging observation of full Sun in the coronal spectral lines and in the spectral lines of the solar transition region. TESIS will be launched at the end of 2007 - early of 2008. About 25 % of the daily TESIS images will be free for use and for downloading from the TESIS data center that is planned to open 2 months before the TESIS launching at http://www.tesis.lebedev.ru

  9. Multi-Scale Analysis of Very High Resolution Satellite Images Using Unsupervised Techniques

    Directory of Open Access Journals (Sweden)

    Jérémie Sublime

    2017-05-01

    Full Text Available This article is concerned with the use of unsupervised methods to process very high resolution satellite images with minimal or little human intervention. In a context where more and more complex and very high resolution satellite images are available, it has become increasingly difficult to propose learning sets for supervised algorithms to process such data and even more complicated to process them manually. Within this context, in this article we propose a fully unsupervised step by step method to process very high resolution images, making it possible to link clusters to the land cover classes of interest. For each step, we discuss the various challenges and state of the art algorithms to make the full process as efficient as possible. In particular, one of the main contributions of this article comes in the form of a multi-scale analysis clustering algorithm that we use during the processing of the image segments. Our proposed methods are tested on a very high resolution image (Pléiades of the urban area around the French city of Strasbourg and show relevant results at each step of the process.

  10. Crop Classification in Satellite Images through Probabilistic Segmentation Based on Multiple Sources

    Directory of Open Access Journals (Sweden)

    Oscar S. Dalmau

    2017-06-01

    Full Text Available Classification methods based on Gaussian Markov Measure Field Models and other probabilistic approaches have to face the problem of construction of the likelihood. Typically, in these methods, the likelihood is computed from 1D or 3D histograms. However, when the number of information sources grows, as in the case of satellite images, the histogram construction becomes more difficult due to the high dimensionality of the feature space. In this work, we propose a generalization of Gaussian Markov Measure Field Models and provide a probabilistic segmentation scheme, which fuses multiple information sources for image segmentation. In particular, we apply the general model to classify types of crops in satellite images. The proposed method allows us to combine several feature spaces. For this purpose, the method requires prior information for building a 3D histogram for each considered feature space. Based on previous histograms, we can compute the likelihood of each site of the image to belong to a class. The computed likelihoods are the main input of the proposed algorithm and are combined in the proposed model using a contrast criteria. Different feature spaces are analyzed, among them are 6 spectral bands from LANDSAT 5 TM, 3 principal components from PCA on 6 spectral bands and 3 principal components from PCA applied on 10 vegetation indices. The proposed algorithm was applied to a real image and obtained excellent results in comparison to different classification algorithms used in crop classification.

  11. High resolution satellite image indexing and retrieval using SURF features and bag of visual words

    Science.gov (United States)

    Bouteldja, Samia; Kourgli, Assia

    2017-03-01

    In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

  12. Integrating satellite images and lidar data for straight-line mapping

    Science.gov (United States)

    Elaksher, Ahmed; Alharthy, Abdullatif; Ali, Tarig

    2017-09-01

    Currently, most mapping tasks are carried out using remote sensing data such as satellite imageries and LIDAR point clouds. This paper presents the integration of a QuickBird imagery set (both pan and multispectral) and LIDAR DEM generated from a LIDAR point cloud for mapping the coastline. A number of image processing techniques were applied to pan image to generate a coastline. Then a supervised classification is performed on the multispectral image followed by a raster to vector conversion to extract another shoreline. A third line was created from the LIDAR data using a set of processing algorithms. The three lines are weighted and pixels belonging to all of them are grouped to fit a final coastline. In order to evaluate the results, we manually extracted the corresponding line from the pan image and compared points belonging to both lines. Differences averaged about 1.37 meters.

  13. Recognition of landforms from digital elevation models and satellite imagery with expert systems, pattern recognition and image processing techniques

    OpenAIRE

    Miliaresis, George

    2014-01-01

    Recognition of landforms from digital elevation models and satellite imagery with expert systems, pattern recognition and image processing techniques. PhD Thesis, Remote Sensing & Terrain Pattern Recognition),National Technical University of Athens, Dpt. of Topography (2000).

  14. Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

    Directory of Open Access Journals (Sweden)

    Irene Erlyn Wina Rachmawan

    2015-06-01

    Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

  15. Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

    Science.gov (United States)

    Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.

    2017-09-01

    The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

  16. Age Spots

    Science.gov (United States)

    ... for Every Season How to Choose the Best Skin Care Products In This Section Dermatologic Surgery What is dermatologic ... for Every Season How to Choose the Best Skin Care Products Age Spots Treatment Options Learn more about treatment ...

  17. 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.

  18. AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Fischer

    2018-04-01

    Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

  19. A graph-based approach to detect spatiotemporal dynamics in satellite image time series

    Science.gov (United States)

    Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

    2017-08-01

    Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

  20. 3D reconstruction from multi-view VHR-satellite images in MicMac

    Science.gov (United States)

    Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur

    2018-05-01

    This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

  1. Potential for calibration of geostationary meteorological satellite imagers using the Moon

    Science.gov (United States)

    Stone, T.C.; Kieffer, H.H.; Grant, I.F.; ,

    2005-01-01

    Solar-band imagery from geostationary meteorological satellites has been utilized in a number of important applications in Earth Science that require radiometric calibration. Because these satellite systems typically lack on-board calibrators, various techniques have been employed to establish "ground truth", including observations of stable ground sites and oceans, and cross-calibrating with coincident observations made by instruments with on-board calibration systems. The Moon appears regularly in the margins and corners of full-disk operational images of the Earth acquired by meteorological instruments with a rectangular field of regard, typically several times each month, which provides an excellent opportunity for radiometric calibration. The USGS RObotic Lunar Observatory (ROLO) project has developed the capability for on-orbit calibration using the Moon via a model for lunar spectral irradiance that accommodates the geometries of illumination and viewing by a spacecraft. The ROLO model has been used to determine on-orbit response characteristics for several NASA EOS instruments in low Earth orbit. Relative response trending with precision approaching 0.1% per year has been achieved for SeaWiFS as a result of the long time-series of lunar observations collected by that instrument. The method has a demonstrated capability for cross-calibration of different instruments that have viewed the Moon. The Moon appears skewed in high-resolution meteorological images, primarily due to satellite orbital motion during acquisition; however, the geometric correction for this is straightforward. By integrating the lunar disk image to an equivalent irradiance, and using knowledge of the sensor's spectral response, a calibration can be developed through comparison against the ROLO lunar model. The inherent stability of the lunar surface means that lunar calibration can be applied to observations made at any time, including retroactively. Archived geostationary imager data

  2. 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*.

  3. Fast Road Network Extraction in Satellite Images Using Mathematical Morphology and Markov Random Fields

    Directory of Open Access Journals (Sweden)

    Géraud Thierry

    2004-01-01

    Full Text Available We present a fast method for road network extraction in satellite images. It can be seen as a transposition of the segmentation scheme "watershed transform region adjacency graph Markov random fields" to the extraction of curvilinear objects. Many road extractors which are composed of two stages can be found in the literature. The first one acts like a filter that can decide from a local analysis, at every image point, if there is a road or not. The second stage aims at obtaining the road network structure. In the method we propose to rely on a "potential" image, that is, unstructured image data that can be derived from any road extractor filter. In such a potential image, the value assigned to a point is a measure of its likelihood to be located in the middle of a road. A filtering step applied on the potential image relies on the area closing operator followed by the watershed transform to obtain a connected line which encloses the road network. Then a graph describing adjacency relationships between watershed lines is built. Defining Markov random fields upon this graph, associated with an energetic model of road networks, leads to the expression of road network extraction as a global energy minimization problem. This method can easily be adapted to other image processing fields, where the recognition of curvilinear structures is involved.

  4. Space situational awareness satellites and ground based radiation counting and imaging detector technology

    Energy Technology Data Exchange (ETDEWEB)

    Jansen, Frank, E-mail: frank.jansen@dlr.de [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Behrens, Joerg [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Pospisil, Stanislav [Czech Technical University, IEAP, 12800 Prague 2, Horska 3a/22 (Czech Republic); Kudela, Karel [Slovak Academy of Sciences, IEP, 04001 Kosice, Watsonova 47 (Slovakia)

    2011-05-15

    We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

  5. Enhancement of thematic mapper satellite images for geological mapping of the Cho Dien area, Northern Vietnam

    Science.gov (United States)

    Won-In, Krit; Charusiri, Punya

    2003-06-01

    Information available from the earth science image processing package (ESIPP) software program was applied to enhance the satellite image data of the Cho Dien area, northern Vietnam. The area with dense vegetation covers is dominated by several small Zn-Pb prospects in middle Paleozoic limestone units. Interpretation of satellite image data using the digital enhancement ESIPP program, forms the prime objective of this study, which is to improve the image quality and visual interpretation of regional geology, lineament and structural geology. Thematic mapper of bands 7, 5 and 4 with the false-color composites: blue, green and red, respectively, are considered to be the most appropriate for geologic interpretation. Dark pixel correction is carried out prior to other enhancement analyses which include high-pass filtering, albedo correction, image classification, principle component analysis (PCA) and band ratios. High-pass filtering enhancement is considered to be the most suitable approach for lineament analysis. Albedo is good for differentiating lithology, and image classification is also successfully used for lineament interpretation and discrimination of lithologies but is regarded not better than high-pass filtering and albedo. PCA and ratio of band enhancements are considered not good because there are many disturbed and excavated land areas such as abandoned and current open pits in the concerned area. The result of Landsat interpretation indicate that most lineament structures developed in a roughly N-trending anticlinal structure are in NE-, E- and N-trends. Minor lineaments are in roughly NW-trend, and cross-cutting the NE- and E-trends. Interpretation from enhanced Landsat information also fits very well with field evidences. The interpreted map is slightly different from those of the previous mapping works, particularly with respect to detailed lithological boundaries.

  6. Satellite approach based on cloud cover classification: Estimation of hourly global solar radiation from meteosat images

    International Nuclear Information System (INIS)

    Mefti, A.; Adane, A.; Bouroubi, M.Y.

    2008-01-01

    Hourly global solar irradiation data useful for the design of solar energy conversion systems is generated using a new satellite based model called SICIC (solar irradiation from cloud image classification). It is a model built by processing high resolution visible Meteosat images and ground measurements of solar radiation flux collected in various locations of France during the 1994/95 period. Taking into account the hourly variability of solar radiation flux, SICIC begins by sorting the sun elevation angles into representative classes. For each location and each class, the clearness index is then computed, and the grey levels of the pixels of the visible Meteosat images are converted into cloud cover indexes. Next, two adjustable thresholds are used to split the set of cloud cover indices into three subsets representing clear, partly covered and overcast skies, respectively. Finally, three regression equations linking the clearness and cloud cover indices are obtained for the three sky categories. In these equations, the SICIC parameters (the regression coefficients and both thresholds) vary against the solar elevation angle. SICIC then yields a good estimate of the hourly global solar irradiation flux for every site displayed in the Meteosat images. This model is compared to GISTEL, which is another model governed by the same hypotheses as SICIC but differing by the invariability of its parameters in time. SICIC is found to be more accurate than GISTEL. In particular, the hourly solar data are estimated with an error (RMSE) varying from 32% to 12% for SICIC and 44% to 14% for GISTEL when the sun altitude increases from 15 o to 75 o . At the daily scale, SICIC is also more efficient than GISTEL. It has been satisfactorily applied to other sites of France and Algeria. The tests made on Wefax and B2 Meteosat images show that this model can be easily extended to other satellite images

  7. High efficient optical remote sensing images acquisition for nano-satellite: reconstruction algorithms

    Science.gov (United States)

    Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming

    2017-10-01

    Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.

  8. Deep learning for the detection of barchan dunes in satellite images

    Science.gov (United States)

    Azzaoui, A. M.; Adnani, M.; Elbelrhiti, H.; Chaouki, B. E. K.; Masmoudi, L.

    2017-12-01

    Barchan dunes are known to be the fastest moving sand dunes in deserts as they form under unidirectional winds and limited sand supply over a firm coherent basement (Elbelrhiti and Hargitai,2015). They were studied in the context of natural hazard monitoring as they could be a threat to human activities and infrastructures. Also, they were studied as a natural phenomenon occurring in other planetary landforms such as Mars or Venus (Bourke et al., 2010). Our region of interest was located in a desert region in the south of Morocco, in a barchan dunes corridor next to the town of Tarfaya. This region which is part of the Sahara desert contained thousands of barchans; which limits the number of dunes that could be studied during field missions. Therefore, we chose to monitor barchan dunes with satellite imagery, which can be seen as a complementary approach to field missions. We collected data from the Sentinel platform (https://scihub.copernicus.eu/dhus/); we used a machine learning method as a basis for the detection of barchan dunes positions in the satellite image. We trained a deep learning model on a mid-sized dataset that contained blocks representing images of barchan dunes, and images of other desert features, that we collected by cropping and annotating the source image. During testing, we browsed the satellite image with a gliding window that evaluated each block, and then produced a probability map. Finally, a threshold on the latter map exposed the location of barchan dunes. We used a subsample of data to train the model and we gradually incremented the size of the training set to get finer results and avoid over fitting. The positions of barchan dunes were successfully detected and deep learning was an effective method for this application. Sentinel-2 images were chosen for their availability and good temporal resolution, which will allow the tracking of barchan dunes in future work. While Sentinel images had sufficient spatial resolution for the

  9. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

    Science.gov (United States)

    Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

    2016-07-01

    Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

  10. Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring

    Directory of Open Access Journals (Sweden)

    Pauline Dusseux

    2014-06-01

    Full Text Available The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four optical and five SAR satellite images with high/very high spatial resolutions acquired during the growing season. A vegetation index, namely the NDVI (Normalized Difference Vegetation Index, and two biophysical variables, the LAI (Leaf Area Index and the fCOVER (fraction of Vegetation Cover were computed using optical time series and polarization (HH, VV, HV, VH. The polarization ratio and polarimetric decomposition (Freeman–Durden and Cloude–Pottier were calculated using SAR time series. Then, variables derived from optical, SAR and both types of remotely-sensed data were successively classified using the Support Vector Machine (SVM technique. The results show that the classification accuracy of SAR variables is higher than those using optical data (0.98 compared to 0.81. They also highlight that the combination of optical and SAR time series data is of prime interest to discriminate grasslands from crops, allowing an improved classification accuracy.

  11. Damage Mapping of Powdery Mildew in Winter Wheat with High-Resolution Satellite Image

    Directory of Open Access Journals (Sweden)

    Lin Yuan

    2014-04-01

    Full Text Available Powdery mildew, caused by the fungus Blumeria graminis, is a major winter wheat disease in China. Accurate delineation of powdery mildew infestations is necessary for site-specific disease management. In this study, high-resolution multispectral imagery of a 25 km2 typical outbreak site in Shaanxi, China, taken by a newly-launched satellite, SPOT-6, was analyzed for mapping powdery mildew disease. Two regions with high representation were selected for conducting a field survey of powdery mildew. Three supervised classification methods—artificial neural network, mahalanobis distance, and maximum likelihood classifier—were implemented and compared for their performance on disease detection. The accuracy assessment showed that the ANN has the highest overall accuracy of 89%, following by MD and MLC with overall accuracies of 84% and 79%, respectively. These results indicated that the high-resolution multispectral imagery with proper classification techniques incorporated with the field investigation can be a useful tool for mapping powdery mildew in winter wheat.

  12. A case of timely satellite image acquisitions in support of coastal emergency environmental response management

    Science.gov (United States)

    Ramsey, Elijah W.; Werle, Dirk; Lu, Zhong; Rangoonwala, Amina; Suzuoki, Yukihiro

    2009-01-01

    The synergistic application of optical and radar satellite imagery improves emergency response and advance coastal monitoring from the realm of “opportunistic” to that of “strategic.” As illustrated by the Hurricane Ike example, synthetic aperture radar imaging capabilities are clearly applicable for emergency response operations, but they are also relevant to emergency environmental management. Integrated with optical monitoring, the nearly real-time availability of synthetic aperture radar provides superior consistency in status and trends monitoring and enhanced information concerning causal forces of change that are critical to coastal resource sustainability, including flooding extent, depth, and frequency.

  13. Monitoring an air pollution episode in Shenzhen by combining MODIS satellite images and the HYSPLIT model

    Science.gov (United States)

    Li, Lili; Liu, Yihong; Wang, Yunpeng

    2017-07-01

    Urban air pollution is influenced not only by local emission sources including industry and vehicles, but also greatly by regional atmospheric pollutant transportation from the surrounding areas, especially in developed city clusters, like the Pearl River Delta (PRD). Taking an air pollution episode in Shenzhen as an example, this paper investigates the occurrence and evolution of the pollution episode and identifies the transport pathways of air pollutants in Shenzhen by combining MODIS satellite images and HYSPLIT back trajectory analysis. Results show that this pollution episode is mainly caused by the local emission of pollutants in PRD and oceanic air masses under specific weather conditions.

  14. Utilization of satellite images to understand the dynamics of Pampas shallow lakes

    Directory of Open Access Journals (Sweden)

    V. S. Aliaga

    2016-06-01

    Full Text Available The aim of this study was to analyze satellite images of different spatial resolutions to interpret the morphometric behavior of six shallow lakes of the Pampas, Argentina. These are characterized by having different rainfall regimes. Morphometric response considering each location, site conditions and dry and wet extreme events is analyzed. Standardized Precipitation Index (IEP for determination of wet, dry and normal years was used. This analysis showed that the Pampas shallow lakes do not behave in the same way to the rainfall events. Its origin, socio-economic use and rainfall patterns affect their spatiotemporal variation and morphometric.

  15. Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO

    Science.gov (United States)

    Choi, Michael K.

    2014-01-01

    This paper uses phase change material (PCM) in the scan cavity of an imager or sounder on satellites in geostationary orbit (GEO) to maintain the telescope temperature stable. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the telescope warm. It has no moving parts or bimetallic springs. It reduces heater power required to make up the heat lost by radiation to space through the aperture. It is an attractive thermal control option to a radiator with a louver and a sunshade.

  16. Wavelet-Based Local Contrast Enhancement for Satellite, Aerial and Close Range Images

    Directory of Open Access Journals (Sweden)

    Krystian Pyka

    2017-01-01

    Full Text Available The methods used for image contrast enhancement in the wavelet domain have been previously documented. The essence of these methods lies in the manipulation of the image during the reconstruction process, by changing the relationship between the components that require transformation. This paper proposes a new variant based on using undecimated wavelet transform and adapting the Gaussian function for scaling the coefficients of detail wavelet components, so that the role of low coefficients in the reconstructed image is greater. The enhanced image is then created by combining the new components. Applying the Haar wavelet minimises the effects of the relationship disturbance between components, and creates a small buffer around the edge. The proposed method was tested using six images at different scales, collected with handheld photo cameras, and aerial and satellite optical sensors. The results of the tests indicate that the method can achieve comparable, or even better enhancement effects for weak edges, than the well-known unsharp masking and Retinex methods. The proposed method can be applied in order to improve the visual interpretation of remote sensing images taken by various sensors at different scales.

  17. kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2018-03-01

    Full Text Available Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. However, most radiometric normalization methods are linear, and they cannot eliminate the regular nonlinear spectral differences. Here we introduce the well-established kernel canonical correlation analysis (kCCA into radiometric normalization for the first time to overcome this problem, which leads to a new kernel method. It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. It also perfectly eliminates the impact of nonlinear changes caused by seasonal variation of natural objects. Comparisons with the multivariate alteration detection (CCA-based normalization and the histogram matching, on Gaofen-1 (GF-1 data, indicate that the kCCA-based normalization can preserve more similarity and better correlation between an image-pair and effectively avoid the color error propagation. The proposed method not only builds the common scale or reference to make the radiometric consistency among GF-1 image sequences, but also highlights the interesting spectral changes while eliminates less interesting spectral changes. Our method enables the application of GF-1 data for change detection, land-use, land-cover change detection etc.

  18. Satellite Image Pansharpening Using a Hybrid Approach for Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Nguyen Thanh Hoan

    2012-10-01

    Full Text Available Intensity-Hue-Saturation (IHS, Brovey Transform (BT, and Smoothing-Filter-Based-Intensity Modulation (SFIM algorithms were used to pansharpen GeoEye-1 imagery. The pansharpened images were then segmented in Berkeley Image Seg using a wide range of segmentation parameters, and the spatial and spectral accuracy of image segments was measured. We found that pansharpening algorithms that preserve more of the spatial information of the higher resolution panchromatic image band (i.e., IHS and BT led to more spatially-accurate segmentations, while pansharpening algorithms that minimize the distortion of spectral information of the lower resolution multispectral image bands (i.e., SFIM led to more spectrally-accurate image segments. Based on these findings, we developed a new IHS-SFIM combination approach, specifically for object-based image analysis (OBIA, which combined the better spatial information of IHS and the more accurate spectral information of SFIM to produce image segments with very high spatial and spectral accuracy.

  19. The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images

    Science.gov (United States)

    Sudakov, Ivan; Essa, Almabrok; Mander, Luke; Gong, Ming; Kariyawasam, Tharanga

    2017-10-01

    Tundra lakes are key components of the Arctic climate system because they represent a source of methane to the atmosphere. In this paper, we aim to analyze the geometry of the patterns formed by large ($>0.8$ km$^2$) tundra lakes in the Russian High Arctic. We have studied images of tundra lakes in historical maps from the State Hydrological Institute, Russia (date 1977; scale $0.21166$ km/pixel) and in Landsat satellite images derived from the Google Earth Engine (G.E.E.; date 2016; scale $0.1503$ km/pixel). The G.E.E. is a cloud-based platform for planetary-scale geospatial analysis on over four decades of Landsat data. We developed an image-processing algorithm to segment these maps and images, measure the area and perimeter of each lake, and compute the fractal dimension of the lakes in the images we have studied. Our results indicate that as lake size increases, their fractal dimension bifurcates. For lakes observed in historical maps, this bifurcation occurs among lakes larger than $100$ km$^2$ (fractal dimension $1.43$ to $1.87$). For lakes observed in satellite images this bifurcation occurs among lakes larger than $\\sim$100 km$^2$ (fractal dimension $1.31$ to $1.95$). Tundra lakes with a fractal dimension close to $2$ have a tendency to be self-similar with respect to their area--perimeter relationships. Area--perimeter measurements indicate that lakes with a length scale greater than $70$ km$^2$ are power-law distributed. Preliminary analysis of changes in lake size over time in paired lakes (lakes that were visually matched in both the historical map and the satellite imagery) indicate that some lakes in our study region have increased in size over time, whereas others have decreased in size over time. Lake size change during this 39-year time interval can be up to half the size of the lake as recorded in the historical map.

  20. The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images

    Directory of Open Access Journals (Sweden)

    Ivan Sudakov

    2017-10-01

    Full Text Available The climate of the Arctic is warming rapidly and this is causing major changes to the cycling of carbon and the distribution of permafrost in this region. Tundra lakes are key components of the Arctic climate system because they represent a source of methane to the atmosphere. In this paper, we aim to analyze the geometry of the patterns formed by large (> 0.8 km 2 tundra lakes in the Russian High Arctic. We have studied images of tundra lakes in historical maps from the State Hydrological Institute, Russia (date 1977; scale 0.21166 km/pixel and in Landsat satellite images derived from the Google Earth Engine (G.E.E.; date 2016; scale 0.1503 km/pixel. The G.E.E. is a cloud-based platform for planetary-scale geospatial analysis on over four decades of Landsat data. We developed an image-processing algorithm to segment these maps and images, measure the area and perimeter of each lake, and compute the fractal dimension of the lakes in the images we have studied. Our results indicate that as lake size increases, their fractal dimension bifurcates. For lakes observed in historical maps, this bifurcation occurs among lakes larger than 100 km 2 (fractal dimension 1.43 to 1.87 . For lakes observed in satellite images this bifurcation occurs among lakes larger than ∼100 km 2 (fractal dimension 1.31 to 1.95 . Tundra lakes with a fractal dimension close to 2 have a tendency to be self-similar with respect to their area–perimeter relationships. Area–perimeter measurements indicate that lakes with a length scale greater than 70 km 2 are power-law distributed. Preliminary analysis of changes in lake size over time in paired lakes (lakes that were visually matched in both the historical map and the satellite imagery indicate that some lakes in our study region have increased in size over time, whereas others have decreased in size over time. Lake size change during this 39-year time interval can be up to half the size of the lake as recorded in the

  1. 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

  2. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images

    International Nuclear Information System (INIS)

    Arellano, Paul; Tansey, Kevin; Balzter, Heiko; Boyd, Doreen S.

    2015-01-01

    The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI 705 ) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. - Highlights: • Leaf biochemical alterations in the rainforest are caused by petroleum pollution. • Lower levels of chlorophyll content are symptom of vegetation stress in polluted sites. • Increased foliar water content was found in vegetation near polluted sites. • Vegetation stress was detected by using vegetation indices from satellite images. • Polluted sites and hydrocarbon seepages in rainforest can be identified from space. - Hydrocarbon pollution in the Amazon forest is observed for first time from satellite data

  3. SPOT Program

    Science.gov (United States)

    Smith, Jason T.; Welsh, Sam J.; Farinetti, Antonio L.; Wegner, Tim; Blakeslee, James; Deboeck, Toni F.; Dyer, Daniel; Corley, Bryan M.; Ollivierre, Jarmaine; Kramer, Leonard; hide

    2010-01-01

    A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.

  4. TIRCIS: Hyperspectral Thermal Infrared Imaging Using a Small-Satellite Compliant Fourier-Transform Imaging Spectrometer, for Natural Hazard Applications

    Science.gov (United States)

    Wright, R.; Lucey, P. G.; Crites, S.; Garbeil, H.; Wood, M.

    2015-12-01

    Many natural hazards, including wildfires, volcanic eruptions, and, from the perspective of climate-related hazards, urban heat islands, could be better quantified via the routine availability of hyperspectral thermal infrared remote sensing data from orbit. However, no sensors are currently in operation that provide such data at high-to-moderate spatial resolution (e.g. Landsat-class resolution). In this presentation we will describe a prototype instrument, developed using funding provided by NASA's Instrument Incubator Program, that can make these important measurements. Significantly, the instrument has been designed such that its size, mass, power, and cost are consistent with its integration into small satellite platforms, or deployment as part of small satellite constellations. The instrument, TIRCIS (Thermal Infra-Red Compact Imaging Spectrometer), uses a Fabry-Perot interferometer, an uncooled microbolometer array, and push-broom scanning to acquire hyperspectral image data cubes. Radiometric calibration is provided by blackbody targets while spectral calibration is achieved using monochromatic light sources. Neither the focal plane nor the optics need to be cooled, and the instrument has a mass of <10 kg and dimensions of 53 cm × 25 cm × 22 cm. Although the prototype has four moving parts, this can easily be reduced to one. The current 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 90 spectral samples are possible, by varying the physical design of the interferometer. Our performance model indicates signal-to-noise ratios of the order of about 200 to 300:1. In this presentation we will provide an overview of the instrument design, fabrication, results from our initial laboratory characterization, and some of the application areas in which small-satellite-ready instruments such as TIRCIS could make a valuable contribution to the study of natural hazards.

  5. Deep and shallow structures in the Arctic region imaged by satellite magnetic and gravity data

    Science.gov (United States)

    Gaina, Carmen; Panet, Isabelle; Shephard, Grace

    2016-07-01

    , volcanic crust, but, as in the case of other oceanic Large Igneous Provinces, only deep sea drilling will be able to reveal the true nature of the underlying crust at the core of the Arctic. The oldest continental crust, usually found in the cratonic areas and as Proterozoic accreted crust, generates the largest positive magnetic anomalies. This crust contains large and deep volcanic bodies in the North American shield, Greenland, the Baltic shield in Eurasia and the Siberian platform in NE Asia, and are imaged by the satellite data. Furthermore, satellite data is not only restricted to revealing crustal and lithospheric depths. Recent workflows have shown that subducted remnants of ocean basins, now located in the lower mantle, as well as large, antipodal features on the core-mantle boundary, can be imaged by satellite gravity. Seismic tomography provides evidence for an extinct Mesozoic Arctic ocean lying around 1400 km under present-day Greenland. However, the variable resolution of seismic tomography at high latitudes, as well as ambiguity in plate reconstructions, renders the existence of the slab open to interpretation. Critically, the current location of the slab also matches perturbations in long-wavelength gravity gradients, providing further support for a deep density anomaly and a slab origin. Gravity data therefore provides a complementary and independent link in linking surface events and deep mantle structure in frontier regions like the Arctic. By revealing the present-day structure, satellite-derived magnetics and gravity offer a critical component in our understanding of Arctic history, over timescales of millions of years and scales of thousands of kilometers.

  6. Using PACS and wavelet-based image compression in a wide-area network to support radiation therapy imaging applications for satellite hospitals

    Science.gov (United States)

    Smith, Charles L.; Chu, Wei-Kom; Wobig, Randy; Chao, Hong-Yang; Enke, Charles

    1999-07-01

    An ongoing PACS project at our facility has been expanded to include providing and managing images used for routine clinical operation of the department of radiation oncology. The intent of our investigation has been to enable out clinical radiotherapy service to enter the tele-medicine environment through the use of a PACS system initially implemented in the department of radiology. The backbone for the imaging network includes five CT and three MR scanners located across three imaging centers. A PC workstation in the department of radiation oncology was used to transmit CT imags to a satellite facility located approximately 60 miles from the primary center. Chest CT images were used to analyze network transmission performance. Connectivity established between the primary department and satellite has fulfilled all image criteria required by the oncologist. Establishing the link tot eh oncologist at the satellite diminished bottlenecking of imaging related tasks at the primary facility due to physician absence. A 30:1 compression ratio using a wavelet-based algorithm provided clinically acceptable images treatment planning. Clinical radiotherapy images can be effectively managed in a wide- area-network to link satellite facilities to larger clinical centers.

  7. New Magnetospheric Substorm Injection Monitor: Image Electron Spectrometer On Board a Chinese Navigation IGSO Satellite

    Science.gov (United States)

    Zong, Qiugang; Wang, Yongfu; Zou, Hong; Wang, Linghua; Rankin, Robert; Zhang, Xiaoxin

    2018-02-01

    Substorm injections are one of the most dynamic processes in Earth's magnetosphere and have global consequences and broad implications for space weather modeling. They can be monitored using energetic electron detectors on geosynchronous satellites. The Imaging Electron Spectrometer (IES) on board a Chinese navigation satellite, launched on 16 October 2015 into an inclined geosynchronous satellite orbit (IGSO), provides the first energetic electron measurement in IGSO orbit to the best of our knowledge. The IES was developed by Peking University and is named hereafter as BD-IES. Using a pin-hole technique, the BD-IES instrument measures 50-600 keV incident electrons in eight energy channels from nine directions covering a range of 180° in polar angle. Data collection by the BD-IES instrument have recently passed the 1 year mark, which reflects a successful milestone for the mission. The innermost and outermost signatures of substorm injection at L 6 and 12 have been observed by the BD-IES with a high L shell spatial coverage, complementary to the existing missions such as the Van Allen Probes that covers the range below L 6. There are another two BD-IES instruments to be installed in the coming Chinese Sun-synchronous and geosynchronous satellites, respectively. Such a configuration will provide a unique opportunity to investigate inward and outward radial propagation of the substorm injection region simultaneously at high and low L shells. It will further elucidate potential mechanisms for the particle energization and transport, two of the most important topics in magnetospheric dynamics.

  8. Satellite Images-Based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles

    Directory of Open Access Journals (Sweden)

    Mehmet Bodur

    2015-12-01

    Full Text Available In this study, a method for the generation of tracking trajectory points, detection and positioning of obstacles in agricultural fields have been presented. Our principal contribution is to produce traceable GPS trajectories for agricultural vehicles to be utilized by path planning algorithms, rather than a new path planning algorithm. The proposed system works with minimal initialization requirements, specifically, a single geographical coordinate entry of an agricultural field. The automation of agricultural plantation requires many aspects to be addressed, many of which have been covered in previous studies. Depending on the type of crop, different agricultural vehicles may be used in the field. However, regardless of their application, they all follow a specified trajectory in the field. This study takes advantage of satellite images for the detection and positioning of obstacles, and the generation of GPS trajectories in the agricultural realm. A set of image processing techniques is applied in Matlab for detection and positioning.

  9. Approaching bathymetry estimation from high resolution multispectral satellite images using a neuro-fuzzy technique

    Science.gov (United States)

    Corucci, Linda; Masini, Andrea; Cococcioni, Marco

    2011-01-01

    This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.

  10. Bandwidth compression of the digitized HDTV images for transmission via satellites

    Science.gov (United States)

    Al-Asmari, A. KH.; Kwatra, S. C.

    1992-01-01

    This paper investigates a subband coding scheme to reduce the transmission bandwidth of the digitized HDTV images. The HDTV signals are decomposed into seven bands. Each band is then independently encoded. The based band is DPCM encoded and the high bands are encoded by using nonuniform Laplacian quantizers with a dead zone. By selecting the dead zone on the basis of energy in the high bands an acceptable image quality is achieved at an average of 45 Mbits/sec (Mbps) rate. This rate is comparable to some very hardware intensive schemes of transform compression or vector quantization proposed in the literature. The subband coding scheme used in this study is considered to be of medium complexity. The 45 Mbps rate is suitable for transmission of HDTV signals via satellites.

  11. Remote microscopy and volumetric imaging on the surface of icy satellites

    Science.gov (United States)

    Soto, Alejandro; Nowicki, Keith; Howett, Carly; Feldkhun, Daniel; Retherford, Kurt D.

    2017-10-01

    With NASA PIDDP support we have applied recent advancements in Fourier-domain microscopy to develop an instrument capable of microscopic imaging from meter-scale distances for use on a planetary lander on the surface of an icy satellite or other planetary bodies. Without moving parts, our instrument projects dynamic patterns of laser light onto a distant target using a lightweight large-aperture reflector, which then collects the light scattered or fluoresced by the target on a fast photon-bucket detector. Using Fourier Transform based techniques, we reconstruct an image from the detected light. The remote microscope has been demonstrated to produce 2D images with better than 15 micron lateral resolution for targets at a distance of 5 meters and is capable of linearly proportionally higher resolution at shorter distances. The remote microscope is also capable of providing three-dimensional (3D) microscopic imaging capabilities, allowing future surface scientists to explore the morphology of microscopic features in surface ices, for example. The instrument enables microscopic in-situ imaging during day or night without the use of a robotic arm, greatly facilitating the surface operations for a lander or rover while expanding the area of investigation near a landing site for improved science targeting. We are developing this remote microscope for in-situ planetary exploration as a collaboration between the Southwest Research Institute, LambdaMetrics, and the University of Colorado.

  12. Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

    Science.gov (United States)

    Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

    2017-12-01

    In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

  13. Quantitative analysis of geomorphic processes using satellite image data at different scales

    Science.gov (United States)

    Williams, R. S., Jr.

    1985-01-01

    When aerial and satellite photographs and images are used in the quantitative analysis of geomorphic processes, either through direct observation of active processes or by analysis of landforms resulting from inferred active or dormant processes, a number of limitations in the use of such data must be considered. Active geomorphic processes work at different scales and rates. Therefore, the capability of imaging an active or dormant process depends primarily on the scale of the process and the spatial-resolution characteristic of the imaging system. Scale is an important factor in recording continuous and discontinuous active geomorphic processes, because what is not recorded will not be considered or even suspected in the analysis of orbital images. If the geomorphic process of landform change caused by the process is less than 200 m in x to y dimension, then it will not be recorded. Although the scale factor is critical, in the recording of discontinuous active geomorphic processes, the repeat interval of orbital-image acquisition of a planetary surface also is a consideration in order to capture a recurring short-lived geomorphic process or to record changes caused by either a continuous or a discontinuous geomorphic process.

  14. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  15. A Novel Algorithm for Satellite Images Fusion Based on Compressed Sensing and PCA

    Directory of Open Access Journals (Sweden)

    Wenkao Yang

    2013-01-01

    Full Text Available This paper studies the image fusion of high-resolution panchromatic image and low-resolution multispectral image. Based on the classic fusion algorithms on remote sensing image fusion, the PCA (principal component analysis transform, and discrete wavelet transform, we carry out in-depth research. The compressed sensing (CS abandons the full sample and shifts the sampling of the signal to sampling information that greatly reduces the potential consumption of traditional signal acquisition and processing. We combine compressed sensing with satellite remote sensing image fusion algorithm and propose an innovative fusion algorithm (CS-FWT-PCA, in which the symmetric fractional B-spline wavelet acts as the sparse base. In the algorithm we use Hama Da matrix as the measurement matrix and SAMP as the reconstruction algorithm and adopt an improved fusion rule based on the local variance. The simulation results show that the CS-FWT-PCA fusion algorithm achieves better fusion effect than the traditional fusion method.

  16. Earth Camp: Exploring Earth Change through the Use of Satellite Images and Scientific Practices

    Science.gov (United States)

    Baldridge, A.; Buxner, S.; Crown, D. A.; Colodner, D.; Orchard, A.; King, B.; Schwartz, K.; Prescott, A.; Prietto, J.; Titcomb, A.

    2014-07-01

    Earth Camp is a NASA-funded program that gives students and teachers opportunities to explore local, regional, and global earth change through a combination of hands-on investigations and the use of satellite images. Each summer, 20 middle school and 20 high school students participate in a two-week leadership program investigating contemporary issues (e.g., changes in river sheds, water quality, and land use management) through hands-on investigations, analyzing remote sensing data, and working with experts. Each year, 20 teachers participate in a year-long professional development program that includes monthly workshops, field investigations on Mt. Lemmon in Tucson, Arizona, and a week-long summer design workshop. Teachers conduct investigations of authentic questions using satellite images and create posters to present results of their study of earth change. In addition, teachers design lesson plans to expand their students' ability to investigate earth change with 21st Century tools. Lessons can be used as classroom exercises or for after-school club programs. Independent evaluation has been an integral part of program development and delivery for all three audiences, enabling the program staff and participants to reflect on and continually improve their practice and learning over the three-year period.

  17. 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.

  18. Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia

    OpenAIRE

    Jan Verbesselt; Achim Zeileis; Martin Herold

    2011-01-01

    Near real-time monitoring of ecosystem disturbances is critical for addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a generic time series based disturbance detection approach by modelling stable historical behaviour to enable detection of a...

  19. Measuring Spatio-temporal Trends in Residential Landscape Irrigation Extent and Rate in Los Angeles, California Using SPOT-5 Satellite Imagery

    OpenAIRE

    Chen, YJ; McFadden, JP; Clarke, KC; Roberts, DA

    2015-01-01

    © 2015, Springer Science+Business Media Dordrecht. Irrigation is a large component of urban water budgets in semi-arid regions and is critical for the management of landscape vegetation and water resources. This is particularly true for Mediterranean climate cities such as Los Angeles, where water availability is limited during dry summers. These interactions were examined by using 10-m resolution satellite imagery and a database of monthly water use records for all residential water customer...

  20. Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    Nina Merkle

    2017-06-01

    Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

  1. Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing

    Science.gov (United States)

    Nag, Sreeja; Hewagama, Tilak; Georgiev, Georgi; Pasquale, Bert; Aslam, Shahid; Gatebe, Charles K.

    2017-01-01

    Multispectral snapshot imagers are capable of producing 2D spatial images with a single exposure at selected, numerous wavelengths using the same camera, therefore operate differently from push broom or whiskbroom imagers. They are payloads of choice in multi-angular, multi-spectral imaging missions that use small satellites flying in controlled formation, to retrieve Earth science measurements dependent on the targets Bidirectional Reflectance-Distribution Function (BRDF). Narrow fields of view are needed to capture images with moderate spatial resolution. This paper quantifies the dependencies of the imagers optical system, spectral elements and camera on the requirements of the formation mission and their impact on performance metrics such as spectral range, swath and signal to noise ratio (SNR). All variables and metrics have been generated from a comprehensive, payload design tool. The baseline optical parameters selected (diameter 7 cm, focal length 10.5 cm, pixel size 20 micron, field of view 1.15 deg) and snapshot imaging technologies are available. The spectral components shortlisted were waveguide spectrometers, acousto-optic tunable filters (AOTF), electronically actuated Fabry-Perot interferometers, and integral field spectrographs. Qualitative evaluation favored AOTFs because of their low weight, small size, and flight heritage. Quantitative analysis showed that waveguide spectrometers perform better in terms of achievable swath (10-90 km) and SNR (greater than 20) for 86 wavebands, but the data volume generated will need very high bandwidth communication to downlink. AOTFs meet the external data volume caps well as the minimum spectral (wavebands) and radiometric (SNR) requirements, therefore are found to be currently feasible in spite of lower swath and SNR.

  2. Grazed grass was estimated via satellite images better then mowed grass

    Science.gov (United States)

    Koncz, Péter; Gubányi, András; Gecse, Bernadett; Tolnai, Márton; Pintér, Krisztina; Kertész, Péter; Fóti, Szilvia; Balogh, János; Nagy, Zoltán

    2017-04-01

    Precise livestock management requires objective alert system about the potential threats of overgrazing and intensive mowing. This kind of system could be based on the estimation of the amount of grazed and mowed biomass by remote sensing of vegetation indices. In our study we used the Normalized Difference Vegetation Index (NDVI) derived from Landsat 7 and 8 satellites to establish a regression between the vegetation index and the biomass (cut from ten, 40× 40 cm plots, during 52 measurement campaigns, 2011-2013) in a semi-arid grassland of Hungary, Bugac. Based on the regression time series of NDVI data were converted into biomass data in case of grazed and mowed areas (2011?2016). Biomass changes, inferred from NDVI data, were compared to the estimated grazed (based on daily dry matter uptake of cattle) and measured mowed (weighted) biomass. We found significant correlation between the NDVI and the total biomass (r2=0.6, pgrazed biomass based on dry matter uptake was in close agreement with the biomass changes inferred from NDVI data (r2=0.42, p=0.11, n=7, RMSE=25.2 g m-2). However, there was no correlation between the biomass of the measured hay and the biomass inferred from NDVI data (r2=0.16, p=0.49, n=5, RMSE=67.4 g m-2). This was most probably due to the fact that mowing is a sudden, while grazing is a prolonged event, hence satellite data are less likely to be available before and after the mowing events (i.e. within days) compared to the grazing periods which usually lasts for months (only 12±2 satellite images were suitable per year). Therefore, NDVI changes are more accurately captured when grazing is observed than when mowing. We concluded that NDVI data from satellite images could be used to estimate the amount of grazed biomass, however to estimate the amount of mowed hay more frequent data coverage would be needed.

  3. An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2018-02-01

    Full Text Available The Chinese GF-3 satellite launched in August 2016 is a Synthetic Aperture Radar (SAR satellite that has the largest number of imaging modes in the world. It achieves a free switch in the spotlight, stripmap, scanSAR, wave, global observation and other imaging modes. In order to further utilize GF-3 SAR images, an automatic and fast image registration procedure needs to be done. In this paper, we propose a novel image registration technique for GF-3 images of different imaging modes. The proposed algorithm consists of two stages: coarse registration and fine registration. In the first stage, we combine an adaptive sampling method with the SAR-SIFT algorithm to efficiently eliminate obvious translation, rotation and scale differences between the reference and sensed images. In the second stage, uniformly-distributed control points are extracted, then the fast normalized cross-correlation of an improved phase congruency model is utilized as a new similarity metric to match the reference image and the coarse-registered image in a local search region. Moreover, a selection strategy is used to remove outliers. Experimental results on several GF-3 SAR images of different imaging modes show that the proposed algorithm gives a robust, efficient and precise registration performance, compared with other state-of-the-art algorithms for SAR image registration.

  4. An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite.

    Science.gov (United States)

    Xiang, Yuming; Wang, Feng; You, Hongjian

    2018-02-24

    The Chinese GF-3 satellite launched in August 2016 is a Synthetic Aperture Radar (SAR) satellite that has the largest number of imaging modes in the world. It achieves a free switch in the spotlight, stripmap, scanSAR, wave, global observation and other imaging modes. In order to further utilize GF-3 SAR images, an automatic and fast image registration procedure needs to be done. In this paper, we propose a novel image registration technique for GF-3 images of different imaging modes. The proposed algorithm consists of two stages: coarse registration and fine registration. In the first stage, we combine an adaptive sampling method with the SAR-SIFT algorithm to efficiently eliminate obvious translation, rotation and scale differences between the reference and sensed images. In the second stage, uniformly-distributed control points are extracted, then the fast normalized cross-correlation of an improved phase congruency model is utilized as a new similarity metric to match the reference image and the coarse-registered image in a local search region. Moreover, a selection strategy is used to remove outliers. Experimental results on several GF-3 SAR images of different imaging modes show that the proposed algorithm gives a robust, efficient and precise registration performance, compared with other state-of-the-art algorithms for SAR image registration.

  5. Neural network multispectral satellite images classification of volcanic ash plumes in a cloudy scenario

    Directory of Open Access Journals (Sweden)

    Matteo Picchiani

    2015-03-01

    Full Text Available This work shows the potential use of neural networks in the characterization of eruptive events monitored by satellite, through fast and automatic classification of multispectral images. The algorithm has been developed for the MODIS instrument and can easily be extended to other similar sensors. Six classes have been defined paying particular attention to image regions that represent the different surfaces that could possibly be found under volcanic ash clouds. Complex cloudy scenarios composed by images collected during the Icelandic eruptions of the Eyjafjallajökull (2010 and Grimsvötn (2011 volcanoes have been considered as test cases. A sensitivity analysis on the MODIS TIR and VIS channels has been performed to optimize the algorithm. The neural network has been trained with the first image of the dataset, while the remaining data have been considered as independent validation sets. Finally, the neural network classifier’s results have been compared with maps classified with several interactive procedures performed in a consolidated operational framework. This comparison shows that the automatic methodology proposed achieves a very promising performance, showing an overall accuracy greater than 84%, for the Eyjafjalla - jökull event, and equal to 74% for the Grimsvötn event. 

  6. Temporal and spatial air quality monitoring using internet protocol camera and LANSAT5 satellite image

    Science.gov (United States)

    Wong, C. J.; Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Chin, T. S.

    2009-05-01

    Atmospheric fine particles with diameter less than 10 micron (PM10) have already become a major public health concern in any part of the world. These particles can be breathed more deeply into the lungs to cause adverse health effects. In order to prevent long exposure to these harmful atmospheric particles, this motivates a growing interest in developing efficient methods of fine particles monitoring. In this study, we proposed that an internet protocol camera and LANDSAT5 satellite image be used to monitor the temporal and spatial air quality. We developed an algorithm to converts multispectral image pixel values acquired from digital images into quantitative values of the concentrations of PM10. This algorithm was developed based on the regression analysis of relationship between the measured reflectance and the reflected components from a surface material and the ambient air. The computed PM10 values were compared to other standard values measured by a DustTrak meter. The correlation results showed that the newly develop algorithm produced a high degree of accuracy as indicated by high correlation coefficient (R2) and low root-mean-square-error (RMS). This study indicates that the temporal and spatial development of air quality can be monitored by using internet protocol camera and LANDSAT5 images.

  7. 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.

  8. Global thermochemical imaging of the lithosphere using satellite and terrestrial observations

    Science.gov (United States)

    Fullea, Javier; Lebedev, Sergei; Martinec, Zdenek; Celli, Nicolas

    2017-04-01

    Conventional methods of seismic tomography, topography, gravity and electromagnetic data analysis and geodynamic modelling constrain distributions of seismic velocity, density, electrical conductivity, and viscosity at depth, all depending on temperature and composition of the rocks within the Earth. However, modelling and interpretation of multiple data sets provide a multifaceted image of the true thermochemical structure of the Earth that needs to be appropriately and consistently integrated. A simple combination of gravity, electromagnetic, geodynamics, petrological and seismic models alone is insufficient due to the non-uniqueness and different sensitivities of these models, and the internal consistency relationships that must connect all the intermediate parameters describing the Earth involved. Thermodynamic and petrological links between seismic velocities, density, electrical conductivity, viscosity, melt, water, temperature, pressure and composition within the Earth can now be modelled accurately using new methods of computational petrology and data from laboratory experiments. The growth of very large terrestrial and satellite (e.g., Swarm and GOCE ESA missions) geophysical data sets over the last few years, together with the advancement of petrological and geophysical modelling techniques, now present an opportunity for global, thermochemical and deformation 3D imaging of the lithosphere and underlying upper mantle with unprecedented resolution. This project combines state-of-the-art seismic waveform tomography (using both surface and body waves), newly available global gravity satellite data (geoid and gravity anomalies and new gradiometric measurements from ESA's GOCE mission) and surface heat flow and elevation within a self-consistent thermodynamic framework. The aim is to develop a method for detailed and robust global thermochemical image of the lithosphere and underlying upper mantle. In a preliminary study, we convert a state-of-the-art global

  9. A prototype method for diagnosing high ice water content probability using satellite imager data

    Directory of Open Access Journals (Sweden)

    C. R. Yost

    2018-03-01

    Full Text Available Recent studies have found that ingestion of high mass concentrations of ice particles in regions of deep convective storms, with radar reflectivity considered safe for aircraft penetration, can adversely impact aircraft engine performance. Previous aviation industry studies have used the term high ice water content (HIWC to define such conditions. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO satellite imager data coupled with in situ total water content (TWC observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: (1 the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, (2 tropopause-relative infrared brightness temperature, and (3 daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite–aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC  ≥  0.5 g m−3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution

  10. Estimate of the effect of micro-vibration on the performance of the Algerian satellite (Alsat-1B) imager

    Science.gov (United States)

    Serief, Chahira

    2017-11-01

    Alsat-1B, launched into a 670 km sun-synchronous orbit on board the PSLV launch vehicle from the Sriharikota launch site in India on 26 September 2016, is a medium resolution Earth Observation satellite with a mass of 100 kg. Alsat-1B will be used for agricultural and resource monitoring, disaster management, land use mapping and urban planning. It is based on the SSTL-100 platform, and flies a 24 m multispectral imager and a 12 m panchromatic imager delivering images with a swath width of 140 km. One of the main factors affecting the performance of satellite-borne optical imaging systems is micro-vibration. Micro-vibration is a low level mechanical disturbance inevitably generated from moving parts on a satellite and exceptionally difficult to be controlled by the attitude and orbital control system (AOCS) of a spacecraft. Micro-vibration usually causes problems for optical imaging systems onboard Earth Observation satellites. The major effect of micro-vibration is the excitation of the support structures for the optical elements during imaging operations which can result in severe degradation of image quality by smearing and distortion. Quantitative characterization of image degradation caused by micro-vibration is thus quite useful and important as part of system level analysis which can help preventing micro-vibration influence by proper design and restoring the degraded image. The aim of this work is to provide quantitative estimates of the effect of micro-vibration on the performance of Alsat-1B imager, which may be experienced operationally, in terms of the modulation transfer function (MTF) and based on ground micro-vibration tests results.

  11. Detecting long-term changes to vegetation in northern Canada using the Landsat satellite image archive

    International Nuclear Information System (INIS)

    Fraser, R H; Olthof, I; Carrière, M; Deschamps, A; Pouliot, D

    2011-01-01

    Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM + satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1–25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.

  12. Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

    Science.gov (United States)

    Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.

    2015-03-01

    Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.

  13. Combining high-resolution satellite images and altimetry to estimate the volume of small lakes

    Science.gov (United States)

    Baup, F.; Frappart, F.; Maubant, J.

    2014-05-01

    This study presents an approach to determining the volume of water in small lakes (manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches (HRBV and ABV) are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2ABV = 0.98, RMSEABV = 5%, R2HRBV = 0.90, and RMSEABV = 7.4%), assuming a time-varying triangular shape for the shore slope of the lake (this form is well adapted since it implies a difference inferior to 2% between the theoretical volume of the lake and the one estimated from bathymetry). The third method (AHRBVC) combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2AHRBVC = 0.98) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.

  14. THE ANALYSIS OF MOISTURE DEFICIT BASED ON MODIS AND LANDSAT SATELLITE IMAGES. CASE STUDY: THE OLTENIA PLAIN

    Directory of Open Access Journals (Sweden)

    ONȚEL IRINA

    2014-03-01

    Full Text Available Satellite images are an important source of information to identify and analyse some hazardous climatic phenomena such as the dryness and drought. These phenomena are characterized by scarce rainfall, increased evapotranspiration and high soil moisture deficit. The soil water reserve depletes to the wilting coefficient, soon followed by the pedological drought which has negative effects on vegetation and agricultural productivity. The MODIS satellite images (Moderate Resolution Imaging Spectroradiometer allow the monitoring of the vegetation throughout the entire vegetative period, with a frequency of 1-2 days and with a spatial resolution of 250 m, 500 m and 1 km away. Another useful source of information is the LANDSAT satellite images, with a spatial resolution of 30 m. Based on MODIS and Landsat satellite images, were calculated moisture monitoring index such as SIWSI (Shortwave Infrared Water Stress Index. Consequently, some years with low moisture such as 2000, 2002, 2007 and 2012 could be identified. Spatially, the areas with moisture deficit varied from one year to another all over the whole analised period (2000-2012. The remote sensing results was corelated with Standard Precipitation Anomaly, which gives a measure of the severity of a wet or dry event.

  15. Vegetation classification and quatification by satellite image processing. A case study in north Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Aranha, J.T. [Dept. Florestal, UTAD, 5001-801 Vila Real (Portugal); Viana, H.F. [Instituto Politecnico de Viseu, Escola Superior Agraria, Viseu (Portugal); Rodrigues, R. [Bioflag - Consulting - Santo Tirso (Portugal)

    2008-07-01

    The expected increase in Forest Biomass demand for energy production leads to derive expeditious and non-expensive techniques in order to classify vegetal land cover and evaluate the available biomass like to be harvested. Satellite image processing and classification, combined to field work, is a suitable tool to achieve these aims. A vegetation index (NDVI) was created by means of a Landsat TM image, from 2006, manipulation, in order to create a general vegetation map. Then, the same image was submitted to a supervised classification process in order to produce a land cover map (overall accuracy of 85%). In a second stage, they were collected NDVI values for each sampling plot, in order to update the database previous developed with data collected within forestry stands and shrubland. This data merging enabled to transform general vegetation map into available biomass within forestry stands and shrubland. The results showed a range of values from 0.25 up to 6.00 dry ton./ha for recent and former burnt areas recovered by Pinus pinaster (maritime pine) young trees and from 2.00 up to 9.00 dry ton./ha for recent and former burnt areas recovered by shrubs (e.g. genista or broom).

  16. TREND ASSESSMENT OF SPATIO-TEMPORAL CHANGE OF TEHRAN HEAT ISLAND USING SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. R. Saradjian

    2015-12-01

    Full Text Available Numerous investigations on Urban Heat Island (UHI show that land cover change is the main factor of increasing Land Surface Temperature (LST in urban areas, especially conversion of vegetation and bare soil to concrete, asphalt and other man-made structures. On the other hand, other human activities like those which cause to burning fossil fuels, that increase the amount of carbon dioxide, may raise temperature in global scale in comparison with small scales (urban areas. In this study, multiple satellite images with different spatial and temporal resolutions have been used to determine Land Surface Temperature (LST variability in Tehran metropolitan area. High temporal resolution of AVHRR images have been used as the main data source when investigating temperature variability in the urban area. The analysis shows that UHI appears more significant at afternoon and night hours. But the urban class temperature is almost equal to its surrounding vegetation and bare soil classes at around noon. It also reveals that there is no specific difference in UHI intense during the days throughout the year. However, it can be concluded that in the process of city expansion in years, UHI has been grown both spatially and in magnitude. In order to locate land-cover types and relate them to LST, Thematic Mapper (TM images have been exploited. The influence of elevation on the LST has also been studied, using digital elevation model derived from SRTM database.

  17. Extracting oil palm crown from WorldView-2 satellite image

    Science.gov (United States)

    Korom, A.; Phua, M.-H.; Hirata, Y.; Matsuura, T.

    2014-02-01

    Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1').

  18. Extracting oil palm crown from WorldView-2 satellite image

    International Nuclear Information System (INIS)

    Korom, A; Phua, M-H; Hirata, Y; Matsuura, T

    2014-01-01

    Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1')

  19. Real time deforestation detection using ann and satellite images the Amazon rainforest study case

    CERN Document Server

    Nunes Kehl, Thiago; Roberto Veronez, Maurício; Cesar Cazella, Silvio

    2015-01-01

    The foremost aim of the present study was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks. The developed tool provides parameterization of the configuration for the neural network training to enable us to select the best neural architecture to address the problem. The tool makes use of confusion matrices to determine the degree of success of the network. A spectrum-temporal analysis of the study area was done on 57 images from May 20 to July 15, 2003 using the trained neural network. The analysis enabled verification of quality of the implemented neural network classification and also aided in understanding the dynamics of deforestation in the Amazon rainforest, thereby highlighting the vast potential of neural networks for image classification. However, the complex task of detection of predatory actions at the beginning, i.e., generation of consistent alarms, instead of false alarms has not bee...

  20. Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

    Science.gov (United States)

    Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

    2018-03-01

    The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

  1. Target Matching Recognition for Satellite Images Based on the Improved FREAK Algorithm

    Directory of Open Access Journals (Sweden)

    Yantong Chen

    2016-01-01

    Full Text Available Satellite remote sensing image target matching recognition exhibits poor robustness and accuracy because of the unfit feature extractor and large data quantity. To address this problem, we propose a new feature extraction algorithm for fast target matching recognition that comprises an improved feature from accelerated segment test (FAST feature detector and a binary fast retina key point (FREAK feature descriptor. To improve robustness, we extend the FAST feature detector by applying scale space theory and then transform the feature vector acquired by the FREAK descriptor from decimal into binary. We reduce the quantity of data in the computer and improve matching accuracy by using the binary space. Simulation test results show that our algorithm outperforms other relevant methods in terms of robustness and accuracy.

  2. DEM GENERATION FROM HIGH RESOLUTION SATELLITE IMAGES THROUGH A NEW 3D LEAST SQUARES MATCHING ALGORITHM

    Directory of Open Access Journals (Sweden)

    T. Kim

    2012-09-01

    Full Text Available Automated generation of digital elevation models (DEMs from high resolution satellite images (HRSIs has been an active research topic for many years. However, stereo matching of HRSIs, in particular based on image-space search, is still difficult due to occlusions and building facades within them. Object-space matching schemes, proposed to overcome these problem, often are very time consuming and critical to the dimensions of voxels. In this paper, we tried a new least square matching (LSM algorithm that works in a 3D object space. The algorithm starts with an initial height value on one location of the object space. From this 3D point, the left and right image points are projected. The true height is calculated by iterative least squares estimation based on the grey level differences between the left and right patches centred on the projected left and right points. We tested the 3D LSM to the Worldview images over 'Terrassa Sud' provided by the ISPRS WG I/4. We also compared the performance of the 3D LSM with the correlation matching based on 2D image space and the correlation matching based on 3D object space. The accuracy of the DEM from each method was analysed against the ground truth. Test results showed that 3D LSM offers more accurate DEMs over the conventional matching algorithms. Results also showed that 3D LSM is sensitive to the accuracy of initial height value to start the estimation. We combined the 3D COM and 3D LSM for accurate and robust DEM generation from HRSIs. The major contribution of this paper is that we proposed and validated that LSM can be applied to object space and that the combination of 3D correlation and 3D LSM can be a good solution for automated DEM generation from HRSIs.

  3. A configurable distributed high-performance computing framework for satellite's TDI-CCD imaging simulation

    Science.gov (United States)

    Xue, Bo; Mao, Bingjing; Chen, Xiaomei; Ni, Guoqiang

    2010-11-01

    This paper renders a configurable distributed high performance computing(HPC) framework for TDI-CCD imaging simulation. It uses strategy pattern to adapt multi-algorithms. Thus, this framework help to decrease the simulation time with low expense. Imaging simulation for TDI-CCD mounted on satellite contains four processes: 1) atmosphere leads degradation, 2) optical system leads degradation, 3) electronic system of TDI-CCD leads degradation and re-sampling process, 4) data integration. Process 1) to 3) utilize diversity data-intensity algorithms such as FFT, convolution and LaGrange Interpol etc., which requires powerful CPU. Even uses Intel Xeon X5550 processor, regular series process method takes more than 30 hours for a simulation whose result image size is 1500 * 1462. With literature study, there isn't any mature distributing HPC framework in this field. Here we developed a distribute computing framework for TDI-CCD imaging simulation, which is based on WCF[1], uses Client/Server (C/S) layer and invokes the free CPU resources in LAN. The server pushes the process 1) to 3) tasks to those free computing capacity. Ultimately we rendered the HPC in low cost. In the computing experiment with 4 symmetric nodes and 1 server , this framework reduced about 74% simulation time. Adding more asymmetric nodes to the computing network, the time decreased namely. In conclusion, this framework could provide unlimited computation capacity in condition that the network and task management server are affordable. And this is the brand new HPC solution for TDI-CCD imaging simulation and similar applications.

  4. Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images

    Directory of Open Access Journals (Sweden)

    Sriram Ganapathi Subramanian

    2018-04-01

    Full Text Available Machine learning algorithms have increased tremendously in power in recent years but have yet to be fully utilized in many ecology and sustainable resource management domains such as wildlife reserve design, forest fire management, and invasive species spread. One thing these domains have in common is that they contain dynamics that can be characterized as a spatially spreading process (SSP, which requires many parameters to be set precisely to model the dynamics, spread rates, and directional biases of the elements which are spreading. We present related work in artificial intelligence and machine learning for SSP sustainability domains including forest wildfire prediction. We then introduce a novel approach for learning in SSP domains using reinforcement learning (RL where fire is the agent at any cell in the landscape and the set of actions the fire can take from a location at any point in time includes spreading north, south, east, or west or not spreading. This approach inverts the usual RL setup since the dynamics of the corresponding Markov Decision Process (MDP is a known function for immediate wildfire spread. Meanwhile, we learn an agent policy for a predictive model of the dynamics of a complex spatial process. Rewards are provided for correctly classifying which cells are on fire or not compared with satellite and other related data. We examine the behavior of five RL algorithms on this problem: value iteration, policy iteration, Q-learning, Monte Carlo Tree Search, and Asynchronous Advantage Actor-Critic (A3C. We compare to a Gaussian process-based supervised learning approach and also discuss the relation of our approach to manually constructed, state-of-the-art methods from forest wildfire modeling. We validate our approach with satellite image data of two massive wildfire events in Northern Alberta, Canada; the Fort McMurray fire of 2016 and the Richardson fire of 2011. The results show that we can learn predictive, agent

  5. Development of a Lyman-α Imaging Solar Telescope for the Satellite

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    M. Jang

    2005-09-01

    Full Text Available Long term observations of full-disk Lyman-α irradiance have been made by the instruments on various satellites. In addition, several sounding rockets dating back to the 1950s and up through the present have measured the Lyman-α irradiance. Previous full disk Lyman-α images of the sun have been very interesting and useful scientifically, but have been only five-minute ``snapshots" obtained on sounding rocket flights. All of these observations to date have been snapshots, with no time resolution to observe changes in the chromospheric structure as a result of the evolving magnetic field, and its effect on the Lyman-α intensity. The Lyman-α Imaging Solar Telescope(LIST can provide a unique opportunity for the study of the sun in the Lyman-α region with the high time and spatial resolution for the first time. Up to the 2nd year development, the preliminary design of the optics, mechanical structure and electronics system has been completed. Also the mechanical structure analysis, thermal analysis were performed and the material for the structure was chosen as a result of these analyses. And the test plan and the verification matrix were decided. The operation systems, technical and scientific operation, were studied and finally decided. Those are the technical operation, mechanical working modes for the observation and safety, the scientific operation and the process of the acquired data. The basic techniques acquired through the development of satellite based solar telescope are essential for the construction of space environment forecast system in the future. The techniques which we developed through this study, like mechanical, optical and data processing techniques, could be applied extensively not only to the process of the future production of flight models of this kind, but also to the related industries. Also, we can utilize the scientific achievements which are obtained throughout the project. And these can be utilized to build a high

  6. Application of satellite images analysis to assess the variability of the surface thermal heat island distribution in urban areas

    Directory of Open Access Journals (Sweden)

    Fudała Janina

    2018-01-01

    Full Text Available One of the elements of the urban plans for adapting to climate change is to identify the range the urban heat island (UHI. To a relatively rare ground station network air temperature, one of the possible methods to identify this phenomenon in cities is the analysis of satellite images, and in particular the thermal images surface cities in conjunction with the land-use structure. In the publication is presented the application of indirect methods of determining surface characteristics of heat island in the cities of Upper Silesia Agglomeration on the basis of the analysis of the thermal images from the satellite Landsat for the period 1986-2016. It presents ways to interpret these images depending on the needs of determination the areas sensitive to the impact of the (UHI and define the areas where adaptation actions to the climate change should be undertaken.

  7. Application of satellite images analysis to assess the variability of the surface thermal heat island distribution in urban areas

    Science.gov (United States)

    Fudała, Janina; Nádudvari, Ádám; Bronder, Joachim; Fudała, Marta

    2018-01-01

    One of the elements of the urban plans for adapting to climate change is to identify the range the urban heat island (UHI). To a relatively rare ground station network air temperature, one of the possible methods to identify this phenomenon in cities is the analysis of satellite images, and in particular the thermal images surface cities in conjunction with the land-use structure. In the publication is presented the application of indirect methods of determining surface characteristics of heat island in the cities of Upper Silesia Agglomeration on the basis of the analysis of the thermal images from the satellite Landsat for the period 1986-2016. It presents ways to interpret these images depending on the needs of determination the areas sensitive to the impact of the (UHI) and define the areas where adaptation actions to the climate change should be undertaken.

  8. A Feasibility Study of Sea Ice Motion and Deformation Measurements Using Multi-Sensor High-Resolution Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    Chang-Uk Hyun

    2017-09-01

    Full Text Available Sea ice motion and deformation have generally been measured using low-resolution passive microwave or mid-resolution radar remote sensing datasets of daily (or few days intervals to monitor long-term trends over a wide polar area. This feasibility study presents an application of high-resolution optical images from operational satellites, which have become more available in polar regions, for sea ice motion and deformation measurements. The sea ice motion, i.e., Lagrangian vector, is measured by using a maximum cross-correlation (MCC technique and multi-temporal high-resolution images acquired on 14–15 August 2014 from multiple spaceborne sensors on board Korea Multi-Purpose Satellites (KOMPSATs with short acquisition time intervals. The sea ice motion extracted from the six image pairs of the spatial resolutions were resampled to 4 m and 15 m yields with vector length measurements of 57.7 m root mean square error (RMSE and −11.4 m bias and 60.7 m RMSE and −13.5 m bias, respectively, compared with buoy location records. The errors from both resolutions indicate more accurate measurements than from conventional sea ice motion datasets from passive microwave and radar data in ice and water mixed surface conditions. In the results of sea ice deformation caused by interaction of individual ice floes, while free drift patterns of ice floes were delineated from the 4 m spatial resolution images, the deformation was less revealing in the 15 m spatial resolution image pairs due to emphasized discretization uncertainty from coarser pixel sizes. The results demonstrate that using multi-temporal high-resolution optical satellite images enabled precise image block matching in the melting season, thus this approach could be used for expanding sea ice motion and deformation dataset, with an advantage of frequent image acquisition capability in multiple areas by means of many operational satellites.

  9. Mongolian spots

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    Divya Gupta

    2013-01-01

    Full Text Available Mongolian spots (MS are birthmarks that are present at birth and their most common location is sacrococcygeal or lumbar area. Lesions may be single or multiple and usually involve < 5% total body surface area. They are macular and round, oval or irregular in shape. The color varies from blue to greenish, gray, black or a combination of any of the above. The size varies from few to more than 20 centimetres. Pigmentation is most intense at the age of one year and gradually fades thereafter. It is rarely seen after the age of 6 years. Aberrant MS over occiput, temple, mandibular area, shoulders and limbs may be confused with other dermal melanocytoses and bruises secondary to child abuse, thus necessitating documentation at birth. Although regarded as benign, recent data suggest that MS may be associated with inborn errors of metabolism and neurocristopathies. Mongolian spots usually resolve by early childhood and hence no treatment is generally needed if they are located in the sacral area. However, sometimes it may be required for extrasacral lesions for cosmesis.

  10. SU-F-I-11: Software Development for 4D-CBCT Research of Real-Time-Image Gated Spot Scanning Proton Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Fujii, T; Fujii, Y; Shimizu, S; Shirato, H [Graduate School of Medicine, Hokkaido University, Sapporo, Hokkaido (Japan); Matsuura, T; Umegaki, K [Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido (Japan); Takao, S; Miyamoto, N; Matsuzaki, Y [Proton Beam Therapy Center, Hokkaido University Hospital, Sapporo, Hokkaido (Japan)

    2016-06-15

    Purpose: To acquire correct information for inside the body in patient positioning of Real-time-image Gated spot scanning Proton Therapy (RGPT), utilization of tomographic image at exhale phase of patient respiration obtained from 4-dimensional Cone beam CT (4D-CBCT) has been desired. We developed software named “Image Analysis Platform” for 4D-CBCT researches which has technique to segment projection-images based on 3D marker position in the body. The 3D marker position can be obtained by using two axes CBCT system at Hokkaido University Hospital Proton Therapy Center. Performance verification of the software was implemented. Methods: The software calculates 3D marker position retrospectively by using matching positions on pair projection-images obtained by two axes fluoroscopy mode of CBCT system. Log data of 3D marker tracking are outputted after the tracking. By linking the Log data and gantry-angle file of projection-image, all projection-images are equally segmented to spatial five-phases according to marker 3D position of SI direction and saved to specified phase folder. Segmented projection-images are used for CBCT reconstruction of each phase. As performance verification of the software, test of segmented projection-images was implemented for sample CT phantom (Catphan) image acquired by two axes fluoroscopy mode of CBCT. Dummy marker was added on the images. Motion of the marker was modeled to move in 3D space. Motion type of marker is sin4 wave function has amplitude 10.0 mm/5.0 mm/0 mm, cycle 4 s/4 s/0 s for SI/AP/RL direction. Results: The marker was tracked within 0.58 mm accuracy in 3D for all images, and it was confirmed that all projection-images were segmented and saved to each phase folder correctly. Conclusion: We developed software for 4D-CBCT research which can segment projection-image based on 3D marker position. It will be helpful to create high quality of 4D-CBCT reconstruction image for RGPT.

  11. Mapping of Polar Areas Based on High-Resolution Satellite Images: The Example of the Henryk Arctowski Polish Antarctic Station

    Science.gov (United States)

    Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

    2017-12-01

    To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.

  12. Is this Red Spot the Blue Spot (locus ceruleum)?

    Energy Technology Data Exchange (ETDEWEB)

    Choe, Won Sick; Lee, Yu Kyung; Lee, Min Kyung; Hwang, Kyung Hoon [Gachon University Gil Hospital, Incheon (Korea, Republic of)

    2010-06-15

    The authors report brain images of 18F-FDG-PET in a case of schizophrenia. The images showed strikingly increased bilateral uptake in the locus ceruleum. The locus ceruleum is called the blue spot and known to be a center of the norepinephrinergic system.

  13. Detection of change in vegetation in the surrounding Desert areas of Northwest China and Mongolia with multi-temporal satellite images

    Science.gov (United States)

    Han, Kyung-Soo; Park, Youn-Young; Yeom, Jong-Min

    2015-05-01

    Vegetation monitoring is an important step in developing a better understanding of land use and its changes, due to the sensitivity of surface vegetation to changes in the global climate and environment. In this study, normalized difference vegetation index (NDVI) of the area surrounding the Gobi Desert in North Asia was multi-temporally interpreted by analyzing time-series Satellite Pour l'Observation de la Terre (SPOT) Vegetation (VGT) data, over a roughly nine-year period from January 1999 to November 2007. The study area was classified into eight classes, and compared to classified Moderate resolution Imaging Spectrometer (MODIS) global land-cover data to select desertification-sensitive areas. The study focused on three classes (barren land, open shrubland, grassland) due to their high sensitivity to climate change. The results showed significant extension of the barren land class from 1992 to 1999, with 47.8% of the open shrubland transformed into barren land. Among five terms (1999-2003, 2003-2005, 2005-2007, 1999-2005, 1999-2007) which are carefully selected from variations of the annual NDVI mean for each class over nine years, significant changes were observed for barren land from 1999-2003, and for open shrubland and grassland from 2005-2007. An analysis of the positive change (the change from sparse vegetation to dense vegetation) and negative change (or desertification) was conducted over the study period; the number of pixels corresponding to a positive change for barren land was similar to the number of negative change pixels. Human activity and afforestation over the study area were also captured in multitemporal satellite imagery. For open shrubland and grassland, the negative change area was bigger than the positive change area. Precipitation data over the nine-year period exhibited a pattern similar to that for the vegetation data, as expected.

  14. Imaging Spectroscopy Techniques for Rapid Assessment of Geologic and Cryospheric Science Data from future Satellite Sensors

    Science.gov (United States)

    Calvin, W. M.; Hill, R.

    2016-12-01

    Several efforts are currently underway to develop and launch the next generation of imaging spectrometer systems on satellite platforms for a wide range of Earth Observation goals. Systems that include the reflected solar wavelength range up to 2.5 μm will be capable of detailed mapping of the composition of the Earth's surface. Sensors under development include EnMAP, HISUI, PRISMA, HERO, and HyspIRI. These systems are expected to be able to provide global data for insights and constraints on fundamental geological processes, natural and anthropogenic hazards, water, energy and mineral resource assessments. Coupled with the development of these sensors is the challenge of bringing a multi-channel user community (from Landsat, MODIS, and ASTER) into the rich science return available from imaging spectrometer systems. Most data end users will never be spectroscopy experts so that making the derived science products accessible to a wide user community is imperative. Simple band parameterizations have been developed for the CRISM instrument at Mars, including mafic and alteration minerals, frost and volatile ice indices. These products enhance and augment the use of that data set by broader group of scientists. Summary products for terrestrial geologic and water resource applications would help build a wider user base for future satellite systems, and rapidly key spectral experts to important regions for detailed spectral mapping. Summary products take advantage of imaging spectroscopy's narrow spectral channels with band depth calculations in addition to band ratios that are commonly used by multi-channel systems (e.g. NDVI, NDWI, NDSI). We are testing summary products for Earth geologic and snow scenes over California using AVIRIS data at 18m/pixel. This has resulted in several algorithms for rapid mineral discrimination and mapping and data collects over the melting Sierra snowpack in spring 2016 are expected to generate algorithms for snow grain size and surface

  15. Satellite-based ET estimation using Landsat 8 images and SEBAL model

    Directory of Open Access Journals (Sweden)

    Bruno Bonemberger da Silva

    Full Text Available ABSTRACT Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Paraná, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.

  16. NASA sea ice validation program for the Defense Meteorological Satellite Program special sensor microwave imager

    Science.gov (United States)

    Cavalieri, Donald J.

    1991-01-01

    Attention is given to the prime objective of the NASA validation program, namely, to establish quantitative relationships between the sea ice parameters derived from the special sensor microwave imager (SSM/I) using an algorithm originally developed for the Nimbus 7 SMMR. The underlying philosophy of the validation program is that confidence in the SSM/I algorithm products is achieved not so much by detailed comparison with localized surface observations as by consistency with independent spatially and temporally coincident data sets. The results of the satellite and aircraft comparisons that serve as the basis for the validation of the NASA SSMI/I sea ice algorithm are presented. High-resolution radiometer and C-band SAR imagery from the March 1988 NASA and Navy SSM/I underflights are used to verify the location of the ice edge and to validate the sea ice concentrations as determined by the SSM/I algorithm. These studies are argued to provide the most comprehensive measure to date of the accuracy of sea ice products derived from a spaceborne multichannel microwave imager.

  17. Effective System for Automatic Bundle Block Adjustment and Ortho Image Generation from Multi Sensor Satellite Imagery

    Science.gov (United States)

    Akilan, A.; Nagasubramanian, V.; Chaudhry, A.; Reddy, D. Rajesh; Sudheer Reddy, D.; Usha Devi, R.; Tirupati, T.; Radhadevi, P. V.; Varadan, G.

    2014-11-01

    Block Adjustment is a technique for large area mapping for images obtained from different remote sensingsatellites.The challenge in this process is to handle huge number of satellite imageries from different sources with different resolution and accuracies at the system level. This paper explains a system with various tools and techniques to effectively handle the end-to-end chain in large area mapping and production with good level of automation and the provisions for intuitive analysis of final results in 3D and 2D environment. In addition, the interface for using open source ortho and DEM references viz., ETM, SRTM etc. and displaying ESRI shapes for the image foot-prints are explained. Rigorous theory, mathematical modelling, workflow automation and sophisticated software engineering tools are included to ensure high photogrammetric accuracy and productivity. Major building blocks like Georeferencing, Geo-capturing and Geo-Modelling tools included in the block adjustment solution are explained in this paper. To provide optimal bundle block adjustment solution with high precision results, the system has been optimized in many stages to exploit the full utilization of hardware resources. The robustness of the system is ensured by handling failure in automatic procedure and saving the process state in every stage for subsequent restoration from the point of interruption. The results obtained from various stages of the system are presented in the paper.

  18. Foodstuff survey around a major nuclear facility with test of satellite images application

    International Nuclear Information System (INIS)

    Twining, S.; Strydom, J.; Rosson, R.; Koffman, L.; Fledderman, P.; Kahn, B.

    2000-01-01

    A foodstuff survey was performed around the Savannah River Site, Aiken, South Carolina. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of the Savannah River Site center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined by the usual process of applying county agricultural statistics reported by state agencies. This process was compared to crop analysis of two LANDSAT Thematic Mapper images. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the site and by 16-km distance intervals from 16 km to 80 km. The median areas per section devoted to each of four food crops based on county agricultural statistics were about two-thirds of those based on satellite image analysis. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption

  19. Impact of large field angles on the requirements for deformable mirror in imaging satellites

    Science.gov (United States)

    Kim, Jae Jun; Mueller, Mark; Martinez, Ty; Agrawal, Brij

    2018-04-01

    For certain imaging satellite missions, a large aperture with wide field-of-view is needed. In order to achieve diffraction limited performance, the mirror surface Root Mean Square (RMS) error has to be less than 0.05 waves. In the case of visible light, it has to be less than 30 nm. This requirement is difficult to meet as the large aperture will need to be segmented in order to fit inside a launch vehicle shroud. To reduce this requirement and to compensate for the residual wavefront error, Micro-Electro-Mechanical System (MEMS) deformable mirrors can be considered in the aft optics of the optical system. MEMS deformable mirrors are affordable and consume low power, but are small in size. Due to the major reduction in pupil size for the deformable mirror, the effective field angle is magnified by the diameter ratio of the primary and deformable mirror. For wide field of view imaging, the required deformable mirror correction is field angle dependant, impacting the required parameters of a deformable mirror such as size, number of actuators, and actuator stroke. In this paper, a representative telescope and deformable mirror system model is developed and the deformable mirror correction is simulated to study the impact of the large field angles in correcting a wavefront error using a deformable mirror in the aft optics.

  20. An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring

    Directory of Open Access Journals (Sweden)

    Marjan Alirezaie

    2017-11-01

    Full Text Available This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

  1. Flash Flood Hazard Mapping Using Satellite Images and GIS Tools: A case study of Najran City, Kingdom of Saudi Arabia (KSA

    Directory of Open Access Journals (Sweden)

    Ismail Elkhrachy

    2015-12-01

    Full Text Available Flash flood in the cities led to high levels of water in the streets and roads, causing many problems such as bridge collapse, building damage and traffic problems. It is impossible to avoid risks of floods or prevent their occurrence, however it is plausible to work on the reduction of their effects and to reduce the losses which they may cause. Flash flood mapping to identify sites in high risk flood zones is one of the powerful tools for this purpose. Mapping flash flood will be beneficial to urban and infrastructure planners, risk managers and disaster response or emergency services during extreme and intense rainfall events. The objective of this paper is to generate flash flood map for Najran city, Saudi Arabia, using satellite images and GIS tools. To do so, we use SPOT and SRTM DEMs data for which accuracy assessment is achieved by using check points, obtained by GPS observations. Analytical Hierarchical Process (AHP is used to determine relative impact weight of flood causative factors to get a composite flood hazard index (FHI. The causative factors in this study are runoff, soil type, surface slope, surface roughness, drainage density, distance to main channel and land use. All used data are finally integrated in an ArcMap to prepare a final flood hazard map for study area. The areas in high risk flood zones are obtained by overlaying the flood hazard index map with the zone boundaries layer. The affected population number and land area are determined and compared.

  2. 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

  3. Modelling patterns of pollinator species richness and diversity using satellite image texture.

    Science.gov (United States)

    Hofmann, Sylvia; Everaars, Jeroen; Schweiger, Oliver; Frenzel, Mark; Bannehr, Lutz; Cord, Anna F

    2017-01-01

    Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

  4. Modelling patterns of pollinator species richness and diversity using satellite image texture

    Science.gov (United States)

    Everaars, Jeroen; Schweiger, Oliver; Frenzel, Mark; Bannehr, Lutz; Cord, Anna F.

    2017-01-01

    Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010–2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3–5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity. PMID:28973006

  5. Modelling patterns of pollinator species richness and diversity using satellite image texture.

    Directory of Open Access Journals (Sweden)

    Sylvia Hofmann

    Full Text Available Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013 from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees. While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

  6. Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO

    Science.gov (United States)

    Choi, Michael

    2013-01-01

    An imager or sounder on satellites, such as the Geostationary Operational Environmental Satellite (GOES), in geostationary orbit (GEO) has a scan mirror and motor in the scan cavity. The GEO orbit is 24 hours long. During part of the orbit, direct sunlight enters the scan aperture and adds heat to components in the scan cavity. Solar heating also increases the scan motor temperature. Overheating of the scan motor could reduce its reliability. For GOES-N to P, a radiator with a thermal louver rejects the solar heat absorbed to keep the scan cavity cool. A sunshield shields the radiator/louver from the Sun. This innovation uses phase change material (PCM) in the scan cavity to maintain the temperature stability of the scan mirror and motor. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the scan cavity warm. It reduces the heater power required to make up the heat lost by radiation to space through the aperture. This is a major advantage when compared to a radiator/ louver. PCM is compact because it has a high solid-to-liquid enthalpy. Also, it could be spread out in the scan cavity. This is another advantage. Paraffin wax is a good PCM candidate, with high solid-to-liquid enthalpy, which is about 225 kJ/kg. For GOES-N to P, a radiator with a louver rejects the solar heat that enters the aperture to keep the scan cavity cool. For the remainder of the orbit, sunlight does not enter the scan aperture. However, the radiator/louver continues radiating heat to space because the louver effective emittance is about 0.12, even if the louver is fully closed. This requires makeup heater power to maintain the temperature within the stability range.

  7. Field survey report and satellite image interpretation of the 2013 Super Typhoon Haiyan in the Philippines

    Science.gov (United States)

    Mas, E.; Bricker, J.; Kure, S.; Adriano, B.; Yi, C.; Suppasri, A.; Koshimura, S.

    2015-04-01

    Three weeks after the deadly Bohol earthquake of Mw 7.2, which claimed at least 222 victims, another disaster struck the Philippines. This time, Super Typhoon Haiyan, also known as Typhoon Yolanda in the Philippines, devastated the Eastern Visayas islands on 8 November 2013. Its classification as a super typhoon was based on its maximum sustained 1 min surface wind speed of 315 km h-1, which is equivalent to a strong Category 5 hurricane on the Saffir-Simpson scale. This was one of the deadliest typhoon events in the Philippines' history, after the 1897 and 1912 tropical cyclones. At least 6268 individuals have been reported dead and 1061 people are missing. In addition, a wide area of destruction was observed in the Eastern Visayas, on Samar and Leyte islands. The International Research Institute of Disaster Science (IRIDeS) at Tohoku University in Sendai, Japan, has deployed several teams for damage recognition, relief support and collaboration with regard to this disaster event. One of the teams, the hazard and damage evaluation team, visited the affected areas in the Eastern Visayas in mid-January 2014. In this paper, we summarize the rapid damage assessment from satellite imagery conducted days after the event and report on the inundation measurements and the damage surveyed in the field. Damage interpretation results by satellite images were qualitatively confirmed for the Tacloban city area on Leyte Island, the most populated city in the Eastern Visayas. During the survey, significant damage was observed from wind and storm surges on poorly designed housing on the east coast of Leyte Island. Damage, mainly from surface waves and winds, was observed on the east coast of Samar Island.

  8. Automated Recognition of Vegetation and Water Bodies on the Territory of Megacities in Satellite Images of Visible and IR Bands

    Science.gov (United States)

    Mozgovoy, Dmitry k.; Hnatushenko, Volodymyr V.; Vasyliev, Volodymyr V.

    2018-04-01

    Vegetation and water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. A methodology of automated recognition of vegetation and water bodies on the territory of megacities in satellite images of sub-meter spatial resolution of the visible and IR bands is proposed. By processing multispectral images from the satellite SuperView-1A, vector layers of recognized plant and water objects were obtained. Analysis of the results of image processing showed a sufficiently high accuracy of the delineation of the boundaries of recognized objects and a good separation of classes. The developed methodology provides a significant increase of the efficiency and reliability of updating maps of large cities while reducing financial costs. Due to the high degree of automation, the proposed methodology can be implemented in the form of a geo-information web service functioning in the interests of a wide range of public services and commercial institutions.

  9. Applying Support Vector Machine in classifying satellite images for the assessment of urban sprawl

    Science.gov (United States)

    murgante, Beniamino; Nolè, Gabriele; Lasaponara, Rosa; Lanorte, Antonio; Calamita, Giuseppe

    2013-04-01

    In last decades the spreading of new buildings, road infrastructures and a scattered proliferation of houses in zones outside urban areas, produced a countryside urbanization with no rules, consuming soils and impoverishing the landscape. Such a phenomenon generated a huge environmental impact, diseconomies and a decrease in life quality. This study analyzes processes concerning land use change, paying particular attention to urban sprawl phenomenon. The application is based on the integration of Geographic Information Systems and Remote Sensing adopting open source technologies. The objective is to understand size distribution and dynamic expansion of urban areas in order to define a methodology useful to both identify and monitor the phenomenon. In order to classify "urban" pixels, over time monitoring of settlements spread, understanding trends of artificial territories, classifications of satellite images at different dates have been realized. In order to obtain these classifications, supervised classification algorithms have been adopted. More particularly, Support Vector Machine (SVM) learning algorithm has been applied to multispectral remote data. One of the more interesting features in SVM is the possibility to obtain good results also adopting few classification pixels of training areas. SVM has several interesting features, such as the capacity to obtain good results also adopting few classification pixels of training areas, a high possibility of configuration parameters and the ability to discriminate pixels with similar spectral responses. Multi-temporal ASTER satellite data at medium resolution have been adopted because are very suitable in evaluating such phenomena. The application is based on the integration of Geographic Information Systems and Remote Sensing technologies by means of open source software. Tools adopted in managing and processing data are GRASS GIS, Quantum GIS and R statistical project. The area of interest is located south of Bari

  10. PRELIMINARY RESULTS OF THE COMPARISON OF SATELLITE IMAGERS USING TUZ GÖLÜ AS A REFERENCE STANDARD

    Directory of Open Access Journals (Sweden)

    H. Özen

    2012-07-01

    Full Text Available Earth surfaces, such as deserts, salt lakes, and playas, have been widely used in the vicarious radiometric calibration of optical earth observation satellites. In 2009, the Infrared and Visible Optical Sensors (IVOS sub-group of the Committee of Earth Observation Satellites (CEOS Working Group on Calibration and Validation (WGCV designated eight LANDNET reference sites to focus international efforts, facilitate traceability and enable the establishment of measurement "best practices." With support from the European Space Agency (ESA, one of the LANDNET sites, the Tuz Gölü salt lake located in central Turkey, was selected to host a cross-comparison of measurement instrumentation and methodologies conducted by 11 different ground teams across the globe. This paper provides an overview of the preliminary results of the cross-comparison of the ground-based spectral measurements made during the CEOS Land Comparison 13-27 August, 2010 with the simultaneous satellite image data acquisitions of the same site.

  11. Mapping urban impervious surface using object-based image analysis with WorldView-3 satellite imagery

    Science.gov (United States)

    Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

    2017-10-01

    Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.

  12. OBJECT-ORIENTED ANALYSIS OF SATELLITE IMAGES USING ARTIFICIAL NEURAL NETWORKS FOR POST-EARTHQUAKE BUILDINGS CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    N. Khodaverdi zahraee

    2017-09-01

    Full Text Available Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged area, the amount and type of damage can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. The purpose of this paper is to propose and implement an automatic approach for mapping destructed buildings after an earthquake using pre- and post-event high resolution satellite images. In the proposed method after preprocessing, segmentation of both images is performed using multi-resolution segmentation technique. Then, the segmentation results are intersected with ArcGIS to obtain equal image objects on both images. After that, appropriate textural features, which make a better difference between changed or unchanged areas, are calculated for all the image objects. Finally, subtracting the extracted textural features from pre- and post-event images, obtained values are applied as an input feature vector in an artificial neural network for classifying the area into two classes of changed and unchanged areas. The proposed method was evaluated using WorldView2 satellite images, acquired before and after the 2010 Haiti earthquake. The reported overall accuracy of 93% proved the ability of the proposed method for post-earthquake buildings change detection.

  13. Object-Oriented Analysis of Satellite Images Using Artificial Neural Networks for Post-Earthquake Buildings Change Detection

    Science.gov (United States)

    Khodaverdi zahraee, N.; Rastiveis, H.

    2017-09-01

    Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged area, the amount and type of damage can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. The purpose of this paper is to propose and implement an automatic approach for mapping destructed buildings after an earthquake using pre- and post-event high resolution satellite images. In the proposed method after preprocessing, segmentation of both images is performed using multi-resolution segmentation technique. Then, the segmentation results are intersected with ArcGIS to obtain equal image objects on both images. After that, appropriate textural features, which make a better difference between changed or unchanged areas, are calculated for all the image objects. Finally, subtracting the extracted textural features from pre- and post-event images, obtained values are applied as an input feature vector in an artificial neural network for classifying the area into two classes of changed and unchanged areas. The proposed method was evaluated using WorldView2 satellite images, acquired before and after the 2010 Haiti earthquake. The reported overall accuracy of 93% proved the ability of the proposed method for post-earthquake buildings change detection.

  14. Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

    Science.gov (United States)

    Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

    2017-12-01

    The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

  15. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

    Science.gov (United States)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

    2016-04-01

    Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

  16. Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

    Science.gov (United States)

    Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

    2017-10-01

    Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Hierarchical semantic cognition for urban functional zones with VHR satellite images and POI data

    Science.gov (United States)

    Zhang, Xiuyuan; Du, Shihong; Wang, Qiao

    2017-10-01

    As the basic units of urban areas, functional zones are essential for city planning and management, but functional-zone maps are hardly available in most cities, as traditional urban investigations focus mainly on land-cover objects instead of functional zones. As a result, an automatic/semi-automatic method for mapping urban functional zones is highly required. Hierarchical semantic cognition (HSC) is presented in this study, and serves as a general cognition structure for recognizing urban functional zones. Unlike traditional classification methods, the HSC relies on geographic cognition and considers four semantic layers, i.e., visual features, object categories, spatial object patterns, and zone functions, as well as their hierarchical relations. Here, we used HSC to classify functional zones in Beijing with a very-high-resolution (VHR) satellite image and point-of-interest (POI) data. Experimental results indicate that this method can produce more accurate results than Support Vector Machine (SVM) and Latent Dirichlet Allocation (LDA) with a larger overall accuracy of 90.8%. Additionally, the contributions of diverse semantic layers are quantified: the object-category layer is the most important and makes 54% contribution to functional-zone classification; while, other semantic layers are less important but their contributions cannot be ignored. Consequently, the presented HSC is effective in classifying urban functional zones, and can further support urban planning and management.

  18. Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.J.

    2000-01-03

    Sandia National Laboratories (SNL), Los Alamos National Laboratory (LANL), and the Savannah River Technology Center (SRTC) have developed a diverse group of algorithms for processing and analyzing the data that will be collected by the Multispectral Thermal Imager (MTI) after launch late in 1999. Each of these algorithms must be verified by comparison to independent surface and atmospheric measurements. SRTC has selected 13 sites in the continental U.S. for ground truth data collections. These sites include a high altitude cold water target (Crater Lake), cooling lakes and towers in the warm, humid southeastern US, Department of Energy (DOE) climate research sites, the NASA Stennis satellite Validation and Verification (V and V) target array, waste sites at the Savannah River Site, mining sites in the Four Corners area and dry lake beds in the southwestern US. SRTC has established mutually beneficial relationships with the organizations that manage these sites to make use of their operating and research data and to install additional instrumentation needed for MTI algorithm V and V.

  19. Bottom Topographic Changes of Poyang Lake During Past Decade Using Multi-temporal Satellite Images

    Science.gov (United States)

    Zhang, S.

    2015-12-01

    Poyang Lake, as a well-known international wetland in the Ramsar Convention List, is the largest freshwater lake in China. It plays crucial ecological role in flood storage and biological diversity. Poyang Lake is facing increasingly serious water crises, including seasonal dry-up, decreased wetland area, and water resource shortage, all of which are closely related to progressive bottom topographic changes over recent years. Time-series of bottom topography would contribute to our understanding of the lake's evolution during the past several decades. However, commonly used methods for mapping bottom topography fail to frequently update quality bathymetric data for Poyang Lake restricted by weather and accessibility. These deficiencies have limited our ability to characterize the bottom topographic changes and understanding lake erosion or deposition trend. To fill the gap, we construct a decadal bottom topography of Poyang Lake with a total of 146 time series medium resolution satellite images based on the Waterline Method. It was found that Poyang Lake has eroded with a rate of -14.4 cm/ yr from 2000 to 2010. The erosion trend was attributed to the impacts of human activities, especially the operation of the Three Gorge Dams, sand excavation, and the implementation of water conservancy project. A decadal quantitative understanding bottom topography of Poyang Lake might provide a foundation to model the lake evolutionary processes and assist both researchers and local policymakers in ecological management, wetland protection and lake navigation safety.

  20. Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images

    Directory of Open Access Journals (Sweden)

    Xiuyuan Zhang

    2018-02-01

    Full Text Available Urban functional zones, such as commercial, residential, and industrial zones, are basic units of urban planning, and play an important role in monitoring urbanization. However, historical functional-zone maps are rarely available for cities in developing countries, as traditional urban investigations focus on geographic objects rather than functional zones. Recent studies have sought to extract functional zones automatically from very-high-resolution (VHR satellite images, and they mainly concentrate on classification techniques, but ignore zone segmentation which delineates functional-zone boundaries and is fundamental to functional-zone analysis. To resolve the issue, this study presents a novel segmentation method, geoscene segmentation, which can identify functional zones at multiple scales by aggregating diverse urban objects considering their features and spatial patterns. In experiments, we applied this method to three Chinese cities—Beijing, Putian, and Zhuhai—and generated detailed functional-zone maps with diverse functional categories. These experimental results indicate our method effectively delineates urban functional zones with VHR imagery; different categories of functional zones extracted by using different scale parameters; and spatial patterns that are more important than the features of individual objects in extracting functional zones. Accordingly, the presented multiscale geoscene segmentation method is important for urban-functional-zone analysis, and can provide valuable data for city planners.

  1. A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing

    Directory of Open Access Journals (Sweden)

    Thomas Udelhoven

    2017-07-01

    Full Text Available This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping. The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1–5 days at off-nadir. At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month. To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1 a hyperspectral TIR system with ~75 bands at 7.2–12.5 µm (instrument NEDT 0.05 K–0.1 K and a ground sampling distance (GSD of 60 m, and (2 a panchromatic high-resolution TIR-imager with two channels (8.0–10.25 µm and 10.25–12.5 µm and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1–3 days to combine data from the visible and near infrared (VNIR, the shortwave infrared (SWIR and TIR spectral regions and to refine parameter retrieval.

  2. Time-domain Astronomy with the Advanced X-ray Imaging Satellite

    Science.gov (United States)

    Winter, Lisa M.; Vestrand, Tom; Smith, Karl; Kippen, Marc; Schirato, Richard

    2018-01-01

    The Advanced X-ray Imaging Satellite (AXIS) is a concept NASA Probe class mission that will enable time-domain X-ray observations after the conclusion of the successful Swift Gamma-ray burst mission. AXIS will achieve rapid response, like Swift, with an improved X-ray monitoring capability through high angular resolution (similar to the 0.5 arc sec resolution of the Chandra X-ray Observatory) and high sensitivity (ten times the Chandra count rate) observations in the 0.3-10 keV band. In the up-coming decades, AXIS’s fast slew rate will provide the only rapid X-ray capability to study explosive transient events. Increased ground-based monitoring with next-generation survey telescopes like the Large Synoptic Survey Telescope will provide a revolution in transient science through the discovery of many new known and unknown phenomena – requiring AXIS follow-ups to establish the highest energy emission from these events. This synergy between AXIS and ground-based detections will constrain the rapid rise through decline in energetic emission from numerous transients including: supernova shock breakout winds, gamma-ray burst X-ray afterglows, ionized gas resulting from the activation of a hidden massive black hole in tidal disruption events, and intense flares from magnetic reconnection processes in stellar coronae. Additionally, the combination of high sensitivity and angular resolution will allow deeper and more precise monitoring for prompt X-ray signatures associated with gravitational wave detections. We present a summary of time-domain science with AXIS, highlighting its capabilities and expected scientific gains from rapid high quality X-ray imaging of transient phenomena.

  3. A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing.

    Science.gov (United States)

    Udelhoven, Thomas; Schlerf, Martin; Segl, Karl; Mallick, Kaniska; Bossung, Christian; Retzlaff, Rebecca; Rock, Gilles; Fischer, Peter; Müller, Andreas; Storch, Tobias; Eisele, Andreas; Weise, Dennis; Hupfer, Werner; Knigge, Thiemo

    2017-07-01

    This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1-5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2-12.5 µm (instrument NEDT 0.05 K-0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0-10.25 µm and 10.25-12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1-3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval.

  4. A Novel Approach for Forecasting Crop Production and Yield Using Remotely Sensed Satellite Images

    Science.gov (United States)

    Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.

    2017-12-01

    Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.

  5. Relasphone—Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping

    Directory of Open Access Journals (Sweden)

    Matthieu Molinier

    2016-10-01

    Full Text Available Due to the high cost of traditional forest plot measurements, the availability of up-to-date in situ forest inventory data has been a bottleneck for remote sensing image analysis in support of the important global forest biomass mapping. Capitalizing on the proliferation of smartphones, citizen science is a promising approach to increase spatial and temporal coverages of in situ forest observations in a cost-effective way. Digital cameras can be used as a relascope device to measure basal area, a forest density variable that is closely related to biomass. In this paper, we present the Relasphone mobile application with extensive accuracy assessment in two mixed forest sites from different biomes. Basal area measurements in Finland (boreal zone were in good agreement with reference forest inventory plot data on pine ( R 2 = 0 . 75 , R M S E = 5 . 33 m 2 /ha, spruce ( R 2 = 0 . 75 , R M S E = 6 . 73 m 2 /ha and birch ( R 2 = 0 . 71 , R M S E = 4 . 98 m 2 /ha, with total relative R M S E ( % = 29 . 66 % . In Durango, Mexico (temperate zone, Relasphone stem volume measurements were best for pine ( R 2 = 0 . 88 , R M S E = 32 . 46 m 3 /ha and total stem volume ( R 2 = 0 . 87 , R M S E = 35 . 21 m 3 /ha. Relasphone data were then successfully utilized as the only reference data in combination with optical satellite images to produce biomass maps. The Relasphone concept has been validated for future use by citizens in other locations.

  6. 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

  7. Research on earth observing satellite segmenting and scheduling problem for area targets

    Science.gov (United States)

    He, Renjie; Ruan, Qiming

    2005-10-01

    The mission of an Earth Observing Satellite (EOS) is to acquire images of specified areas on the Earth surface, in response to observation requests from customers for strategic, environmental, commercial, agricultural, and civil analysis and research. A target imaged can have one out of two shapes: a spot and a large polygonal area. A spot can be covered by a single scene of satellite sensor, while a polygonal area may require cutting-up into several contiguous strips to be completely imaged. Because of the orbit restriction, satellite can only view target during specific windows of opportunity when flying over the target. Furthermore, the satellite can only be tasked during such access time windows. Hence a scheduling method of satellite observing tasks has to be taken into account for utilizing satellite sensor efficiently. This paper intends to solve a specific segmenting and scheduling problem for area targets, which concerned with an optical observing satellite equipped with line array CCD sensor. In the paper, based on the analysis of characters of satellite sensor and observed area target, a new method of segmenting area target is given. And on the basis of segmenting results of area target, a scheduling model for multi area targets is proposed. In the paper end, experimental results and analysis are also presented.

  8. New concepts in molecular imaging: non-invasive MRI spotting of proteolysis using an Overhauser effect switch.

    Directory of Open Access Journals (Sweden)

    Philippe Mellet

    Full Text Available Proteolysis, involved in many processes in living organisms, is tightly regulated in space and time under physiological conditions. However deregulation can occur with local persistent proteolytic activities, e.g. in inflammation, cystic fibrosis, tumors, or pancreatitis. Furthermore, little is known about the role of many proteases, hence there is a need of new imaging methods to visualize specifically normal or disease-related proteolysis in intact bodies.In this paper, a new concept for non invasive proteolysis imaging is proposed. Overhauser-enhanced Magnetic Resonance Imaging (OMRI at 0.2 Tesla was used to monitor the enzymatic hydrolysis of a nitroxide-labeled protein. In vitro, image intensity switched from 1 to 25 upon proteolysis due to the associated decrease in the motional correlation time of the substrate. The OMRI experimental device used in this study is consistent with protease imaging in mice at 0.2 T without significant heating. Simulations show that this enzymatic-driven OMRI signal switch can be obtained at lower frequencies suitable for larger animals or humans.The method is highly sensitive and makes possible proteolysis imaging in three dimensions with a good spatial resolution. Any protease could be targeted specifically through the use of taylor-made cleavable macromolecules. At short term OMRI of proteolysis may be applied to basic research as well as to evaluate therapeutic treatments in small animal models of experimental diseases.

  9. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    KAUST Repository

    Wang, Teng

    2015-09-05

    Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

  10. Intense equatorial flux spots on the surface of Earth's core

    Science.gov (United States)

    Jackson, A.

    2003-04-01

    A vast number of vector measurements of the Earth's magnetic field have recently become available from the satellite Oersted, currently in orbit monitoring the core magnetic field. In this presentation I will present new maps of the Earth's magnetic field at the surface of the fluid core derived from these satellite data which show intense flux spots in equatorial regions; the images are derived using a maximum entropy technique which is capable of reconstructing images with high dynamic range more precisely than conventional techniques. The intensity of these features is unusually large - they are comparable to high-latitude flux patches near the poles, previously identified as the major component of the dynamo field. A comparison with sunspots is tempting, though they are probably not associated with expulsion of toroidal magnetic field as is the case for the sun. Indeed, the tendency for pairing of these spots to the north and south of the geographical equator suggests they might be associated with the tops of so-called `Taylor columns' (indicative of the dominance of the rotation of the Earth) which have previously been suggested to be associated with the four high-latitude flux patches near the poles. Equatorially-trapped waves are known to exist in theory, and a correct interpretation of these features might lead to constraints on the strength of the hidden toroidal magnetic field within the Earth, as well as constraints on other physical regimes.

  11. Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

    Science.gov (United States)

    Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich

    2017-08-01

    In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

  12. Flood hazard and flood risk assessment using a time series of satellite images: a case study in Namibia.

    Science.gov (United States)

    Skakun, Sergii; Kussul, Nataliia; Shelestov, Andrii; Kussul, Olga

    2014-08-01

    In this article, the use of time series of satellite imagery to flood hazard mapping and flood risk assessment is presented. Flooded areas are extracted from satellite images for the flood-prone territory, and a maximum flood extent image for each flood event is produced. These maps are further fused to determine relative frequency of inundation (RFI). The study shows that RFI values and relative water depth exhibit the same probabilistic distribution, which is confirmed by Kolmogorov-Smirnov test. The produced RFI map can be used as a flood hazard map, especially in cases when flood modeling is complicated by lack of available data and high uncertainties. The derived RFI map is further used for flood risk assessment. Efficiency of the presented approach is demonstrated for the Katima Mulilo region (Namibia). A time series of Landsat-5/7 satellite images acquired from 1989 to 2012 is processed to derive RFI map using the presented approach. The following direct damage categories are considered in the study for flood risk assessment: dwelling units, roads, health facilities, and schools. The produced flood risk map shows that the risk is distributed uniformly all over the region. The cities and villages with the highest risk are identified. The proposed approach has minimum data requirements, and RFI maps can be generated rapidly to assist rescuers and decisionmakers in case of emergencies. On the other hand, limitations include: strong dependence on the available data sets, and limitations in simulations with extrapolated water depth values. © 2013 Society for Risk Analysis.

  13. Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

    International Nuclear Information System (INIS)

    Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.

    2014-01-01

    Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models

  14. GHRSST Level 2P Global Sea Surface Temperature from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Visible and Infrared Imager/Radiometer Suite (VIIRS) is a multi-disciplinary instrument that is being flown on the Joint Polar Satellite System (JPSS) series of...

  15. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 1999 on board the Terra satellite platform (a...

  16. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 2002 on board the Aqua satellite platform (a...

  17. Laurel Clark Earth Camp: A Program for Teachers and Students to Explore Their World and Study Global Change Through Field-Experience and Satellite Images

    Science.gov (United States)

    Buxner, S.; Orchard, A.; Colodner, D.; Schwartz, K.; Crown, D. A.; King, B.; Baldridge, A.

    2012-03-01

    The Laurel Clark Earth Camp program provides middle and high school students and teachers opportunities to explore local environmental issues and global change through field-experiences, inquiry exercises, and exploring satellite images.

  18. Design of a nano-satellite demonstrator of an infrared imaging space interferometer: the HyperCube

    Science.gov (United States)

    Dohlen, Kjetil; Vives, Sébastien; Rakotonimbahy, Eddy; Sarkar, Tanmoy; Tasnim Ava, Tanzila; Baccichet, Nicola; Savini, Giorgio; Swinyard, Bruce

    2014-07-01

    The construction of a kilometer-baseline far infrared imaging interferometer is one of the big instrumental challenges for astronomical instrumentation in the coming decades. Recent proposals such as FIRI, SPIRIT, and PFI illustrate both science cases, from exo-planetary science to study of interstellar media and cosmology, and ideas for construction of such instruments, both in space and on the ground. An interesting option for an imaging multi-aperture interferometer with km baseline is the space-based hyper telescope (HT) where a giant, sparsely populated primary mirror is constituted of several free-flying satellites each carrying a mirror segment. All the segments point the same object and direct their part of the pupil towards a common focus where another satellite, containing recombiner optics and a detector unit, is located. In Labeyrie's [1] original HT concept, perfect phasing of all the segments was assumed, allowing snap-shot imaging within a reduced field of view and coronagraphic extinction of the star. However, for a general purpose observatory, image reconstruction using closure phase a posteriori image reconstruction is possible as long as the pupil is fully non-redundant. Such reconstruction allows for much reduced alignment tolerances, since optical path length control is only required to within several tens of wavelengths, rather than within a fraction of a wavelength. In this paper we present preliminary studies for such an instrument and plans for building a miniature version to be flown on a nano satellite. A design for recombiner optics is proposed, including a scheme for exit pupil re-organization, is proposed, indicating the focal plane satellite in the case of a km-baseline interferometer could be contained within a 1m3 unit. Different options for realization of a miniature version are presented, including instruments for solar observations in the visible and the thermal infrared and giant planet observations in the visible, and an

  19. Winter mass balance of Drangajökull ice cap (NW Iceland derived from satellite sub-meter stereo images

    Directory of Open Access Journals (Sweden)

    J. M. C. Belart

    2017-06-01

    Full Text Available Sub-meter resolution, stereoscopic satellite images allow for the generation of accurate and high-resolution digital elevation models (DEMs over glaciers and ice caps. Here, repeated stereo images of Drangajökull ice cap (NW Iceland from Pléiades and WorldView2 (WV2 are combined with in situ estimates of snow density and densification of firn and fresh snow to provide the first estimates of the glacier-wide geodetic winter mass balance obtained from satellite imagery. Statistics in snow- and ice-free areas reveal similar vertical relative accuracy ( <  0.5 m with and without ground control points (GCPs, demonstrating the capability for measuring seasonal snow accumulation. The calculated winter (14 October 2014 to 22 May 2015 mass balance of Drangajökull was 3.33 ± 0.23 m w.e. (meter water equivalent, with ∼ 60 % of the accumulation occurring by February, which is in good agreement with nearby ground observations. On average, the repeated DEMs yield 22 % less elevation change than the length of eight winter snow cores due to (1 the time difference between in situ and satellite observations, (2 firn densification and (3 elevation changes due to ice dynamics. The contributions of these three factors were of similar magnitude. This study demonstrates that seasonal geodetic mass balance can, in many areas, be estimated from sub-meter resolution satellite stereo images.

  20. Analysis and Assessment of Land Use Change in Alexandria, Egypt Using Satellite Images, GIS, and Modelling Techniques

    International Nuclear Information System (INIS)

    Abdou Azaz, L.K.

    2008-01-01

    Alexandria is the second largest urban governorate in Egypt and has seen significant urban growth in its modern and contemporary history. This study investigates the urban growth phenomenon in Alexandria, Egypt, using the integration of remote sensing and GIS. The urban physical expansion and change were detected using Landsat satellite images. The satellite images of years 1984 and 1993 were first geo referenced, achieving a very small RMSE that provided high accuracy data for satellite image analysis. Then, the images were classified using a tailored classification scheme with accuracy of 93.82% and 95.27% for 1984 and 1993 images respectively. This high accuracy enabled detecting land use/land cover changes with high confidence using a post-classification comparison method. One of the most important findings here is the loss of cultivated land in favour of urban expansion. If the current loss rates continued, 75% of green lands would be lost by year 2191. These hazardous rates call for an urban growth management policy that can preserve such valuable resources to achieve sustainable urban development. Modelling techniques can help in defining the scenarios of urban growth. In this study, the SLEUTH urban growth model was applied to predict future urban expansion in Alexandria until the year 2055. The application of this model in Alexandria of Egypt with its different environmental characteristics is the first application outside USA and Europe. The results revealed that future urban growth would continue along the edges of the current urban extent. This means that the cultivated lands in the east and the southeast of the city will be decreased. To deal with such crisis, there is a serious need for a comprehensive urban growth management programme that can be based on the best practices in similar situations

  1. Northeast Puerto Rico and Culebra Island World View 2 Satellite Mosaic - NOAA TIFF Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a mosaic of World View 2 panchromatic satellite imagery of Northeast Puerto Rico that contains the shallow water area (0-35m deep) surrounding...

  2. Eumetcast receiving station integration withinthe satellite image database interface (SAIDIN) system.

    OpenAIRE

    Chic, Òscar

    2010-01-01

    Within the tasks devoted to operational oceanography, Coastal Ocean Observatory at Institut de Ciències del Mar (CSIC) has acquired an European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Broadcast System for Environmental Data (EUMETCast reception system) to replace a satellite direct broadcast system that receives data via High Resolution Picture Transmission (HRPT). EUMETCast system can receive data based on standard Digital Video Broadcastin...

  3. Automated dust storm detection using satellite images. Development of a computer system for the detection of dust storms from MODIS satellite images and the creation of a new dust storm database

    Science.gov (United States)

    El-Ossta, Esam Elmehde Amar

    Dust storms are one of the natural hazards, which have increased in frequency in the recent years over Sahara desert, Australia, the Arabian Desert, Turkmenistan and northern China, which have worsened during the last decade. Dust storms increase air pollution, impact on urban areas and farms as well as affecting ground and air traffic. They cause damage to human health, reduce the temperature, cause damage to communication facilities, reduce visibility which delays both road and air traffic and impact on both urban and rural areas. Thus, it is important to know the causation, movement and radiation effects of dust storms. The monitoring and forecasting of dust storms is increasing in order to help governments reduce the negative impact of these storms. Satellite remote sensing is the most common method but its use over sandy ground is still limited as the two share similar characteristics. However, satellite remote sensing using true-colour images or estimates of aerosol optical thickness (AOT) and algorithms such as the deep blue algorithm have limitations for identifying dust storms. Many researchers have studied the detection of dust storms during daytime in a number of different regions of the world including China, Australia, America, and North Africa using a variety of satellite data but fewer studies have focused on detecting dust storms at night. The key elements of this present study are to use data from the Moderate Resolution Imaging Spectroradiometers on the Terra and Aqua satellites to develop more effective automated method for detecting dust storms during both day and night and generate a MODIS dust storm database..

  4. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

    Science.gov (United States)

    Osipov, Gennady

    2013-04-01

    We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode

  5. Impact of Real-Time Image Gating on Spot Scanning Proton Therapy for Lung Tumors: A Simulation Study

    Energy Technology Data Exchange (ETDEWEB)

    Kanehira, Takahiro [Department of Radiation Medicine, Graduate School of Medicine, Hokkaido University, Sapporo (Japan); Matsuura, Taeko, E-mail: matsuura@med.hokudai.ac.jp [Proton Beam Therapy Center, Hokkaido University Hospital, Sapporo (Japan); Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo (Japan); Takao, Seishin; Matsuzaki, Yuka; Fujii, Yusuke; Fujii, Takaaki [Proton Beam Therapy Center, Hokkaido University Hospital, Sapporo (Japan); Ito, Yoichi M. [Department of Biostatistics, Hokkaido University Graduate School of Medicine, Sapporo (Japan); Miyamoto, Naoki [Department of Medical Physics, Hokkaido University Hospital, Sapporo (Japan); Inoue, Tetsuya [Department of Radiation Medicine, Graduate School of Medicine, Hokkaido University, Sapporo (Japan); Katoh, Norio [Department of Radiation Oncology, Hokkaido University Hospital, Sapporo (Japan); Shimizu, Shinichi [Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Department of Radiation Oncology, Graduate School of Medicine, Hokkaido University, Sapporo (Japan); Umegaki, Kikuo [Proton Beam Therapy Center, Hokkaido University Hospital, Sapporo (Japan); Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo (Japan); Shirato, Hiroki [Department of Radiation Medicine, Graduate School of Medicine, Hokkaido University, Sapporo (Japan); Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan)

    2017-01-01

    Purpose: To investigate the effectiveness of real-time-image gated proton beam therapy for lung tumors and to establish a suitable size for the gating window (GW). Methods and Materials: A proton beam gated by a fiducial marker entering a preassigned GW (as monitored by 2 fluoroscopy units) was used with 7 lung cancer patients. Seven treatment plans were generated: real-time-image gated proton beam therapy with GW sizes of ±1, 2, 3, 4, 5, and 8 mm and free-breathing proton therapy. The prescribed dose was 70 Gy (relative biological effectiveness)/10 fractions to 99% of the target. Each of the 3-dimensional marker positions in the time series was associated with the appropriate 4-dimensional computed tomography phase. The 4-dimensional dose calculations were performed. The dose distribution in each respiratory phase was deformed into the end-exhale computed tomography image. The D99 and D5 to D95 of the clinical target volume scaled by the prescribed dose with criteria of D99 >95% and D5 to D95 <5%, V20 for the normal lung, and treatment times were evaluated. Results: Gating windows ≤ ±2 mm fulfilled the CTV criteria for all patients (whereas the criteria were not always met for GWs ≥ ±3 mm) and gave an average reduction in V20 of more than 17.2% relative to free-breathing proton therapy (whereas GWs ≥ ±4 mm resulted in similar or increased V20). The average (maximum) irradiation times were 384 seconds (818 seconds) for the ±1-mm GW, but less than 226 seconds (292 seconds) for the ±2-mm GW. The maximum increased considerably at ±1-mm GW. Conclusion: Real-time-image gated proton beam therapy with a GW of ±2 mm was demonstrated to be suitable, providing good dose distribution without greatly extending treatment time.

  6. Aperture synthesis imaging of the carbon AGB star R Sculptoris. Detection of a complex structure and a dominating spot on the stellar disk

    Science.gov (United States)

    Wittkowski, M.; Hofmann, K.-H.; Höfner, S.; Le Bouquin, J. B.; Nowotny, W.; Paladini, C.; Young, J.; Berger, J.-P.; Brunner, M.; de Gregorio-Monsalvo, I.; Eriksson, K.; Hron, J.; Humphreys, E. M. L.; Lindqvist, M.; Maercker, M.; Mohamed, S.; Olofsson, H.; Ramstedt, S.; Weigelt, G.

    2017-05-01

    Aims: We present near-infrared interferometry of the carbon-rich asymptotic giant branch (AGB) star R Sculptoris (R Scl). Methods: We employ medium spectral resolution K-band interferometry obtained with the instrument AMBER at the Very Large Telescope Interferometer (VLTI) and H-band low spectral resolution interferometric imaging observations obtained with the VLTI instrument PIONIER. We compare our data to a recent grid of dynamic atmosphere and wind models. We compare derived fundamental parameters to stellar evolution models. Results: The visibility data indicate a broadly circular resolved stellar disk with a complex substructure. The observed AMBER squared visibility values show drops at the positions of CO and CN bands, indicating that these lines form in extended layers above the photosphere. The AMBER visibility values are best fit by a model without a wind. The PIONIER data are consistent with the same model. We obtain a Rosseland angular diameter of 8.9 ± 0.3 mas, corresponding to a Rosseland radius of 355 ± 55 R⊙, an effective temperature of 2640 ± 80 K, and a luminosity of log L/L⊙ = 3.74 ± 0.18. These parameters match evolutionary tracks of initial mass 1.5 ± 0.5 M⊙ and current mass 1.3 ± 0.7 M⊙. The reconstructed PIONIER images exhibit a complex structure within the stellar disk including a dominant bright spot located at the western part of the stellar disk. The spot has an H-band peak intensity of 40% to 60% above the average intensity of the limb-darkening-corrected stellar disk. The contrast between the minimum and maximum intensity on the stellar disk is about 1:2.5. Conclusions: Our observations are broadly consistent with predictions by dynamic atmosphere and wind models, although models with wind appear to have a circumstellar envelope that is too extended compared to our observations. The detected complex structure within the stellar disk is most likely caused by giant convection cells, resulting in large-scale shock fronts

  7. Image Fusion Applied to Satellite Imagery for the Improved Mapping and Monitoring of Coral Reefs: a Proposal

    Science.gov (United States)

    Gholoum, M.; Bruce, D.; Hazeam, S. Al

    2012-07-01

    A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine the quality of the

  8. Classification of semiurban landscapes from very high-resolution satellite images using a regionalized multiscale segmentation approach

    Science.gov (United States)

    Kavzoglu, Taskin; Erdemir, Merve Yildiz; Tonbul, Hasan

    2017-07-01

    In object-based image analysis, obtaining representative image objects is an important prerequisite for a successful image classification. The major threat is the issue of scale selection due to the complex spatial structure of landscapes portrayed as an image. This study proposes a two-stage approach to conduct regionalized multiscale segmentation. In the first stage, an initial high-level segmentation is applied through a "broadscale," and a set of image objects characterizing natural borders of the landscape features are extracted. Contiguous objects are then merged to create regions by considering their normalized difference vegetation index resemblance. In the second stage, optimal scale values are estimated for the extracted regions, and multiresolution segmentation is applied with these settings. Two satellite images with different spatial and spectral resolutions were utilized to test the effectiveness of the proposed approach and its transferability to different geographical sites. Results were compared to those of image-based single-scale segmentation and it was found that the proposed approach outperformed the single-scale segmentations. Using the proposed methodology, significant improvement in terms of segmentation quality and classification accuracy (up to 5%) was achieved. In addition, the highest classification accuracies were produced using fine-scale values.

  9. Combining satellite and seismic images to analyse the shallow structure of the Dead Sea Transform near the DESERT transect

    Science.gov (United States)

    Kesten, D.; Weber, M.; Haberland, Ch.; Janssen, Ch.; Agnon, A.; Bartov, Y.; Rabba, I.

    2008-02-01

    The left-lateral Dead Sea Transform (DST) in the Middle East is one of the largest continental strike-slip faults of the world. The southern segment of the DST in the Arava/Araba Valley between the Dead Sea and the Red Sea, called Arava/Araba Fault (AF), has been studied in detail in the multidisciplinary DESERT (DEad SEa Rift Transect) project. Based on these results, here, the interpretations of multi-spectral (ASTER) satellite images and seismic reflection studies have been combined to analyse geologic structures. Whereas satellite images reveal neotectonic activity in shallow young sediments, reflection seismic image deep faults that are possibly inactive at present. The combination of the two methods allows putting some age constraint on the activity of individual fault strands. Although the AF is clearly the main active fault segment of the southern DST, we propose that it has accommodated only a limited (up to 60 km) part of the overall 105 km of sinistral plate motion since Miocene times. There is evidence for sinistral displacement along other faults, based on geological studies, including satellite image interpretation. Furthermore, a subsurface fault is revealed ≈4 km west of the AF on two ≈E-W running seismic reflection profiles. Whereas these seismic data show a flower structure typical for strike-slip faults, on the satellite image this fault is not expressed in the post-Miocene sediments, implying that it has been inactive for the last few million years. About 1 km to the east of the AF another, now buried fault, was detected in seismic, magnetotelluric and gravity studies of DESERT. Taking together various evidences, we suggest that at the beginning of transform motion deformation occurred in a rather wide belt, possibly with the reactivation of older ≈N-S striking structures. Later, deformation became concentrated in the region of today’s Arava Valley. Till ≈5 Ma ago there might have been other, now inactive fault traces in the vicinity

  10. Addressing the emerging technology of video image compression over commercially available terrestrial and satellite transmission circuits

    Science.gov (United States)

    Kozlowski, Jerry; Ragsdale, Baxter

    The authors address the use of video communications with commercial telephone and satellite services as a cost-effective means of long-distance problem solving and teletraining for US Government applications. A primary objective of this feasibility study and pilot demonstration is to evaluate various video-compression Codecs, interactive computer technology, and high-resolution graphics transmission equipment working with government encryption devices over multiple 56-kb telephone lines, or ISDN-compatible 64-kb satellite circuits. It is concluded that the use of compressed video imagery, toll quality audio, and high-resolution graphics over multiple 64-kb or 128-kb/s satellite circuits is a proven technology with significant cost advantages over T-1 or 1.5 Mb video circuits as provided on the Defense Commercial Telecommunications Network.

  11. SpotADAPT

    DEFF Research Database (Denmark)

    Kaulakiene, Dalia; Thomsen, Christian; Pedersen, Torben Bach

    2015-01-01

    by Amazon Web Services (AWS). The users aiming for the spot market are presented with many instance types placed in multiple datacenters in the world, and thus it is difficult to choose the optimal deployment. In this paper, we propose the framework SpotADAPT (Spot-Aware (re-)Deployment of Analytical...... execution within boundaries). Moreover, during the execution of the workload, SpotADAPT suggests a redeployment if the current spot instance gets terminated by Amazon or a better deployment becomes possible due to fluctuations of the spot prices. The approach is evaluated using the actual execution times...

  12. An Attempt to automate the lithological classification of rocks using geological, gamma-spectrometric and satellite image datasets

    International Nuclear Information System (INIS)

    Fouad, M. K.; Mielik, M. L.; Gharieb, A. N.

    2004-01-01

    The present study aims essentially at proving that the application of the integrated airborne gamma spectrometric and satellite image data is capable of refining the mapped surface geology, and identification of anomalous zones of radioelement content that could provide favorable exploration targets for radioactive mineralizations.The application of the appropriate statistical technique to correlate between satellite image data and gamma-spectrometric data is of great significance in this respect. Experience shows that Landsat T M data in 7 spectral bands are successfully used in such studies rather than MSS. Multivariate statistical analysis techniques are applied to airborne spectrometric and different spectral Landsat T M data. Reduction of the data from n-dimensionality, both qualitatively as color composite image, and quantitatively, as principal component analysis, is performed using some statistical control parameters. This technique shows distinct efficiency in defining areas where different lit ho facies occur. An area located at the north of the Eastern Desert of Egypt, north of Hurgada town, was chosen to test the proposed technique of integrated interpretation of data of different physical nature. The reduced data are represented and interpreted both qualitatively and quantitatively. The advantages and limitations of applying such technique to the different airborne spectrometric, and Landsat T M data are identified. (authors)

  13. Shoreline change assessment using multi-temporal satellite images: a case study of Lake Sapanca, NW Turkey.

    Science.gov (United States)

    Duru, Umit

    2017-08-01

    The research summarized here determines historical shoreline changes along Lake Sapanca by using Remote Sensing (RS) and Geographical Information Systems (GIS). Six multi-temporal satellite images of Landsat Multispectral Scanner (L1-5 MMS), Enhanced Thematic Mapper Plus (L7 ETM+), and Operational Land Imager Sensors (L8 OLI), covering the period between 17 June 1975 and 15 July 2016, were used to monitor shoreline positions and estimate change rates along the coastal zone. After pre-possessing routines, the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and supervised classification techniques were utilized to extract six different shorelines. Digital Shoreline Analysis System (DSAS), a toolbox that enables transect-based computations of shoreline displacement, was used to compute historical shoreline change rates. The average rate of shoreline change for the entire cost was 2.7 m/year of progradation with an uncertainty of 0.2 m/year. While the great part of the lake shoreline remained stable, the study concluded that the easterly and westerly coasts and deltaic coasts are more vulnerable to shoreline displacements over the last four decades. The study also reveals that anthropogenic activities, more specifically over extraction of freshwater from the lake, cyclic variation in rainfall, and deposition of sediment transported by the surrounding creeks dominantly control spatiotemporal shoreline changes in the region. Monitoring shoreline changes using multi-temporal satellite images is a significant component for the coastal decision-making and management.

  14. MACSAT - A Mini-Satellite Approach to High Resolution Space Imaging

    OpenAIRE

    Kim, Byung-Jin; Park, Sungdong; Kim, Ee-Eul; Chang, Hyon-Sock; Park, Wonkyu; Seon, Jongho; Ismail, Maszlan; Ad-Rasheed, Ad-Aziz; Sabirin-Arshad, Ahmad

    2003-01-01

    To be launched in 2004, MACSAT is a 200kg satellite, designed to provide 2.5m ground sampling distance (GSD) resolution imagery on a near equatorial orbit (NEqO). The mission objective is to demonstrate the capability of a high-resolution remote sensing satellite system on a NEqO. Initi-ated by ATSB, the proprietary NEqO mission has advantages for monitoring the environment of equatorial regions of Malaysia with unique revisit characteristics from the baseline circular orbit of 7 degrees of i...

  15. On the quantitative evaluation of edge detection schemes and their comparison with human performance. [image processing of satellite photographs

    Science.gov (United States)

    Fram, J. R.; Deutsch, E. S.

    1975-01-01

    A technique for the quantitative evaluation of edge detection schemes is presented. It is used to assess the performance of three such schemes using a specially-generated set of images containing noise. The ability of human subjects to distinguish the edges in the presence of noise is also measured and compared with that of the edge detection schemes. The edge detection schemes are used on a high-resolution satellite photograph with varying degrees of noise added in order to relate the quantitative comparison to real-life imagery.

  16. GHRSST Level 2P Eastern Pacific Regional Skin Sea Surface Temperature from the Geostationary Operational Environmental Satellites (GOES) Imager on the GOES-11 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Geostationary Operational Environmental Satellites (GOES) operated by the United States National Oceanic and Atmospheric Administration (NOAA) support weather...

  17. GHRSST Level 2P West Atlantic Regional Skin Sea Surface Temperature from the Geostationary Operational Environmental Satellites (GOES) Imager on the GOES-12 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Geostationary Operational Environmental Satellites (GOES) operated by the United States National Oceanic and Atmospheric Administration (NOAA) support weather...

  18. Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

    Science.gov (United States)

    Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng

    2017-06-20

    The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

  19. A new web-based system for unsupervised classification of satellite images from the Google Maps engine

    Science.gov (United States)

    Ferrán, Ángel; Bernabé, Sergio; García-Rodríguez, Pablo; Plaza, Antonio

    2012-10-01

    In this paper, we develop a new web-based system for unsupervised classification of satellite images available from the Google Maps engine. The system has been developed using the Google Maps API and incorporates functionalities such as unsupervised classification of image portions selected by the user (at the desired zoom level). For this purpose, we use a processing chain made up of the well-known ISODATA and k-means algorithms, followed by spatial post-processing based on majority voting. The system is currently hosted on a high performance server which performs the execution of classification algorithms and returns the obtained classification results in a very efficient way. The previous functionalities are necessary to use efficient techniques for the classification of images and the incorporation of content-based image retrieval (CBIR). Several experimental validation types of the classification results with the proposed system are performed by comparing the classification accuracy of the proposed chain by means of techniques available in the well-known Environment for Visualizing Images (ENVI) software package. The server has access to a cluster of commodity graphics processing units (GPUs), hence in future work we plan to perform the processing in parallel by taking advantage of the cluster.

  20. Accuracy comparison of Pléiades satellite ortho-images using GPS ...

    African Journals Online (AJOL)

    image requires four basic components, namely an image, a geometric sensor model ... Nonetheless, the TerraSAR-X based GCPs still produced a sub 2 m accurate ortho-image, which is more than sufficient for the production of most geospatial ...

  1. Nexus of Health and Development: Modelling Crude Birth Rate and Maternal Mortality Ratio Using Nighttime Satellite Images

    Directory of Open Access Journals (Sweden)

    Koel Roychowdhury

    2014-05-01

    Full Text Available Health and development are intricately related. Although India has made significant progress in the last few decades in the health sector and overall growth in GDP, there are still large regional differences in both health and development. The main objective of this paper is to develop techniques for the prediction of health indicators for all the districts of India and examine the correlations between health and development. The level of electrification and district domestic product (DDP are considered as two fundamental indicators of development in this research. These data, along with health metrics and the information from two nighttime satellite images, were used to propose the models. These successfully predicted the health indicators with less than a 7%–10% error. The chosen health metrics, such as crude birth rate (CBR and maternal mortality rate (MMR, were mapped for the whole country at the district level. These metrics showed very strong correlation with development indicators (correlation coefficients ranging from 0.92 to 0.99 at the 99% confidence interval. This is the first attempt to use Visible Infrared Imaging Radiometer Suite (VIIRS (satellite imagery in a socio-economic study. This paper endorses the observation that areas with a higher DDP and level of electrification have overall better health conditions.

  2. Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

    Directory of Open Access Journals (Sweden)

    Hong Sun

    2013-05-01

    Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

  3. Global Solar radiation in Spain from Satellite Images; Radiacion Solar Global en la Espana Peninsular a partir de images de satelite

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez Santigosa, L.; Mora Lopez, L.; Sidrach de Cardona Ortin, M.; Navarro Fernandez, A. A.; Varela conde, M.; Cruz Echeandia, M. de la

    2003-07-01

    In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been revaluate to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar,impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyranometric measures in a concrete localise, but it provides a very valid indicator in places in which, it not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs.

  4. A Web-based Google-Earth Coincident Imaging Tool for Satellite Calibration and Validation

    Science.gov (United States)

    Killough, B. D.; Chander, G.; Gowda, S.

    2009-12-01

    The Group on Earth Observations (GEO) is coordinating international efforts to build a Global Earth Observation System of Systems (GEOSS) to meet the needs of its nine “Societal Benefit Areas”, of which the most demanding, in terms of accuracy, is climate. To accomplish this vision, satellite on-orbit and ground-based data calibration and validation (Cal/Val) of Earth observation measurements are critical to our scientific understanding of the Earth system. Existing tools supporting space mission Cal/Val are often developed for specific campaigns or events with little desire for broad application. This paper describes a web-based Google-Earth based tool for the calculation of coincident satellite observations with the intention to support a diverse international group of satellite missions to improve data continuity, interoperability and data fusion. The Committee on Earth Observing Satellites (CEOS), which includes 28 space agencies and 20 other national and international organizations, are currently operating and planning over 240 Earth observation satellites in the next 15 years. The technology described here will better enable the use of multiple sensors to promote increased coordination toward a GEOSS. The CEOS Systems Engineering Office (SEO) and the Working Group on Calibration and Validation (WGCV) support the development of the CEOS Visualization Environment (COVE) tool to enhance international coordination of data exchange, mission planning and Cal/Val events. The objective is to develop a simple and intuitive application tool that leverages the capabilities of Google-Earth web to display satellite sensor coverage areas and for the identification of coincident scene locations along with dynamic menus for flexibility and content display. Key features and capabilities include user-defined evaluation periods (start and end dates) and regions of interest (rectangular areas) and multi-user collaboration. Users can select two or more CEOS missions from a

  5. Patch-based image segmentation of satellite imagery using minimum spanning tree construction

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2010-01-01

    We present a method for hierarchical image segmentation and feature extraction. This method builds upon the combination of the detection of image spectral discontinuities using Canny edge detection and the image Laplacian, followed by the construction of a hierarchy of segmented images of successively reduced levels of details. These images are represented as sets of polygonized pixel patches (polygons) attributed with spectral and structural characteristics. This hierarchy forms the basis for object-oriented image analysis. To build fine level-of-detail representation of the original image, seed partitions (polygons) are built upon a triangular mesh composed of irregular sized triangles, whose spatial arrangement is adapted to the image content. This is achieved by building the triangular mesh on the top of the detected spectral discontinuities that form a network of constraints for the Delaunay triangulation. A polygonized image is represented as a spatial network in the form of a graph with vertices which correspond to the polygonal partitions and graph edges reflecting pairwise partitions relations. Image graph partitioning is based on the iterative graph oontraction using Boruvka's Minimum Spanning Tree algorithm. An important characteristic of the approach is that the agglomeration of partitions is constrained by the detected spectral discontinuities; thus the shapes of agglomerated partitions are more likely to correspond to the outlines of real-world objects.

  6. Lake Urmia Shrinkage and its Effect on the Settlement of the Surrounding Areas Investigated Using Radar and Optical Satellite Images

    Science.gov (United States)

    Motagh, M.; Shamshiri, R.; Hosseini, F.; Sharifi, M. A.; Baes, M.

    2014-12-01

    With a total area of more than 50000 km^2 Lake Urmia basin in northwest of Iran was once one of the biggest salt lakes in the world. The lake has been shrinking in the recent years, losing in turn dramatically its area. A lot of factors have been attributed to this shrinking including construction of dams on the rivers feeding the lake and overexploitation of groundwater for agricultural and industrial purposes. In this study we first utilized time-series analysis of Landsat images to precisely quantify surface changes in the region between 1984 and 2013. We then analyzed a number of SAR images from 2002 to 2014 including 30 ASAR images from Envisat, 10 PALSAR images from ALOS, and more than 35 TerraSAR-X (TSX) in both Stripmap and Spot modes to assess surface ground deformation. Ground deformation was evaluated for both agricultural regions around the lake and Lake Urmia Causeway (LUC), connecting two provinces of East and West Azerbaijan on both sides of the lake. The InSAR results of the LUC embankments is further investigated using Finite Element approach to better understand the relation between soil parameters, lake level changes and settlement of the LUC. The classification results using optical imagery analysis show that human and anthropogenic activities have resulted in shrinking of Lake Urmia by more than 60% over the past 30 years. The agricultural areas around the lake are dominated by ground subsidence reaching to 10 cm/yr in places. The LUC embankments also show large deformation with peak settlement of more than 5 cm/yr over the last decade. FEM simulation shows that consolidation due to dissipation of excess pore pressure in embankments can satisfactorily explain its surface deformation.

  7. Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Satellite Based on Machine Learning Approaches

    Directory of Open Access Journals (Sweden)

    Hyangsun Han

    2015-07-01

    Full Text Available As convective clouds in Northeast Asia are accompanied by various hazards related with heavy rainfall and thunderstorms, it is very important to detect convective initiation (CI in the region in order to mitigate damage by such hazards. In this study, a novel approach for CI detection using images from Meteorological Imager (MI, a payload of the Communication, Ocean, and Meteorological Satellite (COMS, was developed by improving the criteria of the interest fields of Rapidly Developing Cumulus Areas (RDCA derivation algorithm, an official CI detection algorithm for Multi-functional Transport SATellite-2 (MTSAT-2, based on three machine learning approaches—decision trees (DT, random forest (RF, and support vector machines (SVM. CI was defined as clouds within a 16 × 16 km window with the first detection of lightning occurrence at the center. A total of nine interest fields derived from visible, water vapor, and two thermal infrared images of MI obtained 15–75 min before the lightning occurrence were used as input variables for CI detection. RF produced slightly higher performance (probability of detection (POD of 75.5% and false alarm rate (FAR of 46.2% than DT (POD of 70.7% and FAR of 46.6% for detection of CI caused by migrating frontal cyclones and unstable atmosphere. SVM resulted in relatively poor performance with very high FAR ~83.3%. The averaged lead times of CI detection based on the DT and RF models were 36.8 and 37.7 min, respectively. This implies that CI over Northeast Asia can be forecasted ~30–45 min in advance using COMS MI data.

  8. Automated invariant alignment to improve canonical variates in image fusion of satellite and weather radar data

    DEFF Research Database (Denmark)

    Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg

    2013-01-01

    data sets, was observed, corrupting the subspace. A method for aligning the two data sets is proposed, in order to overcome this issue and render a useful subspace projection. The observed corruption of the subspace gives rise to the hypothesis that the optimal correspondence, between a heavily...... precipitation for optimal correspondence with the satellite data at the same time. This optimization is repeated for an increasing temporal lag until no further improvement can be found. The method is applied to three meteorological events having caused heavy precipitation in Denmark. The three cases...

  9. Artificial intelligence for networks recognition in remote sensing images

    Science.gov (United States)

    Gilliot, Jean-Marc; Amat, Jean-Louis

    1993-12-01

    We describe here a knowledge-based system, NEXSYS (Nextwork EXtraction SYStem) which was designed for the recognition of communication networks in SPOT satellite images. NEXSYS is a frame-based system and uses a co-operative and distributed structure based on a blackboard architecture. Communication networks in SPOT images are composed of thin linear segments. Segments are extracted using mathematical morphology and a Hough transform. An intermediate image representation composed of geometric primitives is obtained. Then an expert module is able to process the segments at the symbolic level trying to recognize networks.

  10. Use of Meteorological Satellite Images (DMSP) as an Environmental policy tool

    Science.gov (United States)

    Petrakis, M.; Psiloglou, B.; Lianou, M.; Chalkias, C.; Akylas, E.

    2003-04-01

    Night light emissions that originate mainly from great urban areas are among the main forms of environmental pollution (night light pollution). Also night light pollution has adverse effects on flora and fauna as disrupts day-night rhythms as well as animals' nervous and harmonic system. At the same time, as night light emissions data reflect mainly on human activities, can be used as a policy tool with a suitable time-spatial correlation coupled with different financial and energy data. In the present study techniques for the processing and correlation of night light emission data from DMSP satellite with the various financial and population data are developed in a Geographical Information System (GIS). After the photometric analysis of evening photos and their incorporation into an integrated GIS (which typically includes various geographic variables as population density, energy consumption, land use, road network data, topography etc.), the research is focused in development of correlation models, between RS data and related variables. Furthermore, the creation of correlation indices was investigated that could proved extremely useful to policy making for different activities, at areas where a limited amount of data is available. The present study was developed within the framework of the MANTLE Project (Mapping Night-time Light Emissions in the EU using satellite-observed visible-near infrared emissions as a policy tool) supported by the European Commission.

  11. Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

    Directory of Open Access Journals (Sweden)

    Meng Lu

    2017-10-01

    Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

  12. Development of thunderstorm monitoring technologies and algorithms by integration of radar, sensors, and satellite images

    Science.gov (United States)

    Adzhieva, Aida A.; Shapovalov, Vitaliy A.; Boldyreff, Anton S.

    2017-10-01

    In the context of rising the frequency of natural disasters and catastrophes humanity has to develop methods and tools to ensure safe living conditions. Effectiveness of preventive measures greatly depends on quality and lead time of the forecast of disastrous natural phenomena, which is based on the amount of knowledge about natural hazards, their causes, manifestations, and impact. To prevent them it is necessary to get complete and comprehensive information about the extent of spread and severity of natural processes that can act within a defined territory. For these purposes the High Mountain Geophysical Institute developed the automated workplace for mining, analysis and archiving of radar, satellite, lightning sensors information and terrestrial (automatic weather station) weather data. The combination and aggregation of data from different sources of meteorological data provides a more informativity of the system. Satellite data shows the global cloud region in visible and infrared ranges, but have an uncertainty in terms of weather events and large time interval between the two periods of measurements, which complicates the use of this information for very short range forecasts of weather phenomena. Radar and lightning sensors data provide the detection of weather phenomena and their localization on the background of the global pattern of cloudiness in the region and have a low period measurement of atmospheric phenomena (hail, thunderstorms, showers, squalls, tornadoes). The authors have developed the improved algorithms for recognition of dangerous weather phenomena, based on the complex analysis of incoming information using the mathematical apparatus of pattern recognition.

  13. A comparison between ERS-1, JERS-1, and Radarsat-1 radar satellite imaging systems and Landsat MSS & TM and Spot Optical Satellite Imaging System to detect and monitor mangrove deforestation in East Kalimantan, Indonesia

    Science.gov (United States)

    Mahfud M. Zuhair; Yousif Ali Hussin; Michael Weir

    2000-01-01

    Mangrove forests are one of the primary features of coastal ecosystems throughout the tropical and subtropical regions of the world. Mangroves are very sensitive and fragile resources, and the pressures of increasing population, food production, and industrial and urban development have caused a significant proportion of the world's mangroves to be destroyed....

  14. HUBBLE FINDS NEW DARK SPOT ON NEPTUNE

    Science.gov (United States)

    2002-01-01

    NASA's Hubble Space Telescope has discovered a new great dark spot, located in the northern hemisphere of the planet Neptune. Because the planet's northern hemisphere is now tilted away from Earth, the new feature appears near the limb of the planet. The spot is a near mirror-image to a similar southern hemisphere dark spot that was discovered in 1989 by the Voyager 2 probe. In 1994, Hubble showed that the southern dark spot had disappeared. Like its predecessor, the new spot has high altitude clouds along its edge, caused by gasses that have been pushed to higher altitudes where they cool to form methane ice crystal clouds. The dark spot may be a zone of clear gas that is a window to a cloud deck lower in the atmosphere. Planetary scientists don t know how long lived this new feature might be. Hubble's high resolution will allow astronomers to follow the spot's evolution and other unexpected changes in Neptune's dynamic atmosphere. The image was taken on November 2, 1994 with Hubble's Wide Field Planetary Camera 2, when Neptune was 2.8 billion miles (4.5 billion kilometers) from Earth. Hubble can resolve features as small as 625 miles (1,000 kilometers) across in Neptune's cloud tops. Credit: H. Hammel (Massachusetts Institute of Technology) and NASA

  15. HIGH-RESOLUTION SATELLITE IMAGING OF THE 2004 TRANSIT OF VENUS AND ASYMMETRIES IN THE CYTHEREAN ATMOSPHERE

    International Nuclear Information System (INIS)

    Pasachoff, Jay M.; Schneider, Glenn; Widemann, Thomas

    2011-01-01

    This paper presents the only space-borne optical-imaging observations of the 2004 June 8 transit of Venus, the first such transit visible from Earth since AD 1882. The high-resolution, high-cadence satellite images we arranged from NASA's Transition Region and Coronal Explorer (TRACE) reveal the onset of visibility of Venus's atmosphere and give further information about the black-drop effect, whose causes we previously demonstrated from TRACE observations of a transit of Mercury. The atmosphere is gradually revealed before second contact and after third contact, resulting from the changing depth of atmospheric layers refracting the photospheric surface into the observer's direction. We use Venus Express observations to relate the atmospheric arcs seen during the transit to the atmospheric structure of Venus. Finally, we relate the transit images to current and future exoplanet observations, providing a sort of ground truth showing an analog in our solar system to effects observable only with light curves in other solar systems with the Kepler and CoRoT missions and ground-based exoplanet-transit observations.

  16. TIRCIS: A Thermal Infrared, Compact Imaging Spectrometer for Small Satellite Applications

    Data.gov (United States)

    National Aeronautics and Space Administration — This project will demonstrate how hyperspectral thermal infrared (TIR; 8-14 microns) image data, with a spectral resolution of up to 8 wavenumbers, can be acquired...

  17. Low-Cost Small Satellite Atmospheric Rotating Solar Occultation Imager (ROI)

    Data.gov (United States)

    National Aeronautics and Space Administration — Utilizing a unique, new occultation technique involving imaging, the ROI concept will meet or exceed the quality of SAGE measurements at a small fraction of the...

  18. High-resolution satellite and airborne thermal infrared imaging of precursory unrest and 2009 eruption of Redoubt Volcano, Alaska

    Science.gov (United States)

    Wessels, Rick L.; Vaughan, R. Greg; Patrick, Matthew R.; Coombs, Michelle L.

    2013-01-01

    A combination of satellite and airborne high-resolution visible and thermal infrared (TIR) image data detected and measured changes at Redoubt Volcano during the 2008–2009 unrest and eruption. The TIR sensors detected persistent elevated temperatures at summit ice-melt holes as seismicity and gas emissions increased in late 2008 to March 2009. A phreatic explosion on 15 March was followed by more than 19 magmatic explosive events from 23 March to 4 April that produced high-altitude ash clouds and large lahars. Two (or three) lava domes extruded and were destroyed between 23 March and 4 April. After 4 April, the eruption extruded a large lava dome that continued to grow until at least early July 2009.

  19. Power laws and inverse motion modelling: application to turbulence measurements from satellite images

    Directory of Open Access Journals (Sweden)

    Pablo D. Mininni

    2012-01-01

    Full Text Available In the context of tackling the ill-posed inverse problem of motion estimation from image sequences, we propose to introduce prior knowledge on flow regularity given by turbulence statistical models. Prior regularity is formalised using turbulence power laws describing statistically self-similar structure of motion increments across scales. The motion estimation method minimises the error of an image observation model while constraining second-order structure function to behave as a power law within a prescribed range. Thanks to a Bayesian modelling framework, the motion estimation method is able to jointly infer the most likely power law directly from image data. The method is assessed on velocity fields of 2-D or quasi-2-D flows. Estimation accuracy is first evaluated on a synthetic image sequence of homogeneous and isotropic 2-D turbulence. Results obtained with the approach based on physics of fluids outperform state-of-the-art. Then, the method analyses atmospheric turbulence using a real meteorological image sequence. Selecting the most likely power law model enables the recovery of physical quantities, which are of major interest for turbulence atmospheric characterisation. In particular, from meteorological images we are able to estimate energy and enstrophy fluxes of turbulent cascades, which are in agreement with previous in situ measurements.

  20. Estimation of landslide-triggering factors using clay minerals, ASTER satellite image and GIS in the Busan area, southeastern Korea

    Science.gov (United States)

    Jeong, G. C.; Kim, M. G.; Choi, J. J.; Ryu, J. O.; Nho, J. G.; Choo, C. O.

    2016-12-01

    This study aims at estimating landslide-inducing factors such as extreme rainfall, slope, and geological factors in Busan city, southeastern Korea, using clay mineralogy, DM analysis and DB construction in order to develop the landslide evaluation standards suitable for the country. GIS-based data collected from the study area include geological maps, topological maps, soil maps, forest maps and others in the DB construction. Data extraction and processing for landslide-induced factors consist of expandable clay minerals identified using XRD, along with XRF and weathering sensitivity analysis and fundamental soil analysis on 38 bulk samples composed of weathered rocks and soils. Finally landslide sensibility maps were constructed using ArcGIS, together with ASTER satellite images for identifying clay minerals on regional areas helpful for saving time and money. In Mt. Cheonma, 16 samples are composed of quartz, albite, illite, vermiculite, and kaolinite, with little difference in mineralogy. In Mt. Hwangryeong and Mt. Geumryeun, 12 samples consist of quartz, albite, illite, vermiculite, kaolinite and hornblende, with little difference in mineralogy. In Mt. Songhak, 10 samples are composed of quartz, illite, vermiculite, and kaolinite. Quartz, albite and illite are abundant in most samples, regardless of sites studied. IDW interpolation method was applied to the Busan area. The resolution of space grids consists of 5 m x 5 m. Especially, illite was used as the most effective factor that induces landslide using IDW interpolation and ASTER satellite images. In conclusion, sensibility maps constructed using 16 layers including illite content, weathered sensibility are well in accordance with the real sites where landslides took place, showing that areas with high sensibility are closely related to the high frequencies of landslide. This research was supported by the Public Welfare & Safety Research Program through the National Research Foundation of Korea (NRF) funded

  1. Satellite observations of snow and ice with an imaging passive microwave spectrometer

    Science.gov (United States)

    Fisher, A. D.; Ledsham, B. L.; Rosenkranz, P. W.; Staelin, D. H.

    1976-01-01

    The scanning microwave spectrometer (SCAMS) on the Nimbus-6 satellite continuously maps the terrestrial surface with a resolution of about 150 km at 22.235 and 31.400 GHz. SCAMS observes at six angles besides nadir, yielding brightness temperatures which are a function of the distribution and character of various types of snow and ice, including microstructure and subsurface profiles in refractive index, loss (moisture or salinity), and temperature. Spectral signatures exhibiting interesting topographical structure have been observed. To aid in the interpretation of these data, a model was developed to describe the propagation of microwave intensity in a scattering medium characterized by three-dimensional random fluctuations of refractive index in addition to nonrandom variations in permittivity, temperature, and loss. The model combines Maxwell's equations in the Born approximation with radiative-transfer theory; this approach yields the variation of intensity with polarization, direction, and position.

  2. Satellite imaging coral reef resilience at regional scale. A case-study from Saudi Arabia.

    Science.gov (United States)

    Rowlands, Gwilym; Purkis, Sam; Riegl, Bernhard; Metsamaa, Liisa; Bruckner, Andrew; Renaud, Philip

    2012-06-01

    We propose a framework for spatially estimating a proxy for coral reef resilience using remote sensing. Data spanning large areas of coral reef habitat were obtained using the commercial QuickBird satellite, and freely available imagery (NASA, Google Earth). Principles of coral reef ecology, field observation, and remote observations, were combined to devise mapped indices. These capture important and accessible components of coral reef resilience. Indices are divided between factors known to stress corals, and factors incorporating properties of the reef landscape that resist stress or promote coral growth. The first-basis for a remote sensed resilience index (RSRI), an estimate of expected reef resilience, is proposed. Developed for the Red Sea, the framework of our analysis is flexible and with minimal adaptation, could be extended to other reef regions. We aim to stimulate discussion as to use of remote sensing to do more than simply deliver habitat maps of coral reefs. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Characterization of the deforestation effect in a semi-arid region by the use of satellite images

    Science.gov (United States)

    Benhanifia, Khatir; Haddouche, Driss; Smahi, Zakaria; Bensaid, Abdelkrim; Hamimed, Abderrahmane

    2004-02-01

    In Algeria, arid and semi-arid regions occupy over than 95% of whole territory. Forests in the semi arid zone constitutes a front face to the advance of the desert towards northern sides. Like in other regions of the world, deforestation phenomenon have a serious consequences on the fragile ecosystem. Severe continuous drought, fires, pasture, insects as well as the absence of a clear forest politics are so many factors that reduced forest areas in this country. However, the conservation of this patrimony must be a priority of any regional development project. This paper describes an evaluating study of the deforestation impact on forests in the region of Djelfa situated in the Saharian Atlas using multitemporal satellite remote sensing data. In order to establish a forest change map, a methodology based on the comparison between normalized difference vegetation indexes (NDVI) generated from satellite images was adopted. For this purpose, a pair of Landsat and (ETM+) images acquired over the region on April 11th, 1987 and march 24th, 2001 have been used. Until being processed, data used have been geometrically and atmospherically corrected. Then, an (NDVI) have been produced for each date. Resulting from compared (NDVI) image presents the forest change map in the study area. Radiometric values of resulting image have been regrouped into three classes according to change types as follow : Increased radiometry = more active vegetation Decreased radiometry = deterioration in vegetation activity Non changed areas = Non changed Investigations made on the terrain permitted to interpret many causes of detected evolutions. Regressive changes were considerable and demonstrates however, the degradation effect on the vegetation state. Some of regressed radiometry are related to forest fires that affected the region in 1994. Almost of regressive changes are due to a deterioration of vegetation caused by multiple factors. Drought, deceases, pasture and infection are considered

  4. 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

  5. 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.

  6. Superluminal Sweeping Spot Pair Events in Astronomical Settings

    Science.gov (United States)

    Nemiroff, Robert J.

    2015-01-01

    Sweeping beams of light can cast spots that move superluminally across scattering surfaces. Such faster-than-light speeds are well-known phenomena that do not violate special relativity. It is shown that under certain circumstances, superluminal spot pair creation and annihilation events can occur that provide unique information to observers. These spot pair events are not particle pair events -- they are the sudden creation or annihilation of a pair of relatively illuminated spots on a scattering surface. Astronomical settings where superluminal spot pairs might be found include Earth's Moon, passing asteroids, pulsars, and variable nebula. Potentially recoverable information includes three dimensional imaging, relative geometric size factors, and distances.

  7. Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data

    Science.gov (United States)

    Ronald E. McRoberts; Steen Magnussen; Erkki O. Tomppo; Gherardo. Chirici

    2011-01-01

    Nearest neighbors techniques have been shown to be useful for estimating forest attributes, particularly when used with forest inventory and satellite image data. Published reports of positive results have been truly international in scope. However, for these techniques to be more useful, they must be able to contribute to scientific inference which, for sample-based...

  8. Multitemporal Satellite Images for Knowledge of the Assyrian Capital Cities and for Monitoring Landscape Transformations in the Upper Course of Tigris River

    Directory of Open Access Journals (Sweden)

    Giuseppe Scardozzi

    2011-01-01

    Full Text Available The paper is concerned with the contribution that a rich documentation of multitemporal optical satellite images with high resolution provides for the knowledge of the five great Assyrian capital cities (Ashur, Kar-Tukulti-Ninurta, Kalhu, Dur-Sharrukin, and Nineveh, in northern Iraq. These images also allow monitoring changes of landscape in the higher course of the Tigris during the last half century and document damages in archaeological sites during the two Gulf Wars. The data set, available for each city, consists of panchromatic and multispectral images taken between 2001 and 2007 by modern commercial satellites (Ikonos-2, QuickBird-2, and WorldView-1 and of panchromatic photographs of U.S. spy satellites operating between 1965 and 1969 (Corona KH-4B and Gambit KH-7. These photos were taken before diffusion of mechanized agriculture and the expansion of urban areas, so they are very useful to document many archaeological features and the landscape that has been modified in the last decades, as shown by recent satellite images.

  9. Benefits of Red-Edge Spectral Band and Texture Features for the Object-based Classification using RapidEye sSatellite Image data

    Science.gov (United States)

    Kim, H. O.; Yeom, J. M.

    2014-12-01

    Space-based remote sensing in agriculture is particularly relevant to issues such as global climate change, food security, and precision agriculture. Recent satellite missions have opened up new perspectives by offering high spatial resolution, various spectral properties, and fast revisit rates to the same regions. Here, we examine the utility of broadband red-edge spectral information in multispectral satellite image data for classifying paddy rice crops in South Korea. Additionally, we examine how object-based spectral features affect the classification of paddy rice growth stages. For the analysis, two seasons of RapidEye satellite image data were used. The results showed that the broadband red-edge information slightly improved the classification accuracy of the crop condition in heterogeneous paddy rice crop environments, particularly when single-season image data were used. This positive effect appeared to be offset by the multi-temporal image data. Additional texture information brought only a minor improvement or a slight decline, although it is well known to be advantageous for object-based classification in general. We conclude that broadband red-edge information derived from conventional multispectral satellite data has the potential to improve space-based crop monitoring. Because the positive or negative effects of texture features for object-based crop classification could barely be interpreted, the relationships between the textual properties and paddy rice crop parameters at the field scale should be further examined in depth.

  10. Using the ratio of optical channels in satellite image decoding in monitoring biodiversity of boreal forests

    Science.gov (United States)

    Rozhkov, Yurj P.; Kondakova, Maria Y.

    2013-10-01

    The study contains the results of forest monitoring at three levels: the forests condition assessment at the time of recording or mapping for this indicator, the seasonal changes assessment in the forests condition, mainly during the vegetation period and the evaluation of long-term changes in the values of the studied parameters on the example of the forests recovery after a fire. The use of two indices - NDVI and Image Difference in the boreal forests monitoring is treated. NDVI assesses the state of plant biomass and its productivity. The rate of Image Difference characterizes the optical density and allows estimate the density of the forest stand. In addition, by identifying Image Difference on summer and autumn pictures it can makes a distinction of different wood species, to divide forest areas, which consist of deciduous and coniferous species and larch which shedded needles at the end of the vegetation period. Therefore, it is possible to differentiate the pine, cedar, spruce forests on the one side and birch, larch, alder on the other side. The optical density of the forest decreases after the needles- and the leaf sheddings. Using the index Image Difference in estimates of long-term changes of the forest stand shows the trend of changes of the forest density and the tree species composition. The results of the analysis of the recovery process of the forest after a fire in the period from 1995 to 2009 showed how shoots of birch, larch and pine recover wastelands.

  11. High-resolution satellite image segmentation using Hölder exponents

    Indian Academy of Sciences (India)

    1Regional Remote Sensing Service Centre, Indian Space Research Organization, IIT Campus,. Kharagpur 721 ... The watershed segmentation methods (Vincent .... it does not require any prior information about the pixel intensity. This work attempts to describe the textures of high-resolution images using Hölder exponent.

  12. A common dominant scale emerges from images of diverse satellite platforms using the wavelet transform

    NARCIS (Netherlands)

    Pittiglio, C.; Skidmore, A.K.; Bie, de C.A.J.M.; Murwira, A.

    2011-01-01

    In this article we investigate the scale dependence of spatial heterogeneity in multiresolution and multisensor data using the wavelet transform. The landscape analysed with the wavelets retains the same dominant pattern irrespective of the original pixel size of the image. In agricultural areas,

  13. Spot market for uranium

    International Nuclear Information System (INIS)

    Colhoun, C.

    1982-01-01

    The spot market is always quoted for the price of uranium because little information is available about long-term contracts. A review of the development of spot market prices shows the same price curve swings that occur with all raw materials. Future long-term contracts will probably be lower to reflect spot market prices, which are currently in the real-value range of $30-$35. An upswing in the price of uranium could come in the next few months as utilities begin making purchases and trading from stockpiles. The US, unlike Europe and Japan, has already reached a supply and demand point where the spot market share is increasing. Forecasters cannot project the market price, they can only predict the presence of an oscillating spot or a secondary market. 5 figures

  14. Satellite Image Analysis along the Kuala Selangor to Sabak Bernam Rural Tourism Routes

    Science.gov (United States)

    Ibrahim, I.; Zakariya, K.; Wahab, N. A.

    2018-02-01

    This research focuses on the analysis of land cover map using satellite imagery along the rural routes. The aim of this research is to study the landscape features that can be seen by the tourists around the rural routes. The objectives of the study are twofold: (i) to analyse the land cover types along the rural routes and (ii) to create a tourist map along the rural routes. The method adopted was to use Supervised Classification by creating multiple polygons to ensure that each information is sufficient to create appropriate spectral signatures. The finding shows that 80% of the landscape features along the Point of Interest (POI) are paddy field. According to the analysis using the indicators criteria for choosing the rural routes, this research shows that this area has the potential to be part of a tourism area because it has many historical and cultural elements that can be exposed to tourists. Future research will be a factor analysis on the significance of the criteria to rural tourism attraction.

  15. Objective estimation of tropical cyclone innercore surface wind structure using infrared satellite images

    Science.gov (United States)

    Zhang, Changjiang; Dai, Lijie; Ma, Leiming; Qian, Jinfang; Yang, Bo

    2017-10-01

    An objective technique is presented for estimating tropical cyclone (TC) innercore two-dimensional (2-D) surface wind field structure using infrared satellite imagery and machine learning. For a TC with eye, the eye contour is first segmented by a geodesic active contour model, based on which the eye circumference is obtained as the TC eye size. A mathematical model is then established between the eye size and the radius of maximum wind obtained from the past official TC report to derive the 2-D surface wind field within the TC eye. Meanwhile, the composite information about the latitude of TC center, surface maximum wind speed, TC age, and critical wind radii of 34- and 50-kt winds can be combined to build another mathematical model for deriving the innercore wind structure. After that, least squares support vector machine (LSSVM), radial basis function neural network (RBFNN), and linear regression are introduced, respectively, in the two mathematical models, which are then tested with sensitivity experiments on real TC cases. Verification shows that the innercore 2-D surface wind field structure estimated by LSSVM is better than that of RBFNN and linear regression.

  16. Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2013-01-01

    Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

  17. Airborne and satellite imager retrievals of clouds and above-cloud aerosols during ORACLES

    Science.gov (United States)

    Meyer, K.; Platnick, S. E.; Arnold, T.; Riedi, J.

    2017-12-01

    The 2016 deployment of the NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) field campaign included wide swath, high spatial resolution imagery from the Enhanced MODIS Airborne Simulator (eMAS) flown onboard the ER-2 high altitude research aircraft. eMAS, with a 37km wide swath and 50m spatial resolution from a 20km flight altitude, measures reflected solar and emitted terrestrial radiation at 38 narrowband channels covering the 0.47 - 14µm spectral range. Here we present a brief overview of the eMAS cloud retrieval science that supported ORACLES, namely the cloud products sharing heritage with the space-borne MODIS operational cloud product (MOD06). We will also present first results of the MOD06ACAERO algorithm applied to eMAS; this at present research-level algorithm provides simultaneous retrievals of above-cloud absorbing aerosol and the unbiased underlying cloud optical thickness and effective particle size from reflectance at multiple spectral channels in the visible, near-infrared, and shortwave infrared spectra. Comparisons with other ORACLES cloud and aerosol observations will be shown. Satellite observations, namely MOD06 (Terra/Aqua MODIS) and the MODIS-like SEV06 (geostationary Meteosat SEVIRI) and Terra/Aqua MOD06ACAERO, will provide context for the eMAS retrievals.

  18. New eyes on the sun a guide to satellite images and amateur observation

    CERN Document Server

    Wilkinson, John

    2012-01-01

    Information collected by satellites recently sent by the USA, the European Space Agency, Japan, Germany, the United Kingdom, and Russia to monitor the Sun has changed our knowledge and understanding of the Sun, particularly its effect on Earth. This book presents these findings in a way that will be welcomed by amateur astronomers, students, educators and anyone interested in the Sun. Enhanced by many colour photographs, the book combines newly acquired scientific understanding with detailed descriptions of features visible on the Sun’s surface and in its atmosphere. In the past, observing the Sun has been left to academics with specialised instruments, since solar observation has been unsafe because of the risk of eye damage.  This book explains how amateur astronomers can safely observe the various solar phenomena using special hydrogen-alpha telescopes that are not too expensive. Amateurs can now make a positive contribution to science by monitoring the Sun as professionals do.  Amateurs can also acces...

  19. Use of high-resolution satellite images for characterization of geothermal reservoirs in the Tarapaca Region, Chile

    Science.gov (United States)

    Arellano-Baeza, A. A.; Montenegro A., C.

    2010-12-01

    The use of renewable and clean sources of energy is becoming crucial for sustainable development of all countries, including Chile. Chilean Government plays special attention to the exploration and exploitation of geothermal energy, total electrical power capacity of which could reach 16.000 MW. In Chile the main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the Lansat satellite have been used to characterize the geothermal field in the region of the Puchuldiza geysers, Colchane, Region of Tarapaca, North of Chile, located at the altitude of 4000 m. Structure of lineaments associated to the geothermal field have been extracted from the images using the lineament detection technique developed by authors. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament analysis is a power tool for the detection of faults and joint zones associated to the geothermal fields.

  20. METimage: an innovative multi-spectral imaging radiometer for the EUMETSAT polar system follow-on satellite mission

    Science.gov (United States)

    Alpers, Matthias; Brüns, Christian; Pillukat, Alexander

    2017-11-01

    The evolving needs of the meteorological community concerning the EUMETSAT Polar System follow-on satellite mission (Post-EPS) require the development of a high-performance multi-spectral imaging radiometer. Recognizing these needs, Jena Optronik GmbH proposed an innovative instrument concept, which comprises a high flexibility to adapt to user requirements as a very important feature. Core parameters like ground sampling distance (GSD), number and width of spectral channels, signal-to-noise ratio, polarization control and calibration facilities can be chosen in a wide range without changing the basic instrument configuration. Core item of the METimage instrument is a rotating telescope scanner to cover the large swath width of about 2800 km, which all polar platforms need for global coverage. The de-rotated image facilitates use of in-field spectral channel separation, which allows tailoring individual channel GSD (ground sampling distance) and features like TDI (time delay and integration). State-of-the-art detector arrays and readout electronics can easily be employed. Currently, the German DLR Space Agency, Jena- Optronik GmbH and AIM Infrarot Module GmbH work together implementing core assemblies of METimage: the rotating telescope scanner and the infrared detectors. The METimage instrument phase B study was kicked-off in September 2008. Germany intents to provide METimage as an in-kind contribution of the first METimage flight model to the EUMETSAT Post-EPS Programme.

  1. Analysis of wind and wave events at the MIZ based on TerraSAR-X satellite images

    Science.gov (United States)

    Gebhardt, Claus; Bidlot, Jean-Raymond; Jacobsen, Sven; Lehner, Susanne; Pleskachevsky, Andrey; Singha, Suman

    2017-04-01

    The seasonal opening-up of large expanses of open water in the Beaufort/Chukchi Sea is a phenomenon observed in recent years. The diameter of the open-water area is on the order of 1000 km around the sea ice minimum in summer. Thus, wind events in the area are accompanied by the build-up of sea waves. Significant wave heights of few to several meters may be reached. Under low to moderate winds, the morphology of the MIZ is governed by oceanic forcing. As a result, the MIZ resembles ocean circulation features such as eddies, meanders, etc.. In the case of strong wind events, however, the wind forcing may gain control. We analyse effects related to wind and wave events at the MIZ using TerraSAR-X satellite imagery. Methods such as the retrieval of sea state and wind data by empirical algorithms and automatic sea ice classification are applied. This is facilitated by a series of TerraSAR-X images acquired in support of a cruise of the research vessel R/V Sikuliaq in the Beaufort/Chukchi Sea in autumn 2015. For selected images, the results are presented and compared to numerical model forecasts which were as well part of the cruise support.

  2. Caractérisation spatiale de l’aléa inondation à partir d’images satellites RADAR

    Directory of Open Access Journals (Sweden)

    Renaud Hostache

    2007-07-01

    Full Text Available Dans le cadre de la gestion du risque d’inondation, la caractérisation spatiale de l’aléa est une problématique récurrente pour laquelle les techniques de télédétection, en particulier satellitales, peuvent s’avérer très utiles. L’objectif général de notre étude est d’évaluer les apports de l’utilisation de ces données et, en particulier, de développer des méthodes de valorisation des images satellites RADAR d’inondations pour la caractérisation spatiale de l’aléa. A terme, notre étude vise l’aide à la modélisation hydraulique par évaluation de hauteurs et de volumes d’eau. La méthode que nous proposons s’articule en trois étapes principales : 1 cartographie de l’extension des eaux à partir d’images RADAR et extraction des limites informatives, 2 estimation primaire de niveaux d’eau par croisement entre les limites informatives et un MNT, 3 réduction des incertitudes d’estimation des niveaux d’eau par introduction de concepts de cohérence hydraulique.

  3. A Study on Retrieval Algorithm of Black Water Aggregation in Taihu Lake Based on HJ-1 Satellite Images

    International Nuclear Information System (INIS)

    Lei, Zou; Bing, Zhang; Junsheng, Li; Qian, Shen; Fangfang, Zhang; Ganlin, Wang

    2014-01-01

    The phenomenon of black water aggregation (BWA) occurs in inland water when massive algal bodies aggregate, die, and react with the toxic sludge in certain climate conditions to deprive the water of oxygen. This process results in the deterioration of water quality and damage to the ecosystem. Because charge coupled device (CCD) camera data from the Chinese HJ environmental satellite shows high potential in monitoring BWA, we acquired four HJ-CCD images of Taihu Lake captured during 2009 to 2011 to study this phenomenon. The first study site was selected near the Shore of Taihu Lake. We pre-processed the HJ-CCD images and analyzed the digital number (DN) gray values in the research area and in typical BWA areas. The results show that the DN values of visible bands in BWA areas are obviously lower than those in the research areas. Moreover, we developed an empirical retrieving algorithm of BWA based on the DN mean values and variances of research areas. Finally, we tested the accuracy of this empirical algorithm. The retrieving accuracies were89.9%, 58.1%, 73.4%, and 85.5%, respectively, which demonstrates the efficiency of empirical algorithm in retrieving the approximate distributions of BWA

  4. Time Resolved X-Ray Spot Size Diagnostic

    CERN Document Server

    Richardson, Roger; Falabella, Steven; Guethlein, Gary; Raymond, Brett; Weir, John

    2005-01-01

    A diagnostic was developed for the determination of temporal history of an X-ray spot. A pair of thin (0.5 mm) slits image the x-ray spot to a fast scintillator which is coupled to a fast detector, thus sampling a slice of the X-Ray spot. Two other scintillator/detectors are used to determine the position of the spot and total forward dose. The slit signal is normalized to the dose and the resulting signal is analyzed to get the spot size. The position information is used to compensate for small changes due to spot motion and misalignment. The time resolution of the diagnostic is about 1 ns and measures spots from 0.5 mm to over 3 mm. The theory and equations used to calculate spot size and position are presented, as well as data. The calculations assume a symmetric, Gaussian spot. The spot data is generated by the ETA II accelerator, a 2kA, 5.5 MeV, 60ns electron beam focused on a Tantalum target. The spot generated is typically about 1 mm FWHM. Comparisons are made to an X-ray pinhole camera which images th...

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

  6. Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

    Science.gov (United States)

    Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

    2016-12-01

    Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general

  7. Primena satelitskih snimaka za dopunu sadržaja topografskih karata / An application of satellite images for improving the content of topographic maps

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2010-10-01

    Full Text Available Neažurnost sadržaja topografskih karata (TK, uslovljena ponajviše stvarnim ekonomskim teškoćama pri izradi novih i dopuni postojećih izdanja, kao i nedovoljnost i sve teže stanje pri izradi ostalih geotopografskih materijala (GTM, u velikoj meri otežavaju geotopografsko obezbeđenje (GTOb vojske u miru, kao i u svim periodima pripreme i vođenja ratnih dejstava. Rešenje ovog problema je u iznalaženju adekvatnog načina upotrebe proizvoda svih vrsta daljinskih snimanja, a naročito u obradi kvalitetnih satelitskih snimaka. Kao najbolji pokazatelj velikih mogućnosti daljinske detekcije, korišćenjem satelitskih snimaka, u kartografskoj praksi primenom kvalitetnih softverskih rešenja, u radu je predstavljena dopuna topografske karte nedostajućim topografskim sadržajem. / Lack of updated content of topographic maps (TMs, mainly due to economic issues regarding the publishing of existing or revised TMs, substantially affects geo-topographic supply (GTS of the Army both in peace and warfare time, as well as shortage of other geo-topographic materials (GTMs. The solution to this problem is in finding an appropriate method of using products of all types of remote sensing, high quality satellite images in particular. Having shown the best possibilities of remote sensing while using satellite images in mapping through the quality software solutions, the author presents an addition to topographic maps based on missing topographic data. Introduction Numerous natural and social phenomena are constantly observed, surveyed, registered and analyzed. Permanent or periodical satellite surveillance and recording for different purposes are growing in importance. The purposes can range from meteorological issues, through study of large water surfaces to military intelligence, etc. These recording can be used in making topographic, thematic and working maps as well as other geo-topographic material. Processing and analyzing of ikonos2 satellite images

  8. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

    Science.gov (United States)

    Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

    2017-05-01

    WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

  9. AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data

    Directory of Open Access Journals (Sweden)

    Daniel Scheffler

    2017-07-01

    Full Text Available Geospatial co-registration is a mandatory prerequisite when dealing with remote sensing data. Inter- or intra-sensoral misregistration will negatively affect any subsequent image analysis, specifically when processing multi-sensoral or multi-temporal data. In recent decades, many algorithms have been developed to enable manual, semi- or fully automatic displacement correction. Especially in the context of big data processing and the development of automated processing chains that aim to be applicable to different remote sensing systems, there is a strong need for efficient, accurate and generally usable co-registration. Here, we present AROSICS (Automated and Robust Open-Source Image Co-Registration Software, a Python-based open-source software including an easy-to-use user interface for automatic detection and correction of sub-pixel misalignments between various remote sensing datasets. It is independent of spatial or spectral characteristics and robust against high degrees of cloud coverage and spectral and temporal land cover dynamics. The co-registration is based on phase correlation for sub-pixel shift estimation in the frequency domain utilizing the Fourier shift theorem in a moving-window manner. A dense grid of spatial shift vectors can be created and automatically filtered by combining various validation and quality estimation metrics. Additionally, the software supports the masking of, e.g., clouds and cloud shadows to exclude such areas from spatial shift detection. The software has been tested on more than 9000 satellite images acquired by different sensors. The results are evaluated exemplarily for two inter-sensoral and two intra-sensoral use cases and show registration results in the sub-pixel range with root mean square error fits around 0.3 pixels and better.

  10. Comparison of two satellite imaging platforms for evaluating quasi-circular vegetation patch in the Yellow River Delta, China

    Science.gov (United States)

    Liu, Qingsheng; Liang, Li; Liu, Gaohuan; Huang, Chong

    2017-09-01

    Vegetation often exists as patch in arid and semi-arid region throughout the world. Vegetation patch can be effectively monitored by remote sensing images. However, not all satellite platforms are suitable to study quasi-circular vegetation patch. This study compares fine (GF-1) and coarse (CBERS-04) resolution platforms, specifically focusing on the quasicircular vegetation patches in the Yellow River Delta (YRD), China. Vegetation patch features (area, shape) were extracted from GF-1 and CBERS-04 imagery using unsupervised classifier (K-Means) and object-oriented approach (Example-based feature extraction with SVM classifier) in order to analyze vegetation patterns. These features were then compared using vector overlay and differencing, and the Root Mean Squared Error (RMSE) was used to determine if the mapped vegetation patches were significantly different. Regardless of K-Means or Example-based feature extraction with SVM classification, it was found that the area of quasi-circular vegetation patches from visual interpretation from QuickBird image (ground truth data) was greater than that from both of GF-1 and CBERS-04, and the number of patches detected from GF-1 data was more than that of CBERS-04 image. It was seen that without expert's experience and professional training on object-oriented approach, K-Means was better than example-based feature extraction with SVM for detecting the patch. It indicated that CBERS-04 could be used to detect the patch with area of more than 300 m2, but GF-1 data was a sufficient source for patch detection in the YRD. However, in the future, finer resolution platforms such as Worldview are needed to gain more detailed insight on patch structures and components and formation mechanism.

  11. Satellite Images and Gaussian Parameterization for an Extensive Analysis of Urban Heat Islands in Thailand

    Directory of Open Access Journals (Sweden)

    Chaiyapon Keeratikasikorn

    2018-04-01

    Full Text Available For the first time, an extensive study of the surface urban heat island (SUHI in Thailand’s six major cities is reported, using 728 MODIS (MODerate Resolution Imaging Spectroradiometer images for each city. The SUHI analysis was performed at three timescales—diurnal, seasonal, and multiyear. The diurnal variation is represented by the four MODIS passages (10:00, 14:00, 22:00, and 02:00 local time and the seasonal variation by summer and winter maps, with images covering a 14-year interval (2003–2016. Also, 126 Landsat scenes were processed to classify and map land cover changes for each city. To analyze and compare the SUHI patterns, a least-square Gaussian fitting method has been applied and the corresponding empirical metrics quantified. Such an approach represents, when applicable, an efficient quantitative tool to perform comparisons that a visual inspection of a great number of maps would not allow. Results point out that SUHI does not show significant seasonality differences, while SUHI in the daytime is a more evident phenomenon with respect to nighttime, mainly due to solar forcing and intense human activities and traffic. Across the 14 years, the biggest city, Bangkok, shows the highest SUHI maximum intensities during daytime, with values ranging between 4 °C and 6 °C; during nighttime, the intensities are rather similar for all the six cities, between 1 °C and 2 °C. However, these maximum intensities are not correlated with the urban growth over the years. For each city, the SUHI spatial extension represented by the Gaussian footprint is generally not affected by the urban area sprawl across the years, except for Bangkok and Chiang Mai, whose daytime SUHI footprints show a slight increase over the years. Orientation angle and central location of the fitted surface also provide information on the SUHI layout in relation to the land use of the urban texture.

  12. 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. Copyright

  13. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Bamyan mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  14. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ahankashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008, 2009, 2010),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this

  15. Comparison of data file and storage configurations for efficient temporal access of satellite image data

    CSIR Research Space (South Africa)

    Bachoo, A

    2009-01-01

    Full Text Available block, while the image stack representation stores one time step of a sequence of spatial neigh- bours (one row of pixels) as a contiguous block. A consequence of this representation is that 2- dimensional queries (e.g., extracting a rectangular re... to reexamine they way in which we structure our data. These SSDs are typically built using banks of NAND-based ash memory, which unfortunately im- plies that data must be read in blocks, rather than using a pure random access addressing scheme...

  16. An evolutionary computing frame work toward object extraction from satellite images

    Directory of Open Access Journals (Sweden)

    P.V. Arun

    2013-12-01

    Full Text Available Image interpretation domains have witnessed the application of many intelligent methodologies over the past decade; however the effective use of evolutionary computing techniques for feature detection has been less explored. In this paper, we critically analyze the possibility of using cellular neural network for accurate feature detection. Contextual knowledge has been effectively represented by incorporating spectral and spatial aspects using adaptive kernel strategy. Developed methodology has been compared with traditional approaches in an object based context and investigations revealed that considerable success has been achieved with the procedure. Intelligent interpretation, automatic interpolation, and effective contextual representations are the features of the system.

  17. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

  18. Retrieval of suspended sediment concentrations using Landsat-8 OLI satellite images in the Orinoco River (Venezuela)

    Science.gov (United States)

    Yepez, Santiago; Laraque, Alain; Martinez, Jean-Michel; De Sa, Jose; Carrera, Juan Manuel; Castellanos, Bartolo; Gallay, Marjorie; Lopez, Jose L.

    2018-01-01

    In this study, 81 Landsat-8 scenes acquired from 2013 to 2015 were used to estimate the suspended sediment concentration (SSC) in the Orinoco River at its main hydrological station at Ciudad Bolivar, Venezuela. This gauging station monitors an upstream area corresponding to 89% of the total catchment area where the mean discharge is of 33,000 m3·s-1. SSC spatial and temporal variabilities were analyzed in relation to the hydrological cycle and to local geomorphological characteristics of the river mainstream. Three types of atmospheric correction models were evaluated to correct the Landsat-8 images: DOS, FLAASH, and L8SR. Surface reflectance was compared with monthly water sampling to calibrate a SSC retrieval model using a bootstrapping resampling. A regression model based on surface reflectance at the Near-Infrared wavelengths showed the best performance: R2 = 0.92 (N = 27) for the whole range of SSC (18 to 203 mg·l-1) measured at this station during the studied period. The method offers a simple new approach to estimate the SSC along the lower Orinoco River and demonstrates the feasibility and reliability of remote sensing images to map the spatiotemporal variability in sediment transport over large rivers.

  19. Using multilayer perceptron and a satellite image for the estimation of soil salinity

    International Nuclear Information System (INIS)

    Lau, A.; Ruiz, M.E.; Garcia, E.

    2008-01-01

    Applying the model of the Perceptron multilayer with momentum of an artificial neural network particularly and a multispectral image of high resolution spatial and radiometric, for the first time estimated the salinity of the soil cultivated with sugar cane. The study area is the UBPC 'Lazaro Romero' of the sugar company 'Hector Molina' of the locality San Nicolas de Bari, Havana province, located at 22° 44' North latitude and 81 ° 56' longitude West. The experiments were made in the framework of the El-479 project funded by the Inter universities Council of Flanders, Belgium. 36 samples geo referenced of soils were taken at 3 depths in each of the 4 sugar cane selected blocks, which determined the electrical conductivity of the saturation extract; half of that amount of data was used for the training of the network and the other half for control in a computer program of the artificial neural network created to that effect, together with the reflectance of vegetation indexes for the image, which were maps of electrical conductivity of each block and bands. They were compared with those obtained by simple linear regression between the normalized difference vegetation index and electrical conductivity, Ndv with the approach of the neuronal network, the correlation coefficient was 0.78 to 0.83, while the linear regression was between 0.65 to 0.75

  20. Satellite angular velocity estimation based on star images and optical flow techniques.

    Science.gov (United States)

    Fasano, Giancarmine; Rufino, Giancarlo; Accardo, Domenico; Grassi, Michele

    2013-09-25

    An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

  1. Satellite Angular Velocity Estimation Based on Star Images and Optical Flow Techniques

    Directory of Open Access Journals (Sweden)

    Giancarmine Fasano

    2013-09-01

    Full Text Available An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

  2. Mapping Pyroclastic Flow Inundation Using Radar and Optical Satellite Images and Lahar Modeling

    Directory of Open Access Journals (Sweden)

    Chang-Wook Lee

    2018-01-01

    Full Text Available Sinabung volcano, located above the Sumatra subduction of the Indo-Australian plate under the Eurasian plate, became active in 2010 after about 400 years of quiescence. We use ALOS/PALSAR interferometric synthetic aperture radar (InSAR images to measure surface deformation from February 2007 to January 2011. We model the observed preeruption inflation and coeruption deflation using Mogi and prolate spheroid sources to infer volume changes of the magma chamber. We interpret that the inflation was due to magma accumulation in a shallow reservoir beneath Mount Sinabung and attribute the deflation due to magma withdrawal from the shallow reservoir during the eruption as well as thermoelastic compaction of erupted material. The pyroclastic flow extent during the eruption is then derived from the LAHARZ model based on the coeruption volume from InSAR modeling and compared to that derived from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ image. The pyroclastic flow inundation extents between the two different methods agree at about 86%, suggesting the capability of mapping pyroclastic flow inundation by combing radar and optical imagery as well as flow modeling.

  3. Automatic Tracking and Characterization of Cumulonimbus Clouds from FY-2C Geostationary Meteorological Satellite Images

    Directory of Open Access Journals (Sweden)

    Yu Liu

    2014-01-01

    Full Text Available This paper presents an automated method to track cumulonimbus (Cb clouds based on cloud classification and characterizes Cb behavior from FengYun-2C (FY-2C. First, a seeded region growing (SRG algorithm is used with artificial neural network (ANN cloud classification as preprocessing to identify consistent homogeneous Cb patches from infrared images. Second, a cross-correlation-based approach is used to track Cb patches within an image sequence. Third, 7 pixel parameters and 19 cloud patch parameters of Cb are derived. To assess the performance of the proposed method, 8 cases exhibiting different life stages and the temporal evolution of a single case are analyzed. The results show that (1 the proposed method is capable of locating and tracking Cb until dissipation and can account for the eventual splitting or merging of clouds; (2 compared to traditional brightness temperature (TB thresholds-based cloud tracking methods, the proposed method reduces the uncertainty stemming from TB thresholds by classifying clouds with multichannel data in an advanced manner; and (3 the configuration and developmental stages of Cb that the method identifies are close to reality, suggesting that the characterization of Cb can provide detailed insight into the study of the motion and development of thunderstorms.

  4. Estimation of land surface temperature based on satellite image data. Paper no. IGEC-1-117

    Energy Technology Data Exchange (ETDEWEB)

    Torii, S. [Kumamoto Univ., Dept. of Mechanical Engineering and Materials Science, Kurokami, Kumamoto (Japan)]. E-mail: torii@mech.kumamoto-u.ac.jp; Yano, T.; Iino, N. [Kagoshima Univ., Dept. of Mechanical Engineering, Korimoto, Kagoshima (Japan)

    2005-07-01

    The aim of the present study is to predict a ground surface temperature (GST) of Kagoshima Prefecture in Kyushu Island, Japan, by using LANDSAT-5/TM and NOAA-11/AVHRR digital data. Image processing procedure is employed to aid in evaluating GST, in which the thermal images of AVHRR bands 4 and 5 are analysed. Emphasis is placed on the prediction accuracy of the existing atmospheric correlation equations taking the atmospheric attenuation effect into account, which are proposed by Tamba et. al., Bates and Diaz, and Sakkaida and Kawamura. It is disclosed that (I) the factor of the zenith angle need to be taken into account when the accurate GST is evaluated by using the atmospheric correction equations, (ii) that of Sakaida and Kawamura has better accuracy, (iii) LANDSAT-5/TM data contains a very high resolution level of the land, the estimated land surface temperature is higher than the measured value, and (iv) improved accuracy of the surface temperature is achieved if LANDSAT-5/TM data are used together with NOAA-11/AVHRR. (author)

  5. Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher

    2013-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

  6. Mononucleosis spot test

    Science.gov (United States)

    Monospot test; Heterophile antibody test; Heterophile agglutination test; Paul-Bunnell test; Forssman antibody test ... The mononucleosis spot test is done when symptoms of mononucleosis are ... Fatigue Fever Large spleen (possibly) Sore throat Tender ...

  7. A new generic method for the semi-automatic extraction of river and road networks in low and mid-resolution satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Grazzini, Jacopo [Los Alamos National Laboratory; Dillard, Scott [PNNL; Soille, Pierre [EC JRC

    2010-10-21

    This paper addresses the problem of semi-automatic extraction of road or hydrographic networks in satellite images. For that purpose, we propose an approach combining concepts arising from mathematical morphology and hydrology. The method exploits both geometrical and topological characteristics of rivers/roads and their tributaries in order to reconstruct the complete networks. It assumes that the images satisfy the following two general assumptions, which are the minimum conditions for a road/river network to be identifiable and are usually verified in low- to mid-resolution satellite images: (i) visual constraint: most pixels composing the network have similar spectral signature that is distinguishable from most of the surrounding areas; (ii) geometric constraint: a line is a region that is relatively long and narrow, compared with other objects in the image. While this approach fully exploits local (roads/rivers are modeled as elongated regions with a smooth spectral signature in the image and a maximum width) and global (they are structured like a tree) characteristics of the networks, further directional information about the image structures is incorporated. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the target network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given network seed with this metric is combined with hydrological operators for overland flow simulation to extract the paths which contain most line evidence and identify them with the target network.

  8. Superluminal Spot Pair Events in Astronomical Settings: Sweeping Beams

    Science.gov (United States)

    Nemiroff, Robert J.

    2015-02-01

    Sweeping beams of light can cast spots moving with superluminal speeds across scattering surfaces. Such faster-than-light speeds are well-known phenomena that do not violate special relativity. It is shown here that under certain circumstances, superluminal spot pair creation and annihilation events can occur that provide unique information to observers. These spot pair events are not particle pair events-they are the sudden creation or annihilation of a pair of relatively illuminated spots on a scattering surface. Real spot pair illumination events occur unambiguously on the scattering surface when spot speeds diverge, while virtual spot pair events are observer dependent and perceived only when real spot radial speeds cross the speed of light. Specifically, a virtual spot pair creation event will be observed when a real spot's speed toward the observer drops below c, while a virtual spot pair annihilation event will be observed when a real spot's radial speed away from the observer rises above c. Superluminal spot pair events might be found angularly, photometrically, or polarimetrically, and might carry useful geometry or distance information. Two example scenarios are briefly considered. The first is a beam swept across a scattering spherical object, exemplified by spots of light moving across Earth's Moon and pulsar companions. The second is a beam swept across a scattering planar wall or linear filament, exemplified by spots of light moving across variable nebulae including Hubble's Variable Nebula. In local cases where the sweeping beam can be controlled and repeated, a three-dimensional map of a target object can be constructed. Used tomographically, this imaging technique is fundamentally different from lens photography, radar, and conventional lidar.

  9. Laser experiments in light cloudiness with the geostationary satellite ARTEMIS

    Science.gov (United States)

    Kuzkov, V.; Kuzkov, S.; Sodnik, Z.

    2016-08-01

    The geostationary satellite ARTEMIS was launched in July 2001. The satellite is equipped with a laser communication terminal, which was used for the world's first inter-satellite laser communication link between ARTEMIS and the low earth orbit satellite SPOT-4. Ground-to-space laser communication experiments were also conducted under various atmospheric conditions involving ESA's optical ground station. With a rapidly increasing volume of information transferred by geostationary satellites, there is a rising demand for high-speed data links between ground stations and satellites. For ground-to-space laser communications there are a number of important design parameters that need to be addressed, among them, the influence of atmospheric turbulence in different atmospheric conditions and link geometries. The Main Astronomical Observatory of NAS of Ukraine developed a precise computer tracking system for its 0.7 m AZT-2 telescope and a compact laser communication package LACES (Laser Atmosphere and Communication experiments with Satellites) for laser communication experiments with geostationary satellites. The specially developed software allows computerized tracking of the satellites using their orbital data. A number of laser experiments between MAO and ARTEMIS were conducted in partial cloudiness with some amount of laser light observed through clouds. Such conditions caused high break-up (splitting) of images from the laser beacon of ARTEMIS. One possible explanation is Raman scattering of photons on molecules of a water vapor in the atmosphere. Raman scattering causes a shift in a wavelength of the photons.In addition, a different value for the refraction index appears in the direction of the meridian for the wavelength-shifted photons. This is similar to the anomalous atmospheric refraction that appears at low angular altitudes above the horizon. We have also estimated the atmospheric attenuation and the influence of atmospheric turbulence on observed results

  10. New on-orbit geometric interior parameters self-calibration approach based on three-view stereoscopic images from high-resolution multi-TDI-CCD optical satellites.

    Science.gov (United States)

    Cheng, Yufeng; Wang, Mi; Jin, Shuying; He, Luxiao; Tian, Yuan

    2018-03-19

    To increase the field of view (FOV), combining multiple time-delayed and integrated charge-coupled devices (TDI-CCD) into the camera and the pushbroom imaging modality are traditionally used with high-resolution optical satellites. It is becoming increasingly labor- and cost-intensive to build and maintain a calibration field with high resolution and broad coverage. This paper introduces a simple and feasible on-orbit geometric self-calibration approach for high-resolution multi-TDI-CCD optical satellites based on three-view stereoscopic images. With the aid of the a priori geometric constraint of tie points in the triple-overlap regions of stereoscopic images, as well as tie points between adjacent single TDI-CCD images (STIs), high accuracy calibration of all TDI-CCD detectors can be achieved using a small number of absolute ground control points (GCPs) covering the selected primary STI. This method greatly reduces the demand on the calibration field and thus is more time-, effort- and cost-effective. Experimental results indicated that the proposed self-calibration approach is effective for increasing the relative internal accuracy without the limitations associated with using a traditional reference calibration field, which could have great significance for future super-high-resolution optical satellites.

  11. Analyzing the Variation of Building Density Using High Spatial Resolution Satellite Images: the Example of Shanghai City

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2008-04-01

    Full Text Available Building density is an important issue in urban planning and land management. In the article, building coverage ratio (BCR and floor area ratio (FAR values extracted from high resolution satellite images were used to indicate buildings’ stretching on the surface and growth along the third dimension within areas of interest in Shanghai City, P.R. China. The results show that the variation of FAR is higher than that of BCR in the inner circle, and that the newer commercial centers have higher FAR and lower BCR values, while the traditional commercial areas have higher FAR and BCR ratios. By comparing different residential areas, it was found that the historical “Shikumen” areas and the old residential areas built before 1980s have higher BCR and lower FAR, while the new residential areas have higher FAR and lower BCR, except for the villa areas. These results suggest that both older building areas and villa areas use land resources in an inefficient way, and therefore better planning and management of urban land are needed for those fast economic growing regions.

  12. 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.

  13. Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

    Directory of Open Access Journals (Sweden)

    MARIA IOANA VLAD

    2011-01-01

    Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

  14. Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

    Science.gov (United States)

    Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

    2017-05-01

    Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.

  15. Geological and Structural Inferences from Satellite Images in Parts of Deccan basalt covered regions of Central India

    Science.gov (United States)

    Harinarayana, Tirumalachetty; Borra, Veeraiah; Basava, Sharana; Suryabali, Singh

    In search of new areas for hydrocarbon exploration, integrated ground geophysical studies have been taken up in Central India with seismic, magnetotellurics, deep resistivity and gravity surveys. Since the region is covered with basalt and well known for its intensive tectonic activity, remote sensing method seems to have value addition to the subsurface information derived from geophysical, geological and tectonic studies. The Narmada and Tapti rift zone and Deccan basalt covered regions of Central India, stems from its complexity. A Resourcesat-1 (IRS- P6) LISS-III satellite images covering an area of approximately 250,000 sq. km corresponding to the region in and around Baroda(Vadodara), Indore, Nandurbar, Khandwa, Akot, Nasik, Aurangabad, Pune and Latur in Central India was digitally processed and interpreted to present a schematic map of the geology and elucidate the structural fabric of the region. From our study, the disposition of the intensive dyke system, various faults and other lineaments in the region are delineated. Ground truth studies have shown good correlation with lineaments/dykes indicated in remote sensing studies and have revealed distinct ENE-WSW trending lineaments, dykes which are more prominent near the Narmada and Tapti river course. Evolution of these features with Deccan volcanism is discussed with available geochronological data set. These findings are significant in relation to structural data and form a part of the geo-structural database for ground surveys.

  16. A Conceptual Model of Surface Reflectance Estimation for Satellite Remote Sensing Images Using in situ Reference Data

    Directory of Open Access Journals (Sweden)

    Ke-Sheng Cheng

    2012-03-01

    Full Text Available For satellite remote sensing, radiances received at the sensor are not only affected by the atmosphere but also by the topographic properties of the terrain surface. As a result, atmospheric correction alone does not yield output images that truly reflect terrain surface properties, namely surface reflectance (bidirectional reflectance factor, BRF of objects on the earth surface. Following the concept of the radiometric control area (RCA-based path radiance estimation method, we herein propose a statistical approach for surface reflectance estimation utilizing DEM data and surface reflectance of selected radiometric control areas. An algorithm for identification of shaded samples and a shape factor model were also developed in this study. The proposed RCA-based surface reflectance estimation method is capable of achieving good reflectance estimates in a region where elevation varies from 0 to approximately 600 m above the mean sea level. However, further study is recommended in order to extend the application of the proposed method to areas with substantial terrain variation.

  17. Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations

    Science.gov (United States)

    Vaughan, R. Greg; Heasler, Henry; Jaworowski, Cheryl; Lowenstern, Jacob B.; Keszthelyi, Laszlo P.

    2014-01-01

    Maps that define the current distribution of geothermally heated ground are useful toward setting a baseline for thermal activity to better detect and understand future anomalous hydrothermal and (or) volcanic activity. Monitoring changes in the dynamic thermal areas also supports decisions regarding the development of Yellowstone National Park infrastructure, preservation and protection of park resources, and ensuring visitor safety. Because of the challenges associated with field-based monitoring of a large, complex geothermal system that is spread out over a large and remote area, satellite-based thermal infrared images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to map the location and spatial extent of active thermal areas, to generate thermal anomaly maps, and to quantify the radiative component of the total geothermal heat flux. ASTER thermal infrared data acquired during winter nights were used to minimize the contribution of solar heating of the surface. The ASTER thermal infrared mapping results were compared to maps of thermal areas based on field investigations and high-resolution aerial photos. Field validation of the ASTER thermal mapping is an ongoing task. The purpose of this report is to make available ASTER-based maps of Yellowstone’s thermal areas. We include an appendix containing the names and characteristics of Yellowstone’s thermal areas, georeferenced TIFF files containing ASTER thermal imagery, and several spatial data sets in Esri shapefile format.

  18. ANALYSIS OF IN-SITU SPECTRAL REFLECTANCE OF SAGO AND OTHER PALMS: IMPLICATIONS FOR THEIR DETECTION IN OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    J. R. Santillan

    2018-04-01

    Full Text Available We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345–1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2. Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

  19. Combination of Satellite Images and Numerical Model for the State Followed the Coast of the Bay of Bejaia-Jijel

    Directory of Open Access Journals (Sweden)

    Bachari Nour El Islam

    2017-03-01

    Full Text Available Bay of Bejaia-Jijel extends over a length of 100 km with the presence of the ports, the beaches of rivers that discharge of the bay. This area characterized by strong economic activity, namely tourism and fisheries. However, severe erosion, high hydrodynamic activity and significant silting of ports affect this bay. Hence, the interest of this study, which tries to explain these phenomena, based on multisource data with multitasking models. First, we developed an algorithm that can convert satellite images in coastline vector. This technique applied to three images LANDSAT TM and OLI sensed in 1987, 2011; 2015. The multi-temporal monitoring coastlines show that the region suffered severe erosion. This erosion is 4.6 m / year for the period of 1987/2011 and 1.5 m / year for the period 2011/2015. To explain this phenomenon we interested to do a study of hydrodynamics using the SWAN software. We used a long time series of wind speed and direction to discern extreme cases in the region. For maximum wind, the significant wave height recorded very high values and a very active orbital current with a speed that exceeds 0.7 m / s. Numerical modelling has allowed us to explain the erosion but does not explain the speed difference coastline. To find the explanation of erosion speed difference between the two periods