Sample records for satellite images depends

  1. Geostationary Satellite (GOES) Images (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...

  2. Biogeography based Satellite Image Classification

    CERN Document Server

    Panchal, V K; Kaur, Navdeep; Kundra, Harish


    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  3. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

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


    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....

  4. Shadow imaging of geosynchronous satellites (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

  5. Smoothing of Fused Spectral Consistent Satellite Images

    DEFF Research Database (Denmark)

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


    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...

  6. Satellite imager calibration and validation

    CSIR Research Space (South Africa)

    Vhengani, L


    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. Forecasting Hurricane by Satellite Image (United States)

    Liu, M. Y.

    Earth is an endanger planet. Severe weather, especially hurricanes, results in great disaster all the world. World Meteorology Organization and United Nations Environment Program established intergovernment Panel on Climate Change (IPCC) to offer warnings about the present and future disasters of the Earth. It is the mission for scientists to design warning system to predict the severe weather system and to reduce the damage of the Earth. Hurricanes invade all the world every year and made millions damage to all the people. Scientists in weather service applied satellite images and synoptic data to forecast the information for the next hours for warning purposes. Regularly, hurricane hits on Taiwan island directly will pass through her domain and neighbor within 10 hours. In this study, we are going to demonstrate a tricky hurricane NARI invaded Taiwan on September 16, 2000. She wandered in the neighborhood of the island more than 72 hours and brought heavy rainfall over the island. Her track is so tricky that scientists can not forecast her path using the regular method. Fortunately, all scientists in the Central Weather Bureau paid their best effort to fight against the tricky hurricane. Applying the new developed technique to analysis the satellite images with synoptic data and radar echo, scientists forecasted the track, intensity and rainfall excellently. Thus the damage of the severe weather reduced significantly.

  8. 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...


    Directory of Open Access Journals (Sweden)

    P. Kupidura


    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. Automatic Approach to Vhr Satellite Image Classification (United States)

    Kupidura, P.; Osińska-Skotak, K.; Pluto-Kossakowska, J.


    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 preliminary step

  11. Structural High-resolution Satellite Image Indexing


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


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

  12. Model-based satellite image fusion

    DEFF Research Database (Denmark)

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


    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...

  13. Low-Cost Satellite Infrared Imager Study (United States)


    2,297.00 10 MATLAB , Simulink , Symbolic Math Toolbox (2 ea @ £894) £1,788.00 11 MATLAB Image Processing Toolbox (2 ea at £192) £384.00 12 MATLAB ...Figure 1: MWIR and TIR satellite imagery. On the left is a BIRD image of forest fires on the Portuguese/ Spanish border3 and the image on right MWIR and TIR imagers, instrument engineers are continually evaluating advances in the miniaturization of detector technology. One

  14. Haystack Ultrawideband Satellite Imaging Radar (United States)


    enable long-range imaging. In 2013, a major upgrade to the facility was completed, adding a millimeter - wave W-band radar capability to Haystack’s X...diameter antenna was completely rebuilt to provide a 100 μm root-mean-square (rms) surface accuracy to support operation at the 3 mm wave - length (W...electromagnetic wave propagation through the troposphere. − The signal processing system lev- eraged Lincoln Laboratory‘s Radar Open Systems

  15. Change detection in satellite images (United States)

    Thonnessen, U.; Hofele, G.; Middelmann, W.


    Change detection plays an important role in different military areas as strategic reconnaissance, verification of armament and disarmament control and damage assessment. It is the process of identifying differences in the state of an object or phenomenon by observing it at different times. The availability of spaceborne reconnaissance systems with high spatial resolution, multi spectral capabilities, and short revisit times offer new perspectives for change detection. Before performing any kind of change detection it is necessary to separate changes of interest from changes caused by differences in data acquisition parameters. In these cases it is necessary to perform a pre-processing to correct the data or to normalize it. Image registration and, corresponding to this task, the ortho-rectification of the image data is a further prerequisite for change detection. If feasible, a 1-to-1 geometric correspondence should be aspired for. Change detection on an iconic level with a succeeding interpretation of the changes by the observer is often proposed; nevertheless an automatic knowledge-based analysis delivering the interpretation of the changes on a semantic level should be the aim of the future. We present first results of change detection on a structural level concerning urban areas. After pre-processing, the images are segmented in areas of interest and structural analysis is applied to these regions to extract descriptions of urban infrastructure like buildings, roads and tanks of refineries. These descriptions are matched to detect changes and similarities.

  16. Internal waves and vortices in satellite images

    CERN Document Server

    Sparavigna, Amelia Carolina


    Some recent papers proposed the use of the satellite images of Google Earth in teaching physics, in particular to see some behaviours of waves. Reflection, refraction, diffraction and interference are easy to be found in these satellite maps. Besides Google Earth, other sites exist, such as Earth Observatory or Earth Snapshot, suitable for illustrating the large-scale phenomena in atmosphere and oceans In this paper, we will see some examples for teaching surface and internal sea waves, and internal waves and the K\\'arm\\'an vortices in the atmosphere. Aim of this proposal is attracting the interest of students of engineering schools to the physics of waves.

  17. AO corrected satellite imaging from Mount Stromlo (United States)

    Bennet, F.; Rigaut, F.; Price, I.; Herrald, N.; Ritchie, I.; Smith, C.


    The Research School of Astronomy and Astrophysics have been developing adaptive optics systems for space situational awareness. As part of this program we have developed satellite imaging using compact adaptive optics systems for small (1-2 m) telescopes such as those operated by Electro Optic Systems (EOS) from the Mount Stromlo Observatory. We have focused on making compact, simple, and high performance AO systems using modern high stroke high speed deformable mirrors and EMCCD cameras. We are able to track satellites down to magnitude 10 with a Strehl in excess of 20% in median seeing.

  18. Antarctica: measuring glacier velocity from satellite images. (United States)

    Lucchitta, B K; Ferguson, H M


    Many Landsat images of Antarctica show distinctive flow and crevasse features in the floating part of ice streams and outlet glaciers immediately below their grounding zones. Some of the features, which move with the glacier or ice stream, remain visible over many years and thus allow time-lapse measurements of ice velocities. Measurements taken from Landsat images of features on Byrd Glacier agree well with detailed ground and aerial observations. The satellite-image technique thus offers a rapid and cost-effective method of obtaining average velocities, to a first order of accuracy, of many ice streams and outlet glaciers near their termini.

  19. A neuromorphic approach to satellite image understanding (United States)

    Partsinevelos, Panagiotis; Perakakis, Manolis


    Remote sensing satellite imagery provides high altitude, top viewing aspects of large geographic regions and as such the depicted features are not always easily recognizable. Nevertheless, geoscientists familiar to remote sensing data, gradually gain experience and enhance their satellite image interpretation skills. The aim of this study is to devise a novel computational neuro-centered classification approach for feature extraction and image understanding. Object recognition through image processing practices is related to a series of known image/feature based attributes including size, shape, association, texture, etc. The objective of the study is to weight these attribute values towards the enhancement of feature recognition. The key cognitive experimentation concern is to define the point when a user recognizes a feature as it varies in terms of the above mentioned attributes and relate it with their corresponding values. Towards this end, we have set up an experimentation methodology that utilizes cognitive data from brain signals (EEG) and eye gaze data (eye tracking) of subjects watching satellite images of varying attributes; this allows the collection of rich real-time data that will be used for designing the image classifier. Since the data are already labeled by users (using an input device) a first step is to compare the performance of various machine-learning algorithms on the collected data. On the long-run, the aim of this work would be to investigate the automatic classification of unlabeled images (unsupervised learning) based purely on image attributes. The outcome of this innovative process is twofold: First, in an abundance of remote sensing image datasets we may define the essential image specifications in order to collect the appropriate data for each application and improve processing and resource efficiency. E.g. for a fault extraction application in a given scale a medium resolution 4-band image, may be more effective than costly

  20. Imaging artificial satellites: An observational challenge (United States)

    Smith, D. A.; Hill, D. C.


    According to the Union of Concerned Scientists, as of the beginning of 2016 there are 1381 active satellites orbiting the Earth, and the United States' Space Surveillance Network tracks about 8000 manmade orbiting objects of baseball-size and larger. NASA estimates debris larger than 1 cm to number more than half a million. The largest ones can be seen by eye—unresolved dots of light that move across the sky in minutes. For most astrophotographers, satellites are annoying streaks that can ruin hours of work. However, capturing a resolved image of an artificial satellite can pose an interesting challenge for a student, and such a project can provide connections between objects in the sky and commercial and political activities here on Earth.

  1. BMP signaling regulates satellite cell-dependent postnatal muscle growth. (United States)

    Stantzou, Amalia; Schirwis, Elija; Swist, Sandra; Alonso-Martin, Sonia; Polydorou, Ioanna; Zarrouki, Faouzi; Mouisel, Etienne; Beley, Cyriaque; Julien, Anaïs; Le Grand, Fabien; Garcia, Luis; Colnot, Céline; Birchmeier, Carmen; Braun, Thomas; Schuelke, Markus; Relaix, Frédéric; Amthor, Helge


    Postnatal growth of skeletal muscle largely depends on the expansion and differentiation of resident stem cells, the so-called satellite cells. Here, we demonstrate that postnatal satellite cells express components of the bone morphogenetic protein (BMP) signaling machinery. Overexpression of noggin in postnatal mice (to antagonize BMP ligands), satellite cell-specific knockout of Alk3 (the gene encoding the BMP transmembrane receptor) or overexpression of inhibitory SMAD6 decreased satellite cell proliferation and accretion during myofiber growth, and ultimately retarded muscle growth. Moreover, reduced BMP signaling diminished the adult satellite cell pool. Abrogation of BMP signaling in satellite cell-derived primary myoblasts strongly diminished cell proliferation and upregulated the expression of cell cycle inhibitors p21 and p57 In conclusion, these results show that BMP signaling defines postnatal muscle development by regulating satellite cell-dependent myofiber growth and the generation of the adult muscle stem cell pool. © 2017. Published by The Company of Biologists Ltd.

  2. Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

    DEFF Research Database (Denmark)

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


    Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...... based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method....

  3. Monitoring of wetlands Ecosystems using satellite images (United States)

    Dabrowska-Zielinska, K.; Gruszczynska, M.; Yesou, H.; Hoscilo, A.

    Wetlands are very sensitive ecosystems, functioning as habitat for many organisms. Protection and regeneration of wetlands has been the crucial importance in ecological research and in nature conservation. Knowledge on biophysical properties of wetlands vegetation retrieved from satellite images will enable us to improve monitoring of these unique areas, very often impenetrable. The study covers Biebrza wetland situated in the Northeast part of Poland and is considered as Ramsar Convention test site. The research aims at establishing of changes in biophysical parameters as the scrub encroachment, lowering of the water table, and changes of the farming activity caused ecological changes at these areas. Data from the optical and microwave satellite images collected for the area of Biebrza marshland ecosystem have been analysed and compared with the detailed soil-vegetation ground measurements conducted in conjunction with the overflights. Satellite data include Landsat ETM, ERS-2 ATSR and SAR, SPOT VEGETATION, ENVISAT MERIS and ASAR, and NOAA AVHRR. From the optical data various vegetation indices have been calculated, which characterize the vegetation surface roughness, its moisture conditions and stage of development. Landsat ETM image has been used for classification of wetlands vegetation. For each class of vegetation various moisture indices have been developed. Ground data collected include wet and dry biomass, LAI, vegetation height, and TDR soil moisture. The water cloud model has been applied for retrieval of soil vegetation parameters taking into account microwave satellite images acquired at VV, HV and HH polarisations at different viewing angles. The vegetation parameters have been used for to distinguish changes, which occurred at the area. For each of the vegetation class the soil moisture was calculated from microwave data using developed algorithms. Results of this study will help mapping and monitoring wetlands with the high spatial and temporal

  4. Developing Geostationary Satellite Imaging at Lowell Observatory (United States)

    van Belle, G.


    Lowell Observatory operates the Navy Precision Optical Interferometer (NPOI), and owns & operates the Discovery Channel Telescope (DCT). This unique & necessary combination of facilities positions Lowell to develop a robust program of observing geostationary, GPS-plane, and other high-altitude (&1000mi) satellites. NPOI is a six-beam long-baseline optical interferometer, located in Flagstaff, Arizona; the facility is supported by a partnership between Lowell Observatory, the US Naval Observatory, and the Naval Research Laboratory. NPOI operates year-round in the visible with baselines between 8 and 100 meters (up to 432m is available), conducting programs of astronomical research and imaging technology development. NPOI is the only such facility as yet to directly observe geostationary satellites, enabling milliarcsecond resolution of these objects. To enhance this capability towards true imaging of geosats, an ongoing program of facility upgrades will be outlined. These upgrades include AO-assisted 1.0-m apertures feeding each beam line, and new near-infrared instrumentation on the back end. The large apertures will enable `at-will' observations of objects brighter than mK = 8:3 in the near-IR, corresponding to brighter than mV = 11:3 in the visible. At its core, the system is enabled by a `wavelength-baseline bootstrapping' approach discussed herein. A complementary pilot imaging study of visible speckle and aperture masked imaging at Lowell's 4.3-m DCT, for constraining the low-spatial frequency imaging information, is also outlined.

  5. Embedded Implementation of VHR Satellite Image Segmentation. (United States)

    Li, Chao; Balla-Arabé, Souleymane; Ginhac, Dominique; Yang, Fan


    Processing and analysis of Very High Resolution (VHR) satellite images provide a mass of crucial information, which can be used for urban planning, security issues or environmental monitoring. However, they are computationally expensive and, thus, time consuming, while some of the applications, such as natural disaster monitoring and prevention, require high efficiency performance. Fortunately, parallel computing techniques and embedded systems have made great progress in recent years, and a series of massively parallel image processing devices, such as digital signal processors or Field Programmable Gate Arrays (FPGAs), have been made available to engineers at a very convenient price and demonstrate significant advantages in terms of running-cost, embeddability, power consumption flexibility, etc. In this work, we designed a texture region segmentation method for very high resolution satellite images by using the level set algorithm and the multi-kernel theory in a high-abstraction C environment and realize its register-transfer level implementation with the help of a new proposed high-level synthesis-based design flow. The evaluation experiments demonstrate that the proposed design can produce high quality image segmentation with a significant running-cost advantage.

  6. System refinement for content based satellite image retrieval

    Directory of Open Access Journals (Sweden)

    NourElDin Laban


    Full Text Available We are witnessing a large increase in satellite generated data especially in the form of images. Hence intelligent processing of the huge amount of data received by dozens of earth observing satellites, with specific satellite image oriented approaches, presents itself as a pressing need. Content based satellite image retrieval (CBSIR approaches have mainly been driven so far by approaches dealing with traditional images. In this paper we introduce a novel approach that refines image retrieval process using the unique properties to satellite images. Our approach uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tiling sizes. Accordingly the system uses these multilevel features within a multilevel retrieval system that refines the retrieval process. Our multilevel refinement approach has been experimentally validated against the conventional one yielding enhanced precision and recall rates.


    Directory of Open Access Journals (Sweden)

    Catherine Mering


    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.

  8. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang


    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...... on a seven-year ERS-1 and a four-year ERS-2 time series, the long term stability is found to be sufficient to allow a single calibration covering the entire mission period. A descending and an ascending orbit tandem pair of the ESA calibration site on Flevoland, suitable for calibration of ERS SAR processors...

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

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

  11. Polar-Orbiting Satellite (POES) Images (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...

  12. Moving Target Information Extraction Based on Single Satellite Image

    Directory of Open Access Journals (Sweden)

    ZHAO Shihu


    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.


    Directory of Open Access Journals (Sweden)

    A. H. Ahrari


    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.

  14. Images of war: using satellite images for human rights monitoring in Turkish Kurdistan. (United States)

    de Vos, Hugo; Jongerden, Joost; van Etten, Jacob


    In areas of war and armed conflict it is difficult to get trustworthy and coherent information. Civil society and human rights groups often face problems of dealing with fragmented witness reports, disinformation of war propaganda, and difficult direct access to these areas. Turkish Kurdistan was used as a case study of armed conflict to evaluate the potential use of satellite images for verification of witness reports collected by human rights groups. The Turkish army was reported to be burning forests, fields and villages as a strategy in the conflict against guerrilla uprising. This paper concludes that satellite images are useful to validate witness reports of forest fires. Even though the use of this technology for human rights groups will depend on some feasibility factors such as prices, access and expertise, the images proved to be key for analysis of spatial aspects of conflict and valuable for reconstructing a more trustworthy picture.

  15. Classification of Pansharpened Urban Satellite Images

    DEFF Research Database (Denmark)

    Palsson, Frosti; Sveinsson, Johannes R.; Benediktsson, Jon Atli


    The classification of high resolution urban remote sensing imagery is addressed with the focus on classification of imagery that has been pansharpened by a number of different pansharpening methods. The pansharpening process introduces some spectral and spatial distortions in the resulting fused...... multispectral image, the amount of which highly varies depending on which pansharpening technique is used. In the majority of the pansharpening techniques that have been proposed, there is a compromise between the spatial enhancement and the spectral consistency. Here we study the effects of the spectral...... information from the panchromatic data. Random Forests (RF) and Support Vector Machines (SVM) will be used as classifiers. Experiments are done for three different datasets that have been obtained by two different imaging sensors, IKONOS and QuickBird. These sensors deliver multispectral images that have four...

  16. Satellite image eavesdropping: a multidisciplinary science education project

    Energy Technology Data Exchange (ETDEWEB)

    Friedt, Jean-Michel [Association Projet Aurore, UFR-ST La Bouloie, 16, route de Gray, 25030 Besancon Cedex (France)


    Amateur reception of satellite images gathers a wide number of concepts and technologies which makes it attractive as an educational tool. We here introduce the reception of images emitted from NOAA series low-altitude Earth-orbiting satellites. We tackle various issues including the identification and prediction of the pass time of visible satellites, the building of the radio-frequency receiver and antenna after modelling their radiation pattern, and then the demodulation of the resulting audio signal for finally displaying an image of the Earth as seen from space.

  17. Dependent surveillance through an experimental satellite data link system (United States)

    Cobley, G. A.

    The development and testing of an experimental dependent aircraft-surveillance system using a satellite data link is reported. In this system, the aircraft position is determined onboard using GPS or inertial navigation, enclosed in a message block using a data-link system, and transmitted to an Inmarsat GEO communication satellites; the ground station receives and analyzes the data to keep constant track of the aircraft position. The hardware implementation and the results of demonstrations performed on flights from Iowa to Wisconsin and the North Atlantic are discussed, and diagrams and maps are provided.

  18. Velocity estimation of an airplane through a single satellite image

    Institute of Scientific and Technical Information of China (English)

    Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li


    The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

  19. Satellite image collection modeling for large area hazard emergency response (United States)

    Liu, Shufan; Hodgson, Michael E.


    Timely collection of critical hazard information is the key to intelligent and effective hazard emergency response decisions. Satellite remote sensing imagery provides an effective way to collect critical information. Natural hazards, however, often have large impact areas - larger than a single satellite scene. Additionally, the hazard impact area may be discontinuous, particularly in flooding or tornado hazard events. In this paper, a spatial optimization model is proposed to solve the large area satellite image acquisition planning problem in the context of hazard emergency response. In the model, a large hazard impact area is represented as multiple polygons and image collection priorities for different portion of impact area are addressed. The optimization problem is solved with an exact algorithm. Application results demonstrate that the proposed method can address the satellite image acquisition planning problem. A spatial decision support system supporting the optimization model was developed. Several examples of image acquisition problems are used to demonstrate the complexity of the problem and derive optimized solutions.

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

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

  2. Spatial Cloud Detection and Retrieval System for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ayman Nasr


    Full Text Available In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection. Satellite images having a large percentage of cloud cannot be used in further analysis. While there are many approaches that deal with different semantic meaning, there are rarely approaches that deal specifically with cloud detection and retrieval. In this paper we introduce a novel approach that spatially detect and retrieve clouds in satellite images using their unique properties .Our approach is developed as spatial cloud detection and retrieval system (SCDRS that introduce a complete framework for specific semantic retrieval system. It uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tile sizes using spatial and textural properties of cloud regions. Second, we retrieve our tiles using a parametric statistical approach within a multilevel refinement process. Our approach has been experimentally validated against the conventional ones yielding enhanced precision and recall rates in the same time it gives more precise detection of cloud coverage regions.

  3. Satellite image time series simulation for environmental monitoring (United States)

    Guo, Tao


    The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

  4. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

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


    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......’s Master Environmental Library. At CLS the a priori wind direction is taken from the ECMWF (European Centre of Medium-range Weather Forecasting). It is also possible to use other sources of wind direction e.g. the satellite-based ASCAT wind directions as demonstrated by CLS. The wind direction has to known...

  5. Very high resolution satellite data: New challenges in image analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...

  6. Geospatial Visualization of Global Satellite Images with Vis-EROS

    Energy Technology Data Exchange (ETDEWEB)

    Standart, G. D.; Stulken, K. R.; Zhang, Xuesong; Zong, Ziliang


    The Earth Resources Observation and Science (EROS) Center of U.S. Geological Survey is currently managing and maintaining the world largest satellite images distribution system, which provides 24/7 free download service for researchers all over the globe in many areas such as Geology, Hydrology, Climate Modeling, and Earth Sciences. A large amount of geospatial data contained in satellite images maintained by EROS is generated every day. However, this data is not well utilized due to the lack of efficient data visualization tools. This software implements a method for visualizing various characteristics of the global satellite image download requests. More specifically, Keyhole Markup Language (KML) files are generated which can be loaded into an earth browser such as Google Earth. Colored rectangles associated with stored satellite scenes are painted onto the earth browser; and the color and opacity of each rectangle is varied as a function of the popularity of the corresponding satellite image. An analysis of the geospatial information obtained relative to specified time constraints provides an ability to relate image download requests to environmental, political, and social events.

  7. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee


    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.

  8. Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis (United States)

    Potter, Christopher S.


    Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).

  9. The best printing methods to print satellite images

    Directory of Open Access Journals (Sweden)

    G.A. Yousif


    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.

  10. Vehicle Detection and Classification from High Resolution Satellite Images (United States)

    Abraham, L.; Sasikumar, M.


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

  11. Comparison of Satellite Image Enhancement Techniques in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    K. Narasimhan


    Full Text Available In this study, a comparison of various existing satellite image resolution enhancement techniques in wavelet domain is done. Each method is analysed quantitatively and visually. There are various wavelet domain based methods such as Wavelet Zero Padding, Dual Tree-Complex Wavelet Transform, Discrete Wavelet Transform, Cycle Spinning and Undecimated Wavelet Transform. On the basis of analysis, the most efficient method is proposed. The algorithms take the low resolution image as the input image and then wavelet transformation using daubechies (db3 is used to decompose the input image into different sub band images containing high and low frequency component. Then these subband images along with the input image are interpolated followed by combining all these images to generate a new resolution enhanced image by an inverse process.

  12. Satellite Imaging with Adaptive Optics on a 1 M Telescope (United States)

    Bennet, F.; Price, I.; Rigaut, F.; Copeland, M.


    The Research School of Astronomy and Astrophysics at the Mount Stromlo Observatory in Canberra, Australia, have been developing adaptive optic (AO) systems for space situational awareness applications. We report on the development and demonstration of an AO system for satellite imaging using a 1 m telescope. The system uses the orbiting object as a natural guide star to measure atmospheric turbulence, and a deformable mirror to provide an optical correction. The AO system utilised modern, high speed and low noise EMCCD technology on both the wavefront sensor and imaging camera to achieve high performance, achieving a Strehl ratio in excess of 30% at 870 nm. Images are post processed with lucky imaging algorithms to further improve the final image quality. We demonstrate the AO system on stellar targets and Iridium satellites, achieving a near diffraction limited full width at half maximum. A specialised realtime controller allows our system to achieve a bandwidth above 100 Hz, with the wavefront sensor and control loop running at 2 kHz. The AO systems we are developing show how ground-based optical sensors can be used to manage the space environment. AO imaging systems can be used for satellite surveillance, while laser ranging can be used to determine precise orbital data used in the critical conjunction analysis required to maintain a safe space environment. We have focused on making this system compact, expandable, and versatile. We are continuing to develop this platform for other space situational awareness applications such as geosynchronous satellite astrometry, space debris characterisation, satellite imaging, and ground-to-space laser communication.

  13. Simultaneous Fusion and Denoising of Panchromatic and Multispectral Satellite Images (United States)

    Ragheb, Amr M.; Osman, Heba; Abbas, Alaa M.; Elkaffas, Saleh M.; El-Tobely, Tarek A.; Khamis, S.; Elhalawany, Mohamed E.; Nasr, Mohamed E.; Dessouky, Moawad I.; Al-Nuaimy, Waleed; Abd El-Samie, Fathi E.


    To identify objects in satellite images, multispectral (MS) images with high spectral resolution and low spatial resolution, and panchromatic (Pan) images with high spatial resolution and low spectral resolution need to be fused. Several fusion methods such as the intensity-hue-saturation (IHS), the discrete wavelet transform, the discrete wavelet frame transform (DWFT), and the principal component analysis have been proposed in recent years to obtain images with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for satellite images comprising both the IHS transform and the DWFT is proposed. This method tries to achieve the highest possible spectral and spatial resolutions with as small distortion in the fused image as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan images from Landsat-5, Spot, Landsat-7, and IKONOS satellites are used in this comparison. The effect of noise on the proposed hybrid fusion method as well as the traditional fusion methods is studied. Experimental results show the superiority of the proposed hybrid method to the traditional methods. The results show also that a wavelet denoising step is required when fusion is performed at low signal-to-noise ratios.

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

    Directory of Open Access Journals (Sweden)

    HAN Jie


    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.

  15. Autonomous Planetary 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz


    is discussed.Based on such features, 3-D representations may be compiled from two or more 2-D satellite images. The main purposes of such a mapping system are extraction of landing sites, objects of scientific interest and general planetary surveying. All data processing is performed autonomously onboard...

  16. Analytical models integrated with satellite images for optimized pest management (United States)

    The global field protection (GFP) was developed to protect and optimize pest management resources integrating satellite images for precise field demarcation with physical models of controlled release devices of pesticides to protect large fields. The GFP was implemented using a graphical user interf...

  17. Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations (United States)


    and the extent to which they cover the necessary portions of the UV plane . Once the photon counting noise becomes smaller than the UV coverage noise, ad...satellites,” in Proc. SPIE 4091, Imaging Technology and Telescopes, J. W. Bilbro, J. B. Breckinridge, R. A. Carreras , S. R. Czyzak, M. J. Eckart, R. D...SPIE 4091, Imaging Technology and Telescopes, J. W. Bilbro, J. B. Breckinridge, R. A. Carreras , S. R. Czyzak, M. J. Eckart, R. D. Fiete, and P. S

  18. 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz


    The aim of this project has been to implement a software system, that is able to create a 3-D reconstruction from two or more 2-D photographic images made from different positions. The height is determined from the disparity difference of the images. The general purpose of the system is mapping o......, where various methods have been tested in order to optimize the performance. The match results are used in the reconstruction part to establish a 3-D digital representation and finally, different presentation forms are discussed....

  19. The cradle of pyramids in satellite images

    CERN Document Server

    Sparavigna, Amelia Carolina


    We propose the use of image processing to enhance the Google Maps of some archaeological areas of Egypt. In particular we analyse that place which is considered the cradle of pyramids, where it was announced the discovery of a new pyramid by means of an infrared remote sensing.

  20. An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiao Ling


    Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

  1. Satellite images analysis for shadow detection and building height estimation (United States)

    Liasis, Gregoris; Stavrou, Stavros


    Satellite images can provide valuable information about the presented urban landscape scenes to remote sensing and telecommunication applications. Obtaining information from satellite images is difficult since all the objects and their surroundings are presented with feature complexity. The shadows cast by buildings in urban scenes can be processed and used for estimating building heights. Thus, a robust and accurate building shadow detection process is important. Region-based active contour models can be used for satellite image segmentation. However, spectral heterogeneity that usually exists in satellite images and the feature similarity representing the shadow and several non-shadow regions makes building shadow detection challenging. In this work, a new automated method for delineating building shadows is proposed. Initially, spectral and spatial features of the satellite image are utilized for designing a custom filter to enhance shadows and reduce intensity heterogeneity. An effective iterative procedure using intensity differences is developed for tuning and subsequently selecting the most appropriate filter settings, able to highlight the building shadows. The response of the filter is then used for automatically estimating the radiometric property of the shadows. The customized filter and the radiometric feature are utilized to form an optimized active contour model where the contours are biased to delineate shadow regions. Post-processing morphological operations are also developed and applied for removing misleading artefacts. Finally, building heights are approximated using shadow length and the predefined or estimated solar elevation angle. Qualitative and quantitative measures are used for evaluating the performance of the proposed method for both shadow detection and building height estimation.

  2. Using Satellite Images for Wireless Network Planing in Baku City (United States)

    Gojamanov, M.; Ismayilov, J.


    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 territory occupying the central part of the city in order to compile 3D digital maps. The images collected from the WorldView-2 satellite are 4-Band Bundle(Pan+MS1) stereo images. Such kind of imagery enable to automatically classificate some required

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

    Energy Technology Data Exchange (ETDEWEB)

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


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


    Directory of Open Access Journals (Sweden)

    T. Sree Sharmila


    Full Text Available Satellite images are corrupted by noise in its acquisition and transmission. The removal of noise from the image by attenuating the high frequency image components, removes some important details as well. In order to retain the useful information and improve the visual appearance, an effective denoising and resolution enhancement techniques are required. In this research, Hybrid Directional Lifting (HDL technique is proposed to retain the important details of the image and improve the visual appearance. The Discrete Wavelet Transform (DWT based interpolation technique is developed for enhancing the resolution of the denoised image. The performance of the proposed techniques are tested by Land Remote-Sensing Satellite (LANDSAT images, using the quantitative performance measure, Peak Signal to Noise Ratio (PSNR and computation time to show the significance of the proposed techniques. The PSNR of the HDL technique increases 1.02 dB compared to the standard denoising technique and the DWT based interpolation technique increases 3.94 dB. From the experimental results it reveals that newly developed image denoising and resolution enhancement techniques improve the image visual quality with rich textures.

  5. Identification of geostationary satellites using polarization data from unresolved images (United States)

    Speicher, Andy

    In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. Since resolved images of geosynchronous satellites are not technically feasible with current technology, another method of distinguishing space objects was explored that exploits the polarization signature from unresolved images. The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved images of geosynchronous satellites taken over various solar phase angles. Different collection geometries were used to evaluate the polarization contribution of solar arrays, thermal control materials, antennas, and the satellite bus as the solar phase angle changed. Since materials on space objects age due to the space environment, it was postulated that their polarization signature may change enough to allow discrimination of identical satellites launched at different times. The instrumentation used in this experiment was a United States Air Force Academy (USAFA) Department of Physics system that consists of a 20-inch Ritchey-Chretien telescope and a dual focal plane optical train fed with a polarizing beam splitter. A rigorous calibration of the system was performed that included corrections for pixel bias, dark current, and response. Additionally, the two channel polarimeter was calibrated by experimentally determining the Mueller matrix for the system and relating image intensity at the two cameras to Stokes parameters S0 and S1. After the system calibration, polarization data was collected during three nights on eight geosynchronous satellites built by various manufacturers and launched several years apart. Three pairs of the eight

  6. Convolutional neural network features based change detection in satellite images (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong


    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  7. High-Resolution Imaging of Asteroids/Satellites with AO (United States)

    Merline, William


    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).


    Directory of Open Access Journals (Sweden)

    H. Kim


    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.

  9. Panchromatic Satellite Image Classification for Flood Hazard Assessment

    Directory of Open Access Journals (Sweden)

    Ahmed Shaker


    Full Text Available The study aims to investigate the use of panchromatic (PAN satellite image data for flood hazard assessment with anaid of various digital image processing techniques. Two SPOT PAN satellite images covering part of the Nile River inEgypt were used to delineate the flood extent during the years 1997 and 1998 (before and after a high flood. Threeclassification techniques, including the contextual classifier, maximum likelihood classifier and minimum distanceclassifier, were applied to the following: 1 the original PAN image data, 2 the original PAN image data and grey-levelco-occurrence matrix texture created from the PAN data, and 3 the enhanced PAN image data using an edgesharpeningfilter. The classification results were assessed with reference to the results derived from manualdigitization and random checkpoints. Generally, the results showed improvement of the calculation of flood area whenan edge-sharpening filter was used. In addition, the maximum likelihood classifier yielded the best classificationaccuracy (up to 97% compared to the other two classifiers. The research demonstrates the benefits of using PANsatellite imagery as a potential data source for flood hazard assessment.

  10. Spacecraft design project: High temperature superconducting infrared imaging satellite (United States)


    The High Temperature Superconductor Infrared Imaging Satellite (HTSCIRIS) is designed to perform the space based infrared imaging and surveillance mission. The design of the satellite follows the black box approach. The payload is a stand alone unit, with the spacecraft bus designed to meet the requirements of the payload as listed in the statement of work. Specifications influencing the design of the spacecraft bus were originated by the Naval Research Lab. A description of the following systems is included: spacecraft configuration, orbital dynamics, radio frequency communication subsystem, electrical power system, propulsion, attitude control system, thermal control, and structural design. The issues of testing and cost analysis are also addressed. This design project was part of the course Advanced Spacecraft Design taught at the Naval Postgraduate School.

  11. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus


    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


    Directory of Open Access Journals (Sweden)

    Diego Correia Maia


    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

  13. Assessment of Satellite Images for Soil Salinity Studies

    Directory of Open Access Journals (Sweden)

    S.H. Sanaeinejad


    Full Text Available Soil salinity is one of the main environmental problems affecting extensive area in the world. There are some problems with traditional data collection methods for soil studies. Using the new methods and techniques such as remote sensing could overcome most of these problems. However using these data in areas with uncommon usages needed some researches to find the best calibration between the data and real situations in soil. This research was carried out using Landsat satellite images in Neyshabour area, North East of Iran. In order to prepare suitable learning samples for the image processing in this study, 300 locations were randomly selected in the area, among which 273 locations were finally selected as suitable surface soil samples. All samples were moved to laboratory and their electrical conductivity was measured. Six reflective bands of ETM+ satellite images taken from the study area in 2002 were used for the image processing analysis. Classification of different soil salinities was carried out using common algorithms of image classification based on the best composition bands and using statistical methods between soil salinity variables and digital numbers of the images to represent a suitable method. the research results showed that the reflective bands 7, 3, 4 and 1 are the best band composition for preparing the color composite images and for the classification of the salinity in this area. The highest coefficient of determination was R2=0.311 and R2=0.44 for saline and non-saline soil respectively using band 2 and 3 of the images at 5% significant level. Based on the results, it can be concluded that the potential of ETM+ images for delineation and identification of different soil salinity are limited.

  14. Authentication Scheme Based on Principal Component Analysis for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ashraf. K. Helmy


    Full Text Available This paper presents a multi-band wavelet image content authentication scheme for satellite images by incorporating the principal component analysis (PCA. The proposed schemeachieves higher perceptual transparency and stronger robustness. Specifically, the developed watermarking scheme can successfully resist common signal processing such as JPEG compression and geometric distortions such as cropping. In addition, the proposed scheme can be parameterized, thus resulting in more security. That is, an attacker may not be able to extract the embedded watermark if the attacker does not know the parameter.In an order to meet these requirements, the host image is transformed to YIQ to decrease the correlation between different bands, Then Multi-band Wavelet transform (M-WT is applied to each channel separately obtaining one approximate sub band and fifteen detail sub bands. PCA is then applied to the coefficients corresponding to the same spatial location in all detail sub bands. The last principle component band represents an excellent domain forinserting the water mark since it represents lowest correlated features in high frequency area of host image.One of the most important aspects of satellite images is spectral signature, the behavior of different features in different spectral bands, the results of proposed algorithm shows that the spectral stamp for different features doesn't tainted after inserting the watermark.

  15. Formal correctness, safety, dependability, and performance analysis of a satellite

    NARCIS (Netherlands)

    Esteve, M.-A.; Katoen, J.P.; Nguyen, V.Y.; Postma, B.; Yushstein, Y.


    This paper reports on the usage of a broad palette of formal modeling and analysis techniques on a regular industrial-size design of an ultra-modern satellite platform. These efforts were carried out in parallel with the conventional software development of the satellite platform. The model itself i

  16. Detection of Burn Area and Severity with MODIS Satellite Images and Spatial Autocorrelation Techniques (United States)

    Kaya, S.; Kavzoglu, T.; Tonbul, H.


    Effects of forest fires and implications are one of the most important natural disasters all over the world. Statistical data observed that forest fires had a variable structure in the last century in Turkey, but correspondingly the population growth amount of forest fires and burn area increase widely in recent years. Depending on this, erosion, landslides, desertification and mass loss come into existence. In addition; after forest fires, renewal of forests and vegetation are very important for land management. Classic methods used for detection of burn area and severity requires a long and challenging process due to time and cost factors. Thanks to advanced techniques used in the field of Remote Sensing, burn area and severity can be determined with high detail and precision. The purpose of this study based on blending MODIS (Moderate Resolution Imaging Spectradiometer) satellite images and spatial autocorrelation techniques together, thus detect burn area and severity absolutely. In this context, spatial autocorrelation statistics like Moran's I and Get is-Ord Local Gi indexes were used to measure and analyze to burned area characteristics. Prefire and postfire satellite images were used to determine fire severity depending on spectral indexes corresponding to biomass loss and carbon emissivity intensities. Satellite images have used for identification of fire damages and risks in terms of fire management for a long time. This study was performed using prefire and postfire satellite images and spatial autocorrelation techniques to determining and analyzing forest fires in Antalya, Turkey region which serious fires occurred. In this context, this approach enables the characterization of distinctive texture of burned area and helps forecasting more precisely. Finally, it is observed that mapping of burned area and severity could be performed from local scale to national scale. Key Words: Spatial autocorrelation, MODIS, Fire, Burn Severity

  17. Analysis of Galileo Style Geostationary Satellite Imaging: Image Reconstruction (United States)


    obtained using only baselines longer than 8 m does not sample the short spacial frequencies, and the image reconstruction is not able to recover the...the long spacial frequencies sampled in a shorter baseline overlap the short spacial frequencies sampled in a longer baseline. This technique will

  18. Soil salinity detection from satellite image analysis: an integrated approach of salinity indices and field data. (United States)

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


    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.

  19. Path planning on satellite images for unmanned surface vehicles

    Directory of Open Access Journals (Sweden)

    Joe-Ming Yang


    Full Text Available In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A * algorithm (FAA *, an advanced A * algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV

  20. NNIC—neural network image compressor for satellite positioning system (United States)

    Danchenko, Pavel; Lifshits, Feodor; Orion, Itzhak; Koren, Sion; Solomon, Alan D.; Mark, Shlomo


    We have developed an algorithm, based on novel techniques of data compression and neural networks for the optimal positioning of a satellite. The algorithm is described in detail, and examples of its application are given. The heart of this algorithm is the program NNIC—neural network image compressor. This program was developed for compression color and grayscale images with artificial neural networks (ANNs). NNIC applies three different methods for compression. Two of them are based on neural networks architectures—multilayer perceptron and kohonen network. The third is based on a widely used method of discrete cosine transform, the basis for the JPEG standard. The program also serves as a tool for determining numerical and visual quality parameters of compression and comparison between different methods. A number of advantages and disadvantages of the compression using ANNs were discovered in the course of the present research, some of them presented in this report. The thrust of the report is the discussion of ANNs implementation problems for modern platforms, such as a satellite positioning system that include intensive image flowing and processing.

  1. An entropy-based approach to automatic image segmentation of satellite images

    CERN Document Server

    Barbieri, A L; Rodrigues, F A; Bruno, O M; Costa, L da F


    An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.

  2. Image Processing Technique for Automatic Detection of Satellite Streaks (United States)


    satellites actifs et d’autres débris doivent être contrôlées. Dans ces cas, les paramètres orbitaux sont connus, mais après un certain temps cette...artéfacts de capteur (tel que des pixels morts, gradient de fond, bruit) et dégradation du signal (coulage, éblouissement, saturation, etc...Cette étude explique comment les artéfacts du capteur peuvent être corrigés, le fond de l’image enlevé et le bruit partiellement effacé. Puis, elle

  3. Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID) (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. A low cost thermal infrared hyperspectral imager for small satellites (United States)

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


    The traditional model for space-based earth observations involves long mission times, high cost, and long development time. Because of the significant time and monetary investment required, riskier instrument development missions or those with very specific scientific goals are unlikely to successfully obtain funding. However, a niche for earth observations exploiting new technologies in focused, short lifetime missions is opening with the growth of the small satellite market and launch opportunities for these satellites. These low-cost, short-lived missions 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 the 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 the 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.

  5. A low cost thermal infrared hyperspectral imager for small satellites (United States)

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


    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.

  6. Satellite image based methods for fuels maps updating (United States)

    Alonso-Benito, Alfonso; Hernandez-Leal, Pedro A.; Arbelo, Manuel; Gonzalez-Calvo, Alejandro; Moreno-Ruiz, Jose A.; Garcia-Lazaro, Jose R.


    Regular updating of fuels maps is important for forest fire management. Nevertheless complex and time consuming field work is usually necessary for this purpose, which prevents a more frequent update. That is why the assessment of the usefulness of satellite data and the development of remote sensing techniques that enable the automatic updating of these maps, is of vital interest. In this work, we have tested the use of the spectral bands of OLI (Operational Land Imager) sensor on board Landsat 8 satellite, for updating the fuels map of El Hierro Island (Spain). From previously digitized map, a set of 200 reference plots for different fuel types was created. A 50% of the plots were randomly used as a training set and the rest were considered for validation. Six supervised and 2 unsupervised classification methods were applied, considering two levels of detail. A first level with only 5 classes (Meadow, Brushwood, Undergrowth canopy cover >50%, Undergrowth canopy cover <15%, and Xeric formations), and the second one containing 19 fuel types. The level 1 classification methods yielded an overall accuracy ranging from 44% for Parellelepided to an 84% for Maximun Likelihood. Meanwhile, level 2 results showed at best, an unacceptable overall accuracy of 34%, which prevents the use of this data for such a detailed characterization. Anyway it has been demonstrated that in some conditions, images of medium spatial resolution, like Landsat 8-OLI, could be a valid tool for an automatic upgrade of fuels maps, minimizing costs and complementing traditional methodologies.

  7. Application of Geostatistical Simulation to Enhance Satellite Image Products (United States)

    Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David


    With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

  8. Airport runway detection in satellite images by Adaboost learning (United States)

    Zongur, Ugur; Halici, Ugur; Aytekin, Orsan; Ulusoy, Ilkay


    Advances in hardware and pattern recognition techniques, along with the widespread utilization of remote sensing satellites, have urged the development of automatic target detection systems in satellite images. Automatic detection of airports is particularly essential, due to the strategic importance of these targets. In this paper, a runway detection method using a segmentation process based on textural properties is proposed for the detection of airport runways, which is the most distinguishing element of an airport. Several local textural features are extracted including not only low level features such as mean, standard deviation of image intensity and gradient, but also Zernike Moments, Circular-Mellin Features, Haralick Features, as well as features involving Gabor Filters, Wavelets and Fourier Power Spectrum Analysis. Since the subset of the mentioned features, which have a role in the discrimination of airport runways from other structures and landforms, cannot be predicted trivially, Adaboost learning algorithm is employed for both classification and determining the feature subset, due to its feature selector nature. By means of the features chosen in this way, a coarse representation of possible runway locations is obtained. Promising experimental results are achieved and given.

  9. The Mass Dependence of Dwarf Satellite Galaxy Quenching

    CERN Document Server

    Slater, Colin T


    We combine observations of the Local Group with data from the NASA-Sloan Atlas to show the variation in the quenched fraction of satellite galaxies from low mass dwarf spheroidals and dwarf irregulars to more massive dwarfs similar to the Magellanic clouds. While almost all of the low mass ($M_\\star \\lesssim 10^7$ $M_\\odot$) dwarfs are quenched, at higher masses the quenched fraction decreases to approximately 40-50%. This change in the quenched fraction is large, and suggests a sudden change in the effectiveness of quenching that correlates with satellite mass. We combine this observation with models of satellite infall and ram pressure stripping to show that the low mass satellites must quench within 1-2 Gyr of pericenter passage to maintain a high quenched fraction, but that many more massive dwarfs must continue to form stars today even though they likely fell in to their host >5 Gyr ago. We also characterize how the susceptibility of dwarfs to ram pressure must vary as a function of mass if it is to acco...

  10. Use of satellite images for the monitoring of water systems (United States)

    Hillebrand, Gudrun; Winterscheid, Axel; Baschek, Björn; Wolf, Thomas


    Satellite images are a proven source of information for monitoring ecological indicators in coastal waters and inland river systems. This potential of remote sensing products was demonstrated by recent research projects (e.g. EU-funded project Freshmon - and other activities by national institutions. Among indicators for water quality, a particular focus was set on the temporal and spatial dynamics of suspended particulate matter (SPM) and Chlorophyll-a (Chl-a). The German Federal Institute of Hydrology (BfG) was using the Weser and Elbe estuaries as test cases to compare in-situ measurements with results obtained from a temporal series of automatically generated maps of SPM distributions based on remote sensing data. Maps of SPM and Chl-a distributions in European inland rivers and alpine lakes were generated by the Freshmon Project. Earth observation based products are a valuable source for additional data that can well supplement in-situ monitoring. For 2015, the BfG and the Institute for Lake Research of the State Institute for the Environment, Measurements and Nature Conservation of Baden-Wuerttemberg, Germany (LUBW) are in the process to start implementing an operational service for monitoring SPM and Chl-a based on satellite images (Landsat 7 & 8, Sentinel 2, and if required other systems with higher spatial resolution, e.g. Rapid Eye). In this 2-years project, which is part of the European Copernicus Programme, the operational service will be set up for - the inland rivers of Rhine and Elbe - the North Sea estuaries of Elbe, Weser and Ems. Furthermore - Lake Constance and other lakes located within the Federal State of Baden-Wuerttemberg. In future, the service can be implemented for other rivers and lakes as well. Key feature of the project is a data base that holds the stock of geo-referenced maps of SPM and Chl-a distributions. Via web-based portals (e.g. GGInA - geo-portal of the BfG; UIS - environmental information system of the

  11. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation (United States)

    Song, Huihui

    Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat


    Directory of Open Access Journals (Sweden)

    K.-Y. Lee


    Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate

  13. Cloud Detection of Optical Satellite Images Using Support Vector Machine (United States)

    Lee, Kuan-Yi; Lin, Chao-Hung


    Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

  14. Building damage scale proposal from VHR satellite image (United States)

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


    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)


    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.

  16. Potential application of Kanade-Lucas-Tomasi tracker on satellite images for automatic change detection (United States)

    Ahmed, Tasneem; Singh, Dharmendra; Raman, Balasubramanian


    Monitoring agricultural areas is still a very challenging task. Various models and methodologies have been developed for monitoring the agricultural areas with satellite images, but their practical applicability is limited due to the complexity in processing and dependence on a priori information. Therefore, in this paper, an attempt has been made to investigate the utility of the Kanade-Lucas-Tomasi (KLT) tracker, which is generally useful for tracking objects in video images, for monitoring agricultural areas. The KLT tracker was proposed to deal with the problem of image registration, but the use of the KLT tracker in satellite images for land cover monitoring is rarely reported. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) data has been used to identify and track the agricultural areas. The tracked pixels were compared with the agriculture pixels obtained from a decision tree algorithm and both results are closely matched. An image differencing change detection technique has been applied after KLT tracker implementation to observe the "change" and "no change" pixels in agricultural areas. It is observed that two kinds of changes are being detected. The areas where agriculture was not there earlier, but now is present, the changes are called positive changes. In the areas where agriculture was present earlier, but now is not present, those changes are referred to as negative changes. Unchanged areas retrieved from both the images are labeled as "no change" pixels. The novelty of the proposed algorithm is that it uses a simplified version of the KLT tracker to efficiently select and track the agriculture features on the basis of their spatial information and does not require a priori information every time.

  17. Accuracy assessment of topographic mapping using UAV image integrated with satellite images (United States)

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


    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.

  18. Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

    Directory of Open Access Journals (Sweden)

    Maocai Wang


    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.

  19. Urban Land Use Change Detection Using Multisensor Satellite Images

    Institute of Scientific and Technical Information of China (English)

    DENG Jin-Song; WANG Ke; LI Jun; DENG Yan-Hua


    Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multiseusor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 muttispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into bnilt-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.

  20. Automated Astrometric Analysis of Satellite Observations using Wide-field Imaging (United States)

    Skuljan, J.; Kay, J.


    An observational trial was conducted in the South Island of New Zealand from 24 to 28 February 2015, as a collaborative effort between the United Kingdom and New Zealand in the area of space situational awareness. The aim of the trial was to observe a number of satellites in low Earth orbit using wide-field imaging from two separate locations, in order to determine the space trajectory and compare the measurements with the predictions based on the standard two-line elements. This activity was an initial step in building a space situational awareness capability at the Defence Technology Agency of the New Zealand Defence Force. New Zealand has an important strategic position as the last land mass that many satellites selected for deorbiting pass before entering the Earth's atmosphere over the dedicated disposal area in the South Pacific. A preliminary analysis of the trial data has demonstrated that relatively inexpensive equipment can be used to successfully detect satellites at moderate altitudes. A total of 60 satellite passes were observed over the five nights of observation and about 2600 images were collected. A combination of cooled CCD and standard DSLR cameras were used, with a selection of lenses between 17 mm and 50 mm in focal length, covering a relatively wide field of view of 25 to 60 degrees. The CCD cameras were equipped with custom-made GPS modules to record the time of exposure with a high accuracy of one millisecond, or better. Specialised software has been developed for automated astrometric analysis of the trial data. The astrometric solution is obtained as a two-dimensional least-squares polynomial fit to the measured pixel positions of a large number of stars (typically 1000) detected across the image. The star identification is fully automated and works well for all camera-lens combinations used in the trial. A moderate polynomial degree of 3 to 5 is selected to take into account any image distortions introduced by the lens. A typical RMS

  1. TIRCIS: thermal infrared compact imaging spectrometer for small satellite applications (United States)

    Wright, Robert; Lucey, Paul; Crites, Sarah; Garbeil, Harold; Wood, Mark; Pilger, Eric; Gabrieli, Andrea; Honniball, Casey


    Measurements of reflectance or emittance in tens of narrow, contiguous wavebands, allow for the derivation of laboratory quality spectra remotely, from which the chemical composition and physical properties of targets can be determined. Although spaceborne (e.g. EO-1 Hyperion) hyperspectral data in the 0.4-2.5 micron (VSWIR) region are available, the provision of equivalent data in the log-wave infrared has lagged behind, there being no currently operational high spatial resolution LWIR imaging spectrometer on orbit. 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. Radiometric calibration is provided by blackbody targets while spectral calibration is achieved using monochromatic light sources. The instrument has a mass of <15 kg and dimensions of 53 cm × 25 cm ♢ 22 cm, and has been designed to be compatible with integration into a micro-satellite platform. (A precursor to this instrument was launched onboard a 55 kg microsatellite in October 2015). The optical design yields a 120 m ground sample size given an orbit of 500 km. Over the wavelength interval of 7.5 to 14 microns up to 50 spectral samples are possible. Measured signal-to-noise ratios range from peak values of 500:1 to 1500:1, for source temperature of 10 to 100°C.

  2. A System to Detect Residential Area in Multispectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Seyfallah Bouraoui


    Full Text Available In this paper, we propose a new solution to extract complex structures from High-Resolution (HR remote-sensing images. We propose to represent shapes and there relations by using region adjacency graphs. They are generated automatically from the segmented images. Thus, the nodes of the graph represent shape like houses, streets or trees, while arcs describe the adjacency relation between them. In order to be invariant to transformations such as rotation and scaling, the extraction of objects of interest is done by combining two techniques: one based on roof color to detect the bounding boxes of houses, and one based on mathematical morphology notions to detect streets. To recognize residential areas, a model described by a regular language is built. The detection is achieved by looking for a path in the region adjacency graph, which can be recognized as a word belonging to the description language. Our algorithm was tested with success on images from the French satellite SPOT 5 representing the urban area of Strasbourg (France at different spatial resolution.

  3. Dsm Based Orientation of Large Stereo Satellite Image Blocks (United States)

    d'Angelo, P.; Reinartz, P.


    High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.

  4. Identifying potential solar power generation sites using satellite apt images (United States)

    Fawz-Ul-Haq, K. R.; Siddiqui, Z. R.


    In this paper, satellite APT images have been used to study cloud-cover over Pakistan, so as to determine those areas which have the least frequency of cloudiness. Such areas are likely to receive maximum insolation, and have been shown on a contour map of Pakistan. It is observed that more than half of Pakistan is highly sunny, and has many promising areas for establishing large scale solar electric power generation stations. It is further observed that, some of the productive mineral-rich areas in remote parts, such as Chagai, are highly cloud-free, therefore, it may be possible to meet their mining needs through solar energy. Thus Pakistan, on the threshold of industrialization, has high prospects of obtaining `clean' energy, free of greenhouse gases.

  5. Galileo's first images of Jupiter and the Galilean satellites (United States)

    Belton, M.J.S.; Head, J. W.; Ingersoll, A.P.; Greeley, R.; McEwen, A.S.; Klaasen, K.P.; Senske, D.; Pappalardo, R.; Collins, G.; Vasavada, A.R.; Sullivan, R.; Simonelli, D.; Geissler, P.; Carr, M.H.; Davies, M.E.; Veverka, J.; Gierasch, P.J.; Banfield, D.; Bell, M.; Chapman, C.R.; Anger, C.; Greenberg, R.; Neukum, G.; Pilcher, C.B.; Beebe, R.F.; Burns, J.A.; Fanale, F.; Ip, W.; Johnson, T.V.; Morrison, D.; Moore, J.; Orton, G.S.; Thomas, P.; West, R.A.


    The first images of Jupiter, Io, Europa, and Ganymede from the Galileo spacecraft reveal new information about Jupiter's Great Red Spot (GRS) and the surfaces of the Galilean satellites. Features similar to clusters of thunderstorms were found in the GRS. Nearby wave structures suggest that the GRS may be a shallow atmospheric feature. Changes in surface color and plume distribution indicate differences in resurfacing processes near hot spots on lo. Patchy emissions were seen while Io was in eclipse by Jupiter. The outer margins of prominent linear markings (triple bands) on Europa are diffuse, suggesting that material has been vented from fractures. Numerous small circular craters indicate localized areas of relatively old surface. Pervasive brittle deformation of an ice layer appears to have formed grooves on Ganymede. Dark terrain unexpectedly shows distinctive albedo variations to the limit of resolution.

  6. Satellite Image Security Improvement by Combining DWT-DCT Watermarking and AES Encryption

    Directory of Open Access Journals (Sweden)



    Full Text Available With the large-scale research in space sciences and technologies, there is a great demand of satellite image security system for providing secure storage and transmission of satellite images. As the demand to protect the sensitive and valuable data from satellites has increased and hence proposed a new method for satellite image security by combining DWT-DCT watermarking and AES encryption. Watermarking techniques developed for multimedia data cannot be directly applied to the satellite images because here the analytic integrity of the data, rather than perceptual quality, is of primary importance. To improve performance, combine discrete wavelet transform (DWT with another equally powerful transform; the discrete cosine transform (DCT. The combined DWT-DCT watermarking algorithm’s imperceptibility was better than the performance of the DWT approach. Modified decision based unsymmetrical trimmed median filter (MDBUTMF algorithm is proposed for the restoration of satellite images that are highly corrupted by salt and pepper noise. Satellite images desire not only the watermarking for copyright protection but also encryption during storage and transmission for preventing information leakage. Hence this paper investigates the security and performance level of joint DWT-DCT watermarking and Advanced Encryption Standard (AES for satellite imagery. Theoretical analysis can be done by calculating PSNR and MSE. The experimental results demonstrate the efficiency of the proposed scheme, which fulfils the strict requirements concerning alterations of satellite images.

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

    Energy Technology Data Exchange (ETDEWEB)

    Cai, D Michael [Los Alamos National Laboratory


    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

  8. The Mass Dependence of Dwarf Satellite Galaxy Quenching (United States)

    Slater, Colin T.; Bell, Eric F.


    We combine observations of the Local Group with data from the NASA-Sloan Atlas to show the variation in the quenched fraction of satellite galaxies from low-mass dwarf spheroidals and dwarf irregulars to more massive dwarfs similar to the Magellanic Clouds. While almost all of the low-mass (M sstarf 5 Gyr ago. We also characterize how the susceptibility of dwarfs to ram pressure must vary as a function of mass if it is to account for the change in quenched fractions. Though neither model predicts the quenching effectiveness a priori, this modeling illustrates the physical requirements that the observed quenched fractions place on possible quenching mechanisms.


    National Research Council Canada - National Science Library

    Kupidura Przemysław; Skulimowska Monika


    ...: the morphological profile, and granulometric maps in detecting buildings on satellite images. It briefly explains the theoretical basis for granulometric analysis of image and compares two methods used in research...

  10. Mapping soil heterogeneity using RapidEye satellite images (United States)

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


    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.

  11. Object-based illumination normalization for multi-temporal satellite images in urban area (United States)

    Su, Nan; Zhang, Ye; Tian, Shu; Yan, Yiming


    Multi-temporal satellite images acquisition with different illumination conditions cause radiometric difference to have a huge effect on image quality during remote sensing image processing. In particular, image matching of satellite stereo images with great difference between acquisition dates is very difficult for the high-precision DSM generation in the field of satellite photogrammetry. Therefore, illumination normalization is one of the greatest application technology to eliminate radiometric difference for image matching and other image applications. In this paper, we proposed a novel method of object-based illumination normalization to improve image matching of different temporal satellite stereo images in urban area. Our proposed method include two main steps: 1) the object extraction 2) multi-level illumination normalization. Firstly, we proposed a object extraction method for the same objects extraction among the multi-temporal satellite images, which can keep the object structural attribute. Moreover, the multi-level illumination normalization is proposed by combining gradient domain method and singular value decomposition (SVD) according to characteristic information of relevant objects. Our proposed method has great improvement for the illumination of object area to be benefit for image matching in urban area with multiple objects. And the histogram similarity parameter and matching rate are used for illumination consistency quantitative evaluation. The experiments have been conducted on different satellite images with different acquisition dates in the same urban area to verify the effectiveness of our proposed method. The experimental results demonstrate a good performance by comparing other methods.

  12. Time Dependence of Collision Probabilities During Satellite Conjunctions (United States)

    Hall, Doyle T.; Hejduk, Matthew D.; Johnson, Lauren C.


    The NASA Conjunction Assessment Risk Analysis (CARA) team has recently implemented updated software to calculate the probability of collision (P (sub c)) for Earth-orbiting satellites. The algorithm can employ complex dynamical models for orbital motion, and account for the effects of non-linear trajectories as well as both position and velocity uncertainties. This “3D P (sub c)” method entails computing a 3-dimensional numerical integral for each estimated probability. Our analysis indicates that the 3D method provides several new insights over the traditional “2D P (sub c)” method, even when approximating the orbital motion using the relatively simple Keplerian two-body dynamical model. First, the formulation provides the means to estimate variations in the time derivative of the collision probability, or the probability rate, R (sub c). For close-proximity satellites, such as those orbiting in formations or clusters, R (sub c) variations can show multiple peaks that repeat or blend with one another, providing insight into the ongoing temporal distribution of risk. For single, isolated conjunctions, R (sub c) analysis provides the means to identify and bound the times of peak collision risk. Additionally, analysis of multiple actual archived conjunctions demonstrates that the commonly used “2D P (sub c)” approximation can occasionally provide inaccurate estimates. These include cases in which the 2D method yields negligibly small probabilities (e.g., P (sub c)) is greater than 10 (sup -10)), but the 3D estimates are sufficiently large to prompt increased monitoring or collision mitigation (e.g., P (sub c) is greater than or equal to 10 (sup -5)). Finally, the archive analysis indicates that a relatively efficient calculation can be used to identify which conjunctions will have negligibly small probabilities. This small-P (sub c) screening test can significantly speed the overall risk analysis computation for large numbers of conjunctions.

  13. GPU Accelerated Automated Feature Extraction From Satellite Images

    Directory of Open Access Journals (Sweden)

    K. Phani Tejaswi


    Full Text Available The availability of large volumes of remote sensing data insists on higher degree of automation in featureextraction, making it a need of thehour. Fusingdata from multiple sources, such as panchromatic,hyperspectraland LiDAR sensors, enhances the probability of identifying and extracting features such asbuildings, vegetation or bodies of water by using a combination of spectral and elevation characteristics.Utilizing theaforementioned featuresin remote sensing is impracticable in the absence ofautomation.Whileefforts are underway to reduce human intervention in data processing, this attempt alone may notsuffice. Thehuge quantum of data that needs to be processed entailsaccelerated processing to be enabled.GPUs, which were originally designed to provide efficient visualization,arebeing massively employed forcomputation intensive parallel processing environments. Image processing in general and hence automatedfeatureextraction, is highly computation intensive, where performance improvements have a direct impacton societal needs. In this context, an algorithm has been formulated for automated feature extraction froma panchromatic or multispectral image based on image processing techniques.Two Laplacian of Guassian(LoGmasks were applied on the image individually followed by detection of zero crossing points andextracting the pixels based on their standard deviationwiththe surrounding pixels. The two extractedimages with different LoG masks were combined together which resulted in an image withthe extractedfeatures and edges.Finally the user is at liberty to apply the image smoothing step depending on the noisecontent in the extracted image.The image ispassed through a hybrid median filter toremove the salt andpepper noise from the image.This paper discusses theaforesaidalgorithmforautomated featureextraction, necessity of deployment of GPUs for thesame;system-level challenges and quantifies thebenefits of integrating GPUs in such environment. The

  14. Satellite Image Time Series Decomposition Based on EEMD

    Directory of Open Access Journals (Sweden)

    Yun-long Kong


    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.

  15. The Advanced X-ray Imaging Satellite (AXIS) (United States)

    Reynolds, Christopher S.; Mushotzky, Richard


    The Advanced X-ray Imaging Satellite (AXIS) will follow in the footsteps of the spectacularly successful Chandra X-ray Observatory with similar or higher angular resolution and an order of magnitude more collecting area in the 0.3-10keV band. These capabilities will enable major advances in many of the most active areas of astrophysics, including (i) mapping event horizon scale structure in AGN accretion disks and the determination of supermassive black hole (SMBH) spins through monitoring of gravitationally-microlensed quasars; (ii) dramatically deepening our understanding of AGN feedback in galaxies and galaxy clusters out to high-z through the direct imaging of AGN winds and the interaction of jets with the hot interstellar/intracluster medium; (iii) understanding the fueling of AGN by probing hot flows inside of the SMBH sphere of influence; (iv) obtaining geometric distance measurements using dust scattering halos. With a nominal 2028 launch, AXIS will be enormously synergistic with LSST, ALMA, WFIRST and ATHENA, and will be a valuable precursor to Lynx. AXIS is enabled by breakthroughs in the construction of light-weight X-ray optics from mono-crystalline silicon blocks, building on recent developments in the semiconductor industry. Here, we describe the straw-man concept for AXIS, some of the high profile science that this observatory will address, and how you can become involved.

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

    Energy Technology Data Exchange (ETDEWEB)

    Marois, C


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

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

    Energy Technology Data Exchange (ETDEWEB)

    Marois, C


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

  18. The abundance of satellites depends strongly on the morphology of the host galaxy

    CERN Document Server

    Ruiz, Pablo; Mármol-Queraltó, Esther


    Using the spectroscopic catalogue of the Sloan Digital Survey Data Release 10 (SDSS DR10), we have explored the abundance of satellites around a sample of 307 massive (M_star > 10^11 M_sun) local (z 10^9 M_sun and R < 300 kpc depends drastically on the morphology of the central galaxy. The average number of satellites per galaxy host (N_Sat/N_Host) down to a mass ratio of 1:100 is: 5.5 +/- 1.0 for E hosts, 2.7 +/- 0.4 for S0, 1.4 +/- 0.3 for Sa and 1.2 +/- 0.3 for Sb/c. The amount of stellar mass enclosed by the satellites around massive E-type galaxies is a factor of 2, 4, and 6 larger than the mass in the satellites of S0, Sa and Sb/c-types, respectively. If these satellites would eventually infall into the host galaxies, for all the morphological types, the merger channel will be largely dominated by satellites with a mass ratio satellite-host $\\mu$ < 0.1. The fact that massive elliptical galaxies have a significant larger number of satellites than massive spirals could point out that elliptical gal...

  19. The Mass Dependance of Satellite Quenching in Milky Way-like Halos

    CERN Document Server

    Phillips, John I; Cooper, Michael C; Boylan-Kolchin, Michael; Bullock, James S; Tollerud, Erik


    Using the Sloan Digital Sky Survey, we examine the quenching of satellite galaxies around isolated Milky Way-like hosts in the local Universe. We find that the efficiency of satellite quenching around isolated galaxies is low and roughly constant over two orders of magnitude in satellite stellar mass ($M_{*}$ = $10^{8.5}-10^{10.5} \\, M_{\\odot}$), with only $\\sim~20\\%$ of systems quenched as a result of environmental processes. While largely independent of satellite stellar mass, satellite quenching does exhibit clear dependence on the properties of the host. We show that satellites of passive hosts are substantially more likely to be quenched than those of star-forming hosts, and we present evidence that more massive halos quench their satellites more efficiently. These results extend trends seen previously in more massive host halos and for higher satellite masses. Taken together, it appears that galaxies with stellar masses larger than about $10^{8}~M_{\\odot}$ are uniformly resistant to environmental quench...

  20. First Satellite Imaging of Auroral Pulsations by the Fast Auroral Imager on e-POP (United States)

    Lui, A.; Cogger, L.; Howarth, A. D.; Yau, A. W.


    We report the first satellite imaging of auroral pulsations by the Fast Auroral Imager (FAI) onboard the Enhanced Polar Outflow Probe (e-POP) satellite. The near-infrared camera of FAI is capable of providing up to two auroral images per second, ideal for investigation of pulsating auroras. The auroral pulsations were observed within the auroral bulge formed during a substorm interval on 2014 February 19. This first satellite view of these pulsations from FAI reveals that (1) several pulsating auroral channels (PACs) occur within the auroral bulge, (2) periods of the intensity pulsations span over one decade within the auroral bulge, and (3) there is no apparent trend of longer pulsation periods associated with higher latitudes for these PACs. Although PACs resemble in some respect stable pulsating auroras reported previously but they have several important differences in characteristics.PACs are not embedded in or emerging from omega bands or torches and are located at significant distances from the equatorward boundary of the auroral oval, unlike the characteristics of stable pulsating auroras.

  1. Estimate Landslide Volume with Genetic Algorithms and Image Similarity Method from Single Satellite Image (United States)

    Yu, Ting-To


    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.

  2. Determination of quasi-static microaccelerations onboard a satellite using video images of moving objects (United States)

    Levtov, V. L.; Romanov, V. V.; Boguslavsky, A. A.; Sazonov, V. V.; Sokolov, S. M.; Glotov, Yu. N.


    A space experiment aimed at determination of quasi-static microaccelerations onboard an artificial satellite of the Earth using video images of the objects executing free motion is considered. The experiment was carried out onboard the Foton M-3 satellite. Several pellets moved in a cubic box fixed on the satellite’s mainframe and having two transparent adjacent walls. Their motion was photographed by a digital video camera. The camera was installed facing one of the transparent walls; a mirror was placed at an angle to another transparent wall. Such an optical system allowed us to have in a single frame two images of the pellets from differing viewpoints. The motion of the pellets was photographed on time intervals lasting 96 s. Pauses between these intervals were also equal to 96 s. A special processing of a separate image allowed us to determine coordinates of the pellet centers in the camera’s coordinate system. The sequence of frames belonging to a continuous interval of photography was processed in the following way. The time dependence of each coordinate of every pellet was approximated by a second degree polynomial using the least squares method. The coefficient of squared time is equal to a half of the corresponding microacceleration component. As has been shown by processing made, the described method of determination of quasi-static microaccelerations turned out to be sufficiently sensitive and accurate.

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

    Directory of Open Access Journals (Sweden)

    Xiao-fang Xie


    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.

  4. Satellite Images-based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles

    Directory of Open Access Journals (Sweden)

    Mehmet Bodur


    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.

  5. Spatio-temporal multi-modality ontology for indexing and retrieving satellite images


    MESSOUDI, Wassim; FARAH, Imed Riadh; SAHEB ETTABAA, Karim; Ben Ghezala, Henda; SOLAIMAN, Basel


    International audience; This paper presents spatio-temporal multi-modality ontology for indexing and retrieving satellite images in the high level to improve the quality of the system retrieval and to perform semantic in the retrieval process.Our approach is based on three modules: (1) regions and features extraction, (2) ontological indexing and (3) semantic image retrieval. The first module allows extracting regions from the satellite image using the fuzzy c-means FCM) segmentation algorith...

  6. Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram


    Paul, F


    Although animated images are very popular on the internet, they have so far found only limited use for glaciological applications. With long time series of satellite images becoming increasingly available and glaciers being well recognized for their rapid changes and variable flow dynamics, animated sequences of multiple satellite images reveal glacier dynamics in a time-lapse mode, making the otherwise slow changes of glacier movement visible and understandable to the wider...

  7. Region of Interest Detection Based on Histogram Segmentation for Satellite Image (United States)

    Kiadtikornthaweeyot, Warinthorn; Tatnall, Adrian R. L.


    High resolution satellite imaging is considered as the outstanding applicant to extract the Earth's surface information. Extraction of a feature of an image is very difficult due to having to find the appropriate image segmentation techniques and combine different methods to detect the Region of Interest (ROI) most effectively. This paper proposes techniques to classify objects in the satellite image by using image processing methods on high-resolution satellite images. The systems to identify the ROI focus on forests, urban and agriculture areas. The proposed system is based on histograms of the image to classify objects using thresholding. The thresholding is performed by considering the behaviour of the histogram mapping to a particular region in the satellite image. The proposed model is based on histogram segmentation and morphology techniques. There are five main steps supporting each other; Histogram classification, Histogram segmentation, Morphological dilation, Morphological fill image area and holes and ROI management. The methods to detect the ROI of the satellite images based on histogram classification have been studied, implemented and tested. The algorithm is be able to detect the area of forests, urban and agriculture separately. The image segmentation methods can detect the ROI and reduce the size of the original image by discarding the unnecessary parts.

  8. Detecting Anomaly Regions in Satellite Image Time Series Based on Sesaonal Autocorrelation Analysis (United States)

    Zhou, Z.-G.; Tang, P.; Zhou, M.


    Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1) it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2) it is flexible to meet some requirement (e.g., z-value or significance level) of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3) it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.


    Directory of Open Access Journals (Sweden)

    Z.-G. Zhou


    Full Text Available Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1 it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2 it is flexible to meet some requirement (e.g., z-value or significance level of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3 it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.

  10. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images. (United States)

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


    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.

  11. Improving multispectral satellite image compression using onboard subpixel registration (United States)

    Albinet, Mathieu; Camarero, Roberto; Isnard, Maxime; Poulet, Christophe; Perret, Jokin


    Future CNES earth observation missions will have to deal with an ever increasing telemetry data rate due to improvements in resolution and addition of spectral bands. Current CNES image compressors implement a discrete wavelet transform (DWT) followed by a bit plane encoding (BPE) but only on a mono spectral basis and do not profit from the multispectral redundancy of the observed scenes. Recent CNES studies have proven a substantial gain on the achievable compression ratio, +20% to +40% on selected scenarios, by implementing a multispectral compression scheme based on a Karhunen Loeve transform (KLT) followed by the classical DWT+BPE. But such results can be achieved only on perfectly registered bands; a default of registration as low as 0.5 pixel ruins all the benefits of multispectral compression. In this work, we first study the possibility to implement a multi-bands subpixel onboard registration based on registration grids generated on-the-fly by the satellite attitude control system and simplified resampling and interpolation techniques. Indeed bands registration is usually performed on ground using sophisticated techniques too computationally intensive for onboard use. This fully quantized algorithm is tuned to meet acceptable registration performances within stringent image quality criteria, with the objective of onboard real-time processing. In a second part, we describe a FPGA implementation developed to evaluate the design complexity and, by extrapolation, the data rate achievable on a spacequalified ASIC. Finally, we present the impact of this approach on the processing chain not only onboard but also on ground and the impacts on the design of the instrument.

  12. Satellite Image Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare


    Full Text Available In this paper, urban growth of Bangalore region is analyzed and discussed by using multi-temporal and multi-spectral Landsat satellite images. Urban growth analysis helps in understanding the change detection of Bangalore region. The change detection is studied over a period of 39 years and the region of interest covers an area of 2182 km2. The main cause for urban growth is the increase in population. In India, rapid urbanization is witnessed due to an increase in the population, continuous development has affected the existence of natural resources. Therefore observing and monitoring the natural resources (land use plays an important role. To analyze changed detection, researcher’s use remote sensing data. Continuous use of remote sensing data helps researchers to analyze the change detection. The main objective of this study is to monitor land cover changes of Bangalore district which covers rural and urban regions using multi-temporal and multi-sensor Landsat - multi-spectral scanner (MSS, thematic mapper (TM, Enhanced Thematic mapper plus (ETM+ MSS, TM and ETM+ images captured in the years 1973, 1992, 1999, 2002, 2005, 2008 and 2011. Temporal changes were determined by using maximum likelihood classification method. The classification results contain four land cover classes namely, built-up, vegetation, water and barren land. The results indicate that the region is densely developed which has resulted in decrease of water and vegetation regions. The continuous transformation of barren land to built-up region has affected water and vegetation regions. Generally, from 1973 to 2011 the percentage of urban region has increased from 4.6% to 25.43%, mainly due to urbanization.

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

    Directory of Open Access Journals (Sweden)

    Xiaonan Niu


    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.

  14. Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing (United States)

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


    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.

  15. Quantitative analysis of geomorphic processes using satellite image data at different scales (United States)

    Williams, R. S., Jr.


    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.

  16. Shadow imaging of geosynchronous satellites: simulation, image reconstruction, and shadow prediction (United States)

    Douglas, Dennis M.; Hunt, Bobby R.; Sheppard, David G.


    Shadow imaging is a technique to obtain highly resolved silhouettes of resident space objects (RSOs) which would otherwise be unattainable using conventional terrestrial based imaging approaches. This is done by post processing the measured irradiance pattern (shadow) cast onto the Earth as the RSO occults a star. The research presented here focuses on shadow imaging of geosynchronous (GEO) satellites with near stationary orbits approximately 36,000 km from the Earth. Shadows pertaining to a set of diverse observing scenarios are simulated and used as inputs to a Fresnel based phase retrieval algorithm. Spatial resolution limits are evaluated and correlated to signal to noise (SNR) metrics. Resolvable feature sizes of less than 1 m are shown to be readily achievable using foreseeable observing scenarios. Initial output from a shadow prediction tool indicates that there are, on average, over 1000 shadows on the Earth on any given time from a single GEO satellite for stars brighter than mv=10. Shadow ground track uncertainties are correlated to stellar astrometric errors. Global and localized shadow track maps are presented demonstrating a high feasibility for future shadow collections.

  17. The environmental dependence of gas accretion onto galaxies: quenching satellites through starvation

    CERN Document Server

    van de Voort, Freeke; Bower, Richard G; Correa, Camila A; Crain, Robert A; Schaye, Joop; Theuns, Tom


    Galaxies that have fallen into massive haloes may no longer be able to accrete gas from their surroundings, a process referred to as 'starvation' or 'strangulation' of satellites. We study the environmental dependence of gas accretion onto galaxies using the cosmological, hydrodynamical EAGLE simulation. We quantify the dependence of gas accretion on stellar mass, redshift, and environment, using halo mass and galaxy overdensity as environmental indicators. We find a strong suppression, by many orders of magnitude, of the gas accretion rate in dense environments, primarily for satellite galaxies. This suppression becomes stronger at lower redshift. However, the scatter in accretion rates is very large for satellites. This is (at least in part) due to the variation in halocentric radius, since gas accretion is more suppressed at smaller radii. Central galaxies are influenced less strongly by their environment and exhibit less scatter in their gas accretion rates. The star formation rates of both centrals and s...

  18. Satellite image blind restoration based on surface fitting and multivariate model

    Institute of Scientific and Technical Information of China (English)

    CHEN Xin-bing; YANG Shi-zhi; WANG Xian-hua; QIAO Yan-li


    Owing to the blurring effect from atmosphere and camera system in the satellite imaging a blind image restoration algo-rithm is proposed which includes the modulation transfer function (MTF) estimation and the image restoration. In the MTF estimation stage, based on every degradation process of satellite imaging-chain, a combined parametric model of MTF is given and used to fit the surface of normalized logarithmic amplitude spectrum of degraded image. In the image restoration stage, a maximum a posteriori (MAP) based edge-preserving image restoration method is presented which introduces multivariate Laplacian model to characterize the prior distribution of wavelet coefficients of original image. During the image restoration, in order to avoid solving high nonlinear equations, optimization transfer algorithm is adopted to decom-pose the image restoration procedure into two simple steps: Landweber iteration and wavelet thresholding denoising. In the numerical experiment, the satellite image restoration results from SPOT-5 and high resolution camera (HR) of China & Brazil earth resource satellite (CBERS-02B) ane compared, and the proposed algorithm is superior in the image edge preservation and noise inhibition.

  19. A method of using commercial virtual satellite image to check the pattern painting spot effect (United States)

    Wang, Zheng-gang; Kang, Qing; Shen, Zhi-qiang; Cui, Chang-bin


    A method of using commercial virtual satellite image to check the pattern painting spot effect contrast with the satellite images before painting and after painting have been discussed. Using a housetop as the testing platform analyses and discusses the factors' influence such as resolution of satellite image, spot size and color of pattern painting spot and pattern painting camouflage method choosing to the plan implement. The pattern painting design and spot size used in the testing has been ensured, and housetop pattern painting has been painted. Finally, the small spot pattern painting camouflage effect of engineering using upon painting pattern size, color and texture have been checked, contrasting with the satellite image before painting and after painting.

  20. A study on quality and availability of COCTS images of HY- 1 satellite by simulation

    Institute of Scientific and Technical Information of China (English)

    李淑菁; 毛天明; 潘德炉


    Hy-1 is a first China's ocean color satellite which will be launched as a piggyback satellite on FY- 1 satellite using Long March rocket. On the satellite there are two sensors: one is the China's ocean color and temperature scanner (COCTS), the other is CCD coastal zone imager (CZI).The COCTS is considered to be a main sensor to play a key role. In order to understand the characteristics of future ocean color images observed, a simulation and evaluation study on the quality and availability of the COCTS image has been done. First, the simulation models are introduced briefly, and typical simulated cases of radiance images at visible bands are introduced, in which the radiance distribution is based on geographic location, the satellite orbital parameters and sensor properties, the simulated method to evaluate the image quality and availability is developed by using the characteristics of image called the complex signal noise ratio ( CSNR ). Meanwhile, a series of the CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of the COCTS images before the HY - 1 is placed in orbit. Finally, the quality and availability of the COCTS images are quantitatively analyzed with the simulated CSNR data. The results will be beneficial to all scientists who are in charge of the COCTS mission and to those who plan to use the data from the COCTS.

  1. Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos (United States)

    Liang, Yu-Li

    Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

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

  3. NEPR World View 2 Satellite Mosaic - NOAA TIFF Image (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...

  4. An Image-Based Sensor System for Autonomous Rendez-Vous with Uncooperative Satellites

    CERN Document Server

    Miravet, Carlos; Krouch, Eloise; del Cura, Juan Manuel


    In this paper are described the image processing algorithms developed by SENER, Ingenieria y Sistemas to cope with the problem of image-based, autonomous rendez-vous (RV) with an orbiting satellite. The methods developed have a direct application in the OLEV (Orbital Life Extension Extension Vehicle) mission. OLEV is a commercial mission under development by a consortium formed by Swedish Space Corporation, Kayser-Threde and SENER, aimed to extend the operational life of geostationary telecommunication satellites by supplying them control, navigation and guidance services. OLEV is planned to use a set of cameras to determine the angular position and distance to the client satellite during the complete phases of rendez-vous and docking, thus enabling the operation with satellites not equipped with any specific navigational aid to provide support during the approach. The ability to operate with un-equipped client satellites significantly expands the range of applicability of the system under development, compar...

  5. Artificial neural network prediction model for geosynchronous electron fluxes: Dependence on satellite position and particle energy (United States)

    Shin, Dae-Kyu; Lee, Dae-Young; Kim, Kyung-Chan; Hwang, Junga; Kim, Jaehun


    Geosynchronous satellites are often exposed to energetic electrons, the flux of which varies often to a large extent. Since the electrons can cause irreparable damage to the satellites, efforts to develop electron flux prediction models have long been made until recently. In this study, we adopt a neural network scheme to construct a prediction model for the geosynchronous electron flux in a wide energy range (40 keV to >2 MeV) and at a high time resolution (as based on 5 min resolution data). As the model inputs, we take the solar wind variables, geomagnetic indices, and geosynchronous electron fluxes themselves. We also take into account the magnetic local time (MLT) dependence of the geosynchronous electron fluxes. We use the electron data from two geosynchronous satellites, GOES 13 and 15, and apply the same neural network scheme separately to each of the GOES satellite data. We focus on the dependence of prediction capability on satellite's magnetic latitude and MLT as well as particle energy. Our model prediction works less efficiently for magnetic latitudes more away from the equator (thus for GOES 13 than for GOES 15) and for MLTs nearer to midnight than noon. The magnetic latitude dependence is most significant for an intermediate energy range (a few hundreds of keV), and the MLT dependence is largest for the lowest energy (40 keV). We interpret this based on degree of variance in the electron fluxes, which depends on magnetic latitude and MLT at geosynchronous orbit as well as particle energy. We demonstrate how substorms affect the flux variance.

  6. Cassini Imaging of Auroral Emissions on the Galilean Satellites (United States)

    Geissler, P.; McEwen, A.; Porco, C.


    Cassini captured several sequences of images showing Io, Europa and Ganymede while the moons were eclipsed by Jupiter. Io was the best studied of the satellites, with 4 eclipses successfully recorded. Earlier eclipse imaging by Galileo (Geissler et al., Science 295, 870-874) had shown colorful atmospheric emissions from Io and raised questions concerning their temporal variability and the identity of the emitting species. With its high data rate and numerous filter combinations, Cassini was able to fill some of the gaps in our knowledge of Io's visible aurorae. Io's bright equatorial glows were detected at previously unknown wavelengths and were also seen in motion. One eclipse took place on 12/29/2000 while Io was far from the plasma torus center. The pair of equatorial glows near the sub-Jupiter and anti-Jupiter points appeared about equal in brightness and changed little in location or intensity over a two hour period. Io crossed the plasma torus center during the next eclipse on 1/01/2001, as it passed through System III magnetic longitudes from 250 to 303 degrees. The equatorial glows were seen to shift in latitude during this eclipse, tracking the tangent points of the jovian magnetic field lines. This behaviour is similar to that observed for ultraviolet and other atomic emissions, and confirms that these visible glows are powered by Birkeland currents connecting Io and Jupiter. The eclipse on 1/05/2001 provided the best spectral measurements of the aurorae. The equatorial glows were detected at near ultraviolet wavelengths, consistent with their interpretation as molecular SO2 emissions. More than 100 kR were recorded in the ISS UV3 filter (300-380 nm) along with a similar intensity in BL1 (290-500 nm), comparable to Galileo estimates. At least 50 kR were detected in UV2 images (265-330 nm). No detection was made in UV1 (235-280 nm), allowing us to place an upper limit of about 100 kR. A new detection of the equatorial glows was made in the IR1 band (670

  7. Multi-Mode GF-3 Satellite Image Geometric Accuracy Verification Using the RPC Model. (United States)

    Wang, Taoyang; Zhang, Guo; Yu, Lei; Zhao, Ruishan; Deng, Mingjun; Xu, Kai


    The GaoFen-3 (GF-3) satellite is the first C-band multi-polarization synthetic aperture radar (SAR) imaging satellite with a resolution up to 1 m in China. It is also the only SAR satellite of the High-Resolution Earth Observation System designed for civilian use. There are 12 different imaging models to meet the needs of different industry users. However, to use SAR satellite images for related applications, they must possess high geometric accuracy. In order to verify the geometric accuracy achieved by the different modes of GF-3 images, we analyze the SAR geometric error source and perform geometric correction tests based on the RPC model with and without ground control points (GCPs) for five imaging modes. These include the spotlight (SL), ultra-fine strip (UFS), Fine Strip I (FSI), Full polarized Strip I (QPSI), and standard strip (SS) modes. Experimental results show that the check point residuals are large and consistent without GCPs, but the root mean square error of the independent checkpoints for the case of four corner control points is better than 1.5 pixels, achieving a similar level of geometric positioning accuracy to that of international satellites. We conclude that the GF-3 satellite can be used for high-accuracy geometric processing and related industry applications.

  8. Satellite Image Edge Detection for Population Distribution Pattern Identification using Levelset with Morphological Filtering Process (United States)

    Harsiti; Munandar, T. A.; Suhendar, A.; Abdullah, A. G.; Rohendi, D.


    Population distribution pattern is directly related with economic gap of a region. Analysis of population distribution pattern is usually performed by studying statistical data on population. This study aimed to analyze population distribution pattern using image analysis concept, i.e. using satellite images. Levelset and morphological image filtering methods were used to analyze images to see distribution pattern. The research result showed that Levelset and morphological image filtering could remove a lot of noises in analysis result images and form object edge contours very clearly. The detected object contours were used as references to recognize population distribution pattern based on satellite image analysis. The pattern made based on the research result didn’t show optimal result because Levelset performed image segmentation based on the contours of the analyzed objects. Other segmentation methods should be combined with it to produce clearer population distribution pattern.

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

    Energy Technology Data Exchange (ETDEWEB)

    Simms, L M


    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.

  10. Three attempts of earthquake prediction with satellite cloud images

    Directory of Open Access Journals (Sweden)

    G. Guangmeng


    Full Text Available Thermal anomalies detected from satellite data are widely reported. Nearly all the anomalies are reported after the quake. Here we report three earthquake predictions in Italy and Iran according to satellite cloud anomalies. These cloud anomalies usually show a linear pattern, stay there for hours and do not move with winds. According to these anomalies, we can give a rough estimation about impending earthquake activities. All the estimated dates and magnitudes are in good agreement with the earthquake facts, and the only unsatisfactory point is that the distance error is 100–300 km. Because the cloud anomaly is long, we can not reduce the distance error further. A possible way is to combine geophysical data and satellite data together to estimate the epicenter and this will increase the prediction accuracy.

  11. Satellite derived precipitation and freshwater flux variability and its dependence on the North Atlantic Oscillation (United States)

    Andersson, Axel; Bakan, Stephan; Graßl, Hartmut


    The variability of satellite retrieved precipitation and freshwater flux from the `Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data' (HOAPS) is assessed with special emphasis on the `North Atlantic Oscillation' (NAO). To cover also land areas, a novel combination of the satellite derived precipitation climatology with the rain gauge based `Full Data Reanalysis Product Version 4', of the `Global Precipitation Climatology Centre' (GPCC) is used. This yields unique high-resolution, quasi-global precipitation fields compiled from two independent data sources. Over the ocean, the response of the freshwater balance and the related parameters to the NAO is investigated for the first time by using a purely satellite based data set. A strong dependence of precipitation patterns to the state of the NAO is found. On synoptic scale this is in accordance with earlier findings by other satellite based and reanalysis products. Furthermore, the consistency of the combined HOAPS-3/GPCC data set allows also detailed regional analyses of precipitation patterns. The response of HOAPS-3 freshwater flux to the NAO is dominated by precipitation at mid and high latitudes, while for the subtropical regions the feedback of the evaporation is stronger.

  12. Dose energy dependence in proton imaging

    Energy Technology Data Exchange (ETDEWEB)

    Denyak, V.V., E-mail: [National Science Centre Kharkov Institute of Physics and Technology, Kharkov 61108 (Ukraine); Federal University of Technology - Parana, Curitiba 80230-901 (Brazil); Paschuk, S.A.; Schelin, H.R.; Rocha, R.L.; Setti, J.A.P.; Klock, M.C.L.; Evseev, I.G. [Federal University of Technology - Parana, Curitiba 80230-901 (Brazil); Yevseyeva, O.I. [Polytechnic Institute of the Rio de Janeiro State University, Nova Friburgo 28610-970 (Brazil)


    In the earliest works dedicated to proton radiography and proton computed tomography it was shown that the advantage of image creation using proton beams appears when the energy is chosen as small as possible, but enough to pass the object. This phenomenon is based on the great sensitivity of the energy flux of the proton beam in relation to the length and density of the object at the end of the proton range. However, this fact was proved experimentally only with thin detectors, such as photographic films, which detect only part of the exit energy of protons. Another method which is based on the measurement of total exit energy of protons contains two effects that act in opposite ways: the necessary irradiation dose increases when the energy of the proton is reduced. In this work, the dependence of the irradiation dose on proton initial energy was studied using analytical formulas and computer simulations. The investigation shows that the irradiation dose depends slightly on the proton energy beyond the region at the end of the proton range and increases sharply in it.

  13. The environmental dependence of gas accretion on to galaxies: quenching satellites through starvation (United States)

    van de Voort, Freeke; Bahé, Yannick M.; Bower, Richard G.; Correa, Camila A.; Crain, Robert A.; Schaye, Joop; Theuns, Tom


    Galaxies that have fallen into massive haloes may no longer be able to accrete gas from their surroundings: a process referred to as 'starvation' or 'strangulation' of satellites. We study the environmental dependence of gas accretion on to galaxies using the cosmological, hydrodynamical EAGLE simulation. We quantify the dependence of gas accretion on stellar mass, redshift, and environment, using halo mass and galaxy overdensity as environmental indicators. We find a strong suppression, of many orders of magnitude, of the gas accretion rate in dense environments, primarily for satellite galaxies. This suppression becomes stronger at lower redshift. However, the scatter in accretion rates is very large for satellites. This is (at least in part) due to the variation in the halocentric radius, since gas accretion is more suppressed at smaller radii. Central galaxies are influenced less strongly by their environment and exhibit less scatter in their gas accretion rates. The star formation rates of both centrals and satellites show similar behaviour to their gas accretion rates. The relatively small differences between gas accretion and star formation rates demonstrate that galaxies generally exhaust their gas reservoir somewhat faster at higher stellar mass, lower redshift, and in denser environments. We conclude that the environmental suppression of gas accretion could directly result in the quenching of star formation.

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

    NARCIS (Netherlands)

    Kyzirakos, K.; Karpathiotakis, M.; Garbis, G.; Nikolaou, C.; Bereta, K.; Papoutsis, I.; Herekakis, T.; Michail, D.; Koubarakis, M.; Kontoes, C.


    Advances 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 scientific and

  15. Remote sensing place : Satellite images as visual spatial imaginaries

    NARCIS (Netherlands)

    Shim, David

    How do people come to know the world? How do they get a sense of place and space? Arguably, one of the ways in which they do this is through the practice of remote sensing, among which satellite imagery is one of the most widespread and potent tools of engaging, representing and constructing space.

  16. Global thermochemical imaging of the lithosphere using satellite and terrestrial observations (United States)

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


    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

  17. Higher resolution satellite remote sensing and the impact on image mapping (United States)

    Watkins, Allen H.; Thormodsgard, June M.


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

  18. Higher resolution satellite remote sensing and the impact on image mapping (United States)

    Watkins, Allen H.; Thormodsgard, June M.

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


    Directory of Open Access Journals (Sweden)

    H. Miyazaki


    Full Text Available We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST, Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel-based cloud assessment and pixel value correction over seasonal variations.

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


    B. De Mol; Ruddick, K


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

  1. Adaptive Optics for Satellite and Debris Imaging in LEO and GEO (United States)

    Copeland, M.; Bennet, F.; Zovaro, A.; Riguat, F.; Piatrou, P.; Korkiakoski, V.; Smith, C.


    The Research School of Astronomy and Astrophysics (RSAA) at the Australian National University has developed and Adaptive Optics (AO) system for satellite and debris imaging in low Earth orbit (LEO) and geostationary orbit (GEO). In LEO the size, shape and orientation of objects will be measured with resolution of 50 cm for objects at 800 km range at an 800 nm imaging wavelength. In GEO satellite position will be measured using precision astrometry of nearby stars. We use an AO system with a deformable mirror (DM) of 277 actuators and Shack-Hartmann wavefront sensor operating at 2 kHz. Imaging is performed at a rate of >30 Hz to reduce image blur due to tip-tilt and rotation. We use two imaging modes; a high resolution mode to obtain Nyquist sampled images and a acquisition mode with 75 arcsecond field of view to aid in finding targets.

  2. Biomass prediction model in maize based on satellite images (United States)

    Mihai, Herbei; Florin, Sala


    Monitoring of crops by satellite techniques is very useful in the context of precision agriculture, regarding crops management and agricultural production. The present study has evaluated the interrelationship between maize biomass production and satellite indices (NDVI and NDBR) during five development stages (BBCH code), highlighting different levels of correlation. Biomass production recorded was between 2.39±0.005 t ha-1 (12-13 BBCH code) and 51.92±0.028 t ha-1 (83-85 BBCH code), in relation to vegetation stages studied. Values of chlorophyll content ranged from 24.1±0.25 SPAD unit (12-13 BBCH code) to 58.63±0.47 SPAD unit (71-73 BBCH code), and the obtained satellite indices ranged from 0.035641±0.002 and 0.320839±0.002 for NDVI indices respectively 0.035095±0.034 and 0.491038±0.018 in the case of NDBR indices. By regression analysis it was possible to obtain predictive models of biomass in maize based on the satellite indices, in statistical accurate conditions. The most accurate prediction was possible based on NDBR index (R2 = 0.986, F = 144.23, p<0.001, RMSE = 1.446), then based on chlorophyll content (R2 = 0.834, F = 16.14, p = 0.012, RMSE = 6.927) and NDVI index (R2 = 0.682, F = 3.869, p = 0.116, RMSE = 12.178).

  3. Nightfire method to track volcanic eruptions from multispectral satellite images (United States)

    Trifonov, Grigory; Zhizhin, Mikhail; Melnikov, Dmitry


    This work presents the first results of an application of the Nightfire hotspot algorithm towards volcano activity detection. Nightfire algorithm have been developed to play along with a Suomi-NPP polar satellite launched in 2011, which has a new generation multispectral VIIRS thermal sensor on board, to detect gas flares related to the upstream and downstream production of oil and natural gas. Simultaneously using of nighttime data in SWIR, MWIR, and LWIR sensor bands the algorithm is able to estimate the hotspot temperature, size and radiant heat. Four years of non-filtered observations have been accumulated in a spatio-temporal detection database, which currently totals 125 GB in size. The first part of this work presents results of retrospective cross-match of the detection database with the publicly available observed eruptions databases. The second part discusses how an approximate 3D shape of a lava lake could be modeled based on the apparent source size and satellite zenith angle. The third part presents the results of fusion Landsat-8 and Himawari-8 satellites data with the VIIRS Nightfire for several active volcanoes.

  4. Crater Relaxation and Stereo Imaging of the Icy Satellites of Jupiter and Saturn (United States)

    Phillips, C. B.; Beyer, R. A.; Nimmo, F.; Roberts, J. H.; Robuchon, G.


    Crater relaxation has been used as a probe of subsurface temperature structure for over thirty years, both on terrestrial bodies and icy satellites. We are developing and testing two independent methods for processing stereo pairs to produce digital elevation models, to address how crater relaxation depends on crater diameter, geographic location, and stratigraphic position on the icy satellites of Jupiter and Saturn. Our topographic profiles will then serve as input into two numerical models, one viscous and one viscoelastic, to allow us to probe the subsurface thermal profiles and relaxation histories of these satellites. We are constructing stereo topography from Galileo and Cassini image pairs using the NASA Ames Stereo Pipeline (Moratto et al. 2010), an automated stereogrammetry tool designed for processing planetary imagery captured from orbiting and landed robotic explorers on other planets. We will also be using the commercial program SOCET SET from BAE Systems (Miller and Walker 1993; 1995). Qualitatively, it is clear that there are large spatial variations in the degree of crater relaxation among Jupiter’s and Saturn’s satellites. However, our use of stereo topography will allow quantitative measures of crater relaxation (e.g. depth:diameter ratio or equivalent) to be derived. Such measures are essential to derive quantitative estimates of the heat fluxes responsible for this relaxation. Estimating how surface heat flux has varied with time provides critical constraints on satellite thermal (and orbital) evolution. Craters undergo viscous relaxation over time at a rate that depends on the temperature gradient and crater scale. We are investigating how the near-surface satellite heat flux varied in time and space, based on our crater relaxation observations. Once we have crater profiles from our DEMs, we use them as input to two theoretical approaches: a relatively simple (viscous) numerical model in which time-varying heat fluxes can be included, and

  5. Updating Object for GIS Database Information Using High Resolution Satellite Images: a Case Study Zonguldak (United States)

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


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

  6. Flood hazard and flood risk assessment using a time series of satellite images: a case study in Namibia. (United States)

    Skakun, Sergii; Kussul, Nataliia; Shelestov, Andrii; Kussul, Olga


    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.

  7. Satellite Imagery Cadastral Features Extractions using Image Processing Algorithms: A Viable Option for Cadastral Science

    Directory of Open Access Journals (Sweden)

    Usman Babawuro


    Full Text Available Satellite images are used for feature extraction among other functions. They are used to extract linear features, like roads, etc. These linear features extractions are important operations in computer vision. Computer vision has varied applications in photogrammetric, hydrographic, cartographic and remote sensing tasks. The extraction of linear features or boundaries defining the extents of lands, land covers features are equally important in Cadastral Surveying. Cadastral Surveying is the cornerstone of any Cadastral System. A two dimensional cadastral plan is a model which represents both the cadastral and geometrical information of a two dimensional labeled Image. This paper aims at using and widening the concepts of high resolution Satellite imagery data for extracting representations of cadastral boundaries using image processing algorithms, hence minimizing the human interventions. The Satellite imagery is firstly rectified hence establishing the satellite imagery in the correct orientation and spatial location for further analysis. We, then employ the much available Satellite imagery to extract the relevant cadastral features using computer vision and image processing algorithms. We evaluate the potential of using high resolution Satellite imagery to achieve Cadastral goals of boundary detection and extraction of farmlands using image processing algorithms. This method proves effective as it minimizes the human demerits associated with the Cadastral surveying method, hence providing another perspective of achieving cadastral goals as emphasized by the UN cadastral vision. Finally, as Cadastral science continues to look to the future, this research aimed at the analysis and getting insights into the characteristics and potential role of computer vision algorithms using high resolution satellite imagery for better digital Cadastre that would provide improved socio economic development.

  8. Object Based and Pixel Based Classification Using Rapideye Satellite Imager of ETI-OSA, Lagos, Nigeria


    Esther Oluwafunmilayo Makinde; Ayobami Taofeek Salami; James Bolarinwa Olaleye; Oluwapelumi Comfort Okewusi


    Several studies have been carried out to find an appropriate method to classify the remote sensing data. Traditional classification approaches are all pixel-based, and do not utilize the spatial information within an object which is an important source of information to image classification. Thus, this study compared the pixel based and object based classification algorithms using RapidEye satellite image of Eti-Osa LGA, Lagos. In the object-oriented approach, the image was segmented to homog...

  9. Developing an efficient technique for satellite image denoising and resolution enhancement for improving classification accuracy (United States)

    Thangaswamy, Sree Sharmila; Kadarkarai, Ramar; Thangaswamy, Sree Renga Raja


    Satellite images are corrupted by noise during image acquisition and transmission. The removal of noise from the image by attenuating the high-frequency image components removes important details as well. In order to retain the useful information, improve the visual appearance, and accurately classify an image, an effective denoising technique is required. We discuss three important steps such as image denoising, resolution enhancement, and classification for improving accuracy in a noisy image. An effective denoising technique, hybrid directional lifting, is proposed to retain the important details of the images and improve visual appearance. The discrete wavelet transform based interpolation is developed for enhancing the resolution of the denoised image. The image is then classified using a support vector machine, which is superior to other neural network classifiers. The quantitative performance measures such as peak signal to noise ratio and classification accuracy show the significance of the proposed techniques.

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

    CERN Document Server

    Kodge, B G


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



    Asaad Noori Hashim; Zahir M. Hussain


    The image is a 2D signal whose pixels are highly correlated in a 2D manner. Hence, using pixel by pixel error what we called previously Mean-Square Error, (MSE) is not an efficient way to compare two similar images (e.g., an original image and a compressed version of it). Due to this correlation, image comparison needs a correlative quality measure. It is clear that correlation between two signals gives an idea about the relation between samples of the two signals. Generally speaking, correla...

  12. Gemini Planet Imager Observational Calibrations VIII: Characterization and Role of Satellite Spots

    CERN Document Server

    Wang, Jason J; Graham, James R; Savransky, Dmitry; Ingraham, Patrick J; Ward-Duong, Kimberly; Patience, Jennifer; De Rosa, Robert J; Bulger, Joanna; Sivaramakrishnan, Anand; Perrin, Marshall D; Thomas, Sandrine J; Sadakuni, Naru; Greenbaum, Alexandra Z; Pueyo, Laurent; Marois, Christian; Oppenheimer, Ben R; Kalas, Paul; Cardwell, Andrew; Goodsell, Stephen; Hibon, Pascale; Rantakyrö, Fredrik T


    The Gemini Planet Imager (GPI) combines extreme adaptive optics, an integral field spectrograph, and a high performance coronagraph to directly image extrasolar planets in the near-infrared. Because the coronagraph blocks most of the light from the star, it prevents the properties of the host star from being measured directly. Instead, satellite spots, which are created by diffraction from a square grid in the pupil plane, can be used to locate the star and extract its spectrum. We describe the techniques implemented into the GPI Data Reduction Pipeline to measure the properties of the satellite spots and discuss the precision of the reconstructed astrometry and spectrophotometry of the occulted star. We find the astrometric precision of the satellite spots in an $H$-band datacube to be $0.05$ pixels and is best when individual satellite spots have a signal to noise ratio (SNR) of $> 20$. In regards to satellite spot spectrophotometry, we find that the total flux from the satellite spots is stable to $\\sim 7\\...

  13. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images (United States)

    Dabrowska-Zielinska, K.; Budzynska, M.; Kowalik, W.; Turlej, K.


    The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  14. Detecting aircrafts from satellite images using saliency and conical pyramid based template representation

    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 involved in locating targets in satellite images are viewpoint, spectral (intensity) and scale variations. Diversity in background texture and target clutter also adds up to the complexity of the problem of localizing aircrafts in satellite images. Failure of modern feature extraction and object detection methods highlight the complexity of the problem. In the proposed work, pre-processing techniques, viz.denoising and contrast enhancement, are first used to improve the quality of the images. Then, the concept of unsupervised saliency is used to detect the potential regions of interest, which reduces the search space. Parts from the salient regions are further processed using clustering and morphological processing to get the probable regions of isolated aircraft targets. Finally, a novel conical pyramid based framework for template representation of the target samples is proposed for matching. Experimental results shown on a few satellite images exhibit the superior performance of the proposed methods.

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

    Institute of Scientific and Technical Information of China (English)

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


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

  16. Effect of satellite formations and imaging modes on global albedo estimation (United States)

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


    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

  17. Digital image processing for the earth resources technology satellite data. (United States)

    Will, P. M.; Bakis, R.; Wesley, M. A.


    This paper discusses the problems of digital processing of the large volumes of multispectral image data that are expected to be received from the ERTS program. Correction of geometric and radiometric distortions are discussed and a byte oriented implementation is proposed. CPU timing estimates are given for a System/360 Model 67, and show that a processing throughput of 1000 image sets per week is feasible.

  18. Image quality dependence on image processing software in computed radiography

    Directory of Open Access Journals (Sweden)

    Lourens Jochemus Strauss


    Full Text Available Background. Image post-processing gives computed radiography (CR a considerable advantage over film-screen systems. After digitisation of information from CR plates, data are routinely processed using manufacturer-specific software. Agfa CR readers use MUSICA software, and an upgrade with significantly different image appearance was recently released: MUSICA2. Aim. This study quantitatively compares the image quality of images acquired without post-processing (flatfield with images processed using these two software packages. Methods. Four aspects of image quality were evaluated. An aluminium step-wedge was imaged using constant mA at tube voltages varying from 40 to 117kV. Signal-to-noise ratios (SNRs and contrast-to-noise Ratios (CNRs were calculated from all steps. Contrast variation with object size was evaluated with visual assessment of images of a Perspex contrast-detail phantom, and an image quality figure (IQF was calculated. Resolution was assessed using modulation transfer functions (MTFs. Results. SNRs for MUSICA2 were generally higher than the other two methods. The CNRs were comparable between the two software versions, although MUSICA2 had slightly higher values at lower kV. The flatfield CNR values were better than those for the processed images. All images showed a decrease in CNRs with tube voltage. The contrast-detail measurements showed that both MUSICA programmes improved the contrast of smaller objects. MUSICA2 was found to give the lowest (best IQF; MTF measurements confirmed this, with values at 3.5 lp/mm of 10% for MUSICA2, 8% for MUSICA and 5% for flatfield. Conclusion. Both MUSICA software packages produced images with better contrast resolution than unprocessed images. MUSICA2 has slightly improved image quality than MUSICA.

  19. Pre-processing Algorithm for Rectification of Geometric Distortions in Satellite Images

    Directory of Open Access Journals (Sweden)

    Narayan Panigrahi


    Full Text Available A number of algorithms have been reported to process and remove geometric distortions in satellite images. Ortho-correction, geometric error correction, radiometric error removal, etc are a few important examples. These algorithm require supplementary meta-information of the satellite images such as ground control points and correspondence, sensor orientation details, elevation profile of the terrain, etc to establish corresponding transformations. In this paper, a pre-processing algorithm has been proposed which removes systematic distortions of a satellite image and thereby removes the blank portion of the image. It is an input-to-output mapping of image pixels, where the transformation computes the coordinate of each output pixel corresponding to the input pixel of an image. The transformation is established by the exact amount of scaling, rotation and translation needed for each pixel in the input image so that the distortion induced during the recording stage is corrected.Defence Science Journal, 2011, 61(2, pp.174-179, DOI:

  20. A fast and automatic mosaic method for high-resolution satellite images (United States)

    Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing


    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. Multiangle Bistatic SAR Imaging and Fusion Based on BeiDou-2 Navigation Satellite System

    Directory of Open Access Journals (Sweden)

    Zeng Tao


    Full Text Available Bistatic Synthetic Aperture Radar (BSAR based on the Global Navigation Service System (GNSSBSAR uses navigation satellites as radar transmitters, which are low in cost. However, GNSS-BSAR images have poor resolution and low Signal-to-Noise Ratios (SNR. In this paper, a multiangle observation and data processing strategy are presented based on BeiDou-2 navigation satellite imagery, from which twenty-six BSAR images in different configurations are obtained. A region-based fusion algorithm using region of interest segmentation is proposed, and a high-quality fusion image is obtained. The results reveal that the multiangle imaging method can extend the applications of GNSS-BSAR.

  2. Wave Period and Coastal Bathymetry Estimations from Satellite Images (United States)

    Danilo, Celine; Melgani, Farid


    We present an approach for wave period and coastal water depth estimation. The approach based on wave observations, is entirely independent of ancillary data and can theoretically be applied to SAR or optical images. In order to demonstrate its feasibility we apply our method to more than 50 Sentinel-1A images of the Hawaiian Islands, well-known for its long waves. Six wave buoys are available to compare our results with in-situ measurements. The results on Sentinel-1A images show that half of the images were unsuitable for applying the method (no swell or wavelength too small to be captured by the SAR). On the other half, 78% of the estimated wave periods are in accordance with buoy measurements. In addition, we present preliminary results of the estimation of the coastal water depth on a Landsat-8 image (with characteristics close to Sentinel-2A). With a squared correlation coefficient of 0.7 for ground truth measurement, this approach reveals promising results for monitoring coastal bathymetry.

  3. Satellite single-axis attitude determination based on Automatic Dependent Surveillance - Broadcast signals (United States)

    Zhou, Kaixing; Sun, Xiucong; Huang, Hai; Wang, Xinsheng; Ren, Guangwei


    The space-based Automatic Dependent Surveillance - Broadcast (ADS-B) is a new technology for air traffic management. The satellite equipped with spaceborne ADS-B system receives the broadcast signals from aircraft and transfers the message to ground stations, so as to extend the coverage area of terrestrial-based ADS-B. In this work, a novel satellite single-axis attitude determination solution based on the ADS-B receiving system is proposed. This solution utilizes the signal-to-noise ratio (SNR) measurement of the broadcast signals from aircraft to determine the boresight orientation of the ADS-B receiving antenna fixed on the satellite. The basic principle of this solution is described. The feasibility study of this new attitude determination solution is implemented, including the link budget and the access analysis. On this basis, the nonlinear least squares estimation based on the Levenberg-Marquardt method is applied to estimate the single-axis orientation. A full digital simulation has been carried out to verify the effectiveness and performance of this solution. Finally, the corresponding results are processed and presented minutely.

  4. Attitude motion compensation for imager on Fengyun-4 geostationary meteorological satellite (United States)

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


    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.

  5. Collection of road traffic information from satellite images and digital map (United States)

    Shinmura, Fumito; Saji, Hitoshi


    There have been many reports on the analysis of the Earth's surface by remote sensing. The purpose of this study is to analyze traffic information, and we have been studying methods of collecting traffic information by remote sensing. To collect traffic information, sensors installed on the roadside are frequently used. However, methods using sensors only collect information around the positions of the sensors. In this study, we attempt to solve this problem by using satellite images, which have recently become increasingly available. We propose a method of collecting traffic information over a large area using satellite images as well as three-dimensional digital maps. We assess traffic conditions by computing the number of edges of vehicles per road section as follows. First, the edges of vehicles are detected in satellite images. During this processing, three-dimensional digital maps are used to increase the accuracy of vehicle edge detection. The number of vehicles per road section, which is computed from the number of edges of vehicles, is computed and referred to as the vehicle density. Traffic conditions can be assessed from the vehicle density and are considered useful for collecting information on traffic congestion. In this study, we experimentally confirm that congested roads can be extracted from satellite images by our method.

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


    Marc Wieland; Massimiliano Pittore


    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 recognitio...

  7. Mapping land cover from satellite images: A basic, low cost approach (United States)

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


    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.

  8. Extraction of DTM from Satellite Images Using Neural Networks


    Tapper, Gustav


    This thesis presents a way to generate a Digital Terrain Model (dtm) from a Digital Surface Model (dsm) and multi spectral images (including the Near Infrared (nir) color band). An Artificial Neural Network (ann) is used to pre-classify the dsm and multi spectral images. This in turn is used to filter the dsm to a dtm. The use of an ann as a classifier provided good results. Additionally, the addition of the nir color band resulted in an improvement of the accuracy of the classifier. Using th...

  9. Magnetic resonance imaging research in sub-Saharan Africa: challenges and satellite-based networking implementation. (United States)

    Latourette, Matthew T; Siebert, James E; Barto, Robert J; Marable, Kenneth L; Muyepa, Anthony; Hammond, Colleen A; Potchen, Michael J; Kampondeni, Samuel D; Taylor, Terrie E


    As part of an NIH-funded study of malaria pathogenesis, a magnetic resonance (MR) imaging research facility was established in Blantyre, Malaŵi to enhance the clinical characterization of pediatric patients with cerebral malaria through application of neurological MR methods. The research program requires daily transmission of MR studies to Michigan State University (MSU) for clinical research interpretation and quantitative post-processing. An intercontinental satellite-based network was implemented for transmission of MR image data in Digital Imaging and Communications in Medicine (DICOM) format, research data collection, project communications, and remote systems administration. Satellite Internet service costs limited the bandwidth to symmetrical 384 kbit/s. DICOM routers deployed at both the Malaŵi MRI facility and MSU manage the end-to-end encrypted compressed data transmission. Network performance between DICOM routers was measured while transmitting both mixed clinical MR studies and synthetic studies. Effective network latency averaged 715 ms. Within a mix of clinical MR studies, the average transmission time for a 256 × 256 image was ~2.25 and ~6.25 s for a 512 × 512 image. Using synthetic studies of 1,000 duplicate images, the interquartile range for 256 × 256 images was [2.30, 2.36] s and [5.94, 6.05] s for 512 × 512 images. Transmission of clinical MRI studies between the DICOM routers averaged 9.35 images per minute, representing an effective channel utilization of ~137% of the 384-kbit/s satellite service as computed using uncompressed image file sizes (including the effects of image compression, protocol overhead, channel latency, etc.). Power unreliability was the primary cause of interrupted operations in the first year, including an outage exceeding 10 days.

  10. 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


    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.

  11. 3D mapping from high resolution satellite images (United States)

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


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

  12. Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series (United States)

    Champion, Nicolas


    Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

  13. Automatic cloud detection for high resolution satellite stereo images and its application in terrain extraction (United States)

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


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

  14. Topic Modelling for Object-Based Unsupervised Classification of VHR Panchromatic Satellite Images Based on Multiscale Image Segmentation

    Directory of Open Access Journals (Sweden)

    Li Shen


    Full Text Available Image segmentation is a key prerequisite for object-based classification. However, it is often difficult, or even impossible, to determine a unique optimal segmentation scale due to the fact that various geo-objects, and even an identical geo-object, present at multiple scales in very high resolution (VHR satellite images. To address this problem, this paper presents a novel unsupervised object-based classification for VHR panchromatic satellite images using multiple segmentations via the latent Dirichlet allocation (LDA model. Firstly, multiple segmentation maps of the original satellite image are produced by means of a common multiscale segmentation technique. Then, the LDA model is utilized to learn the grayscale histogram distribution for each geo-object and the mixture distribution of geo-objects within each segment. Thirdly, the histogram distribution of each segment is compared with that of each geo-object using the Kullback-Leibler (KL divergence measure, which is weighted with a constraint specified by the mixture distribution of geo-objects. Each segment is allocated a geo-object category label with the minimum KL divergence. Finally, the final classification map is achieved by integrating the multiple classification results at different scales. Extensive experimental evaluations are designed to compare the performance of our method with those of some state-of-the-art methods for three different types of images. The experimental results over three different types of VHR panchromatic satellite images demonstrate the proposed method is able to achieve scale-adaptive classification results, and improve the ability to differentiate the geo-objects with spectral overlap, such as water and grass, and water and shadow, in terms of both spatial consistency and semantic consistency.

  15. Building identification from very high-resolution satellite images (United States)

    Lhomme, Stephane

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


    Directory of Open Access Journals (Sweden)

    N. M. S. M. Kadhim


    Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates

  17. Thermal precursors in satellite images of the 1999 eruption of Shishaldin Volcano (United States)

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


    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. Role of Indian remote sensing imaging satellites for the Antarctic monitoring and mapping: a case study around Indian Antarctic research stations (United States)

    Jayaprasad, P.; Mehra, Raghav; Chawla, Saket; Rajak, D. Ram; Oza, Sandip R.


    Antarctic research station's existence largely depend on the supply of fuel, food and other commodities through Antarctic Scientific Expedition using ship voyage. Safer Ship Navigation demands high resolution satellite monitoring of the ice conditions which varies from 30 km to 200 km from the Antarctic coast of Research stations. During the last couple of years Indian Satellites play a major role in safer ship navigation in sea ice regions of the Arctic and the Antarctic. Specifically Indian Scientific Expedition to the Antarctica (ISEA) through National Centre for Antarctic and Oceanic Research (NCAOR) is one of the beneficiaries for safer ship navigation using information derived from Indian Satellite data. Space Applications Centre, Indian Space Research Organisation (SAC-ISRO) is providing Sea Ice Advisories for the safer optimum entry and exit for the expedition ship at two of the Research stations Bharati and Maitri. Two of the Indian Satellites namely Radar Imaging Satellite-1 (RISAT-1) and ResourceSAT-2 (RS-2) are the two major workhorses of ISRO for monitoring and mapping of the Antarctic terrain. The present study demonstrate the utilisation potential of these satellite images for various Polar Science Applications. Mosaic of the Antarctic Terrain was generated from RISAT-1 CRS data. The preliminary results of the mosaic from CRS- circular polarisation data is presented. Demonstration of the study is extended for other applications such as change detection studies, safer ship navigation and extreme events of Antarctica. The use of multi resolution multi sensor data is also shown in the study.

  19. Modifications of the heliostat procedures for irradiance estimates from satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, H.G.; Costanzo, Claudio; Heinemann, Detlev [Oldenburg Univ. (Germany). Fachbereich 8 - Physik


    Images taken by geostationary satellites may be used to estimate solar irradiance fluxes at the earth`s surface. The Heliostat method is a widely applied procedure for this task. It is based on the empirical correlation between a satellite derived cloud index and the irradiance at the ground. Modifications to this procedure that may reduce the temporal variability of the correlation are presented. The modified method may open the way to the use of a generic relation of cloud index and global irradiance. (author)

  20. An Investigation on Water Quality of Darlik Dam Drinking Water using Satellite Images

    Directory of Open Access Journals (Sweden)

    Erhan Alparslan


    Full Text Available Darlik Dam supplies 15% of the water demand of Istanbul Metropolitan City of Turkey. Water quality (WQ in the Darlik Dam was investigated from Landsat 5 TM satellite images of the years 2004, 2005, and 2006 in order to determine land use/land cover changes in the watershed of the dam that may deteriorate its WQ. The images were geometrically and atmospherically corrected for WQ analysis. Next, an investigation was made by multiple regression analysis between the unitless planetary reflectance values of the first four bands of the June 2005 Landsat TM image of the dam and WQ parameters, such as chlorophyll-a, total dissolved matter, turbidity, total phosphorous, and total nitrogen, measured at satellite image acquisition time at seven stations in the dam. Finally, WQ in the dam was studied from satellite images of the years 2004, 2005, and 2006 by pattern recognition techniques in order to determine possible water pollution in the dam. This study was compared to a previous study done by the authors in the Küçükçekmece water reservoir, also in Istanbul City.

  1. Fast segmentation of satellite images using SLIC, WebGL and Google Earth Engine (United States)

    Donchyts, Gennadii; Baart, Fedor; Gorelick, Noel; Eisemann, Elmar; van de Giesen, Nick


    Google Earth Engine (GEE) is a parallel geospatial processing platform, which harmonizes access to petabytes of freely available satellite images. It provides a very rich API, allowing development of dedicated algorithms to extract useful geospatial information from these images. At the same time, modern GPUs provide thousands of computing cores, which are mostly not utilized in this context. In the last years, WebGL became a popular and well-supported API, allowing fast image processing directly in web browsers. In this work, we will evaluate the applicability of WebGL to enable fast segmentation of satellite images. A new implementation of a Simple Linear Iterative Clustering (SLIC) algorithm using GPU shaders will be presented. SLIC is a simple and efficient method to decompose an image in visually homogeneous regions. It adapts a k-means clustering approach to generate superpixels efficiently. While this approach will be hard to scale, due to a significant amount of data to be transferred to the client, it should significantly improve exploratory possibilities and simplify development of dedicated algorithms for geoscience applications. Our prototype implementation will be used to improve surface water detection of the reservoirs using multispectral satellite imagery.

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

    Directory of Open Access Journals (Sweden)

    Peng Zhang


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


    Directory of Open Access Journals (Sweden)

    Kupidura Przemysław


    Full Text Available The article is focused on the analysis of possibilities of using granulometric analysis methods: the morphological profile, and granulometric maps in detecting buildings on satellite images. It briefly explains the theoretical basis for granulometric analysis of image and compares two methods used in research. Tests were carried out on a fragment of QuickBird satellite scene – pansharpened multispectral image. 8 variants of classification differing in terms of the data and the model of classification were compared. Evaluation of the effectiveness of the different options for classification based on the analysis factor kappa values and omission and commission errors. The results indicate the significant potential of the proposed methods, and analysis of the observed imperfections allows to specify the possible fields of their development

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

    Directory of Open Access Journals (Sweden)

    Yun Zhang


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

  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


    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. Parallel algorithms of relative radiometric correction for images of TH-1 satellite (United States)

    Wang, Xiang; Zhang, Tingtao; Cheng, Jiasheng; Yang, Tao


    The first generation of transitive stereo-metric satellites in China, TH-1 Satellite, is able to gain stereo images of three-line-array with resolution of 5 meters, multispectral images of 10 meters, and panchromatic high resolution images of 2 meters. The procedure between level 0 and level 1A of high resolution images is so called relative radiometric correction (RRC for short). The processing algorithm of high resolution images, with large volumes of data, is complicated and time consuming. In order to bring up the processing speed, people in industry commonly apply parallel processing techniques based on CPU or GPU. This article firstly introduces the whole process and each step of the algorithm - that is in application - of RRC for high resolution images in level 0; secondly, the theory and characteristics of MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) parallel programming techniques is briefly described, as well as the superiority for parallel technique in image processing field; thirdly, aiming at each step of the algorithm in application and based on MPI+OpenMP hybrid paradigm, the parallelizability and the strategies of parallelism for three processing steps: Radiometric Correction, Splicing Pieces of TDICCD (Time Delay Integration Charge-Coupled Device) and Gray Level Adjustment among pieces of TDICCD are deeply discussed, and furthermore, deducts the theoretical acceleration rates of each step and the one of whole procedure, according to the processing styles and independence of calculation; for the step Splicing Pieces of TDICCD, two different strategies of parallelism are proposed, which are to be chosen with consideration of hardware capabilities; finally, series of experiments are carried out to verify the parallel algorithms by applying 2-meter panchromatic high resolution images of TH-1 Satellite, and the experimental results are analyzed. Strictly on the basis of former parallel algorithms, the programs in the experiments

  7. Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD. (United States)

    Bhandari, A K; Soni, V; Kumar, A; Singh, G K


    This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Modeling of solar irradiance using satellite images and direct terrestrial measurements with PV modules (United States)

    Tyukhov, Igor; Schakhramanyan, Michael; Strebkov, Dmitry; Tikhonov, Anton; Vignola, Frank


    A simple, affordable and efficient multifaceted system with technical software programs, "Kosmos 3M", was developed for taking images of the Earth from NOAA satellites and for handling this images and analyzing many geographical and meteorological parameters. Technical software programs have been developed that utilize the "Kosmos 3M" Receiver system. Basic capabilities of the multifaceted "Kosmos 3M" system include: receiving signal from NOAA satellites; digital processing of space images with geographical fixing, superposition of maps of cities and coordinate grid; finding of geographical coordinates at any point of space image; finding of temperature of underlying surface at given points; finding of albedo (reflection coefficient) at any point of space image; finding of upper boundary of clouds (cloudiness); forecasting of dangerous weather phenomena; defining wind fields in cyclones; precipitations forecast; measuring distances between given points; measuring surfaces (areas); and forming of electronic library of images of the Earth. Work is underway to use the "Kosmos 3M" cloudiness images to estimate the incident solar radiation values for evaluating terrestrial solar energy performance in real time. Such kind of system would have a wide variety of uses from the classroom to the field.

  9. A study of L-dependent Pc3 pulsations observed by low Earth orbiting CHAMP satellite

    Directory of Open Access Journals (Sweden)

    D. C. Ndiitwani


    Full Text Available Field line resonances (FLR driven by compressional waves are an important mechanism for the generation of ULF geomagnetic pulsations observed at all latitudes during local daytime. References to observations of toroidal standing Alfvén mode oscillations with clearly L-dependent frequencies from spacecraft in the outer magnetosphere for L>3 are limited in the literature. Such observations in the inner magnetosphere for L<3 have not yet been reported in the literature. This study offers two interesting case studies of observations of ULF waves by the low Earth orbiting CHAMP satellite. The magnetic field measurements from CHAMP, which are of unprecedented accuracy and resolution, are compared to Hermanus magnetometer data for times when CHAMP crosses the ground station L-shell, namely for 13 February 2002 and 18 February 2003. The data were analysed for Pc3 pulsation activity using the Maximum Entropy Spectral Analysis (MESA method to visualise FLRs in the vector magnetometer data. For the first time observations of Pc3 toroidal oscillations with clearly L-dependent frequencies for lower L-shell values (L<3 observed by an LEO satellite are reported. These observations show FLR frequencies increasing as a function of decreasing latitude down to L=1.6 and then decreasing as a result of the larger plasma density of the upper ionosphere. The L-dependent frequency oscillations were observed in the presence of a broadband compressional wave spectrum. Our observations thus confirm the well-known magnetohydrodynamic (MHD wave theoretical prediction of a compressional wave being the driver of the field line resonance.

  10. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images (United States)

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


    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.

  11. Direct Geolocation of Satellite Images with the EO-CFI Libraries (United States)

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


    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Fledderman, P.D.


    '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.'

  13. Image and Processing Models for Satellite Detection in Images Acquired by Space-based Surveillance-of-Space Sensors (United States)


    software. Résumé …..... Dans le cadre de la surveillance de l’espace, les objets spatiaux connus en orbite (OSO), i.e., satellites actifs ou débris...SAPPHIRE et NEOSSat. Ce document contient des modèles qui décrivent la formation des images et le processus d’acquisition de capteurs , basés au sol ou dans

  14. Contrail frequency over Europe from NOAA-satellite images

    Directory of Open Access Journals (Sweden)

    V. Gayler

    Full Text Available Contrail cloudiness over Europe and the eastern part of the North Atlantic Ocean was analyzed for the two periods September 1979 - December 1981 and September 1989 - August 1992 by visual inspection of quicklook photographic prints of NOAA/AVHRR infrared images. The averaged contrail cover exhibits maximum values along the transatlantic flight corridor around 50 °N (of almost 2% and over western Europe resulting in 0.5% contrail cloudiness on average. A strong yearly cycle appears with a maximum (<2% in spring and summer over the Atlantic and a smaller maximum (<1% in winter over southwestern Europe. Comparing the two time periods, which are separated by one decade, shows there is a significant decrease in contrail cloudiness over western Europe and a significant increase over the North Atlantic between March and July. Contrail cloud cover during daytime is about twice as high as during nighttime. Contrails are found preferentially in larger fields of 1000 km diameter which usually last for more than a day. Causes, possible errors and consequences are discussed.

  15. Contrail frequency over Europe from NOAA-satellite images (United States)

    Bakan, S.; Betancor, M.; Gayler, V.; Graßl, H.


    Contrail cloudiness over Europe and the eastern part of the North Atlantic Ocean was analyzed for the two periods September 1979 - December 1981 and September 1989 - August 1992 by visual inspection of quicklook photographic prints of NOAA/AVHRR infrared images. The averaged contrail cover exhibits maximum values along the transatlantic flight corridor around 50 °N (of almost 2%) and over western Europe resulting in 0.5% contrail cloudiness on average. A strong yearly cycle appears with a maximum (<2%) in spring and summer over the Atlantic and a smaller maximum (<1%) in winter over southwestern Europe. Comparing the two time periods, which are separated by one decade, shows there is a significant decrease in contrail cloudiness over western Europe and a significant increase over the North Atlantic between March and July. Contrail cloud cover during daytime is about twice as high as during nighttime. Contrails are found preferentially in larger fields of 1000 km diameter which usually last for more than a day. Causes, possible errors and consequences are discussed.

  16. GNSS Carrier Phase Integer Ambiguity Resolution with Camera and Satellite images (United States)

    Henkel, Patrick


    Ambiguity Resolution is the key to high precision position and attitude determination with GNSS. However, ambiguity resolution of kinematic receivers becomes challenging in environments with substantial multipath, limited satellite availability and erroneous cycle slip corrections. There is a need for other sensors, e.g. inertial sensors that allow an independent prediction of the position. The change of the predicted position over time can then be used for cycle slip detection and correction. In this paper, we provide a method to improve the initial ambiguity resolution for RTK and PPP with vision-based position information. Camera images are correlated with geo-referenced aerial/ satellite images to obtain an independent absolute position information. This absolute position information is then coupled with the GNSS and INS measurements in an extended Kalman filter to estimate the position, velocity, acceleration, attitude, angular rates, code multipath and biases of the accelerometers and gyroscopes. The camera and satellite images are matched based on some characteristic image points (e.g. corners of street markers). We extract these characteristic image points from the camera images by performing the following steps: An inverse mapping (homogenous projection) is applied to transform the camera images from the driver's perspective to bird view. Subsequently, we detect the street markers by performing (a) a color transformation and reduction with adaptive brightness correction to focus on relevant features, (b) a subsequent morphological operation to enhance the structure recognition, (c) an edge and corner detection to extract feature points, and (d) a point matching of the corner points with a template to recognize the street markers. We verified the proposed method with two low-cost u-blox LEA 6T GPS receivers, the MPU9150 from Invensense, the ASCOS RTK corrections and a PointGrey camera. The results show very precise and seamless position and attitude

  17. Content dependent selection of image enhancement parameters for mobile displays (United States)

    Lee, Yoon-Gyoo; Kang, Yoo-Jin; Kim, Han-Eol; Kim, Ka-Hee; Kim, Choon-Woo


    Mobile devices such as cellular phones and portable multimedia player with capability of playing terrestrial digital multimedia broadcasting (T-DMB) contents have been introduced into consumer market. In this paper, content dependent image quality enhancement method for sharpness and colorfulness and noise reduction is presented to improve perceived image quality on mobile displays. Human visual experiments are performed to analyze viewers' preference. Relationship between the objective measures and the optimal values of image control parameters are modeled by simple lookup tables based on the results of human visual experiments. Content dependent values of image control parameters are determined based on the calculated measures and predetermined lookup tables. Experimental results indicate that dynamic selection of image control parameters yields better image quality.

  18. Fusion between Satellite and Geophysical images in the study of Archaeological Sites (United States)

    Karamitrou, A. A.; Tsokas, G. N.; Petrou, M.; Maggidis, C.


    In this work various image fusion techniques are used between one satellite (Quickbird) and one geophysical (electric resistivity) image to create various combinations with higher information content than the two original images independently. The resultant images provide more information about possible buried archaeological relics. The examined archaeological area is located in mainland Greece near the city of Boetia at the acropolis of Gla. The acropolis was built on a flat-topped bedrock outcrop at the north-eastern edge of the Kopais basin. When Kopais was filled with water, Glas was emerging as an island. At the end of 14th century the two palaces of Thebes and Orchomenos jointly utilized a large scale engineering project in order to transform the Kopais basin into a fertile plain. They used the acropolis to monitor the project, and as a warehouse to storage the harvest. To examine the Acropolis for potential archaeological remnants we use one Quickbird satellite image that covers the surrounding area of Gla. The satellite image includes one panchromatic (8532x8528 pixels) and one multispectral (2133x2132 pixels) image, collected on 30th of August 2011, covering an area of 20 square kilometers. On the other hand, geophysical measurements were performed using the electric resistivity method to the south west part of the Acropolis. To combine these images we investigate mean-value fusion, wavelets fusion, and curvelet fusion. In the cases of wavelet and curvelet fusion we apply as the fusion criterion the maximum frequency rule. Furthermore, the two original images, and excavations near the area suggest that the dominant orientations of the buried features are north-south and east-west. Therefore, in curvelet fusion method, in curvelet domain we enhance the image details along these specific orientations, additionally to the fusion. The resultant fused images succeed to map linear and rectangular features that were not easily visible in the original images

  19. Persistent scatterers detection on synthetic aperture radar images acquired by Sentinel-1 satellite (United States)

    Dǎnişor, Cosmin; Popescu, Anca; Datcu, Mihai


    Persistent Scatterers Interferometry (PS-InSAR) has become a popular method in remote sensing because of its capability to measure terrain deformations with very high accuracy. It relies on multiple Synthetic Aperture Radar (SAR) acquisitions, to monitor points with stable proprieties over time, called Persistent Scatterers (PS)[1]. These points are unaffected by temporal decorrelation, therefore by analyzing their interferometric phase variation we can estimate the scene's deformation rates within a given time interval. In this work, we apply two incoherent detection algorithms to identify Persistent Scatterers candidates in the city of Focșani, Romania. The first method studies the variation of targets' intensities along the SAR acquisitions and the second method analyzes the spectral proprieties of the scatterers. The algorithms were implemented on a dataset containing 11 complex images of the region covering Buzău, Brăila and Focșani cities. Images were acquired by Sentinel-1 satellite in a time span of 5 months, from October 2014 to February 2015. The processing chain follows the requirements imposed by the new C-band SAR images delivered by the Sentinel-1 satellite (launched in April 2014) imaging in Interferometric Wide (IW) mode. Considering the particularities of the TOPS (Terrain Observation with Progressive Scans in Azimuth) imaging mode[2], special requirements had to be considered for pre-processing steps. The PS detection algorithms were implemented in Gamma RS program, a software which contains various function packages dedicated to SAR images focalization, analysis and processing.

  20. A data mining based approach to predict spatiotemporal changes in satellite images (United States)

    Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben


    The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

  1. Effects of rubber shock absorber on the flywheel micro vibration in the satellite imaging system (United States)

    Deng, Changcheng; Mu, Deqiang; Jia, Xuezhi; Li, Zongxuan


    When a satellite is in orbit, its flywheel will generate micro vibration and affect the imaging quality of the camera. In order to reduce this effect, a rubber shock absorber is used, and a numerical model and an experimental setup are developed to investigate its effect on the micro vibration in the study. An integrated model is developed for the system, and a ray tracing method is used in the modeling. The spot coordinates and displacements of the image plane are obtained, and the modulate transfer function (MTF) of the system is calculated. A satellite including a rubber shock absorber is designed, and the experiments are carried out. Both simulation and experiments results show that the MTF increases almost 10 %, suggesting the rubber shock absorber is useful to decrease the flywheel vibration.

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

    Directory of Open Access Journals (Sweden)

    Salemi Eric


    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. Investigation of Interpolation for Solar Irradiation in Non-Observed Point Based on Satellite Images (United States)

    Shinoda, Yukio; Fujisawa, Sei; Seki, Tomomichi

    Penetrating the Photovoltaic Power Generation System (PV) on an enormous scale over a next decade has some crucial problems which affect on, for example, power grid stabilization and operation including existing power stations for electric power utilities. It would be therefore important for future operation to estimate power output generated by PV in advance. We focus on interpolation using observed solar irradiation (SI) and brightness of pixel on a satellite visible image for estimating SI even in non-observed point. Our results by single regression analysis between observed SI and brightness on a satellite image as cloudiness show that a shift of highest determination coefficient on each hour would represent solar movement and this higher determination coefficient would indicate a position which SI and cloud would cross. Finally assessment of error in this interpolation shows enough accuracy at least in daytime period, which is important for electricity utilities.

  4. Digital elevation model and satellite images an assessment of soil erosion potential in the Pcinja catchment

    Directory of Open Access Journals (Sweden)

    Milevski Ivica


    Full Text Available Pcinja is large left tributary of Vardar River (135 km long, 2877,3 km2 catchment’s area, which drainages surface waters from northeastern Macedonia, and small part of southeastern Serbia. Because of suitable physical-geographic factors (geology, terrain morphology, climate, hydrology, vegetation coverage, soil composition, and high human impact, some parts of the catchment’s suffer significant erosion process. For this reason, it is necessary to research properly spatial distribution of erosion, then influence of physical and anthropogenic factors for the intensity of soil erosion, related erosion landforms (with morphology, genesis, evolution, soil erosion protection etc.. Earlier researches in the area have been performed generally with combination of cartographic and classic field analysis. But in last decades, there are new possibilities available like satellite images and digital elevation models. In this work has been presented the methodology of utilization of satellite images and DEM for erosion research, with analysis and comparisons of outcome data.

  5. Image Dependent Energy-Constrained Local Backlight Dimming

    DEFF Research Database (Denmark)

    Burini, Nino; Nadernejad, Ehsan; Korhonen, Jari;


    In this work, we consider and propose two extensions to an optimization-based image dependent backlight dimming algorithm. The first extension introduces error weighting based on human perception of luminance, aiming to improve the perceived image quality; the second extension adds an adjustable ...

  6. A novel super resolution scheme to acquire and process satellite images (United States)

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


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

  7. Quantitative measurements of Jupiter, Saturn, their rings and satellites made from Voyager imaging data (United States)

    Collins, S. A.; Bunker, A. S.


    The Voyager spacecraft cameras use selenium-sulfur slow scan vidicons to convert focused optical images into sensible electrical signals. The vidicon-generated data thus obtained are the basis of measurements of much greater precision than was previously possible, in virtue of their superior linearity, geometric fidelity, and the use of in-flight calibration. Attention is given to positional, radiometric, and dynamical measurements conducted on the basis of vidicon data for the Saturn rings, the Saturn satellites, and the Jupiter atmosphere.

  8. IoSiS: a radar system for imaging of satellites in space (United States)

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


    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.

  9. Estimating Advective Near-surface Currents from Ocean Color Satellite Images (United States)


    K., Arnone, R.A., et al. (2014). Forecasting the ocean’s optical environment using the BioCast system. Oceanography , 27, 46–57. 14 H. Yang et al...satellite images 0602435N 73-9358-09-5 Haoping Yang, Robert Arnone, Jason Jolliff Naval Research Laboratory Oceanography Division Stennis Space Center...U.S. East and Gulf coasts. The MCC calculation is validated in a series of Bio- Optical Forecasting (BioCast) experiments with predetermined synthetic

  10. Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging (United States)

    Nag, S.; Li, A.


    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

  11. Ecological restoration of groundwater-dependent vegetation in the arid Ejina Delta: evidences from satellite evapotranspiration (United States)

    Kai, Lu; Garcia, Monica; Yu, Jingjie; Zhang, Yichi; Wang, Ping; Wang, Sheng; Liu, Xiao


    The ecological water conveyance project (EWCP) in the Ejina delta, a typical hyper-arid area of China, aimed to restore degraded phreatophytic ecosystems. We assessed the degree of ecosystem recovery using as an ecohydrological indicator a ratio between actual and potential evapotranspiration derived from MODIS since the beginning of the project in 2001. The selected indicator was the Temperature Vegetation Dryness Index (TVDI) which was validated with Eddy covariance (EC) data confirming its applicability to monitor groundwater dependent vegetation. The spatial analyses of the evapotranspiration ratio show drying trends (2000-2015) which are stronger and also cover larger extensions than the wetting trends. Thus, the condition of key riparian areas relying mostly on surface water improved since the project began. However, groundwater dependent ecosystems located in lower river Xihe reaches present drying trends. It seems that despite of the runoff supplemented by the EWCP project, there is nowadays more inequality in the access to water by groundwater dependent ecosystems in the Ejina Delta. The study shows that energy-evaporation indices, relying on radiometric satellite temperature like the TVDI, can detect degradation signals that otherwise might go undetected by NDVI analyses especially in arid regions, where vegetation indices are greatly affected by the soil background signals. Additionally, they can provide timely information to water managers on how much water to allocate for a sustainable restoration program.

  12. A Bayesian approach for solar resource potential assessment using satellite images (United States)

    Linguet, L.; Atif, J.


    The need for a more sustainable and more protective development opens new possibilities for renewable energy. Among the different renewable energy sources, the direct conversion of sunlight into electricity by solar photovoltaic (PV) technology seems to be the most promising and represents a technically viable solution to energy demands. But implantation and deployment of PV energy need solar resource data for utility planning, accommodating grid capacity, and formulating future adaptive policies. Currently, the best approach to determine the solar resource at a given site is based on the use of satellite images. However, the computation of solar resource (non-linear process) from satellite images is unfortunately not straightforward. From a signal processing point of view, it falls within non-stationary, non-linear/non-Gaussian dynamical inverse problems. In this paper, we propose a Bayesian approach combining satellite images and in situ data. We propose original observation and transition functions taking advantages of the characteristics of both the involved type of data. A simulation study of solar irradiance is carried along with this method and a French Guiana solar resource potential map for year 2010 is given.

  13. True Color Images of the Earth created with the Geostationary Satellite Instrument MSG SEVIRI (United States)

    Reuter, Maximilian


    One of the most famous pictures ever taken was by the crew of Apollo 17 in 1972, showing our Earth from a distance of about 45000km. This picture was named 'Blue Marble' and it reminds us of the beauty and uniqueness of our home planet. With geostationary satellites, such views of the Earth are possible without the need to have a photographer in space. However, up to the present, the production of such Blue Marble type images from geostationary satellite data has been impaired by the lack of channels in the visible spectral region. A method for the generation of full disk MSG (METEOSAT Second Generation) SEVIRI (Scanning-Enhanced Visible and Infrared Imager) true colour composite images will be presented. The algorithm mainly uses the SEVIRI channels VIS006 (0.6μm), NIR008 (0.8μm) and NIR016 (1.6μm). The lack of information in the blue and green parts of the visible spectrum is compensated by using data from NASA's (National Aeronautics and Space Administration's) Blue Marble next generation (BMNG) project to fill a look-up table (LUT) transforming RGB (red/green/blue) false colour composite images of VIS006/NIR008/NIR016 into true colour images. Tabulated radiative transfer calculations of a pure Rayleigh atmosphere are used to add an impression of Rayleigh scattering towards the sunlit horizon. The resulting images satisfy naive expectations: clouds are white or transparent, vegetated surfaces are greenish, deserts are sandy-coloured, the ocean is dark blue to black and a narrow halo due to Rayleigh scattering is visible at the sunlit horizon. Therefore, such images are easily interpretable also for inexperienced users not familiar with the characteristics of typical MSG false colour composite images. The images can be used for scientific applications to illustrate specific meteorological conditions or for non-scientific purposes, for example, for raising awareness in the public of the Earth's worthiness of protection.

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

  15. Accelerating Satellite Image Based Large-Scale Settlement Detection with GPU

    Energy Technology Data Exchange (ETDEWEB)

    Patlolla, Dilip Reddy [ORNL; Cheriyadat, Anil M [ORNL; Weaver, Jeanette E [ORNL; Bright, Eddie A [ORNL


    Computer vision algorithms for image analysis are often computationally demanding. Application of such algorithms on large image databases\\---- such as the high-resolution satellite imagery covering the entire land surface, can easily saturate the computational capabilities of conventional CPUs. There is a great demand for vision algorithms running on high performance computing (HPC) architecture capable of processing petascale image data. We exploit the parallel processing capability of GPUs to present a GPU-friendly algorithm for robust and efficient detection of settlements from large-scale high-resolution satellite imagery. Feature descriptor generation is an expensive, but a key step in automated scene analysis. To address this challenge, we present GPU implementations for three different feature descriptors\\-- multiscale Historgram of Oriented Gradients (HOG), Gray Level Co-Occurrence Matrix (GLCM) Contrast and local pixel intensity statistics. We perform extensive experimental evaluations of our implementation using diverse and large image datasets. Our GPU implementation of the feature descriptor algorithms results in speedups of 220 times compared to the CPU version. We present an highly efficient settlement detection system running on a multiGPU architecture capable of extracting human settlement regions from a city-scale sub-meter spatial resolution aerial imagery spanning roughly 1200 sq. kilometers in just 56 seconds with detection accuracy close to 90\\%. This remarkable speedup gained by our vision algorithm maintaining high detection accuracy clearly demonstrates that such computational advancements clearly hold the solution for petascale image analysis challenges.

  16. Search for astronomical sites suitable for infrared observations using GOES satellite images (United States)

    Ducati, Jorge R.; Feijo, Eleandro S.


    Images from GOES satellite were used to develop a method to search for sites suitable to astronomical observations in the infrared. An area of study located in the Peruvian Andes was chosen, with altitudes above 2500 m. Forty-three images from the GOES meteorological satellite in channels 3, 4 and 5 were used. The GOES images, spanning an 11-day period, in each channel, were combined to produced images expressing the surface visibility in each channel. Atmospheric turbulence could be estimated from the variation of visibility over six-hour periods, with one image per hour. As criteria to classify sites on the Andes, we combined information on altitude, visibility of the surface in the infrared, the amount of water vapor in the atmosphere, and atmospheric turbulence. Results of this new method showed that the region of Moquegua, in South Peru, is to be preferred in surveys for astronomical sites. Comparisons with results from other investigators, which used other approaches, indicated that this methodology can produce valid results and can be applied to studies covering larger periods. The general results of this study indicate that the method is valid and can effectively be used as an important resource in surveys for infrared astronomical sites.

  17. Search for astronomical sites suitable for infrared observations using goes satellite images release (United States)

    Ducati, J. R.; Feijó, E.


    Astronomical sites are traditionally found after studies performed over many years, including preliminary selection of places based in general information on climate, clear skies and logistical adequacy. It follows extensive "in situ" monitoring of seeing and cloudiness. Theses procedures are long and expensive, and alternatives can be looked for. In this study, images from GOES meteorological satellite were used to develop a method to search for sites suitable to astronomical observations in the infrared. An area of study located in the Peruvian Andes was chosen, with altitudes above 2500 m. 43 images from the GOES meteorological satellite in chanels 3, 4 and 5 were used. The GOES images, spanning a 11-day period, in each channel, were combined to produced images expressing the surface visibility in each channel. Atmospheric turbulence could be estimated from the variation of visibility over six-hour periods, with one image per hour. As criteria to classify sites on the Andes, we combined information on altitude, visibility of the surface in the infrared, the amount of water vapor in the atmosphere, and atmospheric turbulence. Results of this new method showed that the region of Moquegua, in South Peru, is to be preferred in surveys for astronomical sites. Comparisons with results from other investigators, which used other approaches, indicated that this methodology produces valid results and can be used to studies spanning larger periods. The general results of this study indicate that the method can efectively be used as an important resource in surveys for infrared astronomical sites

  18. a New Algorithm for Void Filling in a Dsm from Stereo Satellite Images in Urban Areas (United States)

    Gharib Bafghi, Z.; Tian, J.; d'Angelo, P.; Reinartz, P.


    Digital Surface Models (DSM) derived from stereo-pair satellite images are the main sources for many Geo-Informatics applications like 3D change detection, object classification and recognition. However since occlusion especially in urban scenes result in some deficiencies in the stereo matching phase, these DSMs contain some voids. In order to fill the voids a range of algorithms have been proposed, mainly including interpolation alone or along with auxiliary DSM. In this paper an algorithm for void filling in DSM from stereo satellite images has been developed. Unlike common previous approaches we didn't use any external DSM to fill the voids. Our proposed algorithm uses only the original images and the unfilled DSM itself. First a neighborhood around every void in the unfilled DSM and its corresponding area in multispectral image is defined. Then it is analysed to extract both spectral and geometric texture and accordingly to assign labels to each cell in the voids. This step contains three phases comprising shadow detection, height thresholding and image segmentation. Thus every cell in void has a label and is filled by the median value of its co-labelled neighbors. The results for datasets from WorldView-2 and IKONOS are shown and discussed.


    Directory of Open Access Journals (Sweden)

    Z. Gharib Bafghi


    Full Text Available Digital Surface Models (DSM derived from stereo-pair satellite images are the main sources for many Geo-Informatics applications like 3D change detection, object classification and recognition. However since occlusion especially in urban scenes result in some deficiencies in the stereo matching phase, these DSMs contain some voids. In order to fill the voids a range of algorithms have been proposed, mainly including interpolation alone or along with auxiliary DSM. In this paper an algorithm for void filling in DSM from stereo satellite images has been developed. Unlike common previous approaches we didn’t use any external DSM to fill the voids. Our proposed algorithm uses only the original images and the unfilled DSM itself. First a neighborhood around every void in the unfilled DSM and its corresponding area in multispectral image is defined. Then it is analysed to extract both spectral and geometric texture and accordingly to assign labels to each cell in the voids. This step contains three phases comprising shadow detection, height thresholding and image segmentation. Thus every cell in void has a label and is filled by the median value of its co-labelled neighbors. The results for datasets from WorldView-2 and IKONOS are shown and discussed.

  20. Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS (United States)

    Hong, Gi Hoon; Yang, Dong Beom; Lee, Hyun-Mi; Yang, Sung Ryull; Chung, Hee Woon; Kim, Chang Joon; Kim, Young-Il; Chung, Chang Soo; Ahn, Yu-Hwan; Park, Young-Je; Moon, Jeong-Eon


    Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.

  1. Imager-to-radiometer inflight cross calibration: RSP radiometric comparison with airborne and satellite sensors

    Directory of Open Access Journals (Sweden)

    J. McCorkel


    Full Text Available This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP that takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS, which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI. First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.


    National Research Council Canada - National Science Library

    Cooper, Nicholas J; Renner, Stéfan; Murray, Carl D; Evans, Michael W


    We present numerically derived orbits and mass estimates for the inner Saturnian satellites, Atlas, Prometheus, Pandora, Janus, and Epimetheus from a fit to 2580 new Cassini Imaging Science Subsystem...

  3. Modeling the spectral response for the soft X-ray imager onboard the ASTRO-H satellite (United States)

    Inoue, Shota; Hayashida, Kiyoshi; Katada, Shuhei; Nakajima, Hiroshi; Nagino, Ryo; Anabuki, Naohisa; Tsunemi, Hiroshi; Tsuru, Takeshi Go; Tanaka, Takaaki; Uchida, Hiroyuki; Nobukawa, Masayoshi; Nobukawa, Kumiko Kawabata; Washino, Ryosaku; Mori, Koji; Isoda, Eri; Sakata, Miho; Kohmura, Takayoshi; Tamasawa, Koki; Tanno, Shoma; Yoshino, Yuma; Konno, Takahiro; Ueda, Shutaro


    The ASTRO-H satellite is the 6th Japanese X-ray astronomical observatory to be launched in early 2016. The satellite carries four kinds of detectors, and one of them is an X-ray CCD camera, the soft X-ray imager (SXI), installed on the focal plane of an X-ray telescope. The SXI contains four CCD chips, each with an imaging area of 31 mm × 31 mm , arrayed in mosaic, covering the field-of-view of 38‧ ×38‧ , the widest ever flown in orbit. The CCDs are a P-channel back-illuminated (BI) type with a depletion layer thickness of 200 μ m . We operate the CCDs in a photon counting mode in which the position and energy of each photon are measured in the energy band of 0.4-12 keV. To evaluate the X-ray spectra obtained with the SXI, an accurate calibration of its response function is essential. For this purpose, we performed calibration experiments at Kyoto and Photon Factory of KEK, each with different X-ray sources with various X-ray energies. We fit the obtained spectra with 5 components; primary peak, secondary peak, constant tail, Si escape and Si fluorescence, and then model their energy dependence using physics-based or empirical formulae. Since this is the first adoption of P-channel BI-type CCDs on an X-ray astronomical satellite, we need to take special care on the constant tail component which is originated in partial charge collection. It is found that we need to assume a trapping layer at the incident surface of the CCD and implement it in the response model. In addition, the Si fluorescence component of the SXI response is significantly weak, compared with those of front-illuminated type CCDs.

  4. Multifractal analysis of satellite images. (Polish Title: Multifraktalna analiza zobrazowan satelitarnych) (United States)

    Wawrzaszek, A.; Krupiński, M.; Drzewiecki, W.; Aleksandrowicz, S.


    Research presented in this paper is focused on the efficiency assessment of multifractal description as a tool for Image Information Mining. Large datasets of very high spatial resolution satellite images (WorldView-2 and EROS-A) have been analysed. The results have confirmed the superiority of multifractals as global image descriptors in comparison to monofractals. Moreover, their usefulness in image classification by using decision trees classifiers was confirmed, also in comparison with textural features. Filtration process preceding fractal and multifractal features estimations was also proved to improve classification results. Additionally, airborne hyperspectral data have been initially analysed. Fractal dimension shows high potential for the description of hyperspectral data. To summarise all conducted tests indicate the usefulness of multifractal formalism in various aspects of remote sensing. Prepared methodology can be further developed and used for more specific tasks, for example in change detection or in the description of hyperspectal data complexity.

  5. Tree detection in orchards from VHR satellite images using scale-space theory (United States)

    Mahour, Milad; Tolpekin, Valentyn; Stein, Alfred


    This study focused on extracting reliable and detailed information from very High Resolution (VHR) satellite images for the detection of individual trees in orchards. The images contain detailed information on spectral and geometrical properties of trees. Their scale level, however, is insufficient for spectral properties of individual trees, because adjacent tree canopies interlock. We modeled trees using a bell shaped spectral profile. Identifying the brightest peak was challenging due to sun illumination effects caused 1 by differences in positions of the sun and the satellite sensor. Crown boundary detection was solved by using the NDVI from the same image. We used Gaussian scale-space methods that search for extrema in the scale-space domain. The procedures were tested on two orchards with different tree types, tree sizes and tree observation patterns in Iran. Validation was done using reference data derived from an UltraCam digital aerial photo. Local extrema of the determinant of the Hessian corresponded well to the geographical coordinates and the size of individual trees. False detections arising from a slight asymmetry of trees were distinguished from multiple detections of the same tree with different extents. Uncertainty assessment was carried out on the presence and spatial extents of individual trees. The study demonstrated how the suggested approach can be used for image segmentation for orchards with different types of trees. We concluded that Gaussian scale-space theory can be applied to extract information from VHR satellite images for individual tree detection. This may lead to improved decision making for irrigation and crop water requirement purposes in future studies.

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

    Directory of Open Access Journals (Sweden)

    Dimitrios Kaimaris


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

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

    Directory of Open Access Journals (Sweden)

    Irene Erlyn Wina Rachmawan


    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.

  8. Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater (United States)

    Werdell, Paul J.; Franz, Bryan Alden; Lefler, Jason Travis; Robinson, Wayne D.; Boss, Emmanuel


    Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

  9. An anti-image interference quadrature IF architecture for satellite receivers

    Directory of Open Access Journals (Sweden)

    He Weidong


    Full Text Available Since Global Navigation Satellite System (GNSS signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF receivers, image aliasing due to in-phase and quadrature (I/Q channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in analog-to-digital converters (ADC. As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is proposed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.

  10. An anti-image interference quadrature IF architecture for satellite receivers

    Institute of Scientific and Technical Information of China (English)

    He Weidong; Lu Xiaochun; He Chengyan; James Torley


    Since Global Navigation Satellite System (GNSS) signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF) receivers, image aliasing due to in-phase and quadrature (I/Q) channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in ana-log-to-digital converters (ADC). As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is pro-posed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR) can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.

  11. A Framework for Satellite Image Enhancement Using Quantum Genetic and Weighted IHS+Wavelet Fusion Method

    Directory of Open Access Journals (Sweden)

    Amal A. HAMED


    Full Text Available this paper examined the applicability of quantum genetic algorithms to solve optimization problems posed by satellite image enhancement techniques, particularly super-resolution, and fusion. We introduce a framework starting from reconstructing the higher-resolution panchromatic image by using the subpixel-shifts between a set of lower-resolution images (registration, then interpolation, restoration, till using the higher-resolution image in pan-sharpening a multispectral image by weighted IHS+Wavelet fusion technique. For successful super-resolution, accurate image registration should be achieved by optimal estimation of subpixel-shifts. Optimal-parameters blind restoration and interpolation should be performed for the optimal quality higher-resolution image. There is a trade-off between spatial and spectral enhancement in image fusion; it is difficult for the existing methods to do the best in both aspects. The objective here is to achieve all combined requirements with optimal fusion weights, and use the parameters constraints to direct the optimization process. QGA is used to estimate the optimal parameters needed for each mathematic model in this framework “Super-resolution and fusion.” The simulation results show that the QGA-based method can be used successfully to estimate automatically the approaching parameters which need the maximal accuracy, and achieve higher quality and efficient convergence rate more than the corresponding conventional GA-based and the classic computational methods.

  12. Post launch calibration and testing of the Advanced Baseline Imager on the GOES-R satellite (United States)

    Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.


    The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

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

    Institute of Scientific and Technical Information of China (English)

    LI DeRen; WANG Mi; HU Fen


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

  14. Image-processing techniques in precisely measuring positions of Saturn and its satellites

    Institute of Scientific and Technical Information of China (English)

    PENG; Qingyu; (彭青玉)


    After overcoming the deficiencies of previous image-processing techniques, a novel technique based on the edge-detection of Saturnian ring is developed to precisely measure Saturn's position. Furthermore, the scattering light (i.e. halo light) of Saturn and its ring is removed effectively based on its center symmetry. Therefore, we have much more opportunities to accurately measure the positions of Mimas and Enceladus-- two satellites very close to the Saturn. Experimental tests with 127 frames of CCD images obtained on the 1-meter telescope at the Yunnan Observatory over three nights show that the geometric center of the Saturnian ring and its 4 satellites (Tethys, Dione, Rhea and Titan) have the same positional precision, and the standard error for a single observation is less than ±0.05 arcsec. It is believed that these new techniques would have important impetus to the positional measurement of both Saturn by using a CCD meridian instrument and its faint satellites by using a long focal length telescope.

  15. Measurement of ground displacement from optical satellite image correlation using the free open-source software MicMac (United States)

    Rosu, Ana-Maria; Pierrot-Deseilligny, Marc; Delorme, Arthur; Binet, Renaud; Klinger, Yann


    Image correlation is one of the most efficient techniques to determine horizontal ground displacements due to earthquakes, landslides, ice flows or sand dune migrations. Analyzing these deformations allows a better understanding of the causes and mechanisms of the events. By using sub-pixel correlation on before- and after-event ortho-images obtained from high resolution satellite images it is possible to compute the displacement field with high planimetric resolution. In this paper, we focus on measuring the ground displacements due to seismotectonic events. The three sub-pixel correlators used are: COSI-Corr - developed by Caltech, a free, closed-source correlator, dependent on commercial software (ENVI) and widely used by the geoscience community for measuring ground displacement; Medicis - developed by CNES, also a closed-source correlator capable of measuring this type of deformation; and MicMac - developed by IGN, the free open-source correlator we study and tune for measuring fine ground displacements. We measured horizontal ground deformation using these three correlators on SPOT images in three study cases: the 2001 Kokoxili earthquake, the 2005 dyke intrusion in the Afar depression and the 2008 Yutian earthquake.

  16. A graph-based approach to detect spatiotemporal dynamics in satellite image time series (United States)

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


    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.

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

    Directory of Open Access Journals (Sweden)

    Rashid Hussain


    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. Amazon Rainforest Deforestation Daily Detection Tool Using Artificial Neural Networks and Satellite Images

    Directory of Open Access Journals (Sweden)

    Silvio César Cazella


    Full Text Available The main purpose of this work was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA [1] sensor and Artificial Neural Networks. The developed tool provides the parameterization of the configuration for the neural network training to enable us to find the best neural architecture to address the problem. The tool makes use of confusion matrixes to determine the degree of success of the network. Part of the municipality of Porto Velho, in Rondônia state, is located inside the tile H11V09 of the MODIS/TERRA sensor, which was used as the study area. A spectrum-temporal analysis of this area was made on 57 images from 20 of May to 15 of July 2003 using the trained neural network. This analysis allowed us to verify the quality of the implemented neural network classification as well as helping our understanding of the dynamics of deforestation in the Amazon rainforest. The great potential of neural networks for image classification was perceived with this work. However, the generation of consistent alarms, in other words, detecting predatory actions at the beginning; instead of firing false alarms is a complex task that has not yet been solved. Therefore, the major contribution of this paper is to provide a theoretical basis and practical use of neural networks and satellite images to combat illegal deforestation.

  19. Triple Linear-array Imaging Geometry Model of ZiYuan-3 Surveying Satellite and its Validation

    Directory of Open Access Journals (Sweden)

    TANG Xinming


    Full Text Available The ZiYuan-3 (ZY-3 surveying satellite is the first civilian high-resolution stereo mapping satellite of China. Its objective is oriented to plot the 1:50,000 and 1:25,000 topographic maps. Comparing with foreign commercial mapping satellite imagery, the establishment of our own imaging geometry model is the core technical problem for different products and various applications of ZY-3 surveying satellite. This paper analyses the key problem on precision geometry processing based on the overall design, and proposes the ZY-3 Surveying satellite imaging geometry model with the technology of virtual CCD line-array imaging. In addition, this paper utilizes the first orbit imagery of ZY-3 satellite with coverage of the region of Dalian, and produces forward, backward and nadir cameras calibration products. Different ground control points are selected for the block adjustment experiment, and the Digital Surface Model (DSM, Digital Ortho Map (DOM are generated. The accuracy is validated by check points. It can be seen from the experiment that the planar and vertical accuracy are better than 3 meters and 2 meters, respectively. The experiment demonstrates the effectiveness of ZY-3 surveying satellite imaging geometry model

  20. Automatic geolocation of targets tracked by aerial imaging platforms using satellite imagery (United States)

    Shukla, P. K.; Goel, S.; Singh, P.; Lohani, B.


    Tracking of targets from aerial platforms is an important activity in several applications, especially surveillance. Knowled ge of geolocation of these targets adds additional significant and useful information to the application. This paper determines the geolocation of a target being tracked from an aerial platform using the technique of image registration. Current approaches utilize a POS to determine the location of the aerial platform and then use the same for geolocation of the targets using the principle of photogrammetry. The constraints of cost and low-payload restrict the applicability of this approach using UAV platforms. This paper proposes a methodology for determining the geolocation of a target tracked from an aerial platform in a partially GPS devoid environment. The method utilises automatic feature based registration technique of a georeferenced satellite image with an ae rial image which is already stored in UAV's database to retrieve the geolocation of the target. Since it is easier to register subsequent aerial images due to similar viewing parameters, the subsequent overlapping images are registered together sequentially thus resulting in the registration of each of the images with georeferenced satellite image thus leading to geolocation of the target under interest. Using the proposed approach, the target can be tracked in all the frames in which it is visible. The proposed concept is verified experimentally and the results are found satisfactory. Using the proposed method, a user can obtain location of target of interest as well features on ground without requiring any POS on-board the aerial platform. The proposed approach has applications in surveillance for target tracking, target geolocation as well as in disaster management projects like search and rescue operations.

  1. Solar resources estimation combining digital terrain models and satellite images techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)


    One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)

  2. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.


    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  3. LineCast: line-based distributed coding and transmission for broadcasting satellite images. (United States)

    Wu, Feng; Peng, Xiulian; Xu, Jizheng


    In this paper, we propose a novel coding and transmission scheme, called LineCast, for broadcasting satellite images to a large number of receivers. The proposed LineCast matches perfectly with the line scanning cameras that are widely adopted in orbit satellites to capture high-resolution images. On the sender side, each captured line is immediately compressed by a transform-domain scalar modulo quantization. Without syndrome coding, the transmission power is directly allocated to quantized coefficients by scaling the coefficients according to their distributions. Finally, the scaled coefficients are transmitted over a dense constellation. This line-based distributed scheme features low delay, low memory cost, and low complexity. On the receiver side, our proposed line-based prediction is used to generate side information from previously decoded lines, which fully utilizes the correlation among lines. The quantized coefficients are decoded by the linear least square estimator from the received data. The image line is then reconstructed by the scalar modulo dequantization using the generated side information. Since there is neither syndrome coding nor channel coding, the proposed LineCast can make a large number of receivers reach the qualities matching their channel conditions. Our theoretical analysis shows that the proposed LineCast can achieve Shannon's optimum performance by using a high-dimensional modulo-lattice quantization. Experiments on satellite images demonstrate that it achieves up to 1.9-dB gain over the state-of-the-art 2D broadcasting scheme and a gain of more than 5 dB over JPEG 2000 with forward error correction.

  4. Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming (United States)

    Benzouai, Siham; Smara, Youcef


    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*.

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

    Directory of Open Access Journals (Sweden)

    Thierry Géraud


    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.

  6. Comparing Manual and Semi-Automated Landslide Mapping Based on Optical Satellite Images from Different Sensors

    Directory of Open Access Journals (Sweden)

    Daniel Hölbling


    Full Text Available Object-based image analysis (OBIA has been increasingly used to map geohazards such as landslides on optical satellite images. OBIA shows various advantages over traditional image analysis methods due to its potential for considering various properties of segmentation-derived image objects (spectral, spatial, contextual, and textural for classification. For accurately identifying and mapping landslides, however, visual image interpretation is still the most widely used method. The major question therefore is if semi-automated methods such as OBIA can achieve results of comparable quality in contrast to visual image interpretation. In this paper we apply OBIA for detecting and delineating landslides in five selected study areas in Austria and Italy using optical Earth Observation (EO data from different sensors (Landsat 7, SPOT-5, WorldView-2/3, and Sentinel-2 and compare the OBIA mapping results to outcomes from visual image interpretation. A detailed evaluation of the mapping results per study area and sensor is performed by a number of spatial accuracy metrics, and the advantages and disadvantages of the two approaches for landslide mapping on optical EO data are discussed. The analyses show that both methods produce similar results, whereby the achieved accuracy values vary between the study areas.

  7. Comparision of Clustering Algorithms usingNeural Network Classifier for Satellite Image Classification

    Directory of Open Access Journals (Sweden)



    Full Text Available This paper presents a hybrid clustering algorithm and feed-forward neural network classifier for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for segmentation. The pre-processed image is segmented using the hybrid genetic-Artificial Bee Colony(ABC algorithm that is developed by hybridizing the ABC and FCM to obtain the effective segmentation in satellite image and classified using neural network . The performance of the proposed hybrid algorithm is compared with the algorithms like, k-means, Fuzzy C means(FCM, Moving K-means, Artificial Bee Colony(ABC algorithm, ABC-GA algorithm, Moving KFCM and KFCM algorithm.

  8. Object-Based Forest Cover Monitoring Using GAOFEN-2 High Resolution Satellite Images (United States)

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


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

  9. High-resolution satellite image segmentation using Hölder exponents

    Indian Academy of Sciences (India)

    Debasish Chakraborty; Gautam Kumar Sen; Sugata Hazra


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

  10. Recognization of Satellite Images of Large Scale Data Based on Map- Reduce Framework

    Directory of Open Access Journals (Sweden)

    Vidya Jadhav,


    Full Text Available Today in the world of cloud and grid computing integration of data from heterogeneous databases is inevitable.This will become complex when size of the database is very large. M-R is a new framework specifically designed for processing huge datasets on distributed sources. Apache’s Hadoop is an implementation of M-R.Currently Hadoop has been applied successfully for file based datasets. This project proposes to utilize the parallel and distributed processing capability of Hadoop M-R for handling Images on large datasets.The presented methodology of land-cover recognition provides a scalable solution for automatic satellite imagery analysis, especially when GIS data is not readily available, or surface change may occur due to catastrophic events such as flooding, hurricane, and snow storm, etc.Here,we are using algorithms such as Image Differentiation,Image Duplication,Zoom-In,Gray-Scale.

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

    Energy Technology Data Exchange (ETDEWEB)

    Jansen, Frank, E-mail: [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)


    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.

  12. The Black Sea coastal zone in the high resolution satellite images (United States)

    Yurovskaya, Maria; Dulov, Vladimir; Kozlov, Igor


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

  13. The distribution of satellites around massive galaxies at 1 < z < 3 in ZFOURGE/CANDELS: Dependence on star formation activity

    Energy Technology Data Exchange (ETDEWEB)

    Kawinwanichakij, Lalitwadee; Papovich, Casey; Quadri, Ryan F.; Tran, Kim-Vy H.; Mehrtens, Nicola [George P. and Cynthia W. Mitchell Institute for Fundamental Physics and Astronomy, Department of Physics and Astronomy, Texas A and M University, College Station, TX 77843 (United States); Spitler, Lee R.; Cowley, Michael [Department of Physics and Astronomy, Faculty of Sciences, Macquarie University, Sydney, NSW 2109 (Australia); Kacprzak, Glenn G.; Glazebrook, Karl; Nanayakkara, Themiya [Centre for Astrophysics and Supercomputing, Swinburne University, Hawthorn, VIC 3122 (Australia); Labbé, Ivo; Straatman, Caroline M. S. [Leiden Observatory, Leiden University, P.O. Box 9513, 2300 RA Leiden (Netherlands); Allen, Rebecca [Australian Astronomical Observatories, P.O. Box 915, North Ryde, NSW 1670 (Australia); Davé, Romeel [University of the Western Cape, Bellville, Cape Town 7535 (South Africa); Dekel, Avishai [Center for Astrophysics and Planetary Science, Racah Institute of Physics, The Hebrew University, Jerusalem 91904 (Israel); Ferguson, Henry C.; Koekemoer, Anton M. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Hartley, W. G. [School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD (United Kingdom); Koo, David C. [University of California Observatories/Lick Observatory, Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States); Lu, Yu, E-mail: [Kavli Institute for Particle Astrophysics and Cosmology, 452 Lomita Mall, Stanford, CA 94305 (United States); and others


    We study the statistical distribution of satellites around star-forming and quiescent central galaxies at 1 < z < 3 using imaging from the FourStar Galaxy Evolution Survey and the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey. The deep near-IR data select satellites down to log (M/M {sub ☉}) > 9 at z < 3. The radial satellite distribution around centrals is consistent with a projected Navarro-Frenk-White profile. Massive quiescent centrals, log (M/M {sub ☉}) > 10.78, have ∼2 times the number of satellites compared to star-forming centrals with a significance of 2.7σ even after accounting for differences in the centrals' stellar-mass distributions. We find no statistical difference in the satellite distributions of intermediate-mass quiescent and star-forming centrals, 10.48 < log (M/M {sub ☉}) < 10.78. Compared to the Guo et al. semi-analytic model, the excess number of satellites indicates that quiescent centrals have halo masses 0.3 dex larger than star-forming centrals, even when the stellar-mass distributions are fixed. We use a simple toy model that relates halo mass and quenching, which roughly reproduces the observed quenched fractions and the differences in halo mass between star-forming and quenched galaxies only if galaxies have a quenching probability that increases with halo mass from ∼0 for log (M{sub h} /M {sub ☉}) ∼ 11 to ∼1 for log (M{sub h} /M {sub ☉}) ∼ 13.5. A single halo-mass quenching threshold is unable to reproduce the quiescent fraction and satellite distribution of centrals. Therefore, while halo quenching may be an important mechanism, it is unlikely to be the only factor driving quenching. It remains unclear why a high fraction of centrals remain star-forming even in relatively massive halos.

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

    Directory of Open Access Journals (Sweden)

    Pauline Dusseux


    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.

  15. Integrated use of satellite images, DEMs, soil and substrate data in studying mountainous lands (United States)

    Giannetti, Fabio; Montanarella, Luca; Salandin, Roberto

    A method based on the integration into a GIS of satellite images of different spatial resolution (Landsat TM and SPOT), Digital Elevation Models, geo-lithological maps and some soil-landscape data was developed and applied to a test area on a sector of the Italian northwestern Alps in the Piemonte region (Pellice, Po, Varaita and Maira valleys southwest of Torino). The main working steps performed (using GIS software) in this area were: (1) acquisition of geo-lithological and geomorphological maps available and a first definition of homogeneous zones obtained by joining different classes with pedogenic criteria; (2) processing and classification of satellite images to define homogeneous areas with reference to prevailing land cover, land use pattern, relief shape and spectral characters; (3) integration of the previous two layers to obtain a first set of cartographic units showing a distinctive and often repetitive pattern of land form, land cover and parent material; and (4) processing DEMs (slope and aspect), soil or soil-landscape data in order to refine data and characterise the units. The resulting cartographic units were superimposed on a soil-landscape map realised by means of stereoscopic interpretation of aerial photographs by IPLA at the same scale (1:250,000). This comparison was used to verify the correctness of the satellite image processing steps and consistency with the map scale used. A larger scale application was also developed for grassland at 1:50,000 scale to demonstrate the practical use of remote sensing and GIS data in assisting mountainous land development.

  16. Solar irradiance assessment in insular areas using Himawari-8 satellite images (United States)

    Liandrat, O.; Cros, S.; Turpin, M.; Pineau, J. F.


    The high amount of surface solar irradiance (SSI) in the tropics is an advantage for a profitable PV production. It will allow many tropical islands to pursue their economic growth with a clean, affordable and locally produced energy. However, the local meteorological conditions induce a very high variability which is problematic for a safe and gainful injection into the power grid. This issue is even more critical in non-interconnected territories where network stability is an absolute necessity. Therefore, the injection of PV power is legally limited in some European oversea territories. In this context, intraday irradiance forecasting (several hours ahead) is particularly useful to mitigate the production variability by reducing the cost of power storage management. At this time scale, cloud cover evolves with a stochastic behaviour not properly represented in numerical weather prediction (NWP) models. Analysing cloud motion using images from geostationary meteorological satellites is a well-known alternative to forecasting SSI up to 6 hours ahead with a better accuracy than NWP models. In this study, we present and apply our satellite-based solar irradiance forecasting methods over two measurement sites located in the field of view of the satellite Himawari-8: Cocos (Keeling) Islands (Australia) and New Caledonia (France). In particular, we converted 4 months of images from Himawari-8 visible channel into cloud index maps. Then, we applied an algorithm computing a cloud motion vector field from a short sequence of consecutive images. Comparisons between forecasted SSI at 1 hour of time horizon and collocated pyranometric measurements show a relative RMSE between 20 and 27%. Error sources related to the tropic insular context (coastal area heterogeneity, sub-pixel scale orographic cloud appearance, convective situation…) are discussed at every implementation step for the different methods.

  17. Evaluation of Satellite Image Correction Methods Caused by Differential Terrain Illumination

    Directory of Open Access Journals (Sweden)

    Purnama Budi Santosa


    Full Text Available The problem due to differential terrain illumination on satellite imagery is experienced by most of areas which are on mountainous terrain. This may cause variations in reflectance of similar ground features which lead to a misclassification of land cover classes due to different topographic positions. This phenomenon most commonly occurred in the areas which are located on southern and northern hemisphere because of the low sun inclination. This problem has been a major interest for researchers to be solved prior to the land cover classification process. For satellite images which experience this kind of problem, topographic correction need to be applied in order to reduce the illumination effects prior to land cover classification process. This research is aimed at conducting topographic correction of multi spectral SPOT satellite data as well as evaluating the three topographic correction methods. They are Cosine which is based on Lambertian reflectance assumption, as well as Minnaert correction and C correction methods which are based on non-Lambertian reflectance assumption. The data used in this study are two scenes of SPOT images of forested mountainous area of Miyazaki Prefecture, Kyushu, Japan. Research steps had been conducted in this study including geometric correction, sample data collection for calculating Minnaert constants and C constants at location which represents the whole study area, topographic correction for two scenes SPOT images, and results analysis. The results show that Cosine method did not show good performance for the study area which is topographically dominated by rugged terrain. Whereas Minnaert method and C method gave satisfactory results as is indicated by the statistical data as well as visual interpretation. However the Minnaert correction method showed slightly better performance than the C correction method.

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

    Directory of Open Access Journals (Sweden)

    V. S. Aliaga


    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.

  19. Monitoring an air pollution episode in Shenzhen by combining MODIS satellite images and the HYSPLIT model (United States)

    Li, Lili; Liu, Yihong; Wang, Yunpeng


    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.

  20. Determination of Destructed and Infracted Forest Areas with Multi-temporal High Resolution Satellite Images (United States)

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


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

  1. Attitude determination for three-axis stabilized geostationary meteorological satellite image navigation (United States)

    Wu, Yaguang; Wang, Zhigang


    To achieve the high accuracy of attitude determination for three-axis stabilized geostationary meteorological satellite image navigation, a new approach combined gyro with star trackers is proposed, and a real-time algorithm for attitude estimation is designed. This algorithm begins with a prediction for angular rate model errors induced by gyro drifting error, and ends with the extended Kalman filtering (EKF) for attitude estimation of three-axis. A Matlab-based time domain simulation model is developed to evaluate the attitude determination performance. Simulation results demonstrate that the proposed algorithm has characteristics of high accuracy, rapid convergence and strong robustness.

  2. Online self-service processing system of ZY-3 satellite: a prospective study of image cloud services (United States)

    Wang, Hongyan; Wang, Huabin; Shi, Shaoyu


    The strong demands for satellite images are increasing not only in professional fields, but also in the non-professionals. But the online map services with up-to-date satellite images can serve few demands. One challenge is how to provide online processing service, which need to handle real-time online data-intensive geospatial computation and visualization. Under the background of the development of cloud computing technology, the problem can be figured out partly. The other challenge is how to implement user-customized online processing without professional background and knowledge. An online self-service processing system of ZY-3 Satellite images is designed to implement an on-demand service mode in this paper. It will work with only some simple parameters being set up for the non-professionals without having to care about the specific processing steps. And the professionals can assemble the basic processing services to a service chain, which can work out a more complex processing and a better result. This intelligent self-service online system for satellite images processing, which is called the prototype of satellite image cloud service in this paper, is accelerated under the development of cloud computing technology and researches on data-intensive computing. To realize the goal, the service mode and framework of the online self-service processing system of ZY-3 Satellite images are figured out in this paper. The details of key technologies are also discussed, including user space virtualization management, algorithm-level parallel image processing, image service chain construction, etc. And the experimental system is built up as a prospective study of image cloud services.

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

    Directory of Open Access Journals (Sweden)

    Nguyen Thanh Hoan


    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.


    Directory of Open Access Journals (Sweden)

    N. Khalili Moghadam


    Full Text Available With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user’s intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.

  5. Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram (United States)

    Paul, F.


    Although animated images are very popular on the internet, they have so far found only limited use for glaciological applications. With long time series of satellite images becoming increasingly available and glaciers being well recognized for their rapid changes and variable flow dynamics, animated sequences of multiple satellite images reveal glacier dynamics in a time-lapse mode, making the otherwise slow changes of glacier movement visible and understandable to the wider public. For this study, animated image sequences were created for four regions in the central Karakoram mountain range over a 25-year time period (1990-2015) from freely available image quick-looks of orthorectified Landsat scenes. The animations play automatically in a web browser and reveal highly complex patterns of glacier flow and surge dynamics that are difficult to obtain by other methods. In contrast to other regions, surging glaciers in the Karakoram are often small (10 km2 or less), steep, debris-free, and advance for several years to decades at relatively low annual rates (about 100 m a-1). These characteristics overlap with those of non-surge-type glaciers, making a clear identification difficult. However, as in other regions, the surging glaciers in the central Karakoram also show sudden increases of flow velocity and mass waves travelling down glacier. The surges of individual glaciers are generally out of phase, indicating a limited climatic control on their dynamics. On the other hand, nearly all other glaciers in the region are either stable or slightly advancing, indicating balanced or even positive mass budgets over the past few decades.

  6. Using very high resolution satellite images to identify coastal zone dynamics at North Western Black Sea (United States)

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


    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

  7. TIRCIS: Hyperspectral Thermal Infrared Imaging Using a Small-Satellite Compliant Fourier-Transform Imaging Spectrometer, for Natural Hazard Applications (United States)

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


    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.

  8. Deep and shallow structures in the Arctic region imaged by satellite magnetic and gravity data (United States)

    Gaina, Carmen; Panet, Isabelle; Shephard, Grace


    , 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.

  9. Satellite-like cells contribute to pax7-dependent skeletal muscle repair in adult zebrafish. (United States)

    Berberoglu, Michael A; Gallagher, Thomas L; Morrow, Zachary T; Talbot, Jared C; Hromowyk, Kimberly J; Tenente, Inês M; Langenau, David M; Amacher, Sharon L


    Satellite cells, also known as muscle stem cells, are responsible for skeletal muscle growth and repair in mammals. Pax7 and Pax3 transcription factors are established satellite cell markers required for muscle development and regeneration, and there is great interest in identifying additional factors that regulate satellite cell proliferation, differentiation, and/or skeletal muscle regeneration. Due to the powerful regenerative capacity of many zebrafish tissues, even in adults, we are exploring the regenerative potential of adult zebrafish skeletal muscle. Here, we show that adult zebrafish skeletal muscle contains cells similar to mammalian satellite cells. Adult zebrafish satellite-like cells have dense heterochromatin, express Pax7 and Pax3, proliferate in response to injury, and show peak myogenic responses 4-5 days post-injury (dpi). Furthermore, using a pax7a-driven GFP reporter, we present evidence implicating satellite-like cells as a possible source of new muscle. In lieu of central nucleation, which distinguishes regenerating myofibers in mammals, we describe several characteristics that robustly identify newly-forming myofibers from surrounding fibers in injured adult zebrafish muscle. These characteristics include partially overlapping expression in satellite-like cells and regenerating myofibers of two RNA-binding proteins Rbfox2 and Rbfoxl1, known to regulate embryonic muscle development and function. Finally, by analyzing pax7a; pax7b double mutant zebrafish, we show that Pax7 is required for adult skeletal muscle repair, as it is in the mouse.

  10. The digital mapping of satellite images under no ground control and the distribution of landform, blue ice and meteorites in the Grove Mountains, Antarctica

    Institute of Scientific and Technical Information of China (English)

    孙家抦; 霍东民; 周军其; 孙朝辉


    The colorful satellite image maps with the scale of 1∶100 000 were made by processing the parameters-on-satellite under the condition of no data of field surveying. The purpose is to ensure the smooth performance of the choice of expedition route, navigation and research task before the Chinese National Antarctic Research Expedition (CHINARE) first made researches on the Grove Mountains. Moreover, on the basis of the visual interpretation of the satellite image, we preliminarily analyze and discuss the relief and landform, blue ice and meteorite distribution characteristics in the Grove Mountains. Key words Grove Mountains, parameters-on-satellite, satellite image, digital mapping, blue ice, meteorites distribution.

  11. The Orbits of Saturn's Small Satellites Derived from Combined Historic and Cassini Imaging Observations (United States)

    Spitale, J. N.; Jacobson, R. A.; Porco, C. C.; Owen, W. M., Jr.


    We report on the orbits of the small, inner Saturnian satellites, either recovered or newly discovered in recent Cassini imaging observations. The orbits presented here reflect improvements over our previously published values in that the time base of Cassini observations has been extended, and numerical orbital integrations have been performed in those cases in which simple precessing elliptical, inclined orbit solutions were found to be inadequate. Using combined Cassini and Voyager observations, we obtain an eccentricity for Pan 7 times smaller than previously reported because of the predominance of higher quality Cassini data in the fit. The orbit of the small satellite (S/2005 S1 [Daphnis]) discovered by Cassini in the Keeler gap in the outer A ring appears to be circular and coplanar; no external perturbations are apparent. Refined orbits of Atlas, Prometheus, Pandora, Janus, and Epimetheus are based on Cassini , Voyager, Hubble Space Telescope, and Earth-based data and a numerical integration perturbed by all the massive satellites and each other. Atlas is significantly perturbed by Prometheus, and to a lesser extent by Pandora, through high-wavenumber mean-motion resonances. Orbital integrations involving Atlas yield a mass of GMAtlas=(0.44+/-0.04)×10-3 km3 s -2, 3 times larger than reported previously (GM is the product of the Newtonian constant of gravitation G and the satellite mass M). Orbital integrations show that Methone is perturbed by Mimas, Pallene is perturbed by Enceladus, and Polydeuces librates around Dione's L5 point with a period of about 791 days. We report on the nature and orbits of bodies sighted in the F ring, two of which may have persisted for a year or more.


    Directory of Open Access Journals (Sweden)

    P. Javadi


    Full Text Available The best technique to extract information from remotely sensed image is classification. The problem of traditional classification methods is that each pixel is assigned to a single class by presuming all pixels within the image. Mixed pixel classification or spectral unmixing, is a process that extracts the proportions of the pure components of each mixed pixel. This approach is called spectral unmixing. Hyper spectral images have higher spectral resolution than multispectral images. In this paper, pixel-based classification methods such as the spectral angle mapper, maximum likelihood classification and subpixel classification method (linear spectral unmixing were implemented on the AVIRIS hyper spectral images. Then, pixel-based and subpixel based classification algorithms were compared. Also, the capabilities and advantages of spectral linear unmixing method were investigated. The spectral unmixing method that implemented here is an effective technique for classifying a hyperspectral image giving the classification accuracy about 89%. The results of classification when applying on the original images are not good because some of the hyperspectral image bands are subject to absorption and they contain only little signal. So it is necessary to prepare the data at the beginning of the process. The bands can be stored according to their variance. In bands with a high variance, we can distinguish the features from each other in a better mode in order to increase the accuracy of classification. Also, applying the MNF transformation on the hyperspectral images increase the individual classes accuracy of pixel based classification methods as well as unmixing method about 20 percent and 9 percent respectively.

  13. Investigation of tautomeric structures of thionin by satellite holes: matrix dependence (United States)

    Weng, Kevin C.; Chiang, Chien-Chih; Cheng, Ji-Yen; Cheng, Shao-Ying; Personov, Roman I.; Chang, Ta-Chau


    We have applied the satellite hole spectroscopy to study the tautomeric structures of thionin dye in glycerol:water glass. Slightly different frequencies (˜15 cm -1) are observed for several satellite holes of thionin upon tuning the burning wavelength, implying that two conformational structures exist. However, only one set of satellite holes occurring in the spectrum of thionin doped in polyvinyl butyral film allows us to investigate the tautomeric structures of thionin in different matrices. Our results suggest that the appearance of two tautomeric structures of thionin in glycerol:water glass is due to the proton exchange between different sites of thionin and the matrix through intermolecular hydrogen bond.

  14. Correction of ZY-3 image distortion caused by satellite jitter via virtual steady reimaging using attitude data (United States)

    Wang, Mi; Zhu, Ying; Jin, Shuying; Pan, Jun; Zhu, Quansheng


    ZiYuan-3 (ZY-3), the first Chinese civilian stereo mapping satellite, suffers from 0.67 Hz satellite jitter that deteriorates its geometric performance in mapping, resource monitoring and other applications. This paper proposes a distortion correction method based on virtual steady reimaging (VSRI) using attitude data to eliminate the negative influence caused by satellite jitter in satellite data preprocessing. VSRI helps linear array pushbroom cameras rescan the ground with a uniform integral time and smooth attitude. In this method, a VSRI model is proposed, and the geometric relationship between the original and corrected image is determined in terms of geolocation consistency based on a rigorous geometric model. Thus, the corrected image is obtained by resampling from the original one. Three areas of ZY-3 three-line images suffering from satellite jitter were used to validate the accuracy and efficiency of the proposed method. First, different attitude interpolation methods were compared. It is found that the Lagrange polynomial model and the cubic piecewise polynomial model have higher interpolation accuracy for original imagery. Then, the replacement accuracy of the rational function model (RFM) for ZY-3 was analyzed with 0.67 Hz satellite jitter. The results indicate that attitude oscillation reduces the fitting precision of the RFM for the rigorous imaging model. Finally, the relative orientation accuracy of the three-line images and the geo-positioning accuracy with ground control points (GCPs) before and after distortion correction were compared. The results show that the distortion caused by satellite jitter is corrected efficiently, and the accuracy of the three experimental datasets is improved in both the image space and the ground space.

  15. 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


    for complementing the content of topographic maps Images taken from aircraft and satellite platforms are very important sources of data for studying and presenting natural and artificial phenomena on the Earth. Understanding the links and relations between digital values of pixels recorded on sensors and the phenomena on a terrain enables a proper interpretation and analysis of an image. The subject of the experiment presented in this article is a satellite image of the Belgrade city area, made by the IKONOS 2 satellite of the European Space Imaging Company. It belongs to the GEO Ortho Kit products category, which means that it is approximately georeferenced and completely orthorectified. Georeferencing of an ikonos2 satellite image A procedure in which an image is taken into a desired coordinate system through orientation points (rectification, where the image is conveyed into a projection close to the orthogonal one, is called georeferencing (process of conveying an image into a reference coordinate system, while the level of geometric transformation is external geometrical transformation [5]. By georeferencing we establish certain mathematical dependence between the points on the image and the known points of the surveyed terrain. These points are called orientation points, control or GCP points (Ground Control Points. Procedures of digital image processing image pre-processing The biggest deficiency of satellite images that could be used in a digital form for making and maintaining working maps is a series of mistakes (deformations of geometric mapping. These deformations that should be removed before further processing are viewed as: - A change of intensity of pixel grey tone caused by the characteristics of the surveyed terrain, object or phenomenon, and - A wrong relative position of a pixel in the image raster matrix. Image quality enhancement After removing deformations and taking image into a desired coordinate system, in further image processing, it is

  16. Analysis Of Usefulness Of Satellite Image Processing Methods For Investigations Of Cultural Heritage Resources (United States)

    Osińska-Skotak, Katarzyna; Zapłata, Rafał


    The paper presents the analysis of usefulness of WorldView-2 satellite image processing, which enhance information concerning the cultural heritage objects. WorldView-2 images are characterised by the very high spatial resolution and high spectral resolution; that is why they create new possibilities for many applications, including investigations of the cultural heritage. The vicinities of Iłża have been selected as the test site for presented investigations. The presented results of works are the effect of research works, which were performed in the frames of the scientific project "Utilisation of laser scanning and remote sensing in protection, investigations and inventory of the cultural heritage. Development of non-invasive, digital methods of documenting and recognising the architectural and archaeological heritage", as the part of "The National Programme for the Development of Humanities" of the Minister of Science and Higher Education in the period of 2012-2015.

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

    Directory of Open Access Journals (Sweden)

    Marc Wieland


    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.

  18. Genetic Optimization for Associative Semantic Ranking Models of Satellite Images by Land Cover

    Directory of Open Access Journals (Sweden)

    Nil Kilicay-Ergin


    Full Text Available Associative methods for content-based image ranking by semantics are attractive due to the similarity of generated models to human models of understanding. Although they tend to return results that are better understood by image analysts, the induction of these models is difficult to build due to factors that affect training complexity, such as coexistence of visual patterns in same images, over-fitting or under-fitting and semantic representation differences among image analysts. This article proposes a methodology to reduce the complexity of ranking satellite images for associative methods. Our approach employs genetic operations to provide faster and more accurate models for ranking by semantic using low level features. The added accuracy is provided by a reduction in the likelihood to reach local minima or to overfit. The experiments show that, using genetic optimization, associative methods perform better or at similar levels as state-of-the-art ensemble methods for ranking. The mean average precision (MAP of ranking by semantic was improved by 14% over similar associative methods that use other optimization techniques while maintaining smaller size for each semantic model.

  19. Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting (United States)

    Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.


    SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

  20. Measuring snow cover using satellite imagery during 1973 and 1974 melt season: North Santiam, Boise, and Upper Snake Basins, phase 1. [LANDSAT satellites, imaging techniques (United States)

    Wiegman, E. J.; Evans, W. E.; Hadfield, R.


    Measurements are examined of snow coverage during the snow-melt season in 1973 and 1974 from LANDSAT imagery for the three Columbia River Subbasins. Satellite derived snow cover inventories for the three test basins were obtained as an alternative to inventories performed with the current operational practice of using small aircraft flights over selected snow fields. The accuracy and precision versus cost for several different interactive image analysis procedures was investigated using a display device, the Electronic Satellite Image Analysis Console. Single-band radiance thresholding was the principal technique employed in the snow detection, although this technique was supplemented by an editing procedure involving reference to hand-generated elevation contours. For each data and view measured, a binary thematic map or "mask" depicting the snow cover was generated by a combination of objective and subjective procedures. Photographs of data analysis equipment (displays) are shown.

  1. Fully automated extraction and analysis of surface Urban Heat Island patterns from moderate resolution satellite images (United States)

    Keramitsoglou, I.; Kiranoudis, C. T.


    Comparison of thermal patterns across different cities is hampered by the lack of an appropriate methodology to extract the patterns and characterize them. What is more, increased attention by the urban climate community has been expressed to assess the magnitude and dynamics of the surface Urban Heat Island effect and to identify environmental impacts of large cities and "megacities". Motivated by this need, we propose an innovative object-based image analysis procedure to extract thermal patterns for the quantitative analysis of satellite-derived land surface temperature maps. The spatial and thermal attributes associated with these objects are then calculated and used for the analyses of the intensity, the position and the spatial extent of SUHIs. The output eventually builds up and populates a database with comparable and consistent attributes, allowing comparisons between cities as well as urban climate studies. The methodology is demonstrated over the Greater Athens Area, Greece, with more than 3000 LST images acquired by MODIS over a decade being analyzed. The approach can be potentially applied to current and future (e.g. Sentinel-3) level-2 satellite-derived land surface temperature maps of 1km spatial resolution acquired over continental and coastal cities.

  2. Earth Camp: Exploring Earth Change through the Use of Satellite Images and Scientific Practices (United States)

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


    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.

  3. A new strategic sampling for offshore wind assessment using radar satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Beaucage, P.; Lafrance, G.; Bernier, M.; Lafrance, J. [Institut National de la Recherche Scientifique, Varennes, PQ (Canada); Choisnard, J. [Hydro-Quebec, Varennes, PQ (Canada)


    Synthetic Aperture Radar (SAR) satellite images have been used for offshore wind assessment. Several offshore wind farms are in operation or under construction in northern Europe. The European target for 2030 is 300 GW, of which half is intended for onshore and half for offshore development. Offshore projects in the east coast United States, the Gulf of Mexico and west coast of Canada are in the planning stage. Information obtained from SAR can be used to supplement current mapping methods of offshore wind energy resources. SAR is a useful tool to localize wind pattern over water surfaces. Other sources of offshore wind observations include meteorological stations such as buoys and masts; remote sensing instruments onboard satellites such as scatterometers (QuikSCAT, ASCAT) or passive microwave radiometers; and numerical weather prediction models. The synergy between scatterometers and SAR was discussed. The SAR system has been used for microscale resolution wind mapping in the Gaspe Peninsula. Strategic sampling zones were chosen in proximity to the QuikSCAT grid. It was concluded that 270 and 570 SAR images are needed to calculate average wind speed (U) and mean power output of a 3 MW wind turbine (P) over the Gaspe Peninsula region, respectively. It was concluded that microscale regional wind mapping can be produced at a lower cost with strategic sampling compared to random sampling. refs., tabs., figs.

  4. Satellite Alignment: I. Distribution of Substructures and Their Dependence On Assembly History From N-Body Simulations

    CERN Document Server

    Wang, Yang Ocean; Kang, Xi; Dutton, Aaron; Yu, Yu; Macciò, Andrea V


    Observations have shown that the spatial distribution of satellite galaxies is not random, but aligned with the major axes of central galaxies. This alignment is dependent on galaxy properties, such that red satellites are more strongly aligned than blue satellites. Theoretical work done to interpret this phenomena has found that it is due to the non-spherical nature of dark matter halos. However, most studies over-predict the alignment signal under the assumption that the central galaxy shape follows the shape of the host halo. It is also not clear whether the color dependence of alignment is due to an assembly bias or an evolution effect. In this paper we study these problems using a cosmological N-body simulation. Subhalos are used to trace the positions of satellite galaxies. It is found that the shape of dark matter halos are mis-aligned at different radii. If the central galaxy shares the same shape as the inner host halo, then the alignment effect is weaker and agrees with observational data. However, ...

  5. Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India (United States)

    Parida, P. K.; Sanabada, M. K.; Tripathi, S.


    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.

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

    Directory of Open Access Journals (Sweden)

    Nina Merkle


    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.

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

    Directory of Open Access Journals (Sweden)

    Elizabeth J. Botha


    Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

  8. Fast Fractal Compression of Satellite and Medical Images Based on Domain-Range Entropy

    Directory of Open Access Journals (Sweden)

    Ramesh Babu Inampudi


    Full Text Available Fractal image Compression is a lossy compression technique developed in the early 1990s. It makes use of the local self-similarity property existing in an image and finds a contractive mapping affine transformation (fractal transformT, such that the fixed point of T is close to the given image in a suitable metric. It has generated much interest due to its promise of high compression ratios with good decompression quality. The other advantage is its multi resolution property, i.e. an image can be decoded at higher or lower resolutions than the original without much degradation in quality. However, the encoding time is computationally intensive. In this paper, a fast fractal image compression method based on the domain-range entropy is proposed to reduce the encoding time, while maintaining the fidelity and compression ratio of the decoded image. The method is a two-step process. First, domains that are similar i.e. domains having nearly equal variances are eliminated from the domain pool. Second, during the encoding phase, only domains and ranges having equal entropies (with an adaptive error threshold, λdepth for each quadtree depth are compared for a match within the rms error tolerance. As a result, many unqualified domains are removed from comparison and a significant reduction in encoding time is expected. The method is applied for compression of satellite and medical images (512x512, 8-bit gray scale. Experimental results show that the proposed method yields superior performance over Fisher’s classified search and other methods.

  9. A learning tool for optical and microwave satellite image processing and analysis (United States)

    Dashondhi, Gaurav K.; Mohanty, Jyotirmoy; Eeti, Laxmi N.; Bhattacharya, Avik; De, Shaunak; Buddhiraju, Krishna M.


    This paper presents a self-learning tool, which contains a number of virtual experiments for processing and analysis of Optical/Infrared and Synthetic Aperture Radar (SAR) images. The tool is named Virtual Satellite Image Processing and Analysis Lab (v-SIPLAB) Experiments that are included in Learning Tool are related to: Optical/Infrared - Image and Edge enhancement, smoothing, PCT, vegetation indices, Mathematical Morphology, Accuracy Assessment, Supervised/Unsupervised classification etc.; Basic SAR - Parameter extraction and range spectrum estimation, Range compression, Doppler centroid estimation, Azimuth reference function generation and compression, Multilooking, image enhancement, texture analysis, edge and detection. etc.; SAR Interferometry - BaseLine Calculation, Extraction of single look SAR images, Registration, Resampling, and Interferogram generation; SAR Polarimetry - Conversion of AirSAR or Radarsat data to S2/C3/T3 matrix, Speckle Filtering, Power/Intensity image generation, Decomposition of S2/C3/T3, Classification of S2/C3/T3 using Wishart Classifier [3]. A professional quality polarimetric SAR software can be found at [8], a part of whose functionality can be found in our system. The learning tool also contains other modules, besides executable software experiments, such as aim, theory, procedure, interpretation, quizzes, link to additional reading material and user feedback. Students can have understanding of Optical and SAR remotely sensed images through discussion of basic principles and supported by structured procedure for running and interpreting the experiments. Quizzes for self-assessment and a provision for online feedback are also being provided to make this Learning tool self-contained. One can download results after performing experiments.

  10. Precision Navigation of Cassini Images Using Rings, Icy Satellites, and Fuzzy Bodies (United States)

    French, Robert S.; Showalter, Mark R.; Gordon, Mitchell K.


    Before images from the Cassini spacecraft can be analyzed, errors in the published pointing information (up to ~110 pixels for the Imaging Science Subsystem Narrow Angle Camera) must be corrected so that the line of sight vector for each pixel is known. This complicated and labor-intensive process involves matching the image contents with known features such as stars, rings, or moons. Metadata, such as lighting geometry or ring radius and longitude, must be computed for each pixel as well. Both steps require mastering the SPICE toolkit, a highly capable piece of software with a steep learning curve. Only after these steps are completed can the actual scientific investigation begin.We have embarked on a three-year project to perform these steps for all 400,000+ Cassini ISS images as well as images taken by the VIMS, UVIS, and CIRS instruments. The result will be a series of SPICE kernels that include accurate pointing information and a series of backplanes that include precomputed metadata for each pixel. All data will be made public through the PDS Ring-Moon Systems Node ( We expect this project to dramatically decrease the time required for scientists to analyze Cassini data.In a previous poster (French et al. 2014, DPS #46, 422.01) we discussed our progress navigating images using stars, simple ring models, and well-defined icy bodies. In this poster we will report on our current progress including the use of more sophisticated ring models, navigation of "fuzzy" bodies such as Titan and Saturn, and use of crater matching on high-resolution images of the icy satellites.

  11. Image jitter detection and compensation using a high-frequency angular displacement method for Yaogan-26 remote sensing satellite (United States)

    Wang, Mi; Fan, Chengcheng; Pan, Jun; Jin, Shuying; Chang, Xueli


    Satellite platform jitter is an important factor restricting the imaging quality of high-resolution (HR) optical satellite images. To address the critical issue of compensation for attitude jitter in HR images, this paper proposes a steady-state reimaging model using high-frequency angular displacement data to detect and compensate for the attitude jitter of HR images. The bidirectional Kalman filter and overall weighted smoothing method helps realizing information fusion of star sensor and angular displacement sensor and obtaining the high-frequency attitude for image jitter detection. Then, the steady reimaging model is used to correct the distorted image with geolocation consistency based on a rigorous geometric model. The Yaogan-26 remote sensing satellite's distorted panchromatic images of airports, targets and calibration fields affected by platform jitter were used to validate the effectiveness and accuracy of the proposed method. The compensation results show that the proposed method can effectively improve the relative geometric quality of images affected by platform jitter, with the images' jitter distortion being clearly eliminated. Compared to the conventional compensation method that bundle adjustment with GCPs, the absolute geometric accuracy can also be improved.

  12. Direct imaging of small scatterers using reduced time dependent data (United States)

    Cakoni, Fioralba; Rezac, Jacob D.


    We introduce qualitative methods for locating small objects using time dependent acoustic near field waves. These methods have reduced data collection requirements compared to typical qualitative imaging techniques. In particular, we only collect scattered field data in a small region surrounding the location from which an incident field was transmitted. The new methods are partially theoretically justified and numerical simulations demonstrate their efficacy. We show that these reduced data techniques give comparable results to methods which require full multistatic data and that these time dependent methods require less scattered field data than their time harmonic analogs.

  13. Object Based and Pixel Based Classification Using Rapideye Satellite Imager of ETI-OSA, Lagos, Nigeria

    Directory of Open Access Journals (Sweden)

    Esther Oluwafunmilayo Makinde


    Full Text Available Several studies have been carried out to find an appropriate method to classify the remote sensing data. Traditional classification approaches are all pixel-based, and do not utilize the spatial information within an object which is an important source of information to image classification. Thus, this study compared the pixel based and object based classification algorithms using RapidEye satellite image of Eti-Osa LGA, Lagos. In the object-oriented approach, the image was segmented to homogenous area by suitable parameters such as scale parameter, compactness, shape etc. Classification based on segments was done by a nearest neighbour classifier. In the pixel-based classification, the spectral angle mapper was used to classify the images. The user accuracy for each class using object based classification were 98.31% for waterbody, 92.31% for vegetation, 86.67% for bare soil and 90.57% for Built up while the user accuracy for the pixel based classification were 98.28% for waterbody, 84.06% for Vegetation 86.36% and 79.41% for Built up. These classification techniques were subjected to accuracy assessment and the overall accuracy of the Object based classification was 94.47%, while that of Pixel based classification yielded 86.64%. The result of classification and accuracy assessment show that the object-based approach gave more accurate and satisfying results

  14. On the Use of Machine Vision Techniques to Detect Human Settlements in Satellite Images

    Energy Technology Data Exchange (ETDEWEB)

    Kamath, C; Sengupta, S K; Poland, D; Futterman, J A H


    The automated production of maps of human settlement from recent satellite images is essential to studies of urbanization, population movement, and the like. The spectral and spatial resolution of such imagery is often high enough to successfully apply computer vision techniques. However, vast amounts of data have to be processed quickly. In this paper, we propose an approach that processes the data in several different stages. At each stage, using features appropriate to that stage, we identify the portion of the data likely to contain information relevant to the identification of human settlements. This data is used as input to the next stage of processing. Since the size of the data has reduced, we can now use more complex features in this next stage. These features can be more representative of human settlements, and also more time consuming to extract from the image data. Such a hierarchical approach enables us to process large amounts of data in a reasonable time, while maintaining the accuracy of human settlement identification. We illustrate our multi-stage approach using IKONOS 4-band and panchromatic images, and compare it with the straight-forward processing of the entire image.

  15. Learning Oriented Region-based Convolutional Neural Networks for Building Detection in Satellite Remote Sensing Images (United States)

    Chen, C.; Gong, W.; Hu, Y.; Chen, Y.; Ding, Y.


    The automated building detection in aerial images is a fundamental problem encountered in aerial and satellite images analysis. Recently, thanks to the advances in feature descriptions, Region-based CNN model (R-CNN) for object detection is receiving an increasing attention. Despite the excellent performance in object detection, it is problematic to directly leverage the features of R-CNN model for building detection in single aerial image. As we know, the single aerial image is in vertical view and the buildings possess significant directional feature. However, in R-CNN model, direction of the building is ignored and the detection results are represented by horizontal rectangles. For this reason, the detection results with horizontal rectangle cannot describe the building precisely. To address this problem, in this paper, we proposed a novel model with a key feature related to orientation, namely, Oriented R-CNN (OR-CNN). Our contributions are mainly in the following two aspects: 1) Introducing a new oriented layer network for detecting the rotation angle of building on the basis of the successful VGG-net R-CNN model; 2) the oriented rectangle is proposed to leverage the powerful R-CNN for remote-sensing building detection. In experiments, we establish a complete and bran-new data set for training our oriented R-CNN model and comprehensively evaluate the proposed method on a publicly available building detection data set. We demonstrate State-of-the-art results compared with the previous baseline methods.

  16. Improving a DWT-based compression algorithm for high image-quality requirement of satellite images (United States)

    Thiebaut, Carole; Latry, Christophe; Camarero, Roberto; Cazanave, Grégory


    Past and current optical Earth observation systems designed by CNES are using a fixed-rate data compression processing performed at a high-rate in a pushbroom mode (also called scan-based mode). This process generates fixed-length data to the mass memory and data downlink is performed at a fixed rate too. Because of on-board memory limitations and high data rate processing needs, the rate allocation procedure is performed over a small image area called a "segment". For both PLEIADES compression algorithm and CCSDS Image Data Compression recommendation, this rate allocation is realised by truncating to the desired rate a hierarchical bitstream of coded and quantized wavelet coefficients for each segment. Because the quantisation induced by truncation of the bit planes description is the same for the whole segment, some parts of the segment have a poor image quality. These artefacts generally occur in low energy areas within a segment of higher level of energy. In order to locally correct these areas, CNES has studied "exceptional processing" targeted for DWT-based compression algorithms. According to a criteria computed for each part of the segment (called block), the wavelet coefficients can be amplified before bit-plane encoding. As usual Region of Interest handling, these multiplied coefficients will be processed earlier by the encoder than in the nominal case (without exceptional processing). The image quality improvement brought by the exceptional processing has been confirmed by visual image analysis and fidelity criteria. The complexity of the proposed improvement for on-board application has also been analysed.

  17. Modelling Angular Dependencies in Land Surface Temperatures From the SEVIRI Instrument onboard the Geostationary Meteosat Second Generation Satellites

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander; Pinheiro, AC; Proud, Simon Richard


    Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence on vegetat......Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence...... on vegetation structure and viewing and illumination geometry. Despite this, these effects are not considered in current operational LST products from neither polar-orbiting nor geostationary satellites. In this paper, we simulate the angular dependence that can be expected when estimating LST with the viewing...... by different land covers. The results show that the sun-target-sensor geometry plays a significant role in the estimated temperature, with variations strictly due to the angular configuration of more than ±3°C in some cases. On the continental scale, the average error is small except in hot-spot conditions...

  18. Assessment of temporal variations of water quality in inland water bodies using atmospheric corrected satellite remotely sensed image data. (United States)

    Hadjimitsis, Diofantos G; Clayton, Chris


    Although there have been many studies conducted on the use of satellite remote sensing for water quality monitoring and assessment in inland water bodies, relatively few studies have considered the problem of atmospheric intervention of the satellite signal. The problem is especially significant when using time series multi-spectral satellite data to monitor water quality surveillance in inland waters such as reservoirs, lakes, and dams because atmospheric effects constitute the majority of the at-satellite reflectance over water. For the assessment of temporal variations of water quality, the use of multi-date satellite images is required so atmospheric corrected image data must be determined. The aim of this study is to provide a simple way of monitoring and assessing temporal variations of water quality in a set of inland water bodies using an earth observation- based approach. The proposed methodology is based on the development of an image-based algorithm which consists of a selection of sampling area on the image (outlet), application of masking and convolution image processing filter, and application of the darkest pixel atmospheric correction. The proposed method has been applied in two different geographical areas, in UK and Cyprus. Mainly, the method has been applied to a series of eight archived Landsat-5 TM images acquired from March 1985 up to November 1985 of the Lower Thames Valley area in the West London (UK) consisting of large water treatment reservoirs. Finally, the method is further tested to the Kourris Dam in Cyprus. It has been found that atmospheric correction is essential in water quality assessment studies using satellite remotely sensed imagery since it improves significantly the water reflectance enabling effective water quality assessment to be made.

  19. Comparison of two Satellite Imaging Platforms for Evaluating Sand Dune Migration in the Ubari Sand Sea (Libyan Fazzan) (United States)

    Els, A.; Merlo, S.; Knight, J.


    Sand dunes can change location, form or dimensions depending on wind direction and strength. Sand dune movements can be effectively monitored through the comparison of multi-temporal satellite images. However, not all remote sensing platforms are suitable to study sand dunes. This study compares coarse (Landsat) and fine (Worldview) resolution platforms, specifically focussing on sand dunes within the Ubari Sand Sea (Libya). Sand dune features (crest line, dune ridge basal outlines) were extracted from Landsat and Worldview 2 imagery in order to construct geomorphic maps. These geomorphic maps were then compared using image overlay and differencing, and the Root Mean Squared Error (RMSE) was used to determine if the mapped dune patterns were significantly different. It was found that Landsat is a sufficient data source when studying dune patterns within a regional sand sea, but smaller dunes identified from Worldview data were not capable of being extracted in the data sourced from Landsat. This means that for studies concerned with the dune patterns and movements within sand seas, Landsat is sufficient. But in studies where the specific dynamics of specific dunes are required, a finer resolution is required; platforms such as Worldview are needed in order to gain more detailed insight and to link the past and present day climate and environmental change.

  20. Distance-Dependent Multimodal Image Registration for Agriculture Tasks

    Directory of Open Access Journals (Sweden)

    Ron Berenstein


    Full Text Available Image registration is the process of aligning two or more images of the same scene taken at different times; from different viewpoints; and/or by different sensors. This research focuses on developing a practical method for automatic image registration for agricultural systems that use multimodal sensory systems and operate in natural environments. While not limited to any particular modalities; here we focus on systems with visual and thermal sensory inputs. Our approach is based on pre-calibrating a distance-dependent transformation matrix (DDTM between the sensors; and representing it in a compact way by regressing the distance-dependent coefficients as distance-dependent functions. The DDTM is measured by calculating a projective transformation matrix for varying distances between the sensors and possible targets. To do so we designed a unique experimental setup including unique Artificial Control Points (ACPs and their detection algorithms for the two sensors. We demonstrate the utility of our approach using different experiments and evaluation criteria.

  1. A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping (United States)

    Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar


    There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

  2. Crop classification using multi-temporal HJ satellite images: case study in Kashgar, Xinjiang (United States)

    Hao, Pengyu; Niu, Zheng; Wang, Li


    The HJ satellite constellation, characterized as high temporal resolution (4 day revisit frequency), has high potential to obtain cloud-free images covering all cruel periods for crop classification during growing season. In this paper, three HJ images (in May, July and September) were acquired, the performances of different multi-spectral HJ CCD data combinations for crop classification in Kashgar, Xinjiang were estimated using library for Support Vector Machine (LIBSVM), and ground reference data obtained in 2011 field work were used as training and validation samples. The result showed that multi-temporal HJ data has a potential to classify crops with an overall classification accuracy of 93.77%. Among the three time periods utilized in this research, the image acquired in July achieved the highest overall accuracy (86.98%) because all summer crops were under dense canopy closure. Cotton could be accurately extracted in May image (both user and produce accuracy are above 90%) because of its lower canopy closure compared with spring, the rotate crop (wheat_maize) and winter crop (wheat) at the time period. Then, the July and September combination performed as good as that of all threetime- period combination, which indicated that images obtained at cruel time periods are enough to identify crops, and the additional images improve little on classification accuracy. In addition, multi-temporal NDVI in cruel time periods of the growing season is testified efficient to classify crops with significant phenonlogical variances since they achieved similar overall accuracy to that of multi-temporal multi-spectral combination.

  3. 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


    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.

  4. Periodic components of the atmospheric drag of Earth artificial satellites and their dependence on the state of space weather (United States)

    Komendant, Volodymyr; Koshkin, Nikolay; Ryabov, Mikhail


    Based on the accumulated in the University Observatory extensive database of evolving orbital elements of low-orbit satellites, the behavior of the parameterwas studied, which characterizes their drag in the atmosphere of the Earth. The time spectra structure of drag of 25 artificial satellites is being studied by applying various methods of spectral analysis. Fifteen artificial satellites with circular orbits and ten artificial satellites with elliptical orbits are studied. The processed information includes ten years of observations that covers: declining and minimum phases of 23 ^{rd}(2005-2008) solar cycle; phases of rise and maximum of 24th(2009-2014) solar cycle. Time-frequency analysis of solar and geomagnetic activity indexes has been conducted. These indexes are: W - Wolf numbers; Sp - the total area of sunspot groups of the northern and southern hemispheres of the Sun, F10.7 - the solar radio flux at 10,7 cm; E - electron flux with energies more than 0,6 MeV i 2 MeV; planetary, high latitude and middle latitude geomagnetic index Ap. Periodograms of satellite's drag data, solar and geomagnetic activity indexes were constructed. In the atmospheric drag dynamics of satellites,the following periodswere detected: 6-year, 2.1-year, annual, semi-annual, 27-days, 13- and 11-days. Similar periods are identified in indexes of solar and geomagnetic activity. The ratios of the amplitudes of the spectral power of these periods vary in different phases of the solar cycle. The tables of the main periods in the drag of the artificial satellites and the main periods in the solar and geomagnetic activity indexes were obtained with the help of spectrograms. Their presence in certain phases of the solar cycle was researched. The calculation of multiple correlation' models of the orbital parameter characterizing the drag of satellites on various orbits, depending on the basic parameters of space weather has been done. These results have practical application for models

  5. Winter mass balance of Drangajökull ice cap (NW Iceland) derived from satellite sub-meter stereo images


    J. M. C. Belart; E. Berthier; E. Magnússon; Anderson, L.S.; F. Pálsson; Thorsteinsson, T; Howat, I. M.; Aðalgeirsdóttir, G.; Jóhannesson, T.; A. H. Jarosch


    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. Sta...

  6. Application of image cross-correlation to the measurement of glacier velocity using satellite image data (United States)

    Scambos, Theodore A.; Dutkiewicz, Melanie J.; Wison, Jeremy C.; Bindschadler, Robert A.


    A high-resolution map of the velocity field of the central portion of Ice Stream E in West Antarctica, generated by the displacement-measuring technique, is presented. The use of cross-correlation software is found to be a significant improvement over previous manually based photogrammetric methods for velocity measurement, and is far more cost-effective than in situ methods in remote polar areas. A hue-intensity-saturation image of Ice Stream E and its velocity field is shown.

  7. Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction (United States)

    Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.


    Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively

  8. Quasi-real-time fluorescence imaging with lifetime dependent contrast (United States)

    Jiang, Pei-Chi; Grundfest, Warren S.; Stafsudd, Oscar M.


    Conventional fluorescence lifetime imaging requires complicated algorithms to extract lifetimes of fluorophores and acquisition of multiple data points at progressively longer delay times to characterize tissues. To address diminishing signal-to-noise ratios at these progressively longer time delays, we report a time-resolved fluorescence imaging method, normalized fluorescence yield imaging that does not require the extraction of lifetimes. The concept is to extract the ``contrast'' instead of the lifetime value of the fluorophores by using simple mathematical algorithms. This process converts differences in decay times directly to different intensities. The technique was verified experimentally using a gated iCCD camera and an ultraviolet light-emitting diode light source. It was shown that this method can distinguish between chemical dyes (Fluorescein and Rhodamine-B) and biomedical samples, such as powders of elastin and collagen. Good contrast was obtained between fluorophores that varied by less than 6% in lifetime. Additionally, it was shown that long gate times up to 16 ns achieve good contrast depending upon the samples to be studied. These results support the feasibility of time-resolved fluorescence imaging without lifetime extraction, which has a potential clinical role in noninvasive real-time imaging.

  9. Feasibility of anomaly occurrence in aerosols time series obtained from MODIS satellite images during hazardous earthquakes (United States)

    Akhoondzadeh, Mehdi; Jahani Chehrebargh, Fatemeh


    Earthquake is one of the most devastating natural disasters that its prediction has not materialized comprehensive. Remote sensing data can be used to access information which is closely related to an earthquake. The unusual variations of lithosphere, atmosphere and ionosphere parameters before the main earthquakes are considered as earthquake precursors. To date the different precursors have been proposed. This paper examines one of the parameters which can be derived from satellite imagery. The mentioned parameter is Aerosol Optical Depth (AOD) that this article reviews its relationship with earthquake. Aerosol parameter can be achieved through various methods such as AERONET ground stations or using satellite images via algorithms such as the DDV (Dark Dense Vegetation), Deep Blue Algorithm and SYNTAM (SYNergy of Terra and Aqua Modis). In this paper, by analyzing AOD's time series (derived from MODIS sensor on the TERRA platform) for 16 major earthquakes, seismic anomalies were observed before and after earthquakes. Before large earthquakes, rate of AOD increases due to the pre-seismic changes before the strong earthquake, which produces gaseous molecules and therefore AOD increases. Also because of aftershocks after the earthquake there is a significant change in AOD due to gaseous molecules and dust. These behaviors suggest that there is a close relationship between earthquakes and the unusual AOD variations. Therefore the unusual AOD variations around the time of earthquakes can be introduced as an earthquake precursor.


    Energy Technology Data Exchange (ETDEWEB)

    López-Corredoira, Martín [Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife (Spain); Kroupa, Pavel, E-mail:, E-mail: [Helmholtz-Institut für Strahlen- und Kernphysik, Universität Bonn, Nussallee 14-16, D-53115 Bonn (Germany)


    We show that a significant correlation (up to 5σ) emerges between the bulge index, defined to be larger for a larger bulge/disk ratio, in spiral galaxies with similar luminosities in the Galaxy Zoo 2 of the Sloan Digital Sky Survey and the number of tidal-dwarf galaxies in the catalog by Kaviraj et al. In the standard cold or warm dark matter cosmological models, the number of satellite galaxies correlates with the circular velocity of the dark matter host halo. In generalized gravity models without cold or warm dark matter, such a correlation does not exist, because host galaxies cannot capture infalling dwarf galaxies due to the absence of dark-matter-induced dynamical friction. However, in such models, a correlation is expected to exist between the bulge mass and the number of satellite galaxies because bulges and tidal-dwarf satellite galaxies form in encounters between host galaxies. This is not predicted by dark matter models in which bulge mass and the number of satellites are a priori uncorrelated because higher bulge/disk ratios do not imply higher dark/luminous ratios. Hence, our correlation reproduces the prediction of scenarios without dark matter, whereas an explanation is not found readily from the a priori predictions of the standard scenario with dark matter. Further research is needed to explore whether some application of the standard theory may explain this correlation.

  11. The number of tidal dwarf satellite galaxies in dependence of bulge index

    CERN Document Server

    Lopez-Corredoira, Martin


    We show that a significant correlation (up to 5sigma) emerges between the bulge index, defined to be larger for larger bulge/disk ratio, in spiral galaxies with similar luminosities in the Galaxy Zoo 2 of SDSS and the number of tidal-dwarf galaxies in the catalogue by Kaviraj et al. (2012). In the standard cold or warm dark-matter cosmological models the number of satellite galaxies correlates with the circular velocity of the dark matter host halo. In generalized-gravity models without cold or warm dark matter such a correlation does not exist, because host galaxies cannot capture in-falling dwarf galaxies due to the absence of dark-matter-induced dynamical friction. However, in such models a correlation is expected to exist between the bulge mass and the number of satellite galaxies, because bulges and tidal-dwarf satellite galaxies form in encounters between host galaxies. This is not predicted by dark matter models in which bulge mass and the number of satellites are a priori uncorrelated because higher b...

  12. [Design and study of a high resolution vacuum ultraviolet imaging spectrometer carried by satellite]. (United States)

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


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

  13. Neural Network Change Detection Model for Satellite Images Using Textural and Spectral Characteristics

    Directory of Open Access Journals (Sweden)

    A. K. Helmy


    Full Text Available Problem statement: Change detection is the process of identifying difference of the state of an object or phenomena by observing it at different time. Essentially, it involves the ability to quantify temporal effects using multi-temporal data sets. Information about change is necessary for evaluating land cover and the management of natural resources. Approach: A neural network model based on both spectral and textural analysis is developed. Change detection system in this study is presented using modified version of back-propagation-training algorithm with dynamic learning rate and momentum. Through proposed model, the two images at different dates are fed into the input layer of neural network, in addition with Variance, Skewness and Eculedian for each image that represent different texture measure. This leads to better discrimination process. Results: The results showed that the trained network with texture measures achieve 23% higher accuracy than that without textural parameters. Conclusion: Adding textural parameters of satellite images through training phase increases the efficiently of change detection process also, it provides adequate information about the type of changes. It also found, when using dynamic momentum and learning rate, time and effort needed to select their appropriate value is reduced.

  14. Trend Assessment of Spatio-Temporal Change of Tehran Heat Island Using Satellite Images (United States)

    Saradjian, M. R.; Sherafati, Sh.


    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.


    Directory of Open Access Journals (Sweden)

    M. R. Saradjian


    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.

  16. 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


    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...

  17. Feasibility study on UV/visible imaging spectrograph (Geo-OPUS) for GOAL satellite proposal (United States)

    Suzuki, M.; Kita, K.; Toshimi, T.; Okumura, S.; Shiomi, K.; Imamura, T.; Nakamura, M.

    Geo-OPUS geostationary ozone and air pollution monitoring UV visible spectrometer is a core instrument of GOAL geostationary observation of atmospheric chemistry and lightning satellite proposal Geo-OPUS is an imaging spectrograph to scan earth disk 20km x 20 km nadir pixel 512 north-south pixels IFOV and whole disk FOV within 1 hour observation cycle which observes 270-450 nm with 0 3 nm spectral sampling Onboard spectral calibration 0 01 nm accuracy is carried out using Hg lamp and solar lines Radio Diffuser plates are used for radiometric calibration Primary observation targets are total column of NO2 SO2 O3 also stratospheric profile HCHO and aerosols It also measures stratospheric species OClO BrO etc High SNR and spectral calibration stability are required to derive species such as tropospheric O3 column in 10-20 accuracy required by IGOS-P IGACO

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

    Directory of Open Access Journals (Sweden)

    Yantong Chen


    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.

  19. Origins and features of oil slicks in the Bohai Sea detected from satellite SAR images. (United States)

    Ding, Yi; Cao, Conghua; Huang, Juan; Song, Yan; Liu, Guiyan; Wu, Lingjuan; Wan, Zhenwen


    Oil slicks were detected using satellite Synthetic Aperture Radar (SAR) images in 2011. We investigated potential origins and regional and seasonal features of oil slick in the Bohai Sea. Distance between oil slicks and potential origins (ships, seaports, and oil exploitation platforms) and the angle at which oil slicks move relative to potential driving forces were evaluated. Most oil slicks were detected along main ship routes rather than around seaports and oil exploitation platforms. Few oil slicks were detected within 20km of seaports. Directions of oil slicks movement were much more strongly correlated with directions of ship routes than with directions of winds and currents. These findings support the premise that oil slicks in the Bohai Sea most likely originate from illegal disposal of oil-polluted wastes from ships. Seasonal variation of oil slicks followed an annual cycle, with a peak in August and a trough in December.

  20. Monitoring the Water Quality of Lake Koronia Using Long Time-Series of Multispectral Satellite Images (United States)

    Perivolioti, Triantafyllia-Maria; Mouratidis, Antonios; Doxani, Georgia; Bobori, Dimitra


    In this study, a comprehensive 30-year (1984-2016) water quality parameter database for lake Koronia - one of the most important Ramsar wetlands of Greece - was compiled from Landsat imagery. The reliability of the data was evaluated by comparing water Quality Element (QE) values computed from Landsat data against in-situ data. Water quality algorithms developed from previous studies, specifically for the determination of Water Temperature, pH, Transparency/Secchi Disk Depth (SDD), Chlorophyll a and Conductivity, were applied to Landsat images. In addition, Water Depth, as well as the distribution of floating vegetation and cyanobacterial blooms were mapped. The performed comprehensive analysis posed certain questions, regarding the applicability of single empirical models across multi- temporal, multi-sensor datasets, towards the accurate prediction of key water quality indicators for shallow inland systems. This assessment demonstrates that satellite imagery can provide an accurate method for obtaining comprehensive spatial and temporal coverage of key water quality characteristics.

  1. Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms (United States)

    Qayyum, A.; Malik, A. S.; Saad, M. N. M.; Iqbal, M.; Abdullah, F.; Rahseed, W.; Abdullah, T. A. R. B. T.; Ramli, A. Q.


    Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more time consuming and expensive. In this paper, we have proposed a novel approach to monitor the vegetation/trees near or under the power transmission poles using satellite stereo images, which were acquired using Pleiades satellites. The 3D depth of vegetation has been measured near power transmission lines using stereo algorithms. The area of interest scanned by Pleiades satellite sensors is 100 square kilometer. Our dataset covers power transmission poles in a state called Sabah in East Malaysia, encompassing a total of 52 poles in the area of 100 km. We have compared the results of Pleiades satellite stereo images using dynamic programming and Graph-Cut algorithms, consequently comparing satellites' imaging sensors and Depth-estimation Algorithms. Our results show that Graph-Cut Algorithm performs better than dynamic programming (DP) in terms of accuracy and speed.

  2. A configurable distributed high-performance computing framework for satellite's TDI-CCD imaging simulation (United States)

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


    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.

  3. Forecasting irrigation demand by assimilating satellite images and numerical weather predictions (United States)

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


    Forecasting irrigation water demand, with small predictive uncertainty in the short-medium term, is fundamental for an efficient planning of water resource allocation among multiple users and for decreasing water and energy consumptions. In this study we present an innovative system for forecasting irrigation water demand, applicable at different spatial scales: from the farm level to the irrigation district level. The forecast system is centred on a crop growth model assimilating data from satellite images and numerical weather forecasts, according to a stochastic ensemble-based approach. Different sources of uncertainty affecting model predictions are represented by an ensemble of model trajectories, each generated by a possible realization of the model components (model parameters, input weather data and model state variables). The crop growth model is based on a set of simplified analytical relations, with the aim to assess biomass, leaf area index (LAI) growth and evapotranspiration rate with a daily time step. Within the crop growth model, LAI dynamics is let be governed by temperature and leaf dry matter supply, according to the development stage of the crop. The model assimilates LAI data retrieved from VIS-NIR high-resolution multispectral satellite images. Numerical weather model outputs are those from the European limited area ensemble prediction system (COSMO-LEPS), which provides forecasts up to five days with a spatial resolution of seven kilometres. Weather forecasts are sequentially bias corrected based on data from ground weather stations. The forecasting system is evaluated in experimental areas of southern Italy during three irrigation seasons. The performance analysis shows very accurate irrigation water demand forecasts, which make the proposed system a valuable support for water planning and saving at farm level as well as for water management at larger spatial scales.

  4. Upstream drivers of poleward moving auroral forms by satellite-imager coordinated observations (United States)

    Wang, B.; Nishimura, T.; Lyons, L. R.; Angelopoulos, V.; Frey, H. U.; Mende, S. B.


    Poleward moving auroral forms (PMAFs) are observed near the dayside poleward auroral oval boundary. PMAFs are thought to be an ionospheric signature of dayside reconnection and flux transfer events. PMAFs tend to occur when the IMF is southward. Although a limited number of PMAFs has been found in association with IMF southward turning, events without appreciable changes in IMF have also been reported. While those PMAFs could be triggered spontaneously, many of the past studies used solar wind measurements far away from the bow shock nose and may have used inaccurate time shift or missed small-scale structures in the solar wind. To examine how often PMAFs are triggered by upstream structures using solar wind measurements close to the bow shock nose, we use the AGO all sky imager in Antarctic and THEMIS B and C satellites in 2008, 2009 and 2011. We identified 24 conjunction events, where at least one of the THEMIS satellites is in the solar wind and the AGO imager is located within 3 MLT from the THEMIS MLT. We found that, in 14 out of 24 conjunction events, PMAFs occur soon after IMF southward turning, indicating that IMF southward turning could be the major triggering of PMAFs. Interestingly, among these 14 cases, there are 7 cases with different IMF structures between THEMIS B/C and OMNI, which obtained IMF information from WIND and ACE. And the larger correlation coefficients between PMAFs and IMFs observed by THMEIS B/C than OMNI present the advantages of THEMIS B/C. Among the 10 cases without correlating with IMF structures, PMAFs in two events are shown to have good correlation with reflected ions in the foreshock. Based on all the conjunction events we identified, IMF southward turning is the major trigger of PMAFs and reflected ions have minor effects. The rest of the cases could be spontaneous PMAFs, although foreshock activities, even if exists, may be missed due to the IMF orientation.

  5. Differential diagnosis of ACTH-dependent hypercortisolism: imaging versus laboratory. (United States)

    Andrioli, Massimiliano; Pecori Giraldi, Francesca; De Martin, Martina; Cattaneo, Agnese; Carzaniga, Chiara; Cavagnini, Francesco


    Differential diagnosis of ACTH-dependent Cushing's syndrome often presents major difficulties. Diagnostic troubles are increased by suboptimal specificity of endocrine tests, the rarity of ectopic ACTH secretion and the frequent incidental discovery of pituitary adenomas. A 43-year-old female reported with mild signs and symptoms of hypercortisolism, and initial hormonal tests and results of pituitary imaging (7-mm adenoma) were suggestive for Cushing's disease. However, inadequate response to corticotrophin-releasing hormone and failure to suppress after 8 mg dexamethasone pointed towards an ectopic source. Total body CT scan visualized only a small, non-specific nodule in the right posterior costophrenic excavation. Inferior petrosal sinus sampling revealed an absent center:periphery ACTH gradient but octreoscan and (18)F-FDG-PET-CT failed to detect abnormal tracer accumulation. We weighed results of the laboratory with those of imaging and decided to remove the lung nodule. Pathology identified a typical, ACTH-staining carcinoid and the diagnosis was confirmed by postsurgical hypoadrenalism. In conclusion, imaging may prove unsatisfactory or even misleading for the etiologial diagnosis of ACTH-dependent Cushing's syndrome and should therefore be interpreted only in context with results of hormonal dynamic testing.

  6. Application of Multifractal Analysis to Segmentation of Water Bodies in Optical and Synthetic Aperture Radar Satellite Images

    CERN Document Server

    Martin, Victor Manuel San


    A method for segmenting water bodies in optical and synthetic aperture radar (SAR) satellite images is proposed. It makes use of the textural features of the different regions in the image for segmentation. The method consists in a multiscale analysis of the images, which allows us to study the images regularity both, locally and globally. As results of the analysis, coarse multifractal spectra of studied images and a group of images that associates each position (pixel) with its corresponding value of local regularity (or singularity) spectrum are obtained. Thresholds are then applied to the multifractal spectra of the images for the classification. These thresholds are selected after studying the characteristics of the spectra under the assumption that water bodies have larger local regularity than other soil types. Classifications obtained by the multifractal method are compared quantitatively with those obtained by neural networks trained to classify the pixels of the images in covered against uncovered b...

  7. Evidence of hydrocarbon pollution in soil exploiting satellite optical and radar images (United States)

    Monsivais-Huertero, A.; Galvan-Pineda, J.; Espinosa-Hernandez, A.; Jimenez-Escalona, J. C.; Ramos-Rodriguez, J. M.


    Oil spills are one of the most important sources of hydrocarbon pollution in soils of areas near centers of extraction, storage or transportation of petroleum products. These spills or leaks can occur arising from deficient maintenance of facilities or accidents. The effects of these spills can spread for kilometers affecting large areas. This has a strong impact on the local ecosystem disturbing the flora and fauna. In costal tourist areas, this type of contaminants represents significant health risks for visitors and therefore, economic losses for the place. For this reason, it is very important to know and identify the areas affected by this type of pollution in order to create action plans for remediation of the ecosystem. Due to the large land extensions that can cover such disasters, satellite images become a valuable tool because of their large spatial coverage. Nowadays, different satellite techniques have been developed to recognize land affected by the presence of hydrocarbons. In the optical spectrum, optical sensing imagery (e.g. Landsat, SPOT, MODIS, etc.) has been widely used. However, these techniques have the intrinsic limitation in scenes with vegetation cover. In contrast, techniques exploiting radar images are still rare. The type of signal that is detected by the radar provides information even in areas with vegetation cover. The radar signal interacts with the vegetation and soil collecting information about the dielectric properties of the soil. This study identifies zones of contaminated soil by using the synergy of optical and radar images. This site of study is located in Paraiso, Tabasco, in Southern Mexico (18°27'N 93°32'W). The region is composed of coastal and tropical forest ecosystems and includes the Port Dos Bocas. The Port Dos Bocas has its points of extractions 130m away from the coast. The annual activities report 10 millions of tons of hydrocarbons transported using around 5500 ships. The methodology presented in this paper

  8. New Generation Meteorological Satellite Imager Aviation Decision Support Applications for Detection of Convection, Turbulence, and Volcanic Ash (United States)

    Feltz, Wayne


    A suite of aviation related decision support products have been in development to meet GOES-R science requirements since 2008 and are being evaluated to assess meteorological hazards to aircraft in flight derived from the current generation of European Spinning Enhanced Visible and Infrared Imager (SEVIRI) imager data. This presentation will focus on GOES-R Advanced Baseline Imager (ABI) measurement requirements relating to satellite-based aviation convective, turbulence, and volcanic ash/SO2 products that can be applied globally on next generation geostationary imagers including the Japanese Himawari, South Korean COMS (AMI), and European Metop-SG imagers. These new methodologies have relevance on current generation GOES and SEVIRI imagers, and overview will include discussion on how product utility has been improved through satellite GOES-R/JPSS Proving Ground NOAA testbed activities. Satellite-based decision support for aviation context toward improvement of future air transportation route planning and warning for the general public with emphasis on successfully bridging research to operations will also be discussed with anticipated October 2016 launch of GOES-R.

  9. Topology Adaptive Water Boundary Extraction Based on a Modified Balloon Snake: Using GF-1 Satellite Images as an Example

    Directory of Open Access Journals (Sweden)

    Wenying Du


    Full Text Available Topology adaptive water boundary extraction from satellite images using parametric snakes remains challenging in the domain of image segmentation. This paper proposed a modified balloon snake (MB-Snake method based on the balloon snake (B-Snake method, overcoming the B-Snake’s drawbacks of inaccurate positioning, topology inflexibility, and non-automatic contour evolution termination. Six satellite images, acquired by the GF-1 wide field of view sensor and with water bodies of different types, inner land numbers, areas, boundary and background complexities, and digital number value contrasts, were used as experimental images, in which the MB-Snake method, and two comparison methods, the B-Snake and the orthogonal topology adaptive snake (OT-Snake methods, were applied for water boundary extraction. All the extracted results were first qualitatively assessed and further quantitatively evaluated via three indexes, including correctness, completeness, and area overlap measure. Both of the qualitative and quantitative evaluation results consistently demonstrated that the MB-Snake method can efficiently improve the positioning accuracy, detect and dispose of topology collisions, and perform automatic contour evolution termination, successfully meeting its design objectives, and exhibiting great superiority to the existing topology-flexible parametric snakes. The sensitivity to initial contours, the effects of model parameters, and spatial resolutions of satellite images, and image demands of the MB-Snake method was also analyzed.

  10. Global near real-time disturbance monitoring using MODIS satellite image time series (United States)

    Verbesselt, J.; Kalomenopoulos, M.; de Jong, R.; Zeileis, A.; Herold, M.


    Global disturbance monitoring in forested ecosystems is critical to retrieve information on carbon storage dynamics, biodiversity, and other socio-ecological processes. Satellite remote sensing provides a means for cost-effective monitoring at frequent time steps over large areas. However, for information about current change processes, it is required to analyse image time series in a fast and accurate manner and to detect abnormal change in near real time. An increasing number of change detection techniques have become available that are able to process historical satellite image time series data to detect changes in the past. However, methods that detect changes near real-time, i.e. analysing newly acquired data with respect to the historical series, are lacking. We propose a statistical technique for monitoring change in near-real time by comparing current data with a seasonal-trend model fitted onto the historical time series. As such, identification of consistent and abnormal change in near-real time becomes possible as soon as new image data is captured. The method is based on the "Break For Additive Seasonal Trend" (BFAST) concept ( Disturbances are detected by analysing 16-daily MODIS combined vegetation and temperature indices. Validation is carried out by comparing the detected disturbances with available disturbance data sets (e.g. deforestation in Brazil and MODIS fire products). Preliminary results demonstrated that abrupt changes at the end of time series can be successfully detected while the method remains robust for strong seasonality and atmospheric noise. Cloud masking, however, was identified as a critical issue since periods of persistent cloudiness can be detected as abnormal change. The proposed method is an automatic and robust change detection approach that can be applied on different types of data (e.g. future sensors like the Sentinel constellation that provide higher spatial resolution at regular time

  11. ASPECT spectral imaging satellite proposal to AIDA/AIM CubeSat payload (United States)

    Kohout, Tomas; Näsilä, Antti; Tikka, Tuomas; Penttilä, Antti; Muinonen, Karri; Kestilä, Antti; Granvik, Mikael; Kallio, Esa


    ASPECT (Asteroid Spectral Imaging Mission) is a part of AIDA/AIM project and aims to study the composition of the Didymos binary asteroid and the effects of space weathering and shock metamorphism in order to gain understanding of the formation and evolution of the Solar System. The joint ESA/NASA AIDA (Asteroid Impact & Deflection Assessment) mission to binary asteroid Didymos consists of AIM (Asteroid Impact Mission, ESA) and DART (Double Asteroid Redirection Test, NASA). DART is targeted to impact Didymos secondary component (Didymoon) and serve as a kinetic impactor to demonstrate deflection of potentially hazardous asteroids. AIM will serve as an observational spacecraft to evaluate the effects of the impact and resulting changes in the Didymos dynamic parameters. The AIM mission will also carry two CubeSat miniaturized satellites, released in Didymoon proximity. This arrangement opens up a possibility for secondary scientific experiments. ASPECT is one of the proposed CubeSat payloads. Whereas Didymos is a space-weathered binary asteroid, the DART impactor is expected to produce a crater and excavate fresh material from the secondary component (Didymoon). Spectral comparison of the mature surface to the freshly exposed material will allow to directly deter-mine space weathering effects. It will be also possible to study spectral shock effects within the impact crater. ASPECT will also demonstrate for the first time the joint spacecraft - CubeSat operations in asteroid proximity and miniature spectral imager operation in deep-space environment. Science objectives: 1. Study of the surface composition of the Didymos system. 2. Photometric observations (and modeling) under varying phase angle and distance. 3. Study of space weathering effects on asteroids (comparison of mature / freshly exposed material). 4. Study of shock effects (spectral properties of crater interior). 5. Observations during the DART impact. Engineering objectives: 1. Demonstration of Cube

  12. A Multi-stage Method to Extract Road from High Resolution Satellite Image (United States)

    Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang


    Extracting road information from high-resolution satellite images is complex and hardly achieves by exploiting only one or two modules. This paper presents a multi-stage method, consisting of automatic information extraction and semi-automatic post-processing. The Multi-scale Enhancement algorithm enlarges the contrast of human-made structures with the background. The Statistical Region Merging segments images into regions, whose skeletons are extracted and pruned according to geometry shape information. Setting the start and the end skeleton points, the shortest skeleton path is constructed as a road centre line. The Bidirectional Adaptive Smoothing technique smoothens the road centre line and adjusts it to right position. With the smoothed line and its average width, a Buffer algorithm reconstructs the road region easily. Seen from the last results, the proposed method eliminates redundant non-road regions, repairs incomplete occlusions, jumps over complete occlusions, and reserves accurate road centre lines and neat road regions. During the whole process, only a few interactions are needed.

  13. Effective System for Automatic Bundle Block Adjustment and Ortho Image Generation from Multi Sensor Satellite Imagery (United States)

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


    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.

  14. A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

    Directory of Open Access Journals (Sweden)

    Huai Yu


    Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.

  15. Detection of facilities in satellite imagery using semi-supervized image classification and auxiliary contextual observables (United States)

    Harvey, Neal R.; Ruggiero, C.; Pawley, N. H.; MacDonald, B.; Oyer, A.; Balick, L.; Brumby, S. P.


    Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervised assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.

  16. Improvement of dem Generation from Aster Images Using Satellite Jitter Estimation and Open Source Implementation (United States)

    Girod, L.; Nuth, C.; Kääb, A.


    The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a source of stereoscopic images covering the whole globe at a 15m resolution at a consistent quality for over 15 years. The potential of this data in terms of geomorphological analysis and change detection in three dimensions is unrivaled and needs to be exploited. However, the quality of the DEMs and ortho-images currently delivered by NASA (ASTER DMO products) is often of insufficient quality for a number of applications such as mountain glacier mass balance. For this study, the use of Ground Control Points (GCPs) or of other ground truth was rejected due to the global "big data" type of processing that we hope to perform on the ASTER archive. We have therefore developed a tool to compute Rational Polynomial Coefficient (RPC) models from the ASTER metadata and a method improving the quality of the matching by identifying and correcting jitter induced cross-track parallax errors. Our method outputs more accurate DEMs with less unmatched areas and reduced overall noise. The algorithms were implemented in the open source photogrammetric library and software suite MicMac.

  17. Detection of facilities in satellite imagery using semi-supervised image classification and auxiliary contextual observables

    Energy Technology Data Exchange (ETDEWEB)

    Harvey, Neal R [Los Alamos National Laboratory; Ruggiero, Christy E [Los Alamos National Laboratory; Pawley, Norma H [Los Alamos National Laboratory; Brumby, Steven P [Los Alamos National Laboratory; Macdonald, Brian [Los Alamos National Laboratory; Balick, Lee [Los Alamos National Laboratory; Oyer, Alden [Los Alamos National Laboratory


    Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervised assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.

  18. Worldwide widespread decadal-scale decrease of glacier speed revealed using repeat optical satellite images

    Directory of Open Access Journals (Sweden)

    T. Heid


    Full Text Available Matching of repeat optical satellite images to derive glacier velocities is an approach that is much used within glaciology. Lately, focus has been put into developing, improving, automating and comparing different image matching methods. This makes it now possible to investigate glacier dynamics within large regions of the world and also between regions to improve knowledge about glacier dynamics in space and time. In this study we investigate whether the negative glacier mass balance seen over large parts of the world has caused the glaciers to change their speeds. The studied regions are Pamir, Caucasus, Penny Ice Cap, Alaska Range and Patagonia. In addition we derive speed changes for Karakoram, a region assumed to have positive mass balance and that contains many surge-type glaciers. We find that the mapped glaciers in the five regions with negative mass balance have decreased their speeds over the last decades, Pamir by 43 % in average per decade, Caucasus by 8 % in average per decade, Penny Ice Cap by 25 % in average per decade, Alaska Range by 11 % in average per decade and Patagonia by 20 % in average per decade. Glaciers in Karakoram have generally increased their speeds, but surging glaciers and glaciers with flow instabilities are most prominent in this area.

  19. The Need of Nested Grids for Aerial and Satellite Images and Digital Elevation Models (United States)

    Villa, G.; Mas, S.; Fernández-Villarino, X.; Martínez-Luceño, J.; Ojeda, J. C.; Pérez-Martín, B.; Tejeiro, J. A.; García-González, C.; López-Romero, E.; Soteres, C.


    Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites) pose big interoperability problems, as for example: non-alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression-decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in "Big Data" environments. Most of them can be avoided, or at least greatly reduced, with the use of a common "nested grid" for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. "Nested grids" are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A "nested grid" must be complemented by an appropriate "tiling schema", ideally based on the "quad-tree" concept. In the last years a "de facto standard" grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its "WMTS Simple Profile" standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.

  20. Field survey report and satellite image interpretation of the 2013 Super Typhoon Haiyan in the Philippines (United States)

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


    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.

  1. Forecast of wheat yield throughout the agricultural season using optical and radar satellite images (United States)

    Fieuzal, R.; Baup, F.


    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.

  2. Meteo-marine parameters for highly variable environment in coastal regions from satellite radar images (United States)

    Pleskachevsky, A. L.; Rosenthal, W.; Lehner, S.


    The German Bight of the North Sea is the area with highly variable sea state conditions, intensive ship traffic and with a high density of offshore installations, e.g. wind farms in use and under construction. Ship navigation and the docking on offshore constructions is impeded by significant wave heights HS > 1.3 m. For these reasons, improvements are required in recognition and forecasting of sea state HS in the range 0-3 m. Thus, this necessitates the development of new methods to determine the distribution of meteo-marine parameters from remote sensing data with an accuracy of decimetres for HS. The operationalization of these methods then allows the robust automatic processing in near real time (NRT) to support forecast agencies by providing validations for model results. A new empirical algorithm XWAVE_C (C = coastal) for estimation of significant wave height from X-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed, adopted for coastal applications using TerraSAR-X (TS-X) and Tandem-X (TD-X) satellites in the German Bight and implemented into the Sea Sate Processor (SSP) for fully automatic processing for NRT services. The algorithm is based on the spectral analysis of subscenes and the model function uses integrated image spectra parameters as well as local wind information from the analyzed subscene. The algorithm is able to recognize and remove the influence of non-sea state produced signals in the Wadden Sea areas such as dry sandbars as well as nonlinear SAR image distortions produced by e.g. short wind waves and breaking waves. Also parameters of very short waves, which are not visible in SAR images and produce only unsystematic clutter, can be accurately estimated. The SSP includes XWAVE_C, a pre-filtering procedure for removing artefacts such as ships, seamarks, buoys, offshore constructions and slicks, and an additional procedure performing a check of results based on the statistics of the whole scene. The SSP allows an

  3. Planets across the HR diagram with the Transiting Exoplanet Survey Satellite Full Frame Images (United States)

    Huang, Xu; Pal, Andras; Wall, Matthew; Liang, Yu; Levine, Alan M.; Owens, Martin; Kraft Vanderspek, Roland; Seager, Sara; Ricker, George R.; TESS Science Team


    Discoveries from the Kepler Mission have revealed that planets close to their host stars are common, despite none in our solar system. The Transiting Exoplanet Survey Satellite (TESS) will perform a wide-field survey for planets over ~75%of the sky for the first time. The 30 min cadence TESS Full Frame Images (FFI) will provide observations of more than 10 million stars brighter than magnitude I=16. The FFI targets include stars from all spectral classes, with ages spanning the range ~10 Myr to ~10 Gyr and with metallicities ranging over more than 1 dex.The FFIs will provide an all-sky magnitude limited sample of short period planetary systems. The precision of TESS will enable planet to be discovered around stars ranging from M-dwarfs, to B-dwarfs. In contrast, the Kepler sample is restricted primarily to main-sequence FGK systems, while the TESS short cadence (2 min) stamps will be centered about cooler stars. We present the current status of the TESS full frame image (FFI) photometry and candidate detection pipeline. We update the predicted detection rates of sub-Neptunes, super-Neptunes and giant planets using simulated TESS images with realistic noise characteristics. We expect that TESS will find more than 20000 planets with sizes larger than 2 Earth radius around stars with very diverse properties. We discuss how these findings will help resolve many long standing questions, including the planet occurrence rateas a function of stellar mass, metallicity, and age. Many of these TESS planets will be suitable for ground-based follow up observations that willestablish masses, orbital obliquities and eccentricities, which will help improve our understanding of the formation channels of theseclose-in planets.

  4. Satellite RNAs and Satellite Viruses. (United States)

    Palukaitis, Peter


    Satellite RNAs and satellite viruses are extraviral components that can affect either the pathogenicity, the accumulation, or both of their associated viruses while themselves being dependent on the associated viruses as helper viruses for their infection. Most of these satellite RNAs are noncoding RNAs, and in many cases, have been shown to alter the interaction of their helper viruses with their hosts. In only a few cases have the functions of these satellite RNAs in such interactions been studied in detail. In particular, work on the satellite RNAs of Cucumber mosaic virus and Turnip crinkle virus have provided novel insights into RNAs functioning as noncoding RNAs. These effects are described and potential roles for satellite RNAs in the processes involved in symptom intensification or attenuation are discussed. In most cases, models describing these roles involve some aspect of RNA silencing or its suppression, either directly or indirectly involving the particular satellite RNA.

  5. Use of MODIS satellite images for detailed lake morphometry: Application to basins with large water level fluctuations (United States)

    Ovakoglou, George; Alexandridis, Thomas K.; Crisman, Thomas L.; Skoulikaris, Charalampos; Vergos, George S.


    Lake morphometry is essential for managing water resources and limnetic ecosystems. For reservoirs that receive high sediment loads, frequent morphometric mapping is necessary to define both the effective life of the reservoir and its water storage capacity for irrigation, power generation, flood control and domestic water supply. The current study presents a methodology for updating the digital depth model (DDM) of lakes and reservoirs with wide intra and interannual fluctuations of water levels using satellite remote sensing. A time series of Terra MODIS satellite images was used to map shorelines formed during the annual water level change cycle, and were validated with concurrent Landsat ETM+ satellite images. The shorelines were connected with in-situ observation of water levels and were treated as elevation contours to produce the DDM using spatial interpolation. The accuracy of the digitized shorelines is within the mapping accuracy of the satellite images, while the resulting DDM is validated using in-situ elevation measurements. Two versions of the DDM were produced to assess the influence of seasonal water fluctuation. Finally, the methodology was applied to Lake Kerkini (Greece) to produce an updated DDM, which was compared with the last available bathymetric survey (1991) and revealed changes in sediment distribution within the lake.

  6. Application of Texture Characteristics for Urban Feature Extraction from Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    D.Shanmukha Rao


    Full Text Available Quest of fool proof methods for extracting various urban features from high resolution satellite imagery with minimal human intervention has resulted in developing texture based algorithms. In view of the fact that the textural properties of images provide valuable information for discrimination purposes, it is appropriate to employ texture based algorithms for feature extraction. The Gray Level Co-occurrence Matrix (GLCM method represents a highly efficient technique of extracting second order statistical texture features. The various urban features can be distinguished based on a set of features viz. energy, entropy, homogeneity etc. that characterize different aspects of the underlying texture. As a preliminary step, notable numbers of regions of interests of the urban feature and contrast locations are identified visually. After calculating Gray Level Co-occurrence matrices of these selected regions, the aforementioned texture features are computed. These features can be used to shape a high-dimensional feature vector to carry out content based retrieval. The insignificant features are eliminated to reduce the dimensionality of the feature vector by executing Principal Components Analysis (PCA. The selection of the discriminating features is also aided by the value of Jeffreys-Matusita (JM distance which serves as a measure of class separability Feature identification is then carried out by computing these chosen feature vectors for every pixel of the entire image and comparing it with their corresponding mean values. This helps in identifying and classifying the pixels corresponding to urban feature being extracted. To reduce the commission errors, various index values viz. Soil Adjusted Vegetation Index (SAVI, Normalized Difference Vegetation Index (NDVI and Normalized Difference Water Index (NDWI are assessed for each pixel. The extracted output is then median filtered to isolate the feature of interest after removing the salt and pepper

  7. Coastal water quality estimation from Geostationary Ocean Color Imager (GOCI) satellite data using machine learning approaches (United States)

    Im, Jungho; Ha, Sunghyun; Kim, Yong Hoon; Ha, Hokyung; Choi, Jongkuk; Kim, Miae


    It is important to monitor coastal water quality using key parameters such as chlorophyll-a concentration and suspended sediment to better manage coastal areas as well as to better understand the nature of biophysical processes in coastal seawater. Remote sensing technology has been commonly used to monitor coastal water quality due to its ability of covering vast areas at high temporal resolution. While it is relatively straightforward to estimate water quality in open ocean (i.e., Case I water) using remote sensing, coastal water quality estimation is still challenging as many factors can influence water quality, including various materials coming from inland water systems and tidal circulation. There are continued efforts to accurately estimate water quality parameters in coastal seawater from remote sensing data in a timely manner. In this study, two major water quality indicators, chlorophyll-a concentration and the amount of suspended sediment, were estimated using Geostationary Ocean Color Imager (GOCI) satellite data. GOCI, launched in June 2010, is the first geostationary ocean color observation satellite in the world. GOCI collects data hourly for 8 hours a day at 6 visible and 2 near-infrared bands at a 500 m resolution with 2,500 x 2,500 km square around Korean peninsula. Along with conventional statistical methods (i.e., various linear and non-linear regression), three machine learning approaches such as random forest, Cubist, and support vector regression were evaluated for coastal water quality estimation. In situ measurements (63 samples; including location, two water quality parameters, and the spectra of surface water using a hand-held spectroradiometer) collected during four days between 2011 and 2012 were used as reference data. Due to the small sample size, leave-one-out cross validation was used to assess the performance of the water quality estimation models. Atmospherically corrected radiance data and selected band-ratioed images were used

  8. Applying Support Vector Machine in classifying satellite images for the assessment of urban sprawl (United States)

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


    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

  9. Hybrid Differential Evolution Optimisation for Earth Observation Satellite Scheduling with Time-Dependent Earliness-Tardiness Penalties

    Directory of Open Access Journals (Sweden)

    Guoliang Li


    Full Text Available We study the order acceptance and scheduling (OAS problem with time-dependent earliness-tardiness penalties in a single agile earth observation satellite environment where orders are defined by their release dates, available processing time windows ranging from earliest start date to deadline, processing times, due dates, sequence-dependent setup times, and revenues. The objective is to maximise total revenue, where the revenue from an order is a piecewise linear function of its earliness and tardiness with reference to its due date. We formulate this problem as a mixed integer linear programming model and develop a novel hybrid differential evolution (DE algorithm under self-adaptation framework to solve this problem. Compared with classical DE, hybrid DE employs two mutation operations, scaling factor adaptation and crossover probability adaptation. Computational tests indicate that the proposed algorithm outperforms classical DE in addition to two other variants of DE.

  10. Potential pitfalls of strain rate imaging: angle dependency (United States)

    Castro, P. L.; Greenberg, N. L.; Drinko, J.; Garcia, M. J.; Thomas, J. D.


    Strain Rate Imaging (SRI) is a new echocardiographic technique that allows for the real-time determination of myocardial SR, which may be used for the early and accurate detection of coronary artery disease. We sought to study whether SR is affected by scan line alignment in a computer simulation and an in vivo experiment. Through the computer simulation and the in vivo experiment we generated and validated safe scanning sectors within the ultrasound scan sector and showed that while SRI will be an extremely valuable tool in detecting coronary artery disease there are potential pitfalls for the unwary clinician. Only after accounting for these affects due to angle dependency, can clinicians utilize SRI's potential as a valuable tool in detecting coronary artery disease.

  11. Crop Investigation Using High-Resolution Worldview-1 and Quickbird-2 Satellite Images on a Test Site in Bulgaria (United States)

    Vassilev, Vassil


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

  12. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content. (United States)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.


    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

  13. Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management. (United States)

    Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn


    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.

  14. Investigation of triggering of poleward moving auroral forms using satellite-imager coordinated observations (United States)

    Wang, Boyi; Nishimura, Yukitoshi; Zou, Ying; Lyons, Larry R.; Angelopoulos, Vassilis; Frey, Harald; Mende, Stephen


    Poleward moving auroral forms (PMAFs) are thought to be an ionospheric signature of dayside magnetic reconnection. While PMAFs are more likely to occur when the interplanetary magnetic field (IMF) is southward, how often PMAFs are triggered by changes in solar wind parameters is still an open question. To address this issue, we used one of the Automatic Geophysical Observatories all-sky imagers in Antarctica and the Time History of Events and Macroscale Interactions during Substorms (THEMIS) B and C satellites, which can give solar wind measurements much closer to the subsolar bow shock than by Wind or ACE, to examine if PMAFs occurred in association with IMF orientation changes. We identified 60 PMAFs in conjunction with THEMIS B and C during 2008, 2009, and 2011 and 70% of events show reduction of Bz before PMAF onset indicating that IMF southward turning plays an important role in triggering a majority of PMAFs. In contrast, the magnitude of the IMF Bz reduction in OMNI data was smaller and the reduction occurred in a slightly smaller percentage of events (40-60%). This suggests that solar wind structures that missed the L1 point or evolution of solar wind between the L1 point and THEMIS may be important for identifying IMF changes responsible for transient dayside reconnection. Additionally, 17 PMAFs that did not have substantial IMF southward turnings are correlated well with foreshock events, indicating that foreshock phenomena may also play a role in triggering PMAFs.

  15. Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.J.


    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.

  16. Processing of Satellite Digital Images for Mapping Atmospheric Transmissivity in Bangladesh

    Directory of Open Access Journals (Sweden)

    Md Shahjahan Ali


    Full Text Available This study investigates the potential of determining atmospheric transmissivity (τ from NOAA-AVHRR satellite images using a simple methodology. Using this method, hourly transmissivity values over the land surface area of Bangladesh has been determined. The spatio-temporal distribution of τ has been studied by constructing monthly average maps for the whole country for one complete year (February 2005 to January 2006. Yearly average map has been prepared by integrating monthly average maps. Geographical distribution of τ exhibits patterns and trends. It is observed that the value of τ varies from 0.3 to 0.65 with the average maximum value in the month of April and minimum value in the month of November. It is also observed that for western parts of the country, which is the drought prone area, transmissivity values are little bit higher than that at the eastern parts. Relatively lower values of τ in the dry months (November to January may be due to the effect of particulate or chemical pollution in the atmosphere.

  17. Bottom Topographic Changes of Poyang Lake During Past Decade Using Multi-temporal Satellite Images (United States)

    Zhang, S.


    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.


    Directory of Open Access Journals (Sweden)

    Jenita Subash


    Full Text Available Users of geospatial data in government, military, industry, research, and other sectors have need foraccurate display of roads and other terrain information in areas where there are ongoing operations orlocations of interest. Hence, road extraction that is significantly more automated than the employment ofcostly and scarce human resources has become a challenging technical issue for the geospatialcommunity. An automatic road extraction based on Extended Kalman Filtering (EKF and variablestructured multiple model particle filter (VS-MMPF from satellite images is addressed. EKF traces themedian axis of a single road segment while VS-MMPF traces all road branches initializing at theintersection. In case of Local Linearization Particle filter (LLPF, a large number of particles are usedand therefore high computational expense is usually required in order to attain certain accuracy androbustness. The basic idea is to reduce the whole sampling space of the multiple model system to the modesubspace by marginalization over the target subspace and choose better importance function for modestate sampling. The core of the system is based on profile matching. During the estimation, new referenceprofiles were generated and stored in the road template memory for future correlation analysis, thuscovering the space of road profiles. .

  19. Retreat of glaciers on Puncak Jaya, Irian Jaya, determined from 2000 and 2002 IKONOS satellite images (United States)

    Klein, Andrew G.; Kincaid, Joni L.

    Puncak Jaya, Irian Jaya, Indonesia, contains the only remaining tropical glaciers in East Asia. The extent of the ice masses on Puncak Jaya has been mapped from high-resolution IKONOS satellite images acquired on 8 June 2000 and 11 June 2002. Exclusive of Southwall Hanging Glacier, the ice extent on Puncak Jaya was 2.326 km2 and 2.152 km2 in 2000 and 2002, respectively. From 2000 to 2002, the Puncak Jaya glaciers lost a surface area of 0.174 km2 or 7.48% of their 2000 ice extent. Comparison of the IKONOS-based glacier extents with previous glacier extents demonstrates a continuing reduction of ice area on Puncak Jaya. By 2000, ice extent on Puncak Jaya had reduced by 88% of its maximum neoglacial extent. Between 1992 and 2000 Meren Glacier disappeared entirely. All remaining ice masses on Puncak Jaya continue their retreat from their neoglacial maxima. Comparison of 2000/2002 ice extents with previous extents suggests that these glaciers have not experienced accelerating rates of retreat during the last half of the 20th century. If the recession rates observed from 2000 to 2002 continue, the remaining ice masses on Puncak Jaya will melt within 50 years.

  20. Repeat optical satellite images reveal widespread and long term decrease in land-terminating glacier speeds

    Directory of Open Access Journals (Sweden)

    T. Heid


    Full Text Available By matching of repeat optical satellite images it is now possible to investigate glacier dynamics within large regions of the world and also between regions to improve knowledge about glacier dynamics in space and time. In this study we investigate whether the negative glacier mass balance seen over large parts of the world has caused the glaciers to change their speeds. The studied regions are Pamir, Caucasus, Penny Ice Cap, Alaska Range and Patagonia. In addition we derive speed changes for Karakoram, a region assumed to have positive mass balance and that contains many surge-type glaciers. We find that the mapped glaciers in the five regions with negative mass balance have over the last decades decreased their velocity at an average rate per decade of: 43 % in the Pamir, 8 % in the Caucasus, 25 % on Penny Ice Cap, 11 % in the Alaska Range and 20 % in Patagonia. Glaciers in Karakoram have generally increased their speeds, but surging glaciers and glaciers with flow instabilities are most prominent in this area. Therefore the calculated average speed change is not representative for this area.


    Directory of Open Access Journals (Sweden)

    G. Villa


    Full Text Available Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites pose big interoperability problems, as for example: non-alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression-decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in “Big Data” environments. Most of them can be avoided, or at least greatly reduced, with the use of a common “nested grid” for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. “Nested grids” are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A “nested grid” must be complemented by an appropriate “tiling schema”, ideally based on the “quad-tree” concept. In the last years a “de facto standard” grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its “WMTS Simple Profile” standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.

  2. Exploring image data assimilation in the prospect of high-resolution satellite oceanic observations (United States)

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


    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

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


    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.

  4. A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing

    Directory of Open Access Journals (Sweden)

    Thomas Udelhoven


    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.

  5. A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing. (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


    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.

  6. Relasphone—Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping

    Directory of Open Access Journals (Sweden)

    Matthieu Molinier


    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.

  7. Satellite Images Analysis of Temporal Change (1979-2000) of the Mangrove Covertures that Surround the Mandinga Coastal Lagoon, Mexico. (United States)

    Aldeco-Ramírez, J.; Cervantes-Candelas, A.


    Knowledge about the historical condition of the resources and the risk of natural hazards is an urgent necessity in developing countries. Satellite images analysis was applied in this study in order to evaluate coverture changes between 1979 and 2000. Mangroves cover large areas of coastal lagoon shoreline in the tropics and subtropics where they are important components in the productivity and integrity of their ecosystems. Visual and digital analysis of satellite images have been applied since the seventies when the first Land sat satellite was put in orbit. The digital analysis technique is mainly based on the reflectance or spectral response of the different objects laid on the earth surface as captured by the satellite. The results are useful for the environmental assessment of natural resources as forest and crops, and the quantification of hazards as fires, plagues, deforestation and urban expansion. This research surveys satellite images from the Mandinga Lagoon System, a coastal lagoon located to the south of the main port of Veracruz (19.1N, 96.1W), during three periods: 1989 1999 and 2000. The mangrove foliar cover was analyzed throughout the time. The reflectance signal of the mangrove that encircles the lagoon was taken as a base line for reference. The normalized difference vegetation index (NDVI) was computed in order to classify the vegetal coverage along the time. From our analysis we obtained that from 1979 to 1990 and from 1990 to 2000 areas of 122 hectares (approx. 305 acres) and 202 hectares (approx. 505 acres) were lost, respectively. The rates of mangrove trimming of 11.1 and 20.2 hectares yr-1 are high compared with other coastal lagoons of Mexico. The main causes of this deforestation are also discussed along with other factors as, the change of use of land and the fishery declination.

  8. Stereoscopic observations from meteorological satellites (United States)

    Hasler, A. F.; Mack, R.; Negri, A.

    The capability of making stereoscopic observations of clouds from meteorological satellites is a new basic analysis tool with a broad spectrum of applications. Stereoscopic observations from satellites were first made using the early vidicon tube weather satellites (e.g., Ondrejka and Conover [1]). However, the only high quality meteorological stereoscopy from low orbit has been done from Apollo and Skylab, (e.g., Shenk et al. [2] and Black [3], [4]). Stereoscopy from geosynchronous satellites was proposed by Shenk [5] and Bristor and Pichel [6] in 1974 which allowed Minzner et al. [7] to demonstrate the first quantitative cloud height analysis. In 1978 Bryson [8] and desJardins [9] independently developed digital processing techniques to remap stereo images which made possible precision height measurement and spectacular display of stereograms (Hasler et al. [10], and Hasler [11]). In 1980 the Japanese Geosynchronous Satellite (GMS) and the U.S. GOES-West satellite were synchronized to obtain stereo over the central Pacific as described by Fujita and Dodge [12] and in this paper. Recently the authors have remapped images from a Low Earth Orbiter (LEO) to the coordinate system of a Geosynchronous Earth Orbiter (GEO) and obtained stereoscopic cloud height measurements which promise to have quality comparable to previous all GEO stereo. It has also been determined that the north-south imaging scan rate of some GEOs can be slowed or reversed. Therefore the feasibility of obtaining stereoscopic observations world wide from combinations of operational GEO and LEO satellites has been demonstrated. Stereoscopy from satellites has many advantages over infrared techniques for the observation of cloud structure because it depends only on basic geometric relationships. Digital remapping of GEO and LEO satellite images is imperative for precision stereo height measurement and high quality displays because of the curvature of the earth and the large angular separation of the

  9. A DHIP Algorithm for SAR Satellite Imaging Planning%SAR卫星成像任务规划的DHIP方法

    Institute of Scientific and Technical Information of China (English)

    朱小满; 王钧; 李军; 景宁


    The emergence of earth observing satellite with Synthetic Aperture Radar (SAR) onboard provides a significant instrument to obtain geo-space information. This paper studies rightly on the SAR satellite imaging planning problem. Firstly, the general imaging process of SAR satellite is described to illustrate that the methods pertinent to optical satellite imaging planning are no longer suitable for the problem of a SAR satellite imaging planning. Secondly, the main influential constraints of SAR satellite are induced. Based on that, an approach called DHIP (Double Hierarchy Insert Planning) is proposed and described detailedly. The main idea of this method is to form an optimized scheme by tentatively inserting every candidate imaging request through two hierarchies, which are the hierarchy of SAR opening and closing, and that of photographing, by a checking while constructing method. The final experimental results show that the DHIP algorithm works fast and is able to get a satisfying scheme under general circumstances.%合成孔径雷达(SAR)卫星的出现为获取地球空间信息提供了重要手段,本文研究的即是SAR卫星成像任务规划问题.首先描述了SAR成像卫星的一般工作流程,说明针对可见光卫星进行成像任务规划的方法不再适用于SAR成像卫星任务规划;然后归纳了影响SAR卫星成像的主要约束.在此基础上,提出了双层插入规划(DHIP)方法,该方法将待规划任务在星载SAR开关机信息元组级和成像信息元组级两个层级上逐次进行试探性插入,采用边构造边检测的方法获得该问题的优化解.实验结果表明,该方法计算速度快,可以有效解决SAR卫星成像任务规划问题.

  10. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    KAUST Repository

    Wang, Teng


    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.

  11. A methodology for near real-time change detection between Unmanned Aerial Vehicle and wide area satellite images (United States)

    Fytsilis, Anastasios L.; Prokos, Anthony; Koutroumbas, Konstantinos D.; Michail, Dimitrios; Kontoes, Charalambos C.


    In this paper a novel integrated hybrid methodology for unsupervised change detection between Unmanned Aerial Vehicle (UAV) and satellite images, which can be utilized in various fields like security applications (e.g. border surveillance) and damage assessment, is proposed. This is a challenging problem mainly due to the difference in geographic coverage and the spatial resolution of the two images, as well as to the acquisition modes which lead to misregistration errors. The methodology consists of the following steps: (a) pre-processing, where the part of the satellite image that corresponds to the UAV image is determined and the UAV image is ortho-rectified using information provided by a Digital Terrain Model, (b) the detection of potential changes, which is based exclusively on intensity and image gradient information, (c) the generation of the region map, where homogeneous regions are produced by the previous potential changes via a seeded region growing algorithm and placed on the region map, and (d) the evaluation of the above regions, in order to characterize them as true changes or not. The methodology has been applied on demanding real datasets with very encouraging results. Finally, its robustness to the misregistration errors is assessed via extensive experimentation.

  12. An Atlas of Original and Mercator-Transformed Satellite-Data Images of the Alboran Sea, August-October 1983, (United States)


    identifiable points on the coast. This was done on an HP-1000 computer using a "Navigation Subsystem" software and a library of "Ground Control Points" (GCP...European, Middle Eastern and N. African coastal ground control points for mapping satellite images, SACLANTCEN SM-170. La Spezia, Italy, SACLANT ASW...DETERMINATE L’UMIDITA’ RELATIVA E LA TEMPERATURA DI RUGIADA 0 DI BRINA MEDIANTE LO PSICROMETRO. AERONAUTICA MILITARE Italiana. Ispettorato delle

  13. Prospects of using the k-NN method of classification of satellite images for the forest inventory in Ukraine


    V. Myroniuk


    This paper deals with modern experience of statistical inventory of forests using ground-based inventory and remote sensing data (RSD). A detailed analysis of the k-NN method of classification of satellite images is given and features of its applying for thematic mapping of forest fund under the statistical forest inventory defined. The algorithm for calculating the stock of plantings for the statistical software with R open source is shown on the example of local research material.

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

    Energy Technology Data Exchange (ETDEWEB)

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


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



    Cooper, Nicholas J.; Renner, Stéfan; Murray, Carl D.; Evans, Michael W.


    International audience; We present numerically derived orbits and mass estimates for the inner Saturnian satellites, Atlas, Prometheus, Pandora, Janus, and Epimetheus from a fit to 2580 new Cassini Imaging Science Subsystem astrometric observations spanning 2004 February to 2013 August. The observations are provided as machine-readable and Virtual Observatory tables. We estimate GM Atlas = (0.384 ± 0.001) × 10 −3 km 3 s −2 , a value 13% smaller than the previously published estimate but with ...

  16. A national system for monitoring the population of agricultural pests using an integrated approach of remote sensing data from in situ automated traps and satellite images (United States)

    Diofantos, Hadjimitsis G.; Panayiotis, Philimis; Elias, Psimolophitis; Georgiou, George K.; Kyriacos, Themistocleous


    A national system for monitoring the population increase of agricultural pest "Lobesia Botrana" (vine moth/fly that attacks grapes) in Cyprus has been developed. The system comprises of automated delta traps with GPS that use wireless(Wi-Fi) camera, automated image analysis for identification of the specific fly species, Wi-Fi technology for transferring the data using mobile telephony network to a central station for result presentation and analysis. A GIS database was developed and included details of the pilot vineyards, environmental conditions and daily data of the number of captured flies from each automated trap. The results were compared with MODIS and LANDSAT satellite thermal images since the appearance of the vine fly is greatly dependent on the microclimate temperatures (degree days). Results showed that satellite data can estimate accurately the appearance of the vine fly. The proposed system can be an important tool for the improvement of a national Integrated Pest Management (IPM) system and it can also be used for monitoring other agricultural pests and insects.

  17. Imager-to-Radiometer In-flight Cross Calibration: RSP Radiometric Comparison with Airborne and Satellite Sensors (United States)

    McCorkel, Joel; Cairns, Brian; Wasilewski, Andrzej


    This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

  18. Dam sediment tracking using spectrometry and Landsat 8 satellite image, Taleghan Basin, Iran. (United States)

    Afshar, Sirous; Shamsai, Abolfazl; Saghafian, Bahram


    Sedimentation in reservoirs, in addition to reducing water storage capacity, causes serious environmental impacts including intensification of river erosion. Detection of sediment origins plays a determining role in control and prevention of sedimentation. Nowadays, with the help of studies on sedimentation and erosion, sediment origins can be detected with high accuracy. This research integrated geographic information system (GIS) and remote sensing (RS) techniques to detect the primary source of sediment to Taleghan Dam in northern Iran. After collecting samples of sediment from the basin outlet, they were divided into two parts. One part was sent to the Mineralogy Laboratory in order to determine the percentage of each mineral in the samples using X-ray. A few were sent to the Spectroscopy Laboratory to determine their spectral signature using the spectrometer. The laboratory test results determined the wavelength of the minerals. In the next step, those spots on the satellite image whose spectral reflectance fell within the spectral signature of the minerals were detected and enhanced by mixture-tuned matched filtering (MTMF) method. These spots were overlapped with the map of geological formations. Accordingly, the origin of the minerals was detected. The greatest proportion of trace minerals was found in sample 4 including 6% of Illite trace mineral, while sample 2 contains only 2% of trace minerals. Accordingly, the origin of the minerals was detected. The obtained results revealed that mudstone, red siltstone, and conglomerate formations, Karaj formation in section Poldokhtar, acidic tuffs, alcanic lavas of Karaj Formation, mudstone and gypsum of upper red formation, and Cambrian dolomites were recognized as the most possible origins of the dam sediments. These formations are vulnerable to erosion and should be conserved so as to substantially prevent the volume of sedimentation in the reservoir.

  19. An objective regional cloud mask algorithm for GOES infrared imager with regime-dependent thresholds for direct radiance assimilation (United States)

    Da, Cheng

    A local, regime-dependent cloud mask (CM) algorithm is developed for isolating cloud-free pixels from cloudy pixels for Geostationary Operational Environmental Satellite (GOES) imager radiance assimilation using mesoscale forecast models. In this CM algorithm, thresholds for six different CM tests are determined by a one-dimensional optimization approach based on probability distribution functions of the nearby cloudy and clear-sky pixels within a 10ox10o box centered at a target pixel. It is shown that the optimized thresholds over land are in general larger and display more spatial variations than over ocean. The performance of the proposed CM algorithm is compared with Moderate Resolution Imaging Spectroradiometer (MODIS) CM for a one-week period from 19 to 23 May 2008. Based on MODIS CM results, the average Probability of Correct Typing (PCT) reaches 92.94% and 91.50% over land and ocean, respectively.

  20. Classification of textures in satellite image with Gabor filters and a multi layer perceptron with back propagation algorithm obtaining high accuracy

    Directory of Open Access Journals (Sweden)

    Adriano Beluco, Paulo M. Engel, Alexandre Beluco


    Full Text Available The classification of images, in many cases, is applied to identify an alphanumeric string, a facial expression or any other characteristic. In the case of satellite images is necessary to classify all the pixels of the image. This article describes a supervised classification method for remote sensing images that integrates the importance of attributes in selecting features with the efficiency of artificial neural networks in the classification process, resulting in high accuracy for real images. The method consists of a texture segmentation based on Gabor filtering followed by an image classification itself with an application of a multi layer artificial neural network with a back propagation algorithm. The method was first applied to a synthetic image, like training, and then applied to a satellite image. Some results of experiments are presented in detail and discussed. The application of the method to the synthetic image resulted in the identification of 89.05% of the pixels of the image, while applying to the satellite image resulted in the identification of 85.15% of the pixels. The result for the satellite image can be considered a result of high accuracy.

  1. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra satellite (GDS version 1) (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...

  2. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite (GDS version 1) (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...

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

    Institute of Scientific and Technical Information of China (English)

    CHENGChengqi; LiBin; MATing


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

  4. Advanced Reservoir Imaging Using Frequency-Dependent Seismic Attributes

    Energy Technology Data Exchange (ETDEWEB)

    Fred Hilterman; Tad Patzek; Gennady Goloshubin; Dmitriy Silin; Charlotte Sullivan; Valeri Korneev


    Our report concerning advanced imaging and interpretation technology includes the development of theory, the implementation of laboratory experiments and the verification of results using field data. We investigated a reflectivity model for porous fluid-saturated reservoirs and demonstrated that the frequency-dependent component of the reflection coefficient is asymptotically proportional to the reservoir fluid mobility. We also analyzed seismic data using different azimuths and offsets over physical models of fractures filled with air and water. By comparing our physical model synthetics to numerical data we have identified several diagnostic indicators for quantifying the fractures. Finally, we developed reflectivity transforms for predicting pore fluid and lithology using rock-property statistics from 500 reservoirs in both the shelf and deep-water Gulf of Mexico. With these transforms and seismic AVO gathers across the prospect and its down-dip water-equivalent reservoir, fluid saturation can be estimated without a calibration well that ties the seismic. Our research provides the important additional mechanisms to recognize, delineate, and validate new hydrocarbon reserves and assist in the development of producing fields.

  5. Design of a nano-satellite demonstrator of an infrared imaging space interferometer: the HyperCube (United States)

    Dohlen, Kjetil; Vives, Sébastien; Rakotonimbahy, Eddy; Sarkar, Tanmoy; Tasnim Ava, Tanzila; Baccichet, Nicola; Savini, Giorgio; Swinyard, Bruce


    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

  6. The influence of topographic structures on night-time surface temperatures: Evaluation of a satellite thermal image of the upper Rhine plain and the surrounding highlands. [Germany and Switzerland (United States)

    Gossmann, H. (Principal Investigator)


    The author has identified the following significant results. Satellite data supplied the same information as aerial IR registrations with corresponding averaging for all studies requiring a survey of the thermal pattern within an area measuring 10 km x 10 km ore more, provided that sufficiently precise control points could be established for the purpose of geometric rectification in the surroundings of the area observed. Satellite thermal data are more comprehensive than aircraft data for studies on a regional, rather than a local scale, since airborne images often obscure the basic correlation in thermal patterns because of a variety of irrelevant topographical detail. The satellite data demonstrate the dependence of surface temperature on relief more clearly than comparable airborne imagery.

  7. Georectification and snow classification of webcam images: potential for complementing satellite-derrived snow maps over Switzerland (United States)

    Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan


    The spatial and temporal variability of snow cover has a significant impact on climate and environment and is of great socio-economic importance for the European Alps. Satellite remote sensing data is widely used to study snow cover variability and can provide spatially comprehensive information on snow cover extent. However, cloud cover strongly impedes the surface view and hence limits the number of useful snow observations. Outdoor webcam images not only offer unique potential for complementing satellite-derived snow retrieval under cloudy conditions but could also serve as a reference for improved validation of satellite-based approaches. Thousands of webcams are currently connected to the Internet and deliver freely available images with high temporal and spatial resolutions. To exploit the untapped potential of these webcams, a semi-automatic procedure was developed to generate snow cover maps based on webcam images. We used daily webcam images of the Swiss alpine region to apply, improve, and extend existing approaches dealing with the positioning of photographs within a terrain model, appropriate georectification, and the automatic snow classification of such photographs. In this presentation, we provide an overview of the implemented procedure and demonstrate how our registration approach automatically resolves the orientation of a webcam by using a high-resolution digital elevation model and the webcam's position. This allows snow-classified pixels of webcam images to be related to their real-world coordinates. We present several examples of resulting snow cover maps, which have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or not visible from webcams' positions. The procedure is expected to work under almost any weather condition and demonstrates the feasibility of using webcams for the retrieval of high-resolution snow cover information.

  8. Computing procedure of spatial geo-referencing of satellite image; Un procedimiento simple de geo-referenciacion de imagenes de satelite

    Energy Technology Data Exchange (ETDEWEB)

    Santos, J.; Vazquez, M.; Fernandes, F.; Prado, T.; Castro, R.


    In this paper a computing procedure of spatial geo-referencing is described that, by means of the terrestrial spatial geometry, permits to obtain the Latitude and Longitude that corresponds to a given pixel of a satellite image, the pixel being defined by a pair Line- Pixel. The procedure also permits to compute the other way round. This procedure is more clear and simple than those proposed by Eumetsat and Goes and can be applied to any satellite image. (Author)

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

    African Journals Online (AJOL)

    Ivan Henrico

    a new and improved dimension to the pointing accuracies of current and future .... It is stated in the TerraSAR-X GCP-3 Coordinate Specification and Accuracy .... parameters for camera timing, alignment, focal plane and satellites altitude.

  10. Northeast Puerto Rico and Culebra Island World View 2 Satellite Mosaic - NOAA TIFF Image (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...

  11. 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 (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..

  12. Spatial resolution is dependent on image content for SPECT with iterative reconstruction incorporating distance dependent resolution (DDR) correction. (United States)

    Badger, Daniel; Barnden, Leighton


    The aim of this study is to determine the dependence of single photon emission computed tomography (SPECT) spatial resolution on the content of images for iterative reconstruction with distance dependent resolution (DDR) correction. An experiment was performed using a perturbation technique to measure change in resolution of line sources in simple and complex images with iterative reconstruction with increasing iteration. Projections of the line sources were reconstructed alone and again after the addition of projections of a uniform flood or a complex phantom. An alternative experiment used images of a realistic brain phantom and evaluated an effective spatial resolution by matching the images to the digital version of the phantom convolved with 3D Gaussian kernels. The experiments were performed using ordered subset expectation maximisation iterative reconstruction with and without the use of DDR correction. The results show a significant difference in reconstructed resolution between images of line sources depending on the content of the added image. The full width at half maximum of images of a line source reconstructed using DDR correction increased by 20-30 % when the added image was complex. Without DDR this difference was much smaller and disappeared with increasing iteration. Reported SPECT resolution should be taken as indicative only with regard to clinical imaging if the measurement is made using a point or line source alone and an iterative reconstruction algorithm is used.


    Institute of Scientific and Technical Information of China (English)


    An improved topographic database for King George Island,one of the most frequently visited regions in Antarctica,is presented.A first step consisted in combining data from differential GPS surveys gained during the austral summers 1997~1998 and 1999~2000,with the current coastline from a SPOT satellite image mosaic,topographic information from existing maps and from the Antarctic Digital Database.From this data sets,a digital terrain model (DTM) was generated using Arc/Info GIS.In a second step,a satellite image map at the scale 1∶100 000 was assembled from contour lines derived from the DTM and the satellite mosaic.A lack of accurate topographic information in the eastern part of the island was identified.Additional topographic surveying or SAR interferometry should be used to improve the data quality in that area.The GIS integrated database will be indispensable for glaciological and climatological studies and administrative and scientific purposes.In future,the application of GIS techniques will be mandatory for environmental impact studies and environmental monitoring as well as for management plans on King George Island.

  14. Temperature dependence of the Kondo resonance and its satellites in CeCu_2Si_2


    Reinert, F.; Ehm, D.; Schmidt, S; Nicolay, G.; H"ufner, S.; Kroha, J.; Trovarelli, O.; Geibel, C.


    We present high-resolution photoemission spectroscopy studies on the Kondo resonance of the strongly-correlated Ce system CeCu$_2$Si$_2$. Exploiting the thermal broadening of the Fermi edge we analyze position, spectral weight, and temperature dependence of the low-energy 4f spectral features, whose major weight lies above the Fermi level $E_F$. We also present theoretical predictions based on the single-impurity Anderson model using an extended non-crossing approximation (NCA), including all...

  15. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods (United States)

    Osipov, Gennady


    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

  16. Perceived Blur in Naturally-Contoured Images Depends on Phase

    Directory of Open Access Journals (Sweden)

    Stephanie Murray


    Full Text Available Perceived blur is an important measure of image quality and clinical visual function. The magnitude of image blur varies across space and time under natural viewing conditions owing to changes in pupil size and accommodation. Blur is frequently studied in the laboratory with a variety of digital filters, without comparing how the choice of filter affects blur perception. We examine the perception of image blur in synthetic images composed of contours whose orientation and curvature spatial properties matched those of natural images but whose blur could be directly controlled. The images were blurred by manipulating the slope of the amplitude spectrum, Gaussian low-pass filtering or filtering with a Sinc function, which, unlike slope or Gaussian filtering, introduces periodic phase reversals similar to those in optically blurred images. For slope-filtered images, blur discrimination thresholds for over-sharpened images were extremely high and perceived blur could not be matched with either Gaussian or Sinc filtered images, suggesting that directly manipulating image slope does not simulate the perception of blur. For Gaussian and Sinc blurred images, blur discrimination thresholds were dipper-shaped and were well-fit with a simple variance discrimination model and with a contrast detection threshold model, but the latter required different contrast sensitivity functions for different types of blur. Blur matches between Gaussian and Sinc blurred images were used to test several models of blur perception and were in good agreement with models based on luminance slope, but not with spatial frequency based models. Collectively, these results show that the relative phases of image components, in addition to their relative amplitudes, determines perceived blur.

  17. Relative navigation for autonomous formation flying satellites using the state-dependent Riccati equation filter (United States)

    Park, Han-Earl; Kim, Young-Rok


    A relative navigation method for autonomous formation flying using the state-dependent Riccati equation filter (SDREF) is presented. In the SDREF, nonlinear relative dynamics, including J2 perturbation, are parameterized into a state-dependent coefficient (SDC) form without any loss of nonlinearity. The relative navigation algorithm is established based on the carrier-phase differential GPS (CDGPS) and single-frequency GPS data, in which the SDREF is used as a nonlinear estimator. To evaluate the SDREF performance, two different extended Kalman filters (EKFR1 and EKFR2) are introduced. The dynamic models of all the filters are based on relative motion including J2 perturbation. However, the SDREF and the EKFR1 use linear state propagation, whereas EKFR2 employs nonlinear state propagation. The navigation simulation is performed for each filter using live GPS signals simulated by a GPS signal generator, and the result is analyzed in terms of estimation accuracy and computational load. As a result, the SDREF provides a relative navigation solution with 3-D RMS accuracies of 6.0 mm and 0.153 mm/s for position and velocity, respectively, for a separation of 50 km with a computation time of approximately 34 s. The simulation results demonstrate that the SDREF estimates the relative states as rapidly as the EKFR1 and as accurately as the EKFR2, which means that the developed SDREF combines the strong points of EKFR1 and EKFR2 and overcomes their disadvantages.

  18. A new tool for supervised classification of satellite images available on web servers: Google Maps as a case study (United States)

    García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun


    This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.

  19. Study of time-lapse processing for dynamic hydrologic conditions. [electronic satellite image analysis console for Earth Resources Technology Satellites imagery (United States)

    Serebreny, S. M.; Evans, W. E.; Wiegman, E. J.


    The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies.

  20. Evaluation of the Seasonal and Spatial Lake Level Change Using by Worldview-2 Satellite Images in the Egirdir Lake (Turkey) (United States)

    Sener, Erhan; Sener, Sehnaz; Uysal, Rahmi; Bulut, Cafer


    Eğirdir Lake is located in the Lake District, it is fourth largest lake and the second largest freshwater lake in Turkey. The lake is still drinking water sources in many residential areas. In this study two Worldview-2 satellite imagery which is high resolution 8-band has been used. The imagery covering the whole lake and belongs to date 10.05.2010 and 24.10.2010. Using Coastal Band (1.Band), Blue (2.Band), Green (3.Band), Yellow (4.Band) and Red (5.Band) on that satellite, seasonal water level in the rainy and dry periods in the selected pilot areas of the Eğirdir Lake has been aimed to determine. In this context, firstly Atmospheric Correction is applied to reduce their atmospheric effects. In order to mask of surface water The Normalized Water Different Index (NWDI) has been applied. Then seasonally varying fields has been identified with change analysis applied to two different image.

  1. Temperature dependence of the Kondo resonance and its satellites in CeCu2Si2. (United States)

    Reinert, F; Ehm, D; Schmidt, S; Nicolay, G; Hüfner, S; Kroha, J; Trovarelli, O; Geibel, C


    We present high-resolution photoemission spectroscopy studies on the Kondo resonance of the strongly correlated Ce system CeCu2Si2. By exploiting the thermal broadening of the Fermi edge we analyze position, spectral weight, and temperature dependence of the low-energy 4f spectral features, whose major weight lies above the Fermi level E(F). We also present theoretical predictions based on the single-impurity Anderson model using an extended noncrossing approximation, including all spin-orbit and crystal field splittings of the 4f states. The excellent agreement between theory and experiment provides strong evidence that the spectral properties of CeCu2Si2 can be described by single-impurity Kondo physics down to T approximately 5 K.

  2. Depth-dependent dispersion compensation for full-depth OCT image. (United States)

    Pan, Liuhua; Wang, Xiangzhao; Li, Zhongliang; Zhang, Xiangyang; Bu, Yang; Nan, Nan; Chen, Yan; Wang, Xuan


    A depth-dependent dispersion compensation algorithm for enhancing the image quality of the Fourier-domain optical coherence tomography (OCT) is presented. The dispersion related with depth in the sample is considered. Using the iterative method, an analytical formula for compensating the depth-dependent dispersion in the sample is obtained. We apply depth-dependent dispersion compensation algorithm to process the phantom images and in vivo images. Using sharpness metric based on variation coefficient to compare the results processed with different dispersion compensation algorithms, we find that the depth-dependent dispersion compensation algorithm can improve image quality at full depth.

  3. Some Methodological Aspects Concerning the Use of Satellite Images and Maps in the Physico-Geographical Regional Determination of the Romania Territory

    Directory of Open Access Journals (Sweden)



    Full Text Available This paper presents some methodological aspects concerning the use of satellite images and maps in the physico-geographical region determination of Romania's territory, as well as some results that can be obtained using this method. In order to determine the physico-geographical units and sub-units using satellite maps (Bucharest page, 1:1.500.000 and satellite images (Landsat, IRS we have analyzed, from the geographical point of view, some samples of such documents. The resulting maps were compared with the already existing physico-geographical region determination maps. Our results show that the method under consideration has both advantages and disadvantages. One conclusion is sure: satellite images and maps can be used for this purpose together with traditional maps.

  4. Digital mapping of loess in Northwest Germany based on satellite images (United States)

    Wagner, Bianca


    Loess maps of various scales are important input data for advanced investigations of spatial loess properties such as variation in grain size, thickness and facies or study of loess provenance. Many representations of loess distribution in Northwest Germany are based on geological maps. Mostly these maps were created at the beginning of the last century. During this time especially thin loess covers were not incorporated in favour of underlying hard rocks or other Quaternary deposits. Due to the change in mapping policy at the end of the last century much more of the unconsolidated rocks, particularly with regard to loess, were displayed on the revised or updated maps. In this study the analysis of optical remote sensing data, ranging from visible light to the infrared, was tested to create a more realistic map of the loess distribution in Northwest Germany. The investigation area includes the loess along the northern loess boundary between Helmstedt and Minden and extends to Kassel and Goettingen in the South. Here, in southern Lower Saxony, northern Hesse and eastern North Rhine-Westphalia, loess and loess derivates are widely distributed apart from river beds, valley flanks, steep slopes and higher mountain ranges. The thickness of the loess cover, that is of Weichselian, sporadic of Saalian or Elsterian age, varies between few centimetres and about 20 m. The hard rocks of the study area were influenced by tectonic and halokinetic processes resulting in a complex and small-scale pattern of folds, depressions, horsts and grabens. Satellite images of the Landsat TM and ETM+ sensors, recorded between 1985 and 2008, were used for this study. After radiometric calibration and atmospheric and geometric correction of every dataset, coniferous forest, water and areas of high urbanization were masked. Then a synthetic file was made up of all remaining pixels, preferring the pixel, displaying the purest soil or bare rock. Various digital mapping techniques e.g. band

  5. Satellite images and geodetic measurements applied to the monitoring of the Horcones Inferior Glacier, Mendoza, Argentina

    Directory of Open Access Journals (Sweden)

    M. Gabriela Lenzano


    Full Text Available This work analyzes the monitoring of the covered and regenerated Horcones Inferior Glacier (HIG since the implementation of a semi-permanent GNSS station (HISS on its surface during the summer seasons of 2009 and 2010. The glacier is located at 32° 41's and 69° 57'w, at the foot of the south wall of Mt. Aconcagua, Aconcagua Provincial Park, Mendoza, Argentina. The average velocities obtained from the HISS station were of 1.3 cm/d and 3.5 cm/d during the 2009 and 2010 seasons respectively. The data procured using satellite images during the last surges (1984 and 2003 gave average velocities for the HIG front of 8.7 m/d for the first event and 11.5 m/d for the second one. These results allowed getting accurate and reliable movement tendency at the terminal part of the HIG during the 1984-2010 period.El presente trabajo realiza el monitoreo del glaciar Horcones Inferior, cubierto y regenerado a partir de la implementación de una estación GNSS semi-permanente (HISS, instalada sobre su superficie durante las temporadas de verano de 2009 y 2010 respectivamente. El glaciar se encuentra ubicado a los 32° 41's y 69° 57'w, al pie de la pared sur del C° Aconcagua, en el Parque Provincial Aconcagua, Mendoza, Argentina. La estación HISS registró valores de velocidades medias de 1.3 cm/d y 3.5 cm/d durante las temporadas de 2009 y 2010. Se utilizaron imágenes satelitales para el seguimiento del frente del glaciar durante los últimos surges (1984 y 2003, cuyas velocidades medias fueron de 8.7 m/d para el primero y de 11.5 m/d para el segundo evento. Estos resultados permitieron obtener de manera precisa y confiable la tendencia de movimiento de la parte terminal del GHI durante el periodo 1984-2010.

  6. Monitoring urban impervious surface area change using China-Brazil Earth Resources Satellites and HJ-1 remote sensing images (United States)

    Du, Peijun; Xia, Junshi; Feng, Li


    Impervious surface area (ISA) plays an important role in monitoring urbanization and related environmental changes, and has become a hotspot in urban and environmental studies. Xuzhou City, located in northwest Jiangsu Province, China, is chosen as the study area, and two scenes of China-Brazil Earth Resources Satellites images and one scene of HJ-1 image are employed to estimate ISA percentage and analyze the change trend from 2001 to 2009. Using a linear spectral mixture model (LSMM) and nonlinear backpropagation neural network (BPNN) method, all pixels are decomposed to derive four fraction images representing the abundance of four endmembers: vegetation, high-albedo objects, low-albedo objects, and soil. The ISA percentage is then derived by the combination of high- and low-albedo fraction images after removing the influence of water. Some high spatial resolution images are selected to validate the ISA estimation results, and the experimental results indicate that the accuracy of BPNN is higher than LSMM. By comparing the urban ISA abundances derived by BPNN from three dates, it is found that the ISA of Xuzhou City has increased rapidly from 2001 to 2009, especially in the northeast and southeast regions, corresponding to the urban planning scheme and fast urbanization. Compared to other medium remote sensing images, the revisit cycle of HJ-1 multispectral image is only two days, demonstrating the potential of such data for ISA extraction in urbanization, disaster, and other related applications.

  7. Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites. (United States)

    Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed


    This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring.

  8. Satellite image processing for precision agriculture and agroindustry using convolutional neural network and genetic algorithm (United States)

    Firdaus; Arkeman, Y.; Buono, A.; Hermadi, I.


    Translating satellite imagery to a useful data for decision making during this time are usually done manually by human. In this research, we are going to translate satellite imagery by using artificial intelligence method specifically using convolutional neural network and genetic algorithm to become a useful data for decision making, especially for precision agriculture and agroindustry. In this research, we are focused on how to made a sustainable land use planning with 3 objectives. The first is maximizing economic factor. Second is minimizing CO2 emission and the last is minimizing land degradation. Results show that by using artificial intelligence method, can produced a good pareto optimum solutions in a short time.

  9. Use of satellite images in snow water equivalent (SWE) estimation in the Upper Vistula drainage basin in southern Poland (United States)

    Kasina, M.; Chamerlinska, A.; Lasek, J.; Przeniczny, P.


    Snow-water equivalent (SWE) and snow depth are the two most important parameters used in hydrological forecasting offices to estimate the amount of water stored in the form of snow. These two parameters are essential during snowmelt periods when rapid snowmelt (often combined with rainfall) causes slow-onset floods. In this case, the water equivalent can be used as an indicator of the amount of water expected in runoff. So far the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB) produces this estimate based only on SWE and snow depth data obtained from meteorological stations at five day intervals. The two measurements are performed at shorter intervals either when heavy snowfall occurs or when the mean daily air temperature exceeds 0οC. The main aim of this project is to improve the existing method of snow water equivalent estimation by using satellite-derived data. Snow-water equivalent data and the extent of snow cover were derived from satellite products prepared within the H-SAF Project, which is the EUMETSAT Network of Satellite Application Facility dedicated to support Operational Hydrology and Water Management. Both H10 - Snow mask by VIS/IR radiometry and H11 - Snow water equivalent by MW radiometry products are derived in a daily time step. It then becomes possible to compare and further assimilate ground-truth data. Other analyses included Bayesian Kriging spatial interpolation, which is suitable for non-stationary data. The method described in this paper - same as other methods based on satellite derived data - is weather dependent and it is limited to cloud-free periods. A comparison of results obtained using this method and results obtained using ground-based data calculations proved its applicability in lowland areas. In mountainous regions, where differences in SWE values strongly depend on elevation, the obtained SWE values were underestimated.

  10. Exploitation of amplitude and phase of satellite SAR images for landslide mapping: the case of Montescaglioso (South Italy) (United States)

    Raspini, Federico; Ciampalini, Andrea; Lombardi, Luca; Nocentini, Massimiliano; Gigli, Giovanni; Casagli, Nicola; Del Conte, Sara; Ferretti, Alessandro


    Pre- event and event landslide deformations have been detected and measured for the landslide that occurred on 3 December 2013 on the south-western slope of the Montescaglioso village (Basilicata Region, southern Italy). The event, triggered by prolonged rainfalls, created significant damage to buildings and local infrastructures. Ground displacements have been mapped through an integrated analysis based on a series of high resolution SAR (Synthetic Aperture Radar) images acquired by the Italian constellation of satellites COSMO-SkyMed. Analysis has been performed by exploiting both phase (through multi-image SAR interferometry) and amplitude information (through speckle tracking techniques) of the satellite images. SAR Interferometry, applied to images taken before the event, revealed a general pre-event movement, in the order of a few mm/yr, in the south-western slope of the Montescaglioso village. Highest pre-event velocities, ranging between 8 and 12 mm/yr, have been recorded in the sector of the slope where the first movement of the landslide took place. Speckle tracking, applied to images acquired before and after the event, allowed the retrieval of the 3D deformation field produced by the landslide. It also showed that ground displacements produced by the landslide have a dominant SSW component, with values exceeding 10 m for large sectors of the landslide area, with local peaks of 20 m in its central and deposit areas. Two minor landslides with a dominant SSE direction, which were detected in the upper parts of the slope, likely also occurred as secondary phenomena as consequence of the SSW movement of the main Montescaglioso landslide. This work demonstrates that this complementary approach, based on the synergistic exploitation of phase and amplitude SAR data, can become a powerful tool for landslide investigation, allowing the detection of slow, precursory deformation patterns as well the retrieval of full 3D surface displacement fields caused by large

  11. Methodology for the detection of land cover changes in time series of daily satellite images. Application to burned area detection

    Directory of Open Access Journals (Sweden)

    J.A. Moreno-Ruiz


    Full Text Available We have developed a methodology for detection of observable phenomena at pixel level over time series of daily satellite images, based on using a Bayesian classifier. This methodology has been applied successfully to detect burned areas in the North American boreal forests using the LTDR dataset. The LTDR dataset represents the longest time series of global daily satellite images with 0.05° (~5 km of spatial resolution. The proposed methodology has several stages: 1 pre-processing daily images to obtain composite images of n days; 2 building of space of statistical variables or attributes to consider; 3 designing an algorithm, by selecting and filtering the training cases; 4 obtaining probability maps related to the considered thematic classes; 5 post-processing to improve the results obtained by applying multiple techniques (filters, ranges, spatial coherence, etc.. The generated results are analyzed using accuracy metrics derived from the error matrix (commission and omission errors, percentage of estimation and using scattering plots against reference data (correlation coefficient and slope of the regression line. The quality of the results obtained improves, in terms of spatial and timing accuracy, to other burned area products that use images of higher spatial resolution (500 m and 1 km, but they are only available after year 2000 as MCD45A1 and BA GEOLAND-2: the total burned area estimation for the study region for the years 2001-2011 was 28.56 millions of ha according to reference data and 12.41, 138.43 and 19.41 millions of ha for the MCD45A1, BA GEOLAND-2 and BA-LTDR burned area products, respectively.

  12. Image Texture Dependence Upon Sensing and Calculation Parameters (United States)

    Rodionova, N. V.


    This paper analyzes various parameters influence on the textural properties of digital remote sensing images using the statistical method of texture description (grey-level co-occurrence matrix (GLCM)). The parameters may be grouped to external (primary) parameters determined by surface and sensor characteristics (radar frequency, polarization, speckle filtering, spatial and radiometric resolution of the sensor, multispectral (MS) band, etc.), and internal (secondary) parameters determined by the texture calculation algorithm.SAR, MS and panchromatic images are used for illustration.

  13. Quantifying dwarf satellites through gravitational imaging: the case of SDSSJ120602.09+514229.5

    NARCIS (Netherlands)

    Vegetti, Simona; Czoske, Oliver; Koopmans, Léon V. E.


    SDSSJ120602.09+514229.5 is a gravitational lens system formed by a group of galaxies at redshift zFG = 0.422 lensing a bright background galaxy at redshift zBG = 2.001. The main peculiarity of this system is the presence of a luminous satellite near the Einstein radius, which slightly deforms the gi

  14. Quantifying dwarf satellites through gravitational imaging : The case of SDSS J120602.09+514229.5

    NARCIS (Netherlands)

    Vegetti, Simona; Czoske, Oliver; Koopmans, Léon V. E.


    SDSS J120602.09+514229.5 is a gravitational lens system formed by a group of galaxies at redshift z(FG) = 0.422 lensing a bright background galaxy at redshift z(BG) = 2.001. The main peculiarity of this system is the presence of a luminous satellite near the Einstein radius, which slightly deforms t

  15. Near real-time disturbance detection using satellite image time series

    NARCIS (Netherlands)

    Verbesselt, J.P.; Zeileis, A.; Herold, M.


    Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and 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

  16. Comparison of data file and storage configurations for efficient temporal access of satellite image data

    CSIR Research Space (South Africa)

    Bachoo, A


    Full Text Available Satellite data volumes have seen a steady increase in recent years due to improvements in sensor technology and increases in data acquisition frequency. The gridded MODIS data products, spanning a region of interest of approximately 10° by 10° for a...

  17. Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera. (United States)

    Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng


    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.

  18. 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) (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...

  19. 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) (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...

  20. All sky imaging observations in visible and infrared waveband for validation of satellite cloud and aerosol products (United States)

    Lu, Daren; Huo, Juan; Zhang, W.; Liu, J.

    A series of satellite sensors in visible and infrared wavelengths have been successfully operated on board a number of research satellites, e.g. NOAA/AVHRR, the MODIS onboard Terra and Aqua, etc. A number of cloud and aerosol products are produced and released in recent years. However, the validation of the product quality and accuracy are still a challenge to the atmospheric remote sensing community. In this paper, we suggest a ground based validation scheme for satellite-derived cloud and aerosol products by using combined visible and thermal infrared all sky imaging observations as well as surface meteorological observations. In the scheme, a visible digital camera with a fish-eye lens is used to continuously monitor the all sky with the view angle greater than 180 deg. The digital camera system is calibrated for both its geometry and radiance (broad blue, green, and red band) so as to a retrieval method can be used to detect the clear and cloudy sky spatial distribution and their temporal variations. A calibrated scanning thermal infrared thermometer is used to monitor the all sky brightness temperature distribution. An algorithm is developed to detect the clear and cloudy sky as well as cloud base height by using sky brightness distribution and surface temperature and humidity as input. Based on these composite retrieval of clear and cloudy sky distribution, it can be used to validate the satellite retrievals in the sense of real-simultaneous comparison and statistics, respectively. What will be presented in this talk include the results of the field observations and comparisons completed in Beijing (40 deg N, 116.5 deg E) in year 2003 and 2004. This work is supported by NSFC grant No. 4002700, and MOST grant No 2001CCA02200

  1. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

    Directory of Open Access Journals (Sweden)

    Athos Agapiou


    Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

  2. GPS Satellite Simulation Facility (United States)

    Federal Laboratory Consortium — The GPS satellite simulation facility consists of a GPS satellite simulator controlled by either a Silicon Graphics Origin 2000 or PC depending upon unit under test...

  3. Determining the Suitability of Different Digital Elevation Models and Satellite Images for Fancy Maps. An Example of Cyprus (United States)

    Drachal, J.; Kawel, A. K.


    The article describes the possibility of developing an overall map of the selected area on the basis of publicly available data. Such a map would take the form designed by the author with the colors that meets his expectations and a content, which he considers to be appropriate. Among the data available it was considered the use of satellite images of the terrain in real colors and, in the form of shaded relief, digital terrain models with different resolutions of the terrain mesh. Specifically the considered data were: MODIS, Landsat 8, GTOPO-30, SRTM-30, SRTM-1, SRTM-3, ASTER. For the test area the island of Cyprus was chosen because of the importance in tourism, a relatively small area and a clearly defined boundary. In the paper there are shown and discussed various options of the Cyprus terrain image obtained synthetically from variants of Modis, Landsat and digital elevation models of different resolutions.

  4. Semi-automatic verification of cropland and grassland using very high resolution mono-temporal satellite images (United States)

    Helmholz, Petra; Rottensteiner, Franz; Heipke, Christian


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

  5. Overlapping image segmentation for context-dependent anomaly detection (United States)

    Theiler, James; Prasad, Lakshman


    The challenge of finding small targets in big images lies in the characterization of the background clutter. The more homogeneous the background, the more distinguishable a typical target will be from its background. One way to homogenize the background is to segment the image into distinct regions, each of which is individually homogeneous, and then to treat each region separately. In this paper we will report on experiments in which the target is unspecified (it is an anomaly), and various segmentation strategies are employed, including an adaptive hierarchical tree-based scheme. We find that segmentations that employ overlap achieve better performance in the low false alarm rate regime.

  6. 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


    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.

  7. Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

    Directory of Open Access Journals (Sweden)

    Hong Sun


    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.

  8. Satellite Images for Monitoring Mangrove Cover Changes in a Fast Growing Economic Region in Southern Peninsular Malaysia

    Directory of Open Access Journals (Sweden)

    Kasturi Devi Kanniah


    Full Text Available Effective monitoring is necessary to conserve mangroves from further loss in Malaysia. In this context, remote sensing is capable of providing information on mangrove status and changes over a large spatial extent and in a continuous manner. In this study we used Landsat satellite images to analyze the changes over a period of 25 years of mangrove areas in Iskandar Malaysia (IM, the fastest growing national special economic region located in southern Johor, Malaysia. We tested the use of two widely used digital classification techniques to classify mangrove areas. The Maximum Likelihood Classification (MLC technique provided significantly higher user, producer and overall accuracies and less “salt and pepper effects” compared to the Support Vector Machine (SVM technique. The classified satellite images using the MLC technique showed that IM lost 6740 ha of mangrove areas from 1989 to 2014. Nevertheless, a gain of 710 ha of mangroves was observed in this region, resulting in a net loss of 6030 ha or 33%. The loss of about 241 ha per year of mangroves was associated with a steady increase in urban land use (1225 ha per year from 1989 until 2014. Action is necessary to protect the existing mangrove cover from further loss. Gazetting of the remaining mangrove sites as protected areas or forest reserves and introducing tourism activities in mangrove areas can ensure the continued survival of mangroves in IM.

  9. 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


    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.

  10. Shear-Flow Induced Secondary Circulation in Parallel Underwater Topographic Corrugation and Its Application to Satellite Image Interpretation

    Institute of Scientific and Technical Information of China (English)

    ZHENG Quanan; ZHAO Qing; YUAN Yeli; LIU Xian; HU Jianyu; LIU Xuehai; YIN Liping; YE Xiaomin


    This study aims to figure out satellite imaging mechanisms for submerged sand ridges in the shallow water region in the case of the flow parallel to the topography corrugation.Solving the disturbance governing equations of the shear-flow yields the analytical solutions of the secondary circulation.The solutions indicate that a flow with a parabolic horizontal velocity shear and a sinusoidal vertical velocity shear will induce a pair of vortexes with opposite signs distributed symmetrically on the two sides of central line of a rectangular canal.In the case of the presence of surface Ekman layer with the direction of Ekman current opposite to (coincident with) the mean flow,the two vortexes converge (diverge) at the central line of canal in the upper layer and form a surface current convergent (divergent) zone along the central line of the canal.In the case of the absence of surface Ekman layer,there is no convergent (divergent) zone formed over the sea surface.The theoretical results are applied to interpretations of three convergent cases,one divergent case and statistics of 27 cases of satellite observations in the submerged sand ridge region of the Liaodong Shoal in the Bohai Sea.We found that the long,finger-like,bright patterns on SAR images are corresponding to the locations of the canals (or tidal channels) formed by two adjacent sand ridges rather than the sand ridges themselves.

  11. Evaluation of Development and Changes in Land Use using Different Satellite Image Processing and Remote Sensing Techniques (Case Study: Kermanshah, Iran)



    Currently the largest city in the western Iran, Kermanshah enjoys fast growing trend because of its strategic location. Remote sensing and satellite imagery are well suited for assessing the changes in land use over different time periods. In this study, satellite images from Landsat TM sensor and ETM sensor have been prepared during 1987 and 2007 as geometric and radiometric corrections have been made to them. The process was followed by selecting the best combination of false color by using...

  12. Clinical Applications of a CT Window Blending Algorithm: RADIO (Relative Attenuation-Dependent Image Overlay). (United States)

    Mandell, Jacob C; Khurana, Bharti; Folio, Les R; Hyun, Hyewon; Smith, Stacy E; Dunne, Ruth M; Andriole, Katherine P


    A methodology is described using Adobe Photoshop and Adobe Extendscript to process DICOM images with a Relative Attenuation-Dependent Image Overlay (RADIO) algorithm to visualize the full dynamic range of CT in one view, without requiring a change in window and level settings. The potential clinical uses for such an algorithm are described in a pictorial overview, including applications in emergency radiology, oncologic imaging, and nuclear medicine and molecular imaging.

  13. Patch-based image segmentation of satellite imagery using minimum spanning tree construction

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory


    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.

  14. Discrete Topology Based Hierarchical Segmentation for Efficient Object-Based Image Analyis: Application to Object Detection in High Resolution Satellite Images (United States)

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


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

  15. Simulation of at-sensor radiance over land for proposed thermal channels of Imager payload onboard INSAT-3D satellite using MODTRAN model

    Indian Academy of Sciences (India)

    M R Pandya; D B Shah; H J Trivedi; S Panigrahy


    INSAT-3D is the new generation Indian satellite designed for improved Earth observations through two payloads – Imager and Sounder. Study was conducted with an aim of simulating satellite level signal over land in the infrared channels of the Imager payload using a radiative transfer model MODTRAN. Satellite level at-sensor radiance corresponding to all four infrared channels of INSAT-3D Imager payload is obtained using MODTRAN and sensitivity of at-sensor radiance was inferred as a function of input parameters namely, surface temperature, emissivity, view angle and atmospheric water vapour, which is helpful in understanding the signal simulation scheme needed for retrieving a very critical parameter namely, land surface temperature.

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

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


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

  17. Geospatial mapping of Antarctic coastal oasis using geographic object-based image analysis and high resolution satellite imagery (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.


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

  18. Geographic Object-based Image Analysis for Developing Cryospheric Surface Mapping Application using Remotely Sensed High-Resolution Satellite Imagery (United States)

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


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

  19. Continuous evaluation of land cover restoration of tsunami struck plains in Japan by using several kinds of optical satellite image in time series (United States)

    Hashiba, H.


    The Mw 9.0 earthquake that struck Japan in 2011 was followed by a large-scale tsunami in the Tohoku region. The damage in the coastal plane was extensively displayed through many satellite images. Furthermore, satellite imaging is requested for the ongoing evaluation of the restoration process. The reconstruction of the urban structure, farmlands, grassland, and coastal forest that collapsed under the large tsunami requires effective long-term monitoring. Moreover, the post-tsunami land cover dynamics can be effectively modeled using time-constrained satellite data to establish a prognosis method for the mitigation of future tsunami impact. However, the remote satellite capture of a long-term restoration process is compromised by accumulating spatial resolution effects and seasonal influences. Therefore, it is necessary to devise a method for data selection and dataset structure. In the present study, the restoration processes were investigated in four years following the disaster in a part of the Sendai plain, northeast Japan, from same-season satellite images acquired by different optical sensors. Coastal plains struck by the tsunami are evaluated through land-cover classification processing using the clustering method. The changes in land cover are analyzed from time-series optical images acquired by Landsat-5/TM, 7/ETM+, 8/OLI, EO-1/ALI, and ALOS-1/AVNIR-2. The study reveals several characteristics of the change in the inundation area and signs of artificial and natural restoration.

  20. Modeling Research on Joint Scheduling of Multiple Imaging Satellites with Multiple Sensors%多星多载荷联合调度问题建模研究

    Institute of Scientific and Technical Information of China (English)

    潘鞘剑; 周装轻; 贺仁杰; 邢立宁


    在对多星多载荷联合调度过程及约束条件分析的基础上,从约束建模及启发式调度规则设计的角度对多星多载联合调度方案生成中的关键问题进行了深入研究.建立了基于阶段优化的多星多载荷联合调度模型.提出了基于规则的发式构造算法.%Guided by the application requirements of imaging satellite, the model construction and heuristic rule design of multi imaging satellites joint scheduling problem are focused. All of the research are based on the a-nalysis of the process of joint scheduling and imaging constraints. Firstly, this thesis analyses satellite imaging procedure , imaging constraints, input and output of the problem, ascertains the basic scheduling flow and characteristics of the multi imaging satellites joint scheduling problem. Secondly, in order to solve the problem the construction of heuristic algorithms is focused on.

  1. 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


    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.

  2. Synoptic Analysis of Heavy Rainfall and Flood Observed in Izmir on 20 May 2015 Using Radar and Satellite Images (United States)

    Avsar, Ercument


    In this study, a meteorological analysis is conducted on the sudden and heavy rainfall that occurred in Izmir on May 20, 2015. The barotropic model that is observed in upper carts is shown in detail. We can access the data of and analyze the type, severity and amount of many meteorological parameters using the meteorological radars that form a remote sensing system. The one field that uses the radars most intensively is rainfall. Images from the satellite and radar systems are used in the meteorological analysis of the heavy rainfall that occurred in Izmir on 20 May 2015, and the development of the system that led to this rainfall is shown. In this study, data received from Bornova Automatic Meteorological Observation Station (OMGI), which is under the management of Meteorology General Directorate (MGM), Izmir 2. Regional Directorate; satellite images; Radar PPI (Plan Position Indicator) and Radar MAX (Maximum Display) images are evaluated. In addition, synoptic situation, outputs of numerical estimation models, indices calculated from Skew T Log-P diagram are shown. All these results are mapped and analyzed. At the end of these analyses, it is found that this sudden rainfall had developed according to the frontal system motion. A barotropic model occurred on the day of the rainfall over the Aegean Region. As a result of the rainfall that happened in Izmir at 12.00 UTC (Universal Coordinated Time), the May month rainfall record for the last 64 years is achieved with a rainfall amount of 67.7 mm per meter square. Keywords: Izmir, barotropic model, heavy rainfall, radar, synoptic analysis

  3. Comparison Between Linear and Nonlinear Models of Mixed Pixels in Remote Sensing Satellite Images Based on Cierniewski Surface BRDF Model by Means of Monte Carlo Ray Tracing Simulation

    Directory of Open Access Journals (Sweden)

    Kohei Arai


    Full Text Available Comparative study on linear and nonlinear mixed pixel models of which pixels in remote sensing satellite images is composed with plural ground cover materials mixed together, is conducted for remote sensing satellite image analysis. The mixed pixel models are based on Cierniewski of ground surface reflectance model. The comparative study is conducted by using of Monte Carlo Ray Tracing: MCRT simulations. Through simulation study, the difference between linear and nonlinear mixed pixel models is clarified. Also it is found that the simulation model is validated.

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

    Li, Baishou; Gao, Yujiu


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

  5. Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series MODIS and LANDSAT satellite images (United States)

    Georgopoulou, Danai; Koutsias, Nikos


    Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS and LANDSAT satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. Satellite remote sensing data from MODIS and LANDSAT satellites in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the satellite data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we

  6. Use of multi-temporal SPOT-5 satellite images for land degradation assessment in Cameron Highlands, Malaysia using Geospatial techniques (United States)

    Nampak, Haleh; Pradhan, Biswajeet


    Soil erosion is the common land degradation problem worldwide because of its economic and environmental impacts. Therefore, land-use change detection has become one of the major concern to geomorphologists, environmentalists, and land use planners due to its impact on natural ecosystems. The objective of this paper is to evaluate the relationship between land use/cover changes and land degradation in the Cameron highlands (Malaysia) through multi-temporal remotely sensed satellite images and ancillary data. Land clearing in the study area has resulted increased soil erosion due to rainfall events. Also unsustainable development and agriculture, mismanagement and lacking policies contribute to increasing soil erosion rates. The LULC distribution of the study area was mapped for 2005, 2010, and 2015 through SPOT-5 satellite imagery data which were classified based on object-based classification. A soil erosion model was also used within a GIS in order to study the susceptibility of the areas affected by changes to overland flow and rain splash erosion. The model consists of four parameters, namely soil erodibility, slope, vegetation cover and overland flow. The results of this research will be used in the selection of the areas that require mitigation processes which will reduce their degrading potential. Key words: Land degradation, Geospatial, LULC change, Soil erosion modelling, Cameron highlands.

  7. Surface rupture and slip distribution of the 2016 Mw7.8 Kaikoura earthquake (New Zealand) from optical satellite image correlation using MicMac (United States)

    Champenois, Johann; Klinger, Yann; Grandin, Raphaël; Satriano, Claudio; Baize, Stéphane; Delorme, Arthur; Scotti, Oona


    Remote sensing techniques, like optical satellite image correlation, are very efficient methods to localize and quantify surface displacements due to earthquakes. In this study, we use the french sub-pixel correlator MicMac (Multi Images Correspondances par Méthodes Automatiques de Corrélation). This free open-source software, developed by IGN, was recently adapted to process satellite images. This correlator uses regularization, and that provides good results especially in near-fault area with a high spatial resolution. We use co-seismic pair of ortho-images to measure the horizontal displacement field during the recent 2016 Mw7.8 Kaikoura earthquake. Optical satellite images from different satellites are processed (Sentinel-2A, Landsat8, etc.) to present a dense map of the surface ruptures and to analyze high density slip distribution along all major ruptures. We also provide a detail pattern of deformation along these main surface ruptures. Moreover, 2D displacement from optical correlation is compared to co-seismic measurements from GPS, static displacement from accelerometric records, geodetic marks and field investigations. Last but not least, we investigate the reconstruction of 3D displacement from combining InSAR, GPS and optic.

  8. Geometric/radiometric calibration from ordinary images for high resolution satellite systems (United States)

    Latry, Christophe


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

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

    Energy Technology Data Exchange (ETDEWEB)

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


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

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

    CERN Document Server

    Arellano-Baeza, A A; Trejo-Soto, M


    Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. "The Lineament Extraction and Stripes Statistic Analysis" (LESSA) software package, developed by Zlatopolsy (1992, 1997). We assume that the lineaments allow to detect, at least partially, the presence ruptures in the Earths crust, and therefore enable one to follow the changes in the system of faults and fractures associated with strong earthquakes. We analysed 6 earthquakes occurred in the Pacific coast of the South America and XXX with the Richter scale magnitude >4.5. They were located in the regions with small season...

  11. Web-based spatial analysis with the ILWIS open source GIS software and satellite images from GEONETCast (United States)

    Lemmens, R.; Maathuis, B.; Mannaerts, C.; Foerster, T.; Schaeffer, B.; Wytzisk, A.


    This paper involves easy accessible integrated web-based analysis of satellite images with a plug-in based open source software. The paper is targeted to both users and developers of geospatial software. Guided by a use case scenario, we describe the ILWIS software and its toolbox to access satellite images through the GEONETCast broadcasting system. The last two decades have shown a major shift from stand-alone software systems to networked ones, often client/server applications using distributed geo-(web-)services. This allows organisations to combine without much effort their own data with remotely available data and processing functionality. Key to this integrated spatial data analysis is a low-cost access to data from within a user-friendly and flexible software. Web-based open source software solutions are more often a powerful option for developing countries. The Integrated Land and Water Information System (ILWIS) is a PC-based GIS & Remote Sensing software, comprising a complete package of image processing, spatial analysis and digital mapping and was developed as commercial software from the early nineties onwards. Recent project efforts have migrated ILWIS into a modular, plug-in-based open source software, and provide web-service support for OGC-based web mapping and processing. The core objective of the ILWIS Open source project is to provide a maintainable framework for researchers and software developers to implement training components, scientific toolboxes and (web-) services. The latest plug-ins have been developed for multi-criteria decision making, water resources analysis and spatial statistics analysis. The development of this framework is done since 2007 in the context of 52°North, which is an open initiative that advances the development of cutting edge open source geospatial software, using the GPL license. GEONETCast, as part of the emerging Global Earth Observation System of Systems (GEOSS), puts essential environmental data at the

  12. Solar radiation estimation using images form geostationary satellites; Estimacao de radiacao solar usando imagens de satelites geoestacionarios

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Cicero Barbosa dos [Centro Federal de Educacao Tecnologica do Parana, PR (Brazil); Zuern, Hans Helmut [Santa Catarina Univ., Florianopolis, SC (Brazil). LABSPOT


    The opportunity of potential measurement Photovoltaic through of studies of solar radiation maximum incidence, aimed the generation of electrical energy, contained in either radial systems or stand-alone or even grid-connected to conventional system, preceded by a study of solar radiation estimation technique, which is the main fuel the Photovoltaic generation. This work presents a technique of solar radiation estimation, using images from satellite geo-stationary in a visible field. The city of Curitiba was an implementation and the results are compared to the estimation made by researches from INPE - National Institute Space Research, whose observations were based on the solar shine duration, obtained in a network of 187 meteorological station for period of 10 years (1961-1970). (author) 24 refs., 2 figs., 2 tabs.; e-mail: cicero at; eellhh at

  13. Biophysical indicators based on satellite images in an irrigated area at the São Francisco River Basin, Brazil (United States)

    Leivas, Janice F.; Teixeira, Antônio Heriberto C.; Bayma-Silva, Gustavo; Ronquim, Carlos Cesar; Ribeiro da Silva Reis, João. Batista


    The Jaíba Irrigated Perimeter is a large irrigated agriculture area, located in the region Forest Jaíba between the São Francisco and Verde Grande rivers, in the Brazilian semi-arid region. In 2014, irrigators this the region face losses in the interruption of new plantings in irrigated areas due to water scarcity. The objective of this study is combine the model to estimate the Monteith BIO with the SAFER algorithm in the case of obtaining ET, to analyze the dynamics of natural vegetation and irrigated crops in water scarcity period. For application of the model are necessary data from meteorological stations and satellite images. Were used 23 satellite images of MODIS with spatial resolution of 250m and temporal 16 days, of 2014 year. For analyze the results, we used central pivots irrigation mask of Minas Gerais state, Brazil. In areas with irrigated agriculture with central pivot, the mean values of BIO over the year 2014 were 88.96 kg.ha-1.d-1. The highest values occurred between April 23 and May 8, with BIO 139 kg.ha-1.d-1. For areas with natural vegetation, the average BIO was 88.34 kg.ha-1.d-1 with lower values in September. Estimates of ET varied with the lowest values of ET observed in natural vegetation 1.91+/-1.22 mm.d-1 and the highest values in irrigated area is observed 3.51+/-0.97 mm.d-1. Results of this study can assist in monitoring of river basins, contributing to the management irrigated agriculture, with the trend of scarcity of water resources and increasing conflicts for the water use.

  14. Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality (United States)

    Sidick, Erkin


    Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions o