WorldWideScience

Sample records for satellite microwave imagery

  1. Normalization of satellite imagery

    Science.gov (United States)

    Kim, Hongsuk H.; Elman, Gregory C.

    1990-01-01

    Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal color changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band color imagery can be directly interpreted for quantitative information of the target.

  2. Thematic mapping from satellite imagery

    CERN Document Server

    Denègre, J

    2013-01-01

    Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

  3. ERTS-A satellite imagery

    Science.gov (United States)

    Colvocoresses, Alden P.

    1970-01-01

    The first satellite designed to survey the Earth's resources is scheduled to be launched in 1972. This satellite, known as ERTS-A, will telemeter frames of imagery each covering 100-nautical-mile squares of the Earth. Except for the internal anomalies in the sensor system, the imagery, after being properly scaled, rectified, and controlled, may be considered an orthographic view of the Earth and used as a planimetric photomap. The accuracy of this photomap will be limited, principally by the geometric fidelity of the sensor system rather than by external effects, such as relief displacement, which restrict the direct cartographic use of the conventional aerial photograph. ERST-A is not designed as a topographic mapping satellite but does have real potential' for thematic mapping particularly in areas now covered by topographic maps.

  4. User Validation of VIIRS Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Don Hillger

    2015-12-01

    Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.

  5. 7 CFR 611.22 - Availability of satellite imagery.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Availability of satellite imagery. 611.22 Section 611... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image...

  6. Commercial satellite imagery comes of age

    Energy Technology Data Exchange (ETDEWEB)

    Jasani, Bhupendra [King' s College, London (United Kingdom). Dept. of War Studies

    2003-05-01

    In the absence of on-site inspections until recently, in the Seventh Quarterly Report to the United Nations Security Council, the Executive Director of the UN Monitoring, Verification and Inspection Commission (UNMOVIC) stated that the imagery acquired over Iraq, which UNMOVIC is receiving through a commercial satellite supplier is continuously, being analysed. Not only this but the report hopes that 'Member States will continue to provide it with imagery from their own assets as such assistance provided to date has proven very valuable' Even after the on-site inspections have begun, satellite imagery over Iraq continues, for example, to be used for inspection planning purposes. This indicates that commercial satellite imagery might finally be used on a routine basis. As the findings by the UNMOVIC are not made public, this paper examines a number of images acquired over Baghdad from different commercial satellite sources and at different times to determine what could be concluded about Iraq's nuclear and chemical weapon activities in the region.

  7. Multi-Decadal Variability of Polynya Characteristics and Ice Production in the North Water Polynya by Means of Passive Microwave and Thermal Infrared Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Andreas Preußer

    2015-11-01

    Full Text Available The North Water (NOW Polynya is a regularly-forming area of open-water and thin-ice, located between northwestern Greenland and Ellesmere Island (Canada at the northern tip of Baffin Bay. Due to its large spatial extent, it is of high importance for a variety of physical and biological processes, especially in wintertime. Here, we present a long-term remote sensing study for the winter seasons 1978/1979 to 2014/2015. Polynya characteristics are inferred from (1 sea ice concentrations and brightness temperatures from passive microwave satellite sensors (Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2, Scanning Multichannel Microwave Radiometer (SMMR, Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS and (2 thin-ice thickness distributions, which are calculated using MODIS ice-surface temperatures and European Center for Medium-Range Weather Forecasts (ECMWF atmospheric reanalysis data in a 1D thermodynamic energy-balance model. Daily ice production rates are retrieved for each winter season from 2002/2003 to 2014/2015, assuming that all heat loss at the ice surface is balanced by ice growth. Two different cloud-cover correction schemes are applied on daily polynya area and ice production values to account for cloud gaps in the MODIS composites. Our results indicate that the NOW polynya experienced significant seasonal changes over the last three decades considering the overall frequency of polynya occurrences, as well as their spatial extent. In the 1980s, there were prolonged periods of a more or less closed ice cover in northern Baffin Bay in winter. This changed towards an average opening on more than 85% of the days between November and March during the last decade. Noticeably, the sea ice cover in the NOW polynya region shows signs of a later-appearing fall freeze-up, starting in the late 1990s. Different methods to obtain daily polynya area using passive microwave AMSR-E/AMSR2 data and SSM/I-SSMIS data were applied. A comparison

  8. Recommended satellite imagery capabilities for disaster management

    Science.gov (United States)

    Richards, P. B.; Robinove, C. J.; Wiesnet, D. R.; Salomonson, V. V.; Maxwell, M. S.

    1982-01-01

    This study explores the role that satellite imaging systems might play in obtaining information needed in the management of natural and manmade disasters. Information requirements which might conceivably be met by satellite were identified for over twenty disasters. These requirements covered pre-disaster mitigation and preparedness activities, disaster response activities, and post-disaster recovery activities. The essential imaging satellite characteristics needed to meet most of the information requirements are 30 meter (or finer) spatial resolution, frequency of observations of one week or less, data delivery times of one day or less, and stereo, synoptic all-weather coverage of large areas in the visible, near infrared, thermal infrared and microwave bands. Of the current and planned satellite systems investigated for possible application to disaster management, Landsat-D and SPOT appear to have the greatest potential during disaster mitigation and preparedness activities, but all satellites studied have serious deficiencies during response and recovery activities. Several strawman concepts are presented for a satellite system optimized to support all disaster management activities.

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

    OpenAIRE

    2014-01-01

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

  10. Using satellite imagery for crime mapping in South Africa.

    CSIR Research Space (South Africa)

    Schmitz, Peter MU

    2002-12-01

    Full Text Available . Increasingly, technologies such as digital orthophotographs, high-resolution satellite imagery and the global positioning system (GPS) are being used for these areas to provide base mapping and application data for geographical information systems (GIS...

  11. Potentials of satellite imagery for monitoring arctic goose productivity

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This paper reports upon the exciting possibility that satellite imagery may now provide feasible means for grossly monitoring arctic habitat conditions in a timely...

  12. Andean terraced hills (a use of satellite imagery)

    CERN Document Server

    Sparavigna, Amelia Carolina

    2010-01-01

    The aim of this paper is in stimulating the use of satellite imagery, in particular the free service of Google Maps, to investigate the distribution of the agricultural technique of terraced hills in Andean countries, near Titicaca Lake. In fact, satellite maps can give a clear view of the overall surface modified by human work, being then a precious help for on-site archaeological researches and for historical analysis. Satellite imagery is also able to give the distribution of burial and worship places. The paper discusses some examples near the Titicaca Lake.

  13. Harnessing Satellite Imageries in Feature Extraction Using Google Earth Pro

    Science.gov (United States)

    Fernandez, Sim Joseph; Milano, Alan

    2016-07-01

    Climate change has been a long-time concern worldwide. Impending flooding, for one, is among its unwanted consequences. The Phil-LiDAR 1 project of the Department of Science and Technology (DOST), Republic of the Philippines, has developed an early warning system in regards to flood hazards. The project utilizes the use of remote sensing technologies in determining the lives in probable dire danger by mapping and attributing building features using LiDAR dataset and satellite imageries. A free mapping software named Google Earth Pro (GEP) is used to load these satellite imageries as base maps. Geotagging of building features has been done so far with the use of handheld Global Positioning System (GPS). Alternatively, mapping and attribution of building features using GEP saves a substantial amount of resources such as manpower, time and budget. Accuracy-wise, geotagging by GEP is dependent on either the satellite imageries or orthophotograph images of half-meter resolution obtained during LiDAR acquisition and not on the GPS of three-meter accuracy. The attributed building features are overlain to the flood hazard map of Phil-LiDAR 1 in order to determine the exposed population. The building features as obtained from satellite imageries may not only be used in flood exposure assessment but may also be used in assessing other hazards and a number of other uses. Several other features may also be extracted from the satellite imageries.

  14. Photogrammetric Processing Using ZY-3 Satellite Imagery

    Science.gov (United States)

    Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.

    2015-03-01

    This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are

  15. Estimating Soil Moisture from Satellite Microwave Observations

    Science.gov (United States)

    Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E.

    1998-01-01

    Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data

  16. On RPC Model of Satellite Imagery

    Institute of Scientific and Technical Information of China (English)

    ZHANG Guo; YUAN Xiuxiao

    2006-01-01

    The RPC model has recently raised considerable interest in the photogrammetry and remote sensing community. The RPC is a generalized sensor model that is capable of achieving high approximation accuracy. Unfortunately, the computation of the parameters of RPC model is subject to the initial of the parameter in all available literature. An algorithm for computation of parameters of RPC model without initial value is presented and tested on SPOT-5, CBERS-2, ERS-1 imageries. RPC model is suitable for both push-broom and SAR imagery.

  17. Mapping cultivable land from satellite imagery with clustering algorithms

    Science.gov (United States)

    Arango, R. B.; Campos, A. M.; Combarro, E. F.; Canas, E. R.; Díaz, I.

    2016-07-01

    Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodology for the automatic delimitation of cultivable land by means of machine learning algorithms and satellite data. The method uses a partition clustering algorithm called Partitioning Around Medoids and considers the quality of the clusters obtained for each satellite band in order to evaluate which one better identifies cultivable land. The proposed method was tested with vineyards using as input the spectral and thermal bands of the Landsat 8 satellite. The experimental results show the great potential of this method for cultivable land monitoring from remote-sensed multispectral imagery.

  18. Get Close to Glaciers with Satellite Imagery.

    Science.gov (United States)

    Hall, Dorothy K.

    1986-01-01

    Discusses the use of remote sensing from satellites to monitor glaciers. Discusses efforts to use remote sensing satellites of the Landsat series for examining the global distribution, mass, balance, movements, and dynamics of the world's glaciers. Includes several Landsat images of various glaciers. (TW)

  19. Parameterization of Vegetation Aerodynamic Roughness of Natural Regions Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard; Stewart, Pamela

    1998-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. The parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  20. Identifying hydro resources with enhanced satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Cambridge, M.; Moore, J.M.; Canas, A.

    1986-10-01

    Landsat multi-spectral scanner (MSS) imagery in photographic form was used, in conjunction with available topographic and geologic maps, during the preliminary planning studies of potential dam sites in the Ulu Jelai river basin, Peninsular Malaysia. The Imperial College (London, UK) prototype analog image processing system was used to provide colour composite and edge-enhanced images for drainage, geological fold, fault and joint trace (tectonic fabric) mapping and to provide information on rock type distribution at scales between 1:250,000 and 1:50,000. Remotely sensed space imagery, enhanced by analog (optical) techniques, is a cheap, convenient and useful supplement to existing geologic and topographic maps for preliminary regional site assessment in tropical terrain.

  1. Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

    Science.gov (United States)

    Molthan, Andrew L.; Fuell, Kevin K.; LaFontaine, Frank; McGrath, Kevin; Smith, Matt

    2013-01-01

    Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will

  2. Updating Maps Using High Resolution Satellite Imagery

    Science.gov (United States)

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

    2016-06-01

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

  3. Hazing Iran: Satellite Imagery, Human Rights, and City as Camp

    OpenAIRE

    Zhang, Amy

    2014-01-01

    As perhaps most obviously evidenced in the political maneuverings that led up to the second Gulf War in 2003, the use of satellite imagery to document spatial terrain is often, and almost instantly, politicized. In the two images presented here, this politicization takes on a two-way relationship and is open to contrasting and inevitably dualistic readings. One way of describing their relationship is as "Target" and "Aftermath". On the left, we have an image of the nuclear plant near the Iran...

  4. Visualization techniques for data mining of Latur district satellite imagery

    OpenAIRE

    Kodge, B. G.; Hiremath, P. S.

    2011-01-01

    This study presents a new visualization tool for classification of satellite imagery. Visualization of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and understanding of the results. In this study, we present a prototype visualization tool for visual dat...

  5. Automatic Mosaicking of Satellite Imagery Considering the Clouds

    Science.gov (United States)

    Kang, Yifei; Pan, Li; Chen, Qi; Zhang, Tong; Zhang, Shasha; Liu, Zhang

    2016-06-01

    With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.

  6. IAEA Safeguards: Cost/benefit analysis of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Kiruna (Sweden)

    1999-03-01

    A major milestone in the efforts to strengthen the Safeguards System was reached in May 1997 when the Board of Governors approved a `Model Protocol Additional to Safeguards Agreements`. The Protocol provides the legal basis necessary to enhance the Agency`s ability to detect undeclared nuclear material and activities by using information available from open sources to complement the declarations made by Member States. Commercially available high-resolution satellite data has emerged as one potential complementary open information source to support the traditional and extended Safeguard activities of IAEA. This document constitutes a first report from SSC Satellitbild giving the Agency tentative and initial estimates of the potential cost and time-savings possible with the new proposed technology. The initial cost/benefit simulation will be further finalised in the following `Implementation Blueprint` study. The general foundation and starting point for the cost/benefit calculation is to simulate a new efficient and relatively small `imagery unit` within the IAEA, capable of performing advanced image processing as a tool for various safeguards tasks. The image processing capacity is suggested to be task- and interpretation-oriented. The study was performed over a period of 1,5 weeks in late 1998, and is based upon interviews of IAEA staff, reviews of existing IAEA documentation as well as from SSC Satellitbild`s long-standing experience of satellite imagery and field missions. The cost/benefit analysis is based on a spreadsheet simulation of five potential applications of commercial satellite imagery: Reference information; Confirmation of Agency acquired and Member State supplied data; Change detection and on-going monitoring; Assessing open source information available to the Agency; Detecting undeclared activities and undeclared sites. The study confirms that the proposed concept of a relatively small `imagery unit` using high-resolution data will be a sound and

  7. Satellite Imagery Assisted Road-Based Visual Navigation System

    Science.gov (United States)

    Volkova, A.; Gibbens, P. W.

    2016-06-01

    There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used

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

    Science.gov (United States)

    Ioannou, Maria Teresa; Georgopoulos, Andreas

    2013-08-01

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

  9. Crop classification using temporal stacks of multispectral satellite imagery

    Science.gov (United States)

    Moody, Daniela I.; Brumby, Steven P.; Chartrand, Rick; Keisler, Ryan; Longbotham, Nathan; Mertes, Carly; Skillman, Samuel W.; Warren, Michael S.

    2017-05-01

    The increase in performance, availability, and coverage of multispectral satellite sensor constellations has led to a drastic increase in data volume and data rate. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. The data analysis capability, however, has lagged behind storage and compute developments, and has traditionally focused on individual scene processing. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and can scale with the high-rate and dimensionality of imagery being collected. We investigate and compare the performance of pixel-level crop identification using tree-based classifiers and its dependence on both temporal and spectral features. Classification performance is assessed using as ground-truth Cropland Data Layer (CDL) crop masks generated by the US Department of Agriculture (USDA). The CDL maps contain 30m spatial resolution, pixel-level labels for around 200 categories of land cover, but are however only available post-growing season. The analysis focuses on McCook county in South Dakota and shows crop classification using a temporal stack of Landsat 8 (L8) imagery over the growing season, from April through October. Specifically, we consider the temporal L8 stack depth, as well as different normalized band difference indices, and evaluate their contribution to crop identification. We also show an extension of our algorithm to map corn and soy crops in the state of Mato Grosso, Brazil.

  10. Processing Satellite Imagery To Detect Waste Tire Piles

    Science.gov (United States)

    Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine

    2007-01-01

    A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed

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

    Institute of Scientific and Technical Information of China (English)

    SHI Wenzhong; Ahmed Shaker

    2004-01-01

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

  12. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    Science.gov (United States)

    Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

    2016-06-01

    Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in

  13. Radiometric Correction of Multitemporal Satellite Imagery

    Directory of Open Access Journals (Sweden)

    S. G. Biday,

    2010-01-01

    Full Text Available Problem statement: Repeated observation of a given area over time yields potential for many forms of change detection analysis. These repeated observations are confounded in terms of radiometric consistency due to changes in sensor calibration over time, differences in illumination, observation angles and variation in atmospheric effects. Also major problem with satellite images is that regions below clouds are not covered by sensor. Cloud detection, removal and data prediction in cloudy region is essential for image interpretation. Approach: This study demonstrated applicability of empirical relative radiometric normalization methods to a set of multitemporal cloudy images acquired by Resourcesat-1 LISS III sensor. Objective of this study was to detect and remove cloud cover and normalize an image radiometrically. Cloud detection was achieved by using Average Brightness Threshold (ABT algorithm. The detected cloud removed and replaced with data from another images of the same area. We proposed a new method in which cloudy pixels are replaced with predicted pixel values obtained by regression. After cloud removal, the proposed normalization method was applied to reduce the radiometric influence caused by non surface factors. This process identified landscape elements whose reflectance values are nearly constant over time, i.e., the subset of non-changing pixels are identified using frequency based correlation technique. Further, we proposed another method of radiometric correction in frequency domain, Pseudo-Invariant Feature regression and this process removed landscape elements such as vegetation whose reflectance values are not constant over time. It takes advantage of vegetation being typically high frequency area, can be removed by low pass filter. Results: The quality of radiometric normalization is statistically assessed by R2 value and Root Mean Square Error (RMSE between each pair of analogous band. Further we verified that difference

  14. Direct determination of surface albedos from satellite imagery

    Science.gov (United States)

    Mekler, Y.; Joseph, J. H.

    1983-01-01

    An empirical method to measure the spectral surface albedo of surfaces from Landsat imagery is presented and analyzed. The empiricism in the method is due only to the fact that three parameters of the solution must be determined for each spectral photograph of an image on the basis of independently known albedos at three points. The approach is otherwise based on exact solutions of the radiative transfer equation for upwelling intensity. Application of the method allows the routine construction of spectral albedo maps from satelite imagery, without requiring detailed knowledge of the atmospheric aerosol content, as long as the optical depth is less than 0.75, and of the calibration of the satellite sensor.

  15. Sugarcane Land Classification with Satellite Imagery using Logistic Regression Model

    Science.gov (United States)

    Henry, F.; Herwindiati, D. E.; Mulyono, S.; Hendryli, J.

    2017-03-01

    This paper discusses the classification of sugarcane plantation area from Landsat-8 satellite imagery. The classification process uses binary logistic regression method with time series data of normalized difference vegetation index as input. The process is divided into two steps: training and classification. The purpose of training step is to identify the best parameter of the regression model using gradient descent algorithm. The best fit of the model can be utilized to classify sugarcane and non-sugarcane area. The experiment shows high accuracy and successfully maps the sugarcane plantation area which obtained best result of Cohen’s Kappa value 0.7833 (strong) with 89.167% accuracy.

  16. Scheduling satellite imagery acquisition for sequential assimilation of water level observation into flood modelling

    Science.gov (United States)

    García-Pintado, Javier; Neal, Jeff C.; Mason, David C.; Dance, Sarah L.; Bates, Paul D.

    2013-04-01

    Satellite-based imagery has proved useful for obtaining information on water levels in flood events. Microwave frequencies are generally more useful for flood detection than visible-band sensors because of its all-weather day-night capability. Specifically, the future SWOT mission, with Ka-band interferometry, will be able to provide direct Water Level Observations (WLOs), and current and future Synthetic Aperture Radar (SAR) sensors can provide information of flood extent, which, when intersected with a Digital Elevation Model (DEM) of the floodplain, provides indirect WLOs. By either means, satellite-based WLOs can be assimilated into a hydrodynamic model to decrease forecast uncertainty and further to estimate river discharge into the flooded domain. Operational scenarios can even make a combined use of imagery from different uncoordinated missions to sequentially estimate river discharge. Thus, with an increasing number of operational satellites with WLO capability, information on the relationship between satellite first visit, revisit times, and forecast performance is required to optimise the operational scheduling of satellite imagery. By using an Ensemble Transform Kalman Filter (ETKF) and a synthetic analysis with the 2D hydrodynamic model LISFLOOD-FP based on a real flooding case affecting an urban area (summer 2007, Tewkesbury, Southwest UK), we evaluate the sensitivity of the forecast performance to visit parameters. As an example, we use different scenarios of revisit times and observational errors expected from the current COSMO-Skymed (CSK) constellation, with X-band SAR. We emulate a generic hydrologic-hydrodynamic modelling cascade by imposing a bias and spatiotemporal correlations to the inflow error ensemble into the hydrodynamic domain. First, in agreement with previous research, estimation and correction for this bias leads to a clear improvement in keeping the forecast on track. Second, imagery obtained early in the flood is shown to have a

  17. NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE): Changing patterns in the use of NRT satellite imagery

    Science.gov (United States)

    Davies, D.; Michael, K.; Schmaltz, J. E.; Harrison, S.; Ding, F.; Durbin, P. B.; Boller, R. A.; Cechini, M. F.; Rinsland, P. L.; Ye, G.; Mauoka, E.

    2015-12-01

    NASA's Land, Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) provides data and imagery approximately 3 hours from satellite observation, to monitor natural events globally and to meet the needs of the near real-time (NRT) applications community. This article describes LANCE, and how the use of NRT data and imagery has evolved. Since 2010 there has been a four-fold increase in both the volume of data and the number of files downloaded. Over the last year there has been a marked shift in the way in which users are accessing NRT imagery; users are gravitating towards Worldview and the Global Imagery Browse Services (GIBS) and away from MODIS Rapid Response, in part due to the increased exposure through social media. In turn this is leading to a broader range of users viewing NASA NRT imagery. This article also describes new, and planned, product enhancements to LANCE. Over the last year, LANCE has expanded to support NRT products from the Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Multi-angle Imaging SpectroRadiometer (MISR). LANCE elements are also planning to ingest and process NRT data from the Visible Infrared Imager Radiometer Suite (VIIRS), and the advanced Ozone Mapping and Profiler Suite (OMPS) instruments onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite in the near future.

  18. Combining satellite imagery and machine learning to predict poverty.

    Science.gov (United States)

    Jean, Neal; Burke, Marshall; Xie, Michael; Davis, W Matthew; Lobell, David B; Ermon, Stefano

    2016-08-19

    Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. Using survey and satellite data from five African countries--Nigeria, Tanzania, Uganda, Malawi, and Rwanda--we show how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes. Our method, which requires only publicly available data, could transform efforts to track and target poverty in developing countries. It also demonstrates how powerful machine learning techniques can be applied in a setting with limited training data, suggesting broad potential application across many scientific domains.

  19. Measurement of sea ice and icebergs topography using satellite imagery

    Science.gov (United States)

    Zakharov, I.; Power, D.; Prasad, S.

    2016-12-01

    Sea ice topography represents geospatial information on the three-dimensional geometrical attributes of the ice surface including height and shape of various ice features. The features interest consist of deformed (pressure ridges, rubbles and hummocks) and level sea ice as well as glacial ice. Sea ice topography is important for scientific research and climate studies because it helps characterise ice volume and thickness and it influences the near-surface atmospheric transport by impacting the drag coefficients. It also represents critical information to marine operational applications, such as ships navigation and risks assessment for offshore infrastructures. The several methods were used to measure sea ice topography from a single satellite image as well as multiple images. The techniques based on the single image, acquired by optical or synthetic aperture radar (SAR) satellites, derive the height and shape information from shadow and shading. Optical stereo images acquired by very high resolution (0.5 m) satellites were used to extract highly detailed digital elevation model (DEM). SAR imagery allowed extraction of DEM using stereo-radargrammetry and interferometry. The images from optical satellites WorldView, Pleiades, GeoEye, Spot, and Landsat-8 were used to measure topography of sea ice deformation features and glacial ice including icebergs and ice islands. These features were mapped in regions of the Central Arctic, Baffin Bay and the coast of Greenland. SAR imagery including interferometric TanDEM-X data and full polarimetric Radarsat-2 were used to extract ridge frequency and measure spatial parameters of glacial features. The accuracy was evaluated by comparison of the results from different methods demonstrating their strengths and limitations. Ridge height and frequency were also compared with the high resolution results from the Los Alamos sea ice model (CICE), regionally implemented for Baffin Bay and the Labrador Sea.

  20. An algorithm to detect sea ice leads using AMSR-E passive microwave imagery

    Directory of Open Access Journals (Sweden)

    J. Röhrs

    2010-02-01

    Full Text Available Leads are major sites of energy fluxes and brine releases at the air-ocean interface of sea ice covered oceans. This study presents an algorithm to detect leads that are broader than 3 km in the entire Arctic Ocean. The algorithm detected 50% of the lead area that is visible in optical satellite images. Passive microwave imagery from the Advanced Microwave Scanning Radiometer – Earth Observation System (AMSR-E is used, allowing daily observations that are independent of daylight or cloud conditions. Using unique signatures of thin ice in the brightness temperature ratio between the 89 GHz and 19 GHz channels, the algorithm allowed to detect thin ice features in the ice cover and is optimized to detect leads. Leads were mapped for the period from 2002–2009 excluding the summer months. Several frequently reoccurring large scale lead patterns were found, especially in regions where sea ice is known to drift out of the Arctic Ocean. The maximum lead occurrence in the Arctic is located in the Beaufort Sea, low lead occurrence was found in the inner Arctic Ocean close to the North Pole.

  1. An algorithm to detect sea ice leads by using AMSR-E passive microwave imagery

    Directory of Open Access Journals (Sweden)

    J. Röhrs

    2012-03-01

    Full Text Available Leads are major sites of energy fluxes and brine releases at the air-ocean interface of sea-ice covered oceans. This study presents an algorithm to detect leads wider than 3 km in the entire Arctic Ocean. The algorithm detects 50 % of the lead area that was visible in optical MODIS satellite images. Passive microwave imagery from the Advanced Microwave Scanning Radiometer – Earth Observation System (AMSR-E is used, allowing daily observations due to the fact that AMSR-E does not depend on daylight or cloud conditions. Using the unique signatures of thin ice in the brightness temperature ratio between the 89 GHz and 19 GHz channels, the algorithm is able to detect thin ice areas in the ice cover and is optimized to detect leads. Leads are mapped for the period from 2002 to 2011 excluding the summer months, and validated qualitatively by using MODIS, Envisat ASAR, and CryoSat-2 data. Several frequently recurring large scale lead patterns are found, especially in regions where sea ice is known to drift out of the Arctic Ocean.

  2. Using satellite imagery to assess the influence of urban development on the impacts of extreme rainfall

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin; Madsen, Henrik;

    We investigate the applicability of medium resolution Landsat satellite imagery for mapping temporal changes in urban land cover for direct use in urban flood models. The overarching aim is to provide accurate and cost- and resource-efficient quantification of temporal changes in risk towards...... the impacts of pluvial flooding. Initial results show that satellite imagery may have considerable potential in this respect....

  3. Vertical Accuracy Comparison of Digital Elevation Model from LIDAR and Multitemporal Satellite Imagery

    Science.gov (United States)

    Octariady, J.; Hikmat, A.; Widyaningrum, E.; Mayasari, R.; Fajari, M. K.

    2017-05-01

    Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013-2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.

  4. Quantifying River Widths of North America from Satellite Imagery

    Science.gov (United States)

    Allen, G. H.; Pavelsky, T.; Miller, Z.

    2013-12-01

    River width is a fundamental predictor variable in many hydrologic, geomorphic, and biogeochemical models, yet current large-scale models rely on theoretical hydraulic geometry relationships that do not fully capture natural variability in river form. Here we present the first high-resolution dataset of long-term mean width of North American rivers wider than 30 m. The dataset contains 7.93 million georeferenced width measurements derived from Landsat TM and ETM+ imagery that were acquired when rivers were most likely to be at mean discharge. We built the dataset by developing an automated procedure that selects and downloads raw imagery, creates cloud-free normalized difference water index images, histogram balances and mosaics them together, and produces a water mask using a dynamic water-land threshold technique. We then visually inspected and corrected the mask for errors and used RivWidth software to calculate river width at each river centerline pixel. We validated our dataset using >1000 United States Geological Survey and Water Survey of Canada in situ gauge station measurements. Error analysis shows a robust relationship between the remotely sensed widths and in situ gauge measurements with an r 2 = 0.86 (Spearman's = 0.81) and a mean absolute error of 27.5 m. We find that North American river widths lie on logarithmic frequency curve with some notable exceptions at widths SWOT) satellite mission.

  5. Surface Characteristics of Green Island Wakes from Satellite Imagery

    Science.gov (United States)

    Cheng, Kai-Ho; Hsu, Po-Chun; Ho, Chung-Ru

    2017-04-01

    Characteristics of an island wake induced by the Kuroshio Current flows pass by Green Island, a small island 40 km off southeast of Taiwan is investigated by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. The MODIS sea surface temperature (SST) and chlorophyll-a (chl-a) imagery is produced at 250-meter resolution from 2014 to 2015 using the SeaDAS software package which is developed by the National Aeronautics and Space Administration. The wake occurrence is 59% observed from SST images during the data span. The average cooling area is 190 km2, but the area is significantly changed with wind directions. The wake area is increased during southerly winds and is reduced during northerly winds. Besides, the average cooling SST was about 2.1 oC between the front and rear island. Comparing the temperature difference between the wake and its left side, the difference is 1.96 oC. In addition, the wakes have 1 3 times higher than normal in chlorophyll concentration. The results indicate the island mass effect makes the surface water of Green island wake colder and chl-a higher.

  6. Automatic detection of ship tracks in ATSR-2 satellite imagery

    Directory of Open Access Journals (Sweden)

    E. Campmany

    2009-03-01

    Full Text Available Ships modify cloud microphysics by adding cloud condensation nuclei (CCN to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. An algorithm has been developed to automate the detection of ship tracks in Along Track Scanning Radiometer 2 (ATSR-2 imagery. The scheme has been integrated into the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of their neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR-2 data. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both West Africa and South-Western Europe. The global distribution of ship tracks shows strong seasonality, little inter-annual variability and a similar spatial pattern to the distribution of ship emissions.

  7. Efficient Algorithm for Railway Tracks Detection Using Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Ali Javed

    2012-10-01

    Full Text Available Satellite imagery can produce maps including roads, railway tracks, buildings, bridges, oceans, lakes, rivers, etc. In developed countries like USA, Canada, Australia, Europe, images produced by Google map are of high resolution and good quality. On the other hand, mostly images of the third world countries like Pakistan, Asian and African countries are of poor quality and not clearly visible. Similarly railway tracks of these countries are hardly visible in Google map. We have developed an efficient algorithm for railway track detection from a low quality image of Google map. This would lead to detect damaged railway track, railway crossings and help to schedule/divert locomotive movements in order to avoid catastrophe.

  8. Estimation of Satellite Orientation from Space Surveillance Imagery Measured with an Adaptive Optics Telescope

    Science.gov (United States)

    1996-12-01

    SATELLITE ORIENTATION FROM SPACE SURVEILLANCE IMAGERY MEASURED WITH AN ADAPTIVE OPTICS TELESCOPE THESIS Gregory E. Wood Lieutenant, USAF AFIT/GSO/ENP...the official policy or position of the Department of Defense or the U. S. Government. AFIT/GSO/ENP/96D-02 ESTIMATION OF SATELLITE ORIENTATION FROM...surveillance operations. xii ESTIMATION OF SATELLITE ORIENTATION FROM SPACE SURVEILLANCE IMAGERY MEASURED WITH AN ADAPTIVE OPTICS TELESCOPE

  9. Towards a climatology of tropical cyclone morphometric structures using a newly standardized passive microwave satellite dataset

    Science.gov (United States)

    Cossuth, J.; Hart, R. E.

    2013-12-01

    storm's rainband and eyewall organization. Ultimately, this project develops a consistent climatology of TC structures using a new database of research-quality historical TC satellite microwave observations. Not only can such data sets more accurately study TC structural evolution, but they may facilitate automated TC intensity estimates and provide methods to enhance current operational and research products, such as at the NRL TC webpage (http://www.nrlmry.navy.mil/TC.html). The process of developing the dataset and possible objective definitions of TC structures using passive microwave imagery will be described, with preliminary results suggesting new methods to identify TC structures that may interrogate and expand upon physical and dynamical theories. Structural metrics such as threshold analysis of the outlines of the TC shape as well as methods to diagnose the inner-core size, completion, and magnitude will be introduced.

  10. Detection of ship tracks in ATSR2 satellite imagery

    Directory of Open Access Journals (Sweden)

    E. Campmany

    2008-08-01

    Full Text Available Ships modify cloud microphysics by adding cloud condensation nuclei (CCN to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both west Africa and south-western Europe. In order to automate their detection within the Along Track Scanning Radiometer 2 (ATSR2 data set an algorithm was developed and integrated with the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of its neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR2 data. A month of results have been compared with other satellite datasets to validate the algorithm. There is a high ratio of false detections. Nevertheless the global distribution of ship tracks shows a similar pattern to the ship emissions distribution.

  11. An ASIFT-Based Local Registration Method for Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiangjun Wang

    2015-05-01

    Full Text Available Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion. Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE and better distribution of feature points.

  12. The development of a land use inventory for regional planning using satellite imagery

    Science.gov (United States)

    Hessling, A. H.; Mara, T. G.

    1975-01-01

    Water quality planning in Ohio, Kentucky, and Indiana is reviewed in terms of use of land use data and satellite imagery. A land use inventory applicable to water quality planning and developed through computer processing of LANDSAT-1 imagery is described.

  13. Casa Grande Ruins National Monument Vegetation Mapping Project - Quickbird Satellite Imagery

    Data.gov (United States)

    National Park Service, Department of the Interior — This imagery was acquired on December 3, 2007 by DigitalGlobe, Inc.'s Quickbird satellite. Its 4 multispectral bands (blue, green, red, near infrared), together with...

  14. Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau)....

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

  17. Nearshore Benthic Habitats of Timor-Leste Derived from WorldView-2 Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Benthic habitat classes were derived for nearshore waters around Timor-Leste from WorldView-2 satellite imagery. Habitat classes include different combinations of...

  18. Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Landsat...

  19. Use of satellite imagery to map and monitor vegetation in New Zealand

    OpenAIRE

    Stephens, P. R.; Dymond, J. R.; Brown, L J

    1995-01-01

    研究概要:Land resource and environmental decision makers require quantitative information on the spatial distribution of vegetation types and their condition, and changes in these over time. Such vegetation mapping and monitoring is often required to be undertaken quickly. Remotely-sensed satellite imagery, in conjunction with other data sources, have been used to satisfy this need. This paper describes the uses of satellite imagery by reference to three regional mapping projects in New Zealand. ...

  20. Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

    Science.gov (United States)

    Molthan, Andrew L.; Fuell, Kevin K.; Knaff, John; Lee, Thomas

    2012-01-01

    Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross

  1. APPLICABILITY EVALUATION OF OBJECT DETECTION METHOD TO SATELLITE AND AERIAL IMAGERIES

    Directory of Open Access Journals (Sweden)

    K. Kamiya

    2016-06-01

    Full Text Available Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

  2. Applicability Evaluation of Object Detection Method to Satellite and Aerial Imageries

    Science.gov (United States)

    Kamiya, K.; Fuse, T.; Takahashi, M.

    2016-06-01

    Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING) method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

  3. Global relation between microwave satellite vegetation products and vegetation productivity

    Science.gov (United States)

    Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Miralles, Diego G.; Dorigo, Wouter A.

    2017-04-01

    The occurrence of unfavourable environmental conditions like droughts commonly reduces the photosynthetic activity of ecosystems and, hence, their potential to take up carbon from the atmosphere. Ecosystem photosynthetic activity is commonly determined using remote sensing observations in the optical domain, which however have limitations particularly in regions of frequent cloud cover, e.g. the tropics. In this study, we explore the potential of vegetation optical depth (VOD) from microwave satellite observations as an alternative source for assessing vegetation productivity. VOD serves as an estimate for vegetation density and water content, which has an impact on plant physiological processes and hence should potentially provide a link to gross primary production (GPP). However, to date, it is unclear how microwave-retrieved VOD data and GPP data are related. We compare seasonal dynamics and anomalies of VOD retrievals from different satellite sensors and microwave frequencies with site level and global GPP estimates. We use VOD observations from active (ASCAT) and passive microwave sensors (AMSR-E, SMOS). We include eddy covariance measurements from the FLUXNET2015 dataset to assess the VOD products at site level. For a global scale analysis, we use the solar-induced chlorophyll fluorescence (SIF) observations from GOME-2 as a proxy for GPP and the FLUXCOM GPP product, which presents an upscaling of site measurements based on remote sensing data. Our results demonstrate that in general a good agreement between VOD and GPP or SIF exists. However, the strength of these relations depends on the microwave frequency, land cover type, and the time within the growing season. Correlations between anomalies of VOD and GPP or SIF support the assumption that microwave-derived VOD can be used to monitor vegetation productivity dynamics. The study is performed as part of the EOWAVE project funded by the Vienna University of Technology (http://eowave.geo.tuwien.ac.at/) and

  4. Demonstrative potential of multitemporal satellite imagery in documenting urban dynamics: generalisation from the Bucharest city case

    Science.gov (United States)

    Aldea, Mihaela; Petrescu, Florian; Parlow, Eberhard; Iacoboaea, Cristina; Luca, Oana; Sercaianu, Mihai; Gaman, Florian

    2016-08-01

    The main objective of this paper is to demonstrate the potential of multitemporal satellite imagery to be processed and used in documenting urban changes that took place over time, with limited resources involved and taking advantage of the opportunity to be able to use the satellite imagery available as open data. The possibilities to analyse and compare the written literature regarding the chronological evolution of a city with the patterns of Land Use/Land Cover obtained from the processing of satellite remotely sensed images of the respective scenery were investigated based upon a case study of a selected city. The extent of the prospects of using remote sensing based methods and multitemporal satellite imagery is also expressed as a result of this investigation.

  5. A review of uses of satellite imagery in monitoring mangrove forests

    Science.gov (United States)

    Rhyma Purnamasayangsukasih, P.; Norizah, K.; Ismail, Adnan A. M.; Shamsudin, I.

    2016-06-01

    Satellite image could provide much information of earth surfaces in a large scale in a short time, thus saving time. With the evolution and development of sensors providing satellite image, resolution of object captured enhanced with advance image processing techniques. In forestry, satellite image has been widely used for resources management, planning, monitoring, predicting, etc. However, the uses of satellite image are reported to be moderate and sometimes poor for mangrove forests due to homogenous species existed in salty and inundation areas. Many researches had been carried out to improve the uses of satellite imagery of either optical or radar data for mangrove forests. This paper reviews the uses of satellite imagery data in mangrove with the main focus of the literature related to mangroves monitoring.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  8. Non-contact and noise tolerant heart rate monitoring using microwave doppler sensor and range imagery.

    Science.gov (United States)

    Matsunag, Daichi; Izumi, Shintaro; Okuno, Keisuke; Kawaguchi, Hiroshi; Yoshimoto, Masahiko

    2015-01-01

    This paper describes a non-contact and noise-tolerant heart beat monitoring system. The proposed system comprises a microwave Doppler sensor and range imagery using Microsoft Kinect™. The possible application of the proposed system is a driver health monitoring. We introduce the sensor fusion approach to minimize the heart beat detection error. The proposed algorithm can subtract a body motion artifact from Doppler sensor output using time-frequency analysis. The body motion artifact is a crucially important problem for biosignal monitoring using microwave Doppler sensor. The body motion speed is obtainable from range imagery, which has 5-mm resolution at 30-cm distance. Measurement results show that the success rate of the heart beat detection is improved about 75% on average when the Doppler wave is degraded by the body motion artifact.

  9. Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

    Science.gov (United States)

    Wang, N.; Ferraro, R. R.

    2013-12-01

    Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

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

    Directory of Open Access Journals (Sweden)

    Usman Babawuro

    2012-07-01

    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.

  11. APPLYING SATELLITE IMAGERY TO TRIAGE ASSESSMENT OF ECOSYSTEM HEALTH

    Science.gov (United States)

    Considerable evidence documents that certain changes in vegetation and soils result in irreversibly degraded rangeland ecosystems. We used Advanced Very High Resolution Radiometer (AVHRR)imagery to develop calibration patterns of change in the Normalized Difference Vegetation Ind...

  12. A thermodynamic geography: night-time satellite imagery as a proxy measure of emergy.

    Science.gov (United States)

    Coscieme, Luca; Pulselli, Federico M; Bastianoni, Simone; Elvidge, Christopher D; Anderson, Sharolyn; Sutton, Paul C

    2014-11-01

    Night-time satellite imagery enables the measurement, visualization, and mapping of energy consumption in an area. In this paper, an index of the "sum of lights" as observed by night-time satellite imagery within national boundaries is compared with the emergy of the nations. Emergy is a measure of the solar energy equivalent used, directly or indirectly, to support the processes that characterize the economic activity in a country. Emergy has renewable and non-renewable components. Our results show that the non-renewable component of national emergy use is positively correlated with night-time satellite imagery. This relationship can be used to produce emergy density maps which enable the incorporation of spatially explicit representations of emergy in geographic information systems. The region of Abruzzo (Italy) is used to demonstrate this relationship as a spatially disaggregate case.

  13. The microwave limb sounder for the Upper Atmosphere Research Satellite

    Science.gov (United States)

    Waters, J. W.; Peckham, G. E.; Suttie, R. A.; Curtis, P. D.; Maddison, B. J.; Harwood, R. S.

    1988-01-01

    The Microwave Limb Sounder was designed to map the concentrations of trace gases from the stratosphere to the lower thermosphere, to improve understanding of the photochemical reactions which take place in this part of the atmosphere. The instrument will measure the intensity of thermal radiation from molecules in the atmosphere at frequencies corresponding to rotational absorption bands of chlorine monoxide, ozone, and water vapor. Molecular concentration profiles will be determined over a height range of 15 to 80 km (20 to 45 km for C10). The 57 deg inclination orbit proposed for the Upper Atmosphere Research Satellite will allow global coverage.

  14. Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

    Science.gov (United States)

    Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

    2016-12-16

    Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

  15. Satellite microwave observations of a storm complex: A comparative analysis

    Science.gov (United States)

    Martin, D. W.

    1985-01-01

    The hypothesis that cold events correspond to a particular stage in a class of thunderstorms was tested. That class is a storms class which updrafts are: (1) strong, broad and moist, and (2) extend well above the freezing level. Condition (1) implies strong mesoscale forcing. Condition (2) implies a tall updraft or a relatively low freezing level. Such storms should have big, intense radar echoes and cold, fast-growing anvils. The thunderstorm events were analyzed by radar, rain gauge and GOES infrared observations. Radar was the starting point for detection and definition of the hypothesized thunderstorms. The radar signature is compared to the signature of the storm in rain gauge observations, satellite infrared images and satellite microwave images.

  16. The Potential Uses of Commercial Satellite Imagery in the Middle East

    Energy Technology Data Exchange (ETDEWEB)

    Vannoni, M.G.

    1999-06-08

    It became clear during the workshop that the applicability of commercial satellite imagery to the verification of future regional arms control agreements is limited at this time. Non-traditional security topics such as environmental protection, natural resource management, and the development of infrastructure offer the more promising applications for commercial satellite imagery in the short-term. Many problems and opportunities in these topics are regional, or at least multilateral, in nature. A further advantage is that, unlike arms control and nonproliferation applications, cooperative use of imagery in these topics can be done independently of the formal Middle East Peace Process. The value of commercial satellite imagery to regional arms control and nonproliferation, however, will increase during the next three years as new, more capable satellite systems are launched. Aerial imagery, such as that used in the Open Skies Treaty, can also make significant contributions to both traditional and non-traditional security applications but has the disadvantage of requiring access to national airspace and potentially higher cost. There was general consensus that commercial satellite imagery is under-utilized in the Middle East and resources for remote sensing, both human and institutional, are limited. This relative scarcity, however, provides a natural motivation for collaboration in non-traditional security topics. Collaborations between scientists, businesses, universities, and non-governmental organizations can work at the grass-roots level and yield contributions to confidence building as well as scientific and economic results. Joint analysis projects would benefit the region as well as establish precedents for cooperation.

  17. Satellite Imagery Measures of the Astronomically Aligned Megaliths at Nabta Playa

    Science.gov (United States)

    Brophy, T. G.; Rosen, P. A.

    2003-12-01

    Astronomically aligned megalithic structures described in field reports (Wendorf, F. and Malville, J.M., The Megalith Alignments, pp.489-502 in Holocene Settlement of the Egyptian Sahara, Vol.I, 2001.) are identified in newly acquired georectified 60 cm panchromatic satellite imagery of Nabta Playa, southern Egypt. The satellite images allow refinement, often significant, of the reported locations of the megaliths. The report that the primary megalithic alignment was constructed to point to the bright star Sirius, circa 4,820 BC, is reconsidered in light of the satellite data, new field data, radiocarbon, lithostratigraphic and geochronologic data, and the playa sedimentation history. Other possible archaeoastronomical interpretations are considered for that alignment, including the three stars of Orion's Belt circa 6,270 BC that are also implicated in the small Nabta Playa `calendar circle'. Other new features apparent in the satellite imagery are also considered.

  18. Speckle filtering in satellite SAR change detection imagery

    NARCIS (Netherlands)

    Dekker, R.J.

    1998-01-01

    Repeat-pass Synthetic Aperture Radar (SAR) imagery is useful for change detection. A disadvantage of SAR is the system-inherent speckle noise. This can be reduced by filtering. Various filter types and methods are described in the literature, but not one fits the speckle noise in change detection

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

    Science.gov (United States)

    AlShamsi, Meera R.

    2016-10-01

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

  20. Antartic sea ice, 1973 - 1976: Satellite passive-microwave observations

    Science.gov (United States)

    Zwally, H. J.; Comiso, J. C.; Parkinson, C. L.; Campbell, W. J.; Carsey, F. D.; Gloersen, P.

    1983-01-01

    Data from the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite are used to determine the extent and distribution of Antarctic sea ice. The characteristics of the southern ocean, the mathematical formulas used to obtain quantitative sea ice concentrations, the general characteristics of the seasonal sea ice growth/decay cycle and regional differences, and the observed seasonal growth/decay cycle for individual years and interannual variations of the ice cover are discussed. The sea ice data from the ESMR are presented in the form of color-coded maps of the Antarctic and the southern oceans. The maps show brightness temperatures and concentrations of pack ice averaged for each month, 4-year monthly averages, and month-to-month changes. Graphs summarizing the results, such as areas of sea ice as a function of time in the various sectors of the southern ocean are included. The images demonstrate that satellite microwave data provide unique information on large-scale sea ice conditions for determining climatic conditions in polar regions and possible global climatic changes.

  1. The Upper Atmosphere Research Satellite microwave limb sounder instrument

    Science.gov (United States)

    Barath, F. T.; Chavez, M. C.; Cofield, R. E.; Flower, D. A.; Frerking, M. A.; Gram, M. B.; Harris, W. M.; Holden, J. R.; Jarnot, R. F.; Kloezeman, W. G.

    1993-01-01

    The microwave limb sounder (MLS) on the Upper Atmosphere Research Satellite (UARS) is the first satellite experiment using limb sounding techniques at microwave frequencies. Primary measurement objectives are stratospheric ClO, O3, H2O, temperature, and pressure. Measurements are of thermal emission: all are performed simultaneously and continuously and are not degraded by ice clouds or volcanic aerosols. The instrument has a 1.6-m mechanically scanning antenna system and contains heterodyne radiometers in spectral bands centred near 63, 183, and 205 GHz. The radiometers operate at ambient temperature and use Schottky-diode mixers with local oscillators derived from phase-locked Gunn oscillators. Frequency tripling by varactor multipliers generates the 183- and 205-GHz local oscillators, and quasi-optical techniques inject these into the mixers. Six 15-channel filter banks spectrally resolve stratospheric thermal emission lines and produce an output spectrum every 2 s. Thermal stability is sufficient for 'total power' measurements which do not require fast chopping. Radiometric calibration, consisting of measurements of cold space and an internal target, is performed every 65-s limb scan. Instrument in-orbit performance has been excellent, and all objectives are being met.

  2. The pan-sharpening of satellite and UAV imagery for agricultural applications

    Science.gov (United States)

    Jenerowicz, Agnieszka; Woroszkiewicz, Malgorzata

    2016-10-01

    Remote sensing techniques are widely used in many different areas of interest, i.e. urban studies, environmental studies, agriculture, etc., due to fact that they provide rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. Agricultural management is one of the most common application of remote sensing methods nowadays. Monitoring of agricultural sites and creating information regarding spatial distribution and characteristics of crops are important tasks to provide data for precision agriculture, crop management and registries of agricultural lands. For monitoring of cultivated areas many different types of remote sensing data can be used- most popular are multispectral satellites imagery. Such data allow for generating land use and land cover maps, based on various methods of image processing and remote sensing methods. This paper presents fusion of satellite and unnamed aerial vehicle (UAV) imagery for agricultural applications, especially for distinguishing crop types. Authors in their article presented chosen data fusion methods for satellite images and data obtained from low altitudes. Moreover the authors described pan- sharpening approaches and applied chosen pan- sharpening methods for multiresolution image fusion of satellite and UAV imagery. For such purpose, satellite images from Landsat- 8 OLI sensor and data collected within various UAV flights (with mounted RGB camera) were used. In this article, the authors not only had shown the potential of fusion of satellite and UAV images, but also presented the application of pan- sharpening in crop identification and management.

  3. Reconstruction of an infrared band of meteorological satellite imagery with abductive networks

    Science.gov (United States)

    Singer, Harvey A.; Cockayne, John E.; Versteegen, Peter L.

    1995-01-01

    As the current fleet of meteorological satellites age, the accuracy of the imagery sensed on a spectral channel of the image scanning system is continually and progressively degraded by noise. In time, that data may even become unusable. We describe a novel approach to the reconstruction of the noisy satellite imagery according to empirical functional relationships that tie the spectral channels together. Abductive networks are applied to automatically learn the empirical functional relationships between the data sensed on the other spectral channels to calculate the data that should have been sensed on the corrupted channel. Using imagery unaffected by noise, it is demonstrated that abductive networks correctly predict the noise-free observed data.

  4. Correcting Errors in Catchment-Scale Satellite Rainfall Accumulation Using Microwave Satellite Soil Moisture Products

    Science.gov (United States)

    Ryu, D.; Crow, W. T.

    2011-12-01

    Streamflow forecasting in the poorly gauged or ungauged catchments is very difficult mainly due to the absence of the input forcing data for forecasting models. This challenge poses a threat to human safety and industry in the areas where proper warning system is not provided. Currently, a number of studies are in progress to calibrate streamflow models without relying on ground observations as an effort to construct a streamflow forecasting systems in the ungauged catchments. Also, recent advances in satellite altimetry and innovative application of the optical has enabled mapping streamflow rate and flood extent in the remote areas. In addition, remotely sensed hydrological variables such as the real-time satellite precipitation data, microwave soil moisture retrievals, and surface thermal infrared observations have the great potential to be used as a direct input or signature information to run the forecasting models. In this work, we evaluate a real-time satellite precipitation product, TRMM 3B42RT, and correct errors of the product using the microwave satellite soil moisture products over 240 catchments in Australia. The error correction is made by analyzing the difference between output soil moisture of a simple model forced by the TRMM product and the satellite retrievals of soil moisture. The real-time satellite precipitation products before and after the error correction are compared with the daily gauge-interpolated precipitation data produced by the Australian Bureau of Meteorology. The error correction improves overall accuracy of the catchment-scale satellite precipitation, especially the root mean squared error (RMSE), correlation, and the false alarm ratio (FAR), however, only a marginal improvement is observed in the probability of detection (POD). It is shown that the efficiency of the error correction is affected by the surface vegetation density and the annual precipitation of the catchments.

  5. Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

    Science.gov (United States)

    Dryden, Rachel L.; Molthan, Andrew L.; Cole, Tony A.; Bell, Jordan R.

    2014-01-01

    Hail scars are identifiable in MODIS satellite imagery based on NDVI change, which was dominantly negative. Hail damage spatially correlates with SPC hail reports and MESH. This study developed a proxy for quantifying crop loss at varying thresholds to address the gap between SPC damage estimates and insurance payouts.

  6. Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  7. Detection of ZY-3 Satellite Platform Jitter Using Multi-spectral Imagery

    Directory of Open Access Journals (Sweden)

    ZHU Ying

    2015-04-01

    Full Text Available Satellite platform jitter is one of the factors that affect the quality of high resolution imagery, which can cause image blur and internal distortion. Taking ZiYuan-3 (ZY-3 multi-spectral camera as a prototype, this paper proposes a satellite platform jitter detection method by utilizing multi-spectral imagery. First, imaging characteristics of multispectral camera and the main factors affecting band-to-band registration error are introduced. Then the regularity of registration error caused by platform jitter is analyzed by theoretical derivation and simulation. Meanwhile, the platform jitter detection method based on high accuracy dense points matching is presented. Finally, the experiments were conducted by using ZY-3 multi-spectral imagery captured in different time. The result indicates that ZY-3 has a periodic platform jitter about 0.6 Hz in the imaging period of test data, and the jitter amplitude across track is greater than that along track, which causes periodic band-to-band registration error with the same frequency. The result shows the possibility of the improvement in geometric processing accuracy for ZY-3 imagery products and provides an important reference for satellite platform jitter source analysis and satellite platform design optimization.

  8. A data mining approach for sharpening satellite thermal imagery over land

    Science.gov (United States)

    Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

  9. De-noising of microwave satellite soil moisture time series

    Science.gov (United States)

    Su, Chun-Hsu; Ryu, Dongryeol; Western, Andrew; Wagner, Wolfgang

    2013-04-01

    The use of satellite soil moisture data for scientific and operational hydrologic, meteorological and climatological applications is advancing rapidly due to increasing capability and temporal coverage of current and future missions. However evaluation studies of various existing remotely-sensed soil moisture products from these space-borne microwave sensors, which include AMSR-E (Advanced Microwave Scanning Radiometer) on Aqua satellite, SMOS (Soil Moisture and Ocean Salinity) mission and ASCAT (Advanced Scatterometer) on MetOp-A satellite, found them to be significantly different from in-situ observations, showing large biases and different dynamic ranges and temporal patterns (e.g., Albergel et al., 2012; Su et al., 2012). Moreover they can have different error profiles in terms of bias, variance and correlations and their performance varies with land surface characteristics (Su et al., 2012). These severely impede the effort to use soil moisture retrievals from multiple sensors concurrently in land surface modelling, cross-validation and multi-satellite blending. The issue of systematic errors present in data sets should be addressed prior to renormalisation of the data for blending and data assimilation. Triple collocation estimation technique has successfully yielded realistic error estimates (Scipal et al., 2008), but this method relies on availability of large number of coincident data from multiple independent satellite data sets. In this work, we propose, i) a conceptual framework for distinguishing systematic periodic errors in the form of false spectral resonances from non-systematic errors (stochastic noise) in remotely-sensed soil moisture data in the frequency domain; and ii) the use of digital filters to reduce the variance- and correlation-related errors in satellite data. In this work, we focus on the VUA-NASA (Vrije Universiteit Amsterdam with NASA) AMSR-E, CATDS (Centre National d'Etudes Spatiales, CNES) SMOS and TUWIEN (Vienna University of

  10. Fully automated procedure for ship detection using optical satellite imagery

    Science.gov (United States)

    Corbane, C.; Pecoul, E.; Demagistri, L.; Petit, M.

    2009-01-01

    Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the framework of a European integrated project GMES-Security/LIMES, we developed an operational ship detection algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing control system. The automatic detection model is based on statistical methods, mathematical morphology and other signal processing techniques such as the wavelet analysis and Radon transform. This paper presents current progress made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on panchromatic SPOT 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship detection strategies.

  11. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Solna (Sweden)

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  12. Visualization and unsupervised classification of changes in multispectral satellite imagery

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2006-01-01

    The statistical techniques of multivariate alteration detection, minimum/maximum autocorrelation factors transformation, expectation maximization and probabilistic label relaxation are combined in a unified scheme to visualize and to classify changes in multispectral satellite data. The methods...

  13. Unsupervised classification of changes in multispectral satellite imagery

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2004-01-01

    The statistical techniques of multivariate alteration detection, maximum autocorrelation factor transformation, expectation maximization, fuzzy maximum likelihood estimation and probabilistic label relaxation are combined in a unified scheme to classify changes in multispectral satellite data...

  14. Visualization and unsupervised classification of changes in multispectral satellite imagery

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2006-01-01

    The statistical techniques of multivariate alteration detection, minimum/maximum autocorrelation factors transformation, expectation maximization and probabilistic label relaxation are combined in a unified scheme to visualize and to classify changes in multispectral satellite data. The methods...

  15. Epipolar Resampling of Cross-Track Pushbroom Satellite Imagery Using the Rigorous Sensor Model.

    Science.gov (United States)

    Jannati, Mojtaba; Valadan Zoej, Mohammad Javad; Mokhtarzade, Mehdi

    2017-01-11

    Epipolar resampling aims to eliminate the vertical parallax of stereo images. Due to the dynamic nature of the exterior orientation parameters of linear pushbroom satellite imagery and the complexity of reconstructing the epipolar geometry using rigorous sensor models, so far, no epipolar resampling approach has been proposed based on these models. In this paper for the first time it is shown that the orientation of the instantaneous baseline (IB) of conjugate image points (CIPs) in the linear pushbroom satellite imagery can be modeled with high precision in terms of the rows- and the columns-number of CIPs. Taking advantage of this feature, a novel approach is then presented for epipolar resampling of cross-track linear pushbroom satellite imagery. The proposed method is based on the rigorous sensor model. As the instantaneous position of sensors remains fixed, the digital elevation model of the area of interest is not required in the resampling process. Experimental results obtained from two pairs of SPOT and one pair of RapidEye stereo imagery with different terrain conditions shows that the proposed epipolar resampling approach benefits from a superior accuracy, as the remained vertical parallaxes of all CIPs in the normalized images are close to zero.

  16. Epipolar Resampling of Cross-Track Pushbroom Satellite Imagery Using the Rigorous Sensor Model

    Directory of Open Access Journals (Sweden)

    Mojtaba Jannati

    2017-01-01

    Full Text Available Epipolar resampling aims to eliminate the vertical parallax of stereo images. Due to the dynamic nature of the exterior orientation parameters of linear pushbroom satellite imagery and the complexity of reconstructing the epipolar geometry using rigorous sensor models, so far, no epipolar resampling approach has been proposed based on these models. In this paper for the first time it is shown that the orientation of the instantaneous baseline (IB of conjugate image points (CIPs in the linear pushbroom satellite imagery can be modeled with high precision in terms of the rows- and the columns-number of CIPs. Taking advantage of this feature, a novel approach is then presented for epipolar resampling of cross-track linear pushbroom satellite imagery. The proposed method is based on the rigorous sensor model. As the instantaneous position of sensors remains fixed, the digital elevation model of the area of interest is not required in the resampling process. Experimental results obtained from two pairs of SPOT and one pair of RapidEye stereo imagery with different terrain conditions shows that the proposed epipolar resampling approach benefits from a superior accuracy, as the remained vertical parallaxes of all CIPs in the normalized images are close to zero.

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

    Science.gov (United States)

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

    2015-10-01

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

  18. Study of the Nevada Test Site using Landsat satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Zimmerman, P.D. [Georgetown Univ., Washington, DC (United States). Center for Strategic and International Studies

    1993-07-01

    In the period covered by the purchase order CSIS has obtained one Landsat image and determined that two images previously supplied to the principal investigator under a subcontract with George Washington University were inherently defective. We have negotiated with EOSAT over the reprocessing of those scenes and anticipate final delivery within the next few weeks. A critical early purchase during the subcontract period was of an EXABYTE tape drive, Adaptec SCSI interface, and the appropriate software with which to read Landsat images at CSIS. This gives us the capability of reading and manipulating imagery in house without reliance on outside services which have not proven satisfactory. In addition to obtaining imagery for the study, we have also performed considerable analytic work on the newly and previously purchased images. A technique developed under an earlier subcontract for identifying underground nuclear tests at Pahute Mesa has been significantly refined, and similar techniques were applied to the summit of Rainier Mesa and to the Yucca Flats area. An entirely new technique for enhancing the spectral signatures of different regions of NTS was recently developed, and appears to have great promise of success.

  19. Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery

    Science.gov (United States)

    Kit, Oleksandr; Lüdeke, Matthias

    2013-09-01

    This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.

  20. Extracting cosmic microwave background polarisation from satellite astrophysical maps

    CERN Document Server

    Baccigalupi, C; De Zotti, G; Smoot, G F; Burigana, C; Maino, D; Bedini, L; Salerno, E

    2002-01-01

    We present the application of the Fast Independent Component Analysis technique for blind component separation to polarised astrophysical emission. We study how the Cosmic Microwave Background (CMB) polarised signal, consisting of $E$ and $B$ modes, can be extracted from maps affected by substantial contamination from diffuse Galactic foregrounds and instrumental noise. We perform the analysis of all sky maps simulated accordingly to the nominal performances of the Low Frequency Instrument (LFI) aboard the Planck satellite; the sky signal is modeled as a superposition of CMB, generated by a Gaussian, nearly scale invariant cosmological perturbation spectrum, and the existing simulated polarisation templates of Galactic synchrotron. Our results indicate that the angular power spectrum of CMB $E$ modes can be recovered on all scales up to $\\ell\\simeq 1000$, corresponding to the fourth acoustic oscillation, while $B$ modes can be detected, up to their turnover at $\\ell\\simeq 100$ if cosmological tensor amplitude...

  1. Satellite orientation and position for geometric correction of scanner imagery.

    Science.gov (United States)

    Salamonowicz, P.H.

    1986-01-01

    The USGS Mini Image Processing System currently relies on a polynomial method for geometric correction of Landsat multispectral scanner (MSS) data. A large number of ground control points are required because polynomials do not model the sources of error. In order to reduce the number of necessary points, a set of mathematical equations modeling the Landsat satellite motions and MSS scanner has been derived and programmed. A best fit to the equations is obtained by using a least-squares technique that permits computation of the satellite orientation and position parameters based on only a few control points.-from Author

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

    Science.gov (United States)

    Gong, K.; Fritsch, D.

    2016-06-01

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

  3. Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

    Science.gov (United States)

    Wang, N. Y.; You, Y.; Ferraro, R. R.

    2015-12-01

    Precipitation plays a key role in the earth's climate system, particularly in the aspect of its water and energy balance. Satellite microwave (MW) observations of precipitation provide a viable mean to achieve global measurement of precipitation with sufficient sampling density and accuracy. However, accurate precipitation information over land from satellite MW is a challenging problem. The Goddard Profiling Algorithm (GPROF) algorithm for the Global Precipitation Measurement (GPM) is built around the Bayesian formulation (Evans et al., 1995; Kummerow et al., 1996). GPROF uses the likelihood function and the prior probability distribution function to calculate the expected value of precipitation rate, given the observed brightness temperatures. It is particularly convenient to draw samples from a prior PDF from a predefined database of observations or models. GPROF algorithm does not search all database entries but only the subset thought to correspond to the actual observation. The GPM GPROF V1 database focuses on stratification by surface emissivity class, land surface temperature and total precipitable water. However, there is much uncertainty as to what is the optimal information needed to subset the database for different conditions. To this end, we conduct a database stratification study of using National Mosaic and Multi-Sensor Quantitative Precipitation Estimation, Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Technology Microwave Sounder (ATMS) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA). Our database study (You et al., 2015) shows that environmental factors such as surface elevation, relative humidity, and storm vertical structure and height, and ice thickness can help in stratifying a single large database to smaller and more homogeneous subsets, in which the surface condition and precipitation vertical profiles are similar. It is found that the probability of detection (POD) increases

  4. A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery

    Directory of Open Access Journals (Sweden)

    Kaveh Shahi

    2015-06-01

    Full Text Available This research develops a spectral index to automatically extract asphalt road networks named road extraction index (REI. This index uses WorldView-2 (WV-2 imagery, which has high spatial resolution and is multispectral. To determine the best bands for WV-2, field spectral data using a field spectroradiometer were collected. These data were then analyzed statistically. The bands were selected through the methodology of stepwise discriminant analysis. The appropriate WV-2 bands were distinguished from one another as per significant wavelengths. The proposed index is based on this classification. By applying REI to WV-2 imagery, we can extract asphalt roads accurately. Results demonstrate that REI is automated, transferable, and efficient in asphalt road extraction from high-resolution satellite imagery.

  5. The Application Achievements And Perspective Of CBERS Series Satellite Imagery

    Institute of Scientific and Technical Information of China (English)

    Li Xingchao; Qi Xueyong; Lu Yilin

    2009-01-01

    @@ Since the first China-Brazil Earth Resources Satellite (CBERS-1),launched in 1999,the CBERS data has been applied in many fields extensively.Remarkable social and economic benefits have been achieved.This article presents the application achievements during the past nine years,and gives a perspective for the future.All these applications demonstrate that the CBERS data has been an important data source for resources investigation and monitoring.

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

    Directory of Open Access Journals (Sweden)

    HAN Jie

    2016-12-01

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

  7. Detecting inter-annual variability in the phenological characteristics of southern Africa’s vegetation using satellite imagery

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2011-01-01

    Full Text Available Vegetation phenology refers to the timing of seasonal biological events (for example, bud burst, leaf unfolding, vegetation growth and leaf senescence) and biotic and abiotic forces that control these. Daily, coarse-resolution satellite imagery...

  8. A geographic investigation of hazards, disasters and recovery using satellite imagery

    Science.gov (United States)

    Keys-Mathews, Lisa D.

    Disaster recovery is depicted on the landscape by change through time. Given the classic uses of remote sensing for detecting change, this dissertation assessed the applicability of remote sensing image analysis to the study of long-term recovery from disasters. Because recovery is complex and dynamic a framework was that established that divided the recovery landscape into three components: the built, relief, and natural environments. Four study sites were selected for this research representing three types of hazard events (earthquakes, tsunami and hurricane), three climatic environments (tropical, dry and humid subtropical), and four cultures (Iran, Indonesia, Peru and the United States). The four disasters occurred between 2001 and 2005 with each a catastrophic event. To begin the research, a list of diagnostic features of recovery was created through field observations, reconnaissance reports, descriptions of disaster recovery case studies, and current literature. These features were then documented in the satellite imagery as examples of their portrayal on the landscape. Second, elements of each environment (built, relief, and natural) were explored through application of digital image processing techniques including: principal components analysis, texture analysis, normalized differenced vegetation index, and digital image classification. Each of these techniques was applied to the imagery with the final results being a digital analysis through time. Finally, the analysis was integrated to determine if differential recovery was visible through the analysis of satellite imagery. This neighborhood scale investigation compared satellite imagery findings to a rapid visual assessment in Gulfport and synthesized the findings toward an understanding of differential recovery. This dissertation determined that satellite imagery and remote sensing techniques supported by fieldwork are appropriate and valuable tools in the study of disaster recovery. Features and

  9. Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

    Science.gov (United States)

    Dryden, Rachel L.; Molthan, Andrew L.; Cole, Tony A.; Bell, Jordan

    2014-01-01

    Severe thunderstorms can produce large hail that causes property damage, livestock fatalities, and crop failure. However, detailed storm surveys of hail damage conducted by the National Weather Service (NWS) are not required. Current gaps also exist between Storm Prediction Center (SPC) hail damage estimates and crop-insurance payouts. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra and Aqua satellites can be used to support NWS damage assessments, particularly to crops during the growing season. The two-day severe weather event across western Nebraska and central Kansas during 9-10 August 2011 offers a case study for investigating hail damage signatures by examining changes in Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery. By analyzing hail damage swaths in satellite imagery, potential economic losses due to crop damage can be quantified and further improve the estimation of weather impacts on agriculture without significantly increasing manpower requirements.

  10. Progress of research to identify rotating thunderstorms using satellite imagery

    Science.gov (United States)

    Anderson, Charles E.

    1988-01-01

    The possibility of detecting potentially tornadic thunderstorm cells from geosynchronous satelite imagery is determined. During the life of the contract, we examined eight tornado outbreak cases which had a total of 124 individual thunderstorm cells, 37 of which were tornadic.These 37 cells produced a total of 119 tornadoes. The outflow characteristics of all the cells were measured. Through the use of a 2-D flow field model, we were able to simulate the downstream developmemt of an anvil cloud plume which was emitted by the storm updraft at or near the tropopause. We used two parameters to characterize the anvil plume behavior: its speed of downstream propagation (U max) and the clockwise deviation of the centerline of the anvil plume from the storm relative ambient wind at the anvil plume outflow level (MDA). U max was the maximum U-component of the anvil wind parameter required to successfully maintain an envelope of translating particles at the tip of the expanding anvil cloud. MDA was the measured deviation angle acquired from McIDAS, between the storm relative ambient wind direction and the storm relative anvil plume outflow direction; tha latter being manipulated by controlling a tangential wind component to force the envelope of particles to maintain their position of surrounding the expanding outflow cloud.

  11. Needs for registration and rectification of satellite imagery for land use and land cover and hydrologic applications

    Science.gov (United States)

    Gaydos, L.

    1982-01-01

    The use of satellite imagery and data for registration of land use, land cover and hydrology was discussed. Maps and aggregations are made from existing the data in concert with other data in a geographic information system. Basic needs for registration and rectification of satellite imagery related to specifying, reformatting, and overlaying the data are noted. It is found that the data are sufficient for users who must expand much effort in registering data.

  12. Geospatial Information from Satellite Imagery for Geovisualisation of Smart Cities in India

    Science.gov (United States)

    Mohan, M.

    2016-06-01

    In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

  13. Commercial Imagery Satellite Threat: How Can U.S. Forces Protect Themselves?

    Science.gov (United States)

    2006-05-31

    10 Joint Chiefs of Staff, Joint Warfare of the Armed Forces of the United States, Appendix B. 11 Laurence Nardon, "The Dilemma of...January 2004]. Nardon, Laurence . "The Dilemma of Satellite Imagery Control." Military Technology, July 2002, 37-46. National Defense Panel...34 Fact Sheet. Washington DC: White House, 13 May 2003. <http://www.au.af.mil/au/awc/awcgate/space/ 2003remotesensing.htm> [3 December 2003]. Rees

  14. GEOSPATIAL INFORMATION FROM SATELLITE IMAGERY FOR GEOVISUALISATION OF SMART CITIES IN INDIA

    Directory of Open Access Journals (Sweden)

    M. Mohan

    2016-06-01

    Full Text Available In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

  15. Estimating Monthly Rainfall from Geostationary Satellite Imagery Over Amazonia, Brazil.

    Science.gov (United States)

    Cutrim, Elen Maria Camara

    The infrared regression and the grid-history satellite rainfall estimating techniques were utilized to estimate monthly rainfall in Amazonia during one month of the rainy season (March, 1980) and one month of the dry season (September, 1980). The estimates were based on 3-hourly SMS-II infrared and visible images. Three sets of coefficients for the grid history method (Marajo, Arabian Sea, and GATE) were used to estimate rainfall. The estimated rain was compared with gauge measurements over the region. The infrared regression technique overestimated by a factor of 1.5. The Marajo coefficients yielded the best estimate, especially for eastern Amazonia. In the wet month Marajo coefficients overestimated rain by 10% and in the dry month by 70%. The Arabian Sea coefficients overestimated rain and the GATE coefficients slightly underestimated rain for Amazonia. Two maps of monthly rainfall over Amazonia were constructed for March and September, 1980, combining the ground station and satellite inferred rainfall of the grid history method using the Marajo coefficients. The satellite observations and ground data were mutually compatible and were contourable on these final, composite maps. Monthly rainfall was found to be much more inhomogeneous than previously reported. In March there was a belt of high precipitation trending southwest, with higher values and sharpest gradients in the coastal area. The upper Amazon was also an area of high precipitation, both north and south of the equator. In Roraima rainfall decreased drastically to the north. In September, the area of highest precipitation was the northwestern part of Amazonas State (northern hemisphere). Rainfall elsewhere was very localized and in northeastern Amazonia varied from 0 to 150 mm. Even though the grid history method presented better results for estimating rainfall over Amazonia, the IR model could be utilized more efficiently and economically on an operational basis if the calibration were properly made

  16. Modelling tick abundance using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Kjær, Lene Jung; Korslund, L.; Kjelland, V.

    satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution (presence/absence of ticks) and relative tick abundance of nymphs and larvae in southern Scandinavia. For nymphs, the predicted abundance had a positive correlation with observed abundance...... the predicted distribution of larvae was mostly even throughout Denmark, it was primarily around the coastlines in Norway and Sweden. Abundance was fairly low overall except in some fragmented patches corresponding to forested habitats in the region. Machine learning techniques allow us to predict for larger...... the collected ticks for pathogens and using the same machine learning techniques to develop prevalence maps of the ScandTick region....

  17. SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8

    Directory of Open Access Journals (Sweden)

    A. Fryskowska

    2016-06-01

    Full Text Available The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI and the Thermal Infrared Sensor (TIRS. What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands. Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5‐0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4‐0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2 and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.

  18. Forests through the Eye of a Satellite: Understanding regional forest-cover dynamics using Landsat Imagery

    Science.gov (United States)

    Baumann, Matthias

    Forests are changing at an alarming pace worldwide. Forests are an important provider of ecosystem services that contribute to human wellbeing, including the provision of timber and non-timber products, habitat for biodiversity, recreation amenities. Most prominently, forests serve as a sink for atmospheric carbon dioxide that ultimately helps to mitigate changes in the global climate. It is thus important to understand where, how and why forests change worldwide. My dissertation provides answers to these questions. The overarching goal of my dissertation is to improve our understanding of regional forest-cover dynamics by analyzing Landsat satellite imagery. I answer where forests change following drastic socio-economic shocks by using the breakdown of the Soviet Union as a natural experiment. My dissertation provides innovative algorithms to answer why forests change---because of human activities or because of natural events such as storms. Finally, I will show how dynamic forests are within one year by providing ways to characterize green-leaf phenology from satellite imagery. With my findings I directly contribute to a better understanding of the processes on the Earth's surface and I highlight the importance of satellite imagery to learn about regional and local forest-cover dynamics.

  19. Polar bears from space: assessing satellite imagery as a tool to track Arctic wildlife.

    Directory of Open Access Journals (Sweden)

    Seth Stapleton

    Full Text Available Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark-recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105 was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152. Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

  20. Plastic and Glass Greenhouses Detection and Delineation from WORLDVIEW-2 Satellite Imagery

    Science.gov (United States)

    Koc-San, D.; Sonmez, N. K.

    2016-06-01

    Greenhouse detection using remote sensing technologies is an important research area for yield estimation, sustainable development, urban and rural planning and management. An approach was developed in this study for the detection and delineation of greenhouse areas from high resolution satellite imagery. Initially, the candidate greenhouse patches were detected using supervised classification techniques. For this purpose, Maximum Likelihood (ML), Random Forest (RF), and Support Vector Machines (SVM) classification techniques were applied and compared. Then, sieve filter and morphological operations were performed for improving the classification results. Finally, the obtained candidate plastic and glass greenhouse areas were delineated using boundary tracing and Douglas Peucker line simplification algorithms. The proposed approach was implemented in the Kumluca district of Antalya, Turkey utilizing pan-sharpened WorldView-2 satellite imageries. Kumluca is the prominent district of Antalya with greenhouse cultivation and includes both plastic and glass greenhouses intensively. When the greenhouse classification results were analysed, it can be stated that the SVM classification provides most accurate results and RF classification follows this. The SVM classification overall accuracy was obtained as 90.28%. When the greenhouse boundary delineation results were considered, the plastic greenhouses were delineated with 92.11% accuracy, while glass greenhouses were delineated with 80.67% accuracy. The obtained results indicate that, generally plastic and glass greenhouses can be detected and delineated successfully from WorldView-2 satellite imagery.

  1. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Solna (Sweden)

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  2. Performance Evaluation of Data Compression Systems Applied to Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Lilian N. Faria

    2012-01-01

    Full Text Available Onboard image compression systems reduce the data storage and downlink bandwidth requirements in space missions. This paper presents an overview and evaluation of some compression algorithms suitable for remote sensing applications. Prediction-based compression systems, such as DPCM and JPEG-LS, and transform-based compression systems, such as CCSDS-IDC and JPEG-XR, were tested over twenty multispectral (5-band images from CCD optical sensor of the CBERS-2B satellite. Performance evaluation of these algorithms was conducted using both quantitative rate-distortion measurements and subjective image quality analysis. The PSNR, MSSIM, and compression ratio results plotted in charts and the SSIM maps are used for comparison of quantitative performance. Broadly speaking, the lossless JPEG-LS outperforms other lossless compression schemes, and, for lossy compression, JPEG-XR can provide lower bit rate and better tradeoff between compression ratio and image quality.

  3. Physical effect of cloud seeding revealed by NOAA satellite imagery

    Institute of Scientific and Technical Information of China (English)

    YU Xing; DAI Jin; LEI Hengchi; XU Xiaohong; FAN Peng; CHEN Zhengqi; DUAN Changhui; WANG Yong

    2005-01-01

    From 0615 to 0749 UTC, 14 March 2000, a precipitation enhancement operation with AgI using an aircraft was conducted at the middle part of Shaanxi Province, China. 80 min after cloud seeding (0735 UTC), NOAA-14 satellite data showed a vivid zigzag cloud track on the satellite image. Its length is 301 km, and its average and maximum width are 8.3 and 11 km. The cloud track is very similar in shape with, but different in position and width from that of cloud seeding line. In order to determine that the cloud track is indeed caused by cloud seeding, a three-dimensional numerical model of transport and diffusion of seeding material is used to simulate the shape of seeding material concentration distribution, the turning points, width and length of seeding line. The simulated results are compared with the features of cloud track at 0735 UTC. Every segment of the cloud track is consistent with the transport and diffusion of every segment of seeding line. The transport position, length, width and the variation trend of seeding line agree with those of cloud track. All suggest that the cloud track is the direct physical reflection of cloud seeding effect on the cloud top, which can respond to the transport and diffusion of seeding material. For this study case, the main effecting duration for every segment of seeding line is from 20 to 80 min, the time for each segment of seeding line diffusing to the maximum width is from about 50 to 70 min. This time is obtained from the appearing and disappearing time, width variation of the cloud track segments and simulated results. Also, the comparisons demonstrate that the numerical model of transport and diffusion can simulate the main characteristics of transport and diffusion of seeding material, and the simulating results are sound and trustworthy.

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

    Science.gov (United States)

    LaRue, Michelle Ann

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

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

    Directory of Open Access Journals (Sweden)

    Nahuel R. Peralta

    2016-10-01

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

  6. River-ice and sea-ice velocity fields from near-simultaneous satellite imagery

    Science.gov (United States)

    Kaeaeb, A.; Leprince, S.; Prowse, T. D.; Beltaos, S.; Lamare, M.; Abrams, M.

    2013-12-01

    Satellite stereo and satellites that follow each other on similar orbits within short time periods produce near-simultaneous space imagery, a kind of data that is little exploited. In this study, we track river-ice and sea-ice motion over time periods of tens of seconds to several minutes, which is the typical time lag between the two or more images of such near-simultaneous acquisition constellations. Using this novel approach, we measure and visualize for the first time the almost complete two-dimensional minute-scale velocity fields over several thousand square-kilometers of sea ice cover or over up to several hundred kilometers long river reaches. We present the types of near-simultaneous imagery and constellations suitable for the measurements and discuss application examples, using a range of high and medium resolution imagery such as from ASTER, ALOS PRISM, Ikonos, WorldView-2, Landsat and EO-1. The river ice velocities obtained provide new insights into ice dynamics, river flow and river morphology, in particular during ice breakup. River-ice breakup and the associated downstream transport of ice debris is often the most important hydrological event of the year, producing flood levels that commonly exceed those for the open-water period and dramatic consequences for river infrastructure and ecology. We also estimate river discharge from ice/water surface velocities using near-simultaneous satellite imagery. Our results for sea ice complement velocity fields typically obtained over time-scales of days and can thus contribute to better understanding of a number of processes involved in sea ice drift, such as wind impact, tidal currents and interaction of ice floes with each other and with obstacles.

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

    Science.gov (United States)

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

    2015-12-01

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

  8. Integrated snow and avalanche monitoring syatem for Indian Himalaya using multi-temporal satellite imagery and ancillary data

    Science.gov (United States)

    Sharma, S. S.; Mani, Sneh; Mathur, P.

    The variations in the local climate, environment and altitude as well as fast snow cover build up and rapid changes in snow characteristics with passage of winter are major contributing factors to make snow avalanches as one of the threatening problems in the North West Himalaya. For sustainable development of these mountainous areas, a number of multi-purpose projects are being planned. In recent times, the danger of natural and man-made hazards is increasing and the availability of water is fluctuating; and thus, making the project implementation difficult. To overcome these difficulties to a great extent, an integrated monitoring system is required for short term as well as long term assessment of snowcover variation and avalanche hazard. In order to monitor the spatial extent of snow cover, satellite data can be employed on an operational basis. Spectral settings as well as the temporal and spatial resolution make time series NOAA-AVHHR and MODIS sensor data well suited for operational snow cover monitoring at regional or continental scale; Indian Remote Sensing Satellite (IRS) LISS, WiFS and AWiFS sensor data suitable for studies at larger scale; and microwave data for extraction of snow wetness information.. In the present paper, an attempt is made to study the trends of changes in snow characteristics and related avalanche phenomenon using time series multi-temporal, multi-resolution satellite data with respect to different ranges in Western Himalaya, namely Pir Panjal range, Great Himalaya range, Zanskar range, Ladakh range and Great Karakoram range. The operational processing of these data included geocoding, calibration, terrain normalization, classification, statistical post classification and derivation of snow cover statistics. The calibration and normalization of imageries allowed the application of physically based classification thresholds possible for albedo, brightness temperature and the Normalized Difference Snow Index (NDSI) parameters

  9. Integrated snow and avalanche monitoring system for Indian Himalaya using multi-temporal satellite imagery and ancillary data

    Science.gov (United States)

    Sharma, S. S.; Mani, Sneh; Mathur, P.

    The variations in the local climate, environment and altitude as well as fast snow cover build up and rapid changes in snow characteristics with passage of winter are major contributing factors to make snow avalanches as one of the threatening problems in the North West Himalaya. For sustainable development of these mountainous areas, a number of multi-purpose projects are being planned. In recent times, the danger of natural and man-made hazards is increasing and the availability of water is fluctuating; and thus, making the project implementation difficult. To overcome these difficulties to a great extent, an integrated monitoring system is required for short term as well as long term assessment of snowcover variation and avalanche hazard. In order to monitor the spatial extent of snow cover, satellite data can be employed on an operational basis. Spectral settings as well as the temporal and spatial resolution make time series NOAA-AVHHR and MODIS sensor data well suited for operational snow cover monitoring at regional or continental scale; Indian Remote Sensing Satellite (IRS) LISS, WiFS and AWiFS sensor data suitable for studies at larger scale; and microwave data for extraction of snow wetness information.. In the present paper, an attempt is made to study the trends of changes in snow characteristics and related avalanche phenomenon using time series multi-temporal, multi-resolution satellite data with respect to different ranges in Western Himalaya, namely Pir Panjal range, Great Himalaya range, Zanskar range, Ladakh range and Great Karakoram range. The operational processing of these data included geocoding, calibration, terrain normalization, classification, statistical post classification and derivation of snow cover statistics. The calibration and normalization of imageries allowed the application of physically based classification thresholds possible for albedo, brightness temperature and the Normalized Difference Snow Index (NDSI) parameters

  10. Rice yield forecasting models using satellite imagery in Egypt

    Directory of Open Access Journals (Sweden)

    N.A. Noureldin

    2013-06-01

    Full Text Available Ability to make yield prediction before harvest using satellite remote sensing is important in many aspects of agricultural decision-making. In this study, canopy reflectance band and different band ratios in form of vegetation indices (VI with leaf area index (LAI were used to generate remotely sensed pre-harvest empirical rice yield prediction models. LAI measurements, spectral data derived from two SPOT data acquired on August 24, 2008 and August 23, 2009 and observed rice yield were used as main inputs for rice yield modeling. Each remotely sensed factor was used separately and in combination with LAI to generate the models. The results showed that green spectral band, middle infra-red spectral band and green vegetation index (GVI did not show sufficient capability as rice yield estimators while other inputs such as red spectral band, near infrared spectral band and vegetation indices that are algebraic ratios from these two spectral bands when used separately or in combined with leaf area index (LAI produced high accurate rice yield estimation models. The validation process was carried out using two statistical tests; standard error of estimate and the correlation coefficient between modeled and predicted yield. The validation results indicated that using normalized difference vegetation index (NDVI combined with leaf area index (LAI produced the model with highest accuracy and stability during the two rice seasons. The generated models are applicable 90 days after planting in any similar environmental conditions and agricultural practices.

  11. Man-made objects cuing in satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2009-01-01

    We present a multi-scale framework for man-made structures cuing in satellite image regions. The approach is based on a hierarchical image segmentation followed by structural analysis. A hierarchical segmentation produces an image pyramid that contains a stack of irregular image partitions, represented as polygonized pixel patches, of successively reduced levels of detail (LOOs). We are jumping off from the over-segmented image represented by polygons attributed with spectral and texture information. The image is represented as a proximity graph with vertices corresponding to the polygons and edges reflecting polygon relations. This is followed by the iterative graph contraction based on Boruvka's Minimum Spanning Tree (MST) construction algorithm. The graph contractions merge the patches based on their pairwise spectral and texture differences. Concurrently with the construction of the irregular image pyramid, structural analysis is done on the agglomerated patches. Man-made object cuing is based on the analysis of shape properties of the constructed patches and their spatial relations. The presented framework can be used as pre-scanning tool for wide area monitoring to quickly guide the further analysis to regions of interest.

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

    Science.gov (United States)

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

    2014-06-01

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

  13. Satellite Imagery Measures of the Astronomically Aligned Megalithis at Nabta Playa.

    Science.gov (United States)

    Brophy, T.; Rosen, P.

    The Nabta Playa megalithic complex consists of two types of features: first are the large stones, many of them shaped, placed on or in the sediments of an ancient seasonal lake bed that is now hyper-ariad, second are large sculpted bedrocks features underneath the sediments and associated with the surface megaliths (Wendorf et al. 1992). The astronomically aligned surface megalithic structures described in field reports (Wendorf and Malville, 2001) are identified in recent georectified 60cm panchromatic satellite imagery of Nabta Playa, Southern Egypt. The satellite images allow refinement, often significant of the reported locations of the megaliths (Malville et al 1998, and Wendorf and Malville 2001). The report that a primary megalithic alignment was constructed to point to the bright star Sirius, circa 4820BC, is reconsidered in light of the satellite data, new field, data, radiocarbon, lithostratigraphic and geochronological data, and the playa sedimentation history. Other possible archaeoastronomical interpretations are considered for that alignment, including the three star asterism (of Alnitak, Alniham and Mintaka) circa 6270BC that is also implicated in the small Nebta Playa "calendar circle". Signatures of other possible features apparent in the satellite imagery and a recent field study are also considered. Only a small number of the subsurface bedrock sculptures have been excavated. We recommend the use of ground penetrating imaging methods to illuminate the known but not yet excavated subsurface features. The problem of determining the astronomical intent of the builders of the megalithic structures is approached by considering the complex of features as a whole.

  14. Orbital performance of communication satellite microwave power amplifiers (MPAs)

    Science.gov (United States)

    Strauss, R.

    1993-01-01

    This paper presents background data on the performance of microwave power amplifiers (MPAs) used as transmitters in currently operating commercial communication satellites. Specifically aspects of two competing MPA types are discussed. These are well known TWTA (travelling wave tube amplifier) and the SSPA (solid state power amplifier). Extensive in-orbit data has been collected from over 2000 MPAs in 1991 and 1993. The study in 1991 invovlved 75 S/C (spacecraft) covering 463 S/C years. The 1993 'second-look' study encompassed a slightly different population of 72 S/C with 497 S/C years of operation. A surprising result of both studies was that SSPAs, although quite reliable, did not achieve the reliability of TWTAs were one-third more reliable in the 1993 study. This was at C-band with comparable power amplifiers, e.g. 6-16W of RF output power and similar gains. Data at K(sub u)-band is for TWTAs only since there are no SSPAs in the current S/C inventory. The other complementary result was that the projected failure rates used as S/C payload design guidelines were, on average, somewhat higher for TWTAs than the actual failure rates uncovered by this study. SSPA rates were as projected.

  15. Optimizing statistical classification accuracy of satellite remotely sensed imagery for supporting fast flood hydrological analysis

    Science.gov (United States)

    Alexakis, Dimitrios; Agapiou, Athos; Hadjimitsis, Diofantos; Retalis, Adrianos

    2012-06-01

    The aim of this study is to improve classification results of multispectral satellite imagery for supporting flood risk assessment analysis in a catchment area in Cyprus. For this purpose, precipitation and ground spectroradiometric data have been collected and analyzed with innovative statistical analysis methods. Samples of regolith and construction material were in situ collected and examined in the spectroscopy laboratory for their spectral response under consecutive different conditions of humidity. Moreover, reflectance values were extracted from the same targets using Landsat TM/ETM+ images, for drought and humid time periods, using archived meteorological data. The comparison of the results showed that spectral responses for all the specimens were less correlated in cases of substantial humidity, both in laboratory and satellite images. These results were validated with the application of different classification algorithms (ISODATA, maximum likelihood, object based, maximum entropy) to satellite images acquired during time period when precipitation phenomena had been recorded.

  16. Analysis on the Utility of Satellite Imagery for Detection of Agricultural Facility

    Science.gov (United States)

    Kang, J.-M.; Baek, S.-H.; Jung, K.-Y.

    2012-07-01

    Now that the agricultural facilities are being increase owing to development of technology and diversification of agriculture and the ratio of garden crops that are imported a lot and the crops cultivated in facilities are raised in Korea, the number of vinyl greenhouses is tending upward. So, it is important to grasp the distribution of vinyl greenhouses as much as that of rice fields, dry fields and orchards, but it is difficult to collect the information of wide areas economically and correctly. Remote sensing using satellite imagery is able to obtain data of wide area at the same time, quickly and cost-effectively collect, monitor and analyze information from every object on earth. In this study, in order to analyze the utilization of satellite imagery at detection of agricultural facility, image classification was performed about the agricultural facility, vinyl greenhouse using Formosat-2 satellite imagery. The training set of sea, vegetation, building, bare ground and vinyl greenhouse was set to monitor the agricultural facilities of the object area and the training set for the vinyl greenhouses that are main monitoring object was classified and set again into 3 types according the spectral characteristics. The image classification using 4 kinds of supervise classification methods applied by the same training set were carried out to grasp the image classification method which is effective for monitoring agricultural facilities. And, in order to minimize the misclassification appeared in the classification using the spectral information, the accuracy of classification was intended to be raised by adding texture information. The results of classification were analyzed regarding the accuracy comparing with that of naked-eyed detection. As the results of classification, the method of Mahalanobis distance was shown as more efficient than other methods and the accuracy of classification was higher when adding texture information. Hence the more effective

  17. Swords into Ploughshares: Archaeological Applications of CORONA Satellite Imagery in the Near East

    Directory of Open Access Journals (Sweden)

    Jesse Casana

    2012-09-01

    Full Text Available Since their declassification in 1995, CORONA satellite images collected by the United States military from 1960-1972 have proved to be an invaluable resource in the archaeology of the Near East. Because CORONA images pre-date the widespread construction of reservoirs, urban expansion, and agricultural intensification the region has undergone in recent decades, these high-resolution, stereo images preserve a picture of archaeological sites and landscapes that have often been destroyed or obscured by modern development. Despite its widely recognised value, the application of CORONA imagery in archaeological research has remained limited to a small group of specialists, largely because of the challenges involved in correcting spatial distortions produced by the satellites' unusual panoramic cameras. This article presents results of an effort to develop new methods of efficiently orthorectifying CORONA imagery and to use these methods to produce geographically corrected images across the Near East, now freely available through an online database. Following an overview of our methods, we present examples of how recent development has affected the archaeological record, new discoveries that analysis of our CORONA imagery database has already made possible, and emerging applications of CORONA including stereo analysis and DEM extraction.

  18. Surface flow structure of the Gulf Stream from composite imagery and satellite-tracked drifters

    Directory of Open Access Journals (Sweden)

    C. P. Mullen

    1994-01-01

    Full Text Available A unique set of coutemporaneous satellite-tracked drifters and five-day composite Advanced Very High Resolution Radionmeter (AVHRR satellite imagery of the North Atlantic has been analyzed to examine the surface flow structure of the Gulf Stream. The study region was divided into two sections, greater than 37° N and less than 37° N, in order to answer the question of geographic variability. Fractal and spectral analyses methods were applied to the data. Fractal analysis of the Lagrangian trajectories showed a fractal dimension of 1.21 + 0.02 with a scaling range of 83 - 343 km. The fractal dimension of the temperature fronts of the composite imagery is similar for the two regions with D = 1.11 + 0.01 over a scaling range of 4 - 44 km. Spectral analysis also reports a fairly consistent value for the spectral slope and its scaling range. Therefore, we conclude there is no geographic variability in the data set. A suitable scaling range for this contemporaneous data set is 80 - 200 km which is consistent with the expected physical conditions in the region. Finally, we address the idea of using five-day composite imagery to infer the surface flow of the Gulf Stream. Close analyses of the composite thermal fronts and the Lagrangian drifter trajectories show that the former is not a good indicator of the latter.

  19. PlumeSat: A Micro-Satellite Based Plume Imagery Collection Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Ledebuhr, A.G.; Ng, L.C.

    2002-06-30

    This paper describes a technical approach to cost-effectively collect plume imagery of boosting targets using a novel micro-satellite based platform operating in low earth orbit (LEO). The plume collection Micro-satellite or PlueSat for short, will be capable of carrying an array of multi-spectral (UV through LWIR) passive and active (Imaging LADAR) sensors and maneuvering with a lateral divert propulsion system to different observation altitudes (100 to 300 km) and different closing geometries to achieve a range of aspect angles (15 to 60 degrees) in order to simulate a variety of boost phase intercept missions. The PlumeSat will be a cost effective platform to collect boost phase plume imagery from within 1 to 10 km ranges, resulting in 0.1 to 1 meter resolution imagery of a variety of potential target missiles with a goal of demonstrating reliable plume-to-hardbody handover algorithms for future boost phase intercept missions. Once deployed on orbit, the PlumeSat would perform a series phenomenology collection experiments until expends its on-board propellants. The baseline PlumeSat concept is sized to provide from 5 to 7 separate fly by data collects of boosting targets. The total number of data collects will depend on the orbital basing altitude and the accuracy in delivering the boosting target vehicle to the nominal PlumeSat fly-by volume.

  20. Satellite Hyperspectral Imagery to Support Tick-Borne Infectious Diseases Surveillance.

    Directory of Open Access Journals (Sweden)

    Gina Polo

    Full Text Available This study proposed the use of satellite hyperspectral imagery to support tick-borne infectious diseases surveillance based on monitoring the variation in amplifier hosts food sources. To verify this strategy, we used the data of the human rickettsiosis occurrences in southeastern Brazil, region in which the emergence of this disease is associated with the rising capybara population. Spatio-temporal analysis based on Monte Carlo simulations was used to identify risk areas of human rickettsiosis and hyperspectral moderate-resolution imagery was used to identify the increment and expansion of sugarcane crops, main food source of capybaras. In general, a pixel abundance associated with increment of sugarcane crops was detected in risk areas of human rickettsiosis. Thus, the hypothesis that there is a spatio-temporal relationship between the occurrence of human rickettsiosis and the sugarcane crops increment was verified. Therefore, due to the difficulty of monitoring locally the distribution of infectious agents, vectors and animal host's, satellite hyperspectral imagery can be used as a complementary tool for the surveillance of tick-borne infectious diseases and potentially of other vector-borne diseases.

  1. Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

    Science.gov (United States)

    Logan, T. L.; Huning, J. R.; Glackin, D. L.

    1983-01-01

    The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

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

    Science.gov (United States)

    Cross, M.

    2016-12-01

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

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

    Directory of Open Access Journals (Sweden)

    DK Bhattacharyya

    2010-07-01

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

  4. Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

    Science.gov (United States)

    Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

    2016-06-01

    Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

  5. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Directory of Open Access Journals (Sweden)

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  6. On land-use modeling: A treatise of satellite imagery data and misclassification error

    Science.gov (United States)

    Sandler, Austin M.

    Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

  7. Calibration of Numerical Model for Shoreline Change Prediction Using Satellite Imagery Data

    Directory of Open Access Journals (Sweden)

    Sigit Sutikno

    2015-12-01

    Full Text Available This paper presents a method for calibration of numerical model for shoreline change prediction using satellite imagery data in muddy beach. Tanjung Motong beach, a muddy beach that is suffered high abrasion in Rangsang Island, Riau province, Indonesia was picked as study area. The primary numerical modeling tool used in this research was GENESIS (GENEralized Model for Simulating Shoreline change, which has been successfully applied in many case studies of shoreline change phenomena on a sandy beach.The model was calibrated using two extracted coastlines satellite imagery data, such as Landsat-5 TM and Landsat-8 OLI/TIRS. The extracted coastline data were analyzed by using DSAS (Digital Shoreline Analysis System tool to get the rate of shoreline change from 1990 to 2014. The main purpose of the calibration process was to find out the appropriate value for K 1 and K coefficients so that the predicted shoreline change had an acceptable correlation with the output of the satellite data processing. The result of this research showed that the shoreline change prediction had a good correlation with the historical evidence data in Tanjung Motong coast. It means that the GENESIS tool is not only applicable for shoreline prediction in sandy beach but also in muddy beach.

  8. Integrating satellite imagery with simulation modeling to improve burn severity mapping.

    Science.gov (United States)

    Karau, Eva C; Sikkink, Pamela G; Keane, Robert E; Dillon, Gregory K

    2014-07-01

    Both satellite imagery and spatial fire effects models are valuable tools for generating burn severity maps that are useful to fire scientists and resource managers. The purpose of this study was to test a new mapping approach that integrates imagery and modeling to create more accurate burn severity maps. We developed and assessed a statistical model that combines the Relative differenced Normalized Burn Ratio, a satellite image-based change detection procedure commonly used to map burn severity, with output from the Fire Hazard and Risk Model, a simulation model that estimates fire effects at a landscape scale. Using 285 Composite Burn Index (CBI) plots in Washington and Montana as ground reference, we found that an integrated model explained more variability in CBI (R (2) = 0.47) and had lower mean squared error (MSE = 0.28) than image (R (2) = 0.42 and MSE = 0.30) or simulation-based models (R (2) = 0.07 and MSE = 0.49) alone. Overall map accuracy was also highest for maps created with the Integrated Model (63 %). We suspect that Simulation Model performance would greatly improve with higher quality and more accurate spatial input data. Results of this study indicate the potential benefit of combining satellite image-based methods with a fire effects simulation model to create improved burn severity maps.

  9. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land

    Directory of Open Access Journals (Sweden)

    Feng Gao

    2012-10-01

    Full Text Available Thermal infrared (TIR imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes that are at significantly finer spatial scales. Consequently, thermal sharpening techniques have been developed to sharpen TIR imagery to shortwave band pixel resolutions, which are often fine enough for field-scale applications. A classic thermal sharpening technique, TsHARP, uses a relationship between land surface temperature (LST and Normalized Difference Vegetation Index (NDVI developed empirically at the TIR pixel resolution and applied at the NDVI pixel resolution. However, recent studies show that unique relationships between temperature and NDVI may only exist for a limited class of landscapes, with mostly green vegetation and homogeneous air and soil conditions. To extend application of thermal sharpening to more complex conditions, a new data mining sharpener (DMS technique is developed. The DMS approach builds regression trees between TIR band brightness temperatures and shortwave spectral reflectances based on intrinsic sample characteristics. A comparison of sharpening techniques applied over a rainfed agricultural area in central Iowa, an irrigated agricultural region in the Texas High Plains, and a heterogeneous naturally vegetated landscape in Alaska indicates that the DMS outperformed TsHARP in all cases. The artificial box-like patterns in LST generated by the TsHARP approach are greatly reduced using the DMS scheme, especially for areas containing irrigated crops, water bodies, thin clouds or terrain. While the DMS technique can provide fine resolution TIR imagery, there are limits to the sharpening ratios that can be reasonably implemented. Consequently, sharpening techniques cannot replace actual thermal band imagery at fine resolutions or missions that

  10. Tactical Approaches for Making a Successful Satellite Passive Microwave ESDR

    Science.gov (United States)

    Hardman, M.; Brodzik, M. J.; Gotberg, J.; Long, D. G.; Paget, A. C.

    2014-12-01

    Our NASA MEaSUREs project is producing a new, enhanced resolution gridded Earth System Data Record for the entire satellite passive microwave (SMMR, SSM/I-SSMIS and AMSR-E) time series. Our project goals are twofold: to produce a well-documented, consistently processed, high-quality historical record at higher spatial resolutions than have previously been available, and to transition the production software to the NSIDC DAAC for ongoing processing after our project completion. In support of these goals, our distributed team at BYU and NSIDC faces project coordination challenges to produce a high-quality data set that our user community will accept as a replacement for the currently available historical versions of these data. We work closely with our DAAC liaison on format specifications, data and metadata plans, and project progress. In order for the user community to understand and support our project, we have solicited a team of Early Adopters who are reviewing and evaluating a prototype version of the data. Early Adopter feedback will be critical input to our final data content and format decisions. For algorithm transparency and accountability, we have released an Algorithm Theoretical Basis Document (ATBD) and detailed supporting technical documentation, with rationale for all algorithm implementation decisions. For distributed team management, we are using collaborative tools for software revision control and issue tracking. For reliably transitioning a research-quality image reconstruction software system to production-quality software suitable for use at the DAAC, we have adopted continuous integration methods for running automated regression testing. Our presentation will summarize bothadvantages and challenges of each of these tactics in ensuring production of a successful ESDR and an enduring production software system.

  11. Geometric Quality Assessment of Bundle Block Adjusted Mulit- Sensor Satellite Imageries

    Science.gov (United States)

    Ghosh, S.; Bhawani Kumar, P. S.; Radhadevi, P. V.; Srinivas, V.; Saibaba, J.; Varadan, G.

    2014-11-01

    The integration of multi-sensor earth observation data belonging to same area has become one of the most important input for resource mapping and management. Geometric error and fidelity between adjacent scenes affects large-area digital mosaic if the images/ scenes are processed independently. A block triangulation approach "Bundle Block Adjustment (BBA)" system has been developed at ADRIN for combined processing of multi-sensor, multi-resolution satellite imagery to achieve better geometric continuity. In this paper we present the evaluation results of BBA software along with performance assessment and operational use of products thus generated. The application evaluation deals with functional aspects of block-adjustment of satellite imagery consisting of data from multiple sources, i.e. AWiFs, LISS-3, LISS-4 and Cartosat-1 in various combinations as single block. It has provision for automatic generation of GCPs and tie-points using image metafile/ Rational Polynomial Coefficient's (RPC's) and ortho/ merged/ mosaicked products generation. The study is carried out with datasets covering different terrain types (ranging from high mountainous area, moderately undulating terrain, coastal plain, agriculture fields, urban area and water-body) across Indian subcontinent with varying block sizes and spatial reference systems. Geometric accuracy assessment is carried out to figure out error propagation at scene based ortho/ merged products as well as block level. The experimental results confirm that pixel tagging, geometric fidelity and feature continuity across adjacent scenes as well as for multiple sensors reduced to a great extent, due to the high redundancy. The results demonstrate that it is one of the most affective geometric corrections for generating large area digital mosaic over High mountainous terrain using high resolution good swath satellite imagery, like Cartosat-1, with minimum human intervention.

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

    Directory of Open Access Journals (Sweden)

    ÁRPÁD BARSI

    2010-06-01

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

  13. Environmental waste site characterization utilizing aerial photographs and satellite imagery: Three sites in New Mexico, USA

    Energy Technology Data Exchange (ETDEWEB)

    Van Eeckhout, E.; Pope, P.; Becker, N.; Wells, B. [Los Alamos National Lab., NM (United States); Lewis, A.; David, N. [Environmental Research Inst. of Michigan, Santa Fe, NM (United States)

    1996-04-01

    The proper handling and characterization of past hazardous waste sites is becoming more and more important as world population extends into areas previously deemed undesirable. Historical photographs, past records, current aerial satellite imagery can play an important role in characterizing these sites. These data provide clear insight into defining problem areas which can be surface samples for further detail. Three such areas are discussed in this paper: (1) nuclear wastes buried in trenches at Los Alamos National Laboratory, (2) surface dumping at one site at Los Alamos National Laboratory, and (3) the historical development of a municipal landfill near Las Cruces, New Mexico.

  14. Building Damage Estimation by Integration of Seismic Intensity Information and Satellite L-band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Nobuoto Nojima

    2010-09-01

    Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.

  15. Investigating the error budget of tropical rainfall accumulations derived from combined passive microwave and infrared satellite measurements

    Science.gov (United States)

    Roca, R.; Chambon, P.; jobard, I.; Viltard, N.

    2012-04-01

    Measuring rainfall requires a high density of observations, which, over the whole tropical elt, can only be provided from space. For several decades, the availability of satellite observations has greatly increased; thanks to newly implemented missions like the Megha-Tropiques mission and the forthcoming GPM constellation, measurements from space become available from a set of observing systems. In this work, we focus on rainfall error estimations at the 1 °/1-day accumulated scale, key scale of meteorological and hydrological studies. A novel methodology for quantitative precipitation estimation is introduced; its name is TAPEER (Tropical Amount of Precipitation with an Estimate of ERrors) and it aims to provide 1 °/1-day rain accumulations and associated errors over the whole Tropical belt. This approach is based on a combination of infrared imagery from a fleet of geostationary satellites and passive microwave derived rain rates from a constellation of low earth orbiting satellites. A three-stage disaggregation of error into sampling, algorithmic and calibration errors is performed; the magnitudes of the three terms are then estimated separately. A dedicated error model is used to evaluate sampling errors and a forward error propagation approach is used for an estimation of algorithmic and calibration errors. One of the main findings in this study is the large contribution of the sampling errors and the algorithmic errors of BRAIN on medium rain rates (2 mm h-1 to 10 mm h-1) in the total error budget.

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

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2010-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Christopher Munyati

    2014-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  19. Satellite imagery and airborne geophysics for geologic mapping of the Edembo area, Eastern Hoggar (Algerian Sahara)

    Science.gov (United States)

    Lamri, Takfarinas; Djemaï, Safouane; Hamoudi, Mohamed; Zoheir, Basem; Bendaoud, Abderrahmane; Ouzegane, Khadidja; Amara, Massinissa

    2016-03-01

    Satellite imagery combined with airborne geophysical data and field observations were employed for new geologic mapping of the Edembo area in the Eastern Hoggar (Tuareg Shield, Sahara). Multi-spectral band fusion, filtering, and transformation techniques, i.e., band combination, band-rationing and principal component analysis of ETM+ and ASTER data are used for better spectral discrimination of the different rocks units. A thematic map assessed by field data and available geologic information is compiled by supervised classification of satellite data with high overall accuracy (>90%). The automated extraction technique efficiently aided the detection of the structural lineaments, i.e., faults, shear zones, and joints. Airborne magnetic and Gamma-ray spectrometry data showed the pervasiveness of the large structures beneath the Paleozoic sedimentary cover and aeolian sands. The aeroradiometric K-range is used for discrimination of the high-K granitoids of Djanet from the peralumineous granites of Edembo, and to verify the Silurian sediments with their high K-bearing minerals. The new geological map is considered to be a high resolution improvement on all pre-existing maps of this hardly accessible area in the Tuareg Shield. Integration of the airborne geophysical and space-borne imagery data can hence provide a rapid means of geologically mapping areas hitherto poorly known or difficult to access.

  20. Ship detection in satellite imagery using rank-order greyscale hit-or-miss transforms

    Energy Technology Data Exchange (ETDEWEB)

    Harvey, Neal R [Los Alamos National Laboratory; Porter, Reid B [Los Alamos National Laboratory; Theiler, James [Los Alamos National Laboratory

    2010-01-01

    Ship detection from satellite imagery is something that has great utility in various communities. Knowing where ships are and their types provides useful intelligence information. However, detecting and recognizing ships is a difficult problem. Existing techniques suffer from too many false-alarms. We describe approaches we have taken in trying to build ship detection algorithms that have reduced false alarms. Our approach uses a version of the grayscale morphological Hit-or-Miss transform. While this is well known and used in its standard form, we use a version in which we use a rank-order selection for the dilation and erosion parts of the transform, instead of the standard maximum and minimum operators. This provides some slack in the fitting that the algorithm employs and provides a method for tuning the algorithm's performance for particular detection problems. We describe our algorithms, show the effect of the rank-order parameter on the algorithm's performance and illustrate the use of this approach for real ship detection problems with panchromatic satellite imagery.

  1. Assessing Glacial Lake Outburst Flood Hazard in the Nepal Himalayas using Satellite Imagery and Hydraulic Models

    Science.gov (United States)

    Rounce, D.; McKinney, D. C.

    2015-12-01

    The last half century has witnessed considerable glacier melt that has led to the formation of large glacial lakes. These glacial lakes typically form behind terminal moraines comprising loose boulders, debris, and soil, which are susceptible to fail and cause a glacial lake outburst flood (GLOF). These lakes also act as a heat sink that accelerates glacier melt and in many cases is accompanied by rapid areal expansion. As these glacial lakes continue to grow, their hazard also increases due to the increase in potential flood volume and the lakes' proximity to triggering events such as avalanches and landslides. Despite the large threat these lakes may pose to downstream communities, there are few detailed studies that combine satellite imagery with hydraulic models to present a holistic understanding of the GLOF hazard. The aim of this work is to assess the GLOF hazard of glacial lakes in Nepal using a holistic approach based on a combination of satellite imagery and hydraulic models. Imja Lake will be the primary focus of the modeling efforts, but the methods will be developed in a manner that is transferable to other potentially dangerous glacial lakes in Nepal.

  2. Wind class sampling of satellite SAR imagery for offshore wind resource mapping

    DEFF Research Database (Denmark)

    Badger, Merete; Badger, Jake; Nielsen, Morten

    2010-01-01

    High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical-dynamical down......High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical......-dynamical downscaling of large-scale wind conditions using a set of wind classes that describe representative wind situations. One or more SAR scenes are then selected to represent each wind class and the classes are weighted according to their frequency of occurrence. The wind class methodology was originally...... developed for mesoscale modeling of wind resources. Its performance in connection with sampling of SAR scenes is tested against two sets of random SAR samples and meteorological observations at three sites in the North Sea during 2005–08. Predictions of the mean wind speed and the Weibull scale parameter...

  3. Spatial Prediction of Coastal Bathymetry Based on Multispectral Satellite Imagery and Multibeam Data

    Directory of Open Access Journals (Sweden)

    Xavier Monteys

    2015-10-01

    Full Text Available The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods. Much of the coastal shallow water zone worldwide remains unmapped using recent techniques and is, therefore, poorly understood. Optical satellite imagery is proving to be a useful tool in predicting water depth in coastal zones, particularly in conjunction with other standard datasets, though its quality and accuracy remains largely unconstrained. A common challenge in any prediction study is to choose a small but representative group of predictors, one of which can be determined as the best. In this respect, exploratory analyses are used to guide the make-up of this group, where we choose to compare a basic non-spatial model versus four spatial alternatives, each catering for a variety of spatial effects. Using one instance of RapidEye satellite imagery, we show that all four spatial models show better adjustments than the non-spatial model in the water depth predictions, with the best predictor yielding a correlation coefficient of actual versus predicted at 0.985. All five predictors also factor in the influence of bottom type in explaining water depth variation. However, the prediction ranges are too large to be used in high accuracy bathymetry products such as navigation charts; nevertheless, they are considered beneficial in a variety of other applications in sensitive disciplines such as environmental monitoring, seabed mapping, or coastal zone management.

  4. THE IMPACT OF SHADOWS IN THE RECENT INDIAN REMOTE SENSING SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    Mrs. G.Devi

    2011-08-01

    Full Text Available Remote sensing technology is emerging as a strong tool to extract information about the earth resources from the satellite imagery. However, shadow in fine resolution imagery affects this information. The fine resolution images from recent Indian Remote Sensing (IRS satellites are compared for the pixel values in shadow and non-shadow areas using histogram occupy large shadow area compared to Cartosat-1 of resolution 2.5m. The solar elevation angle is 41degree for which long shadows are formed in case of Cartosat-2 images. The solarelevation angle is 59 degree for which short shadows are formed in case of Cartosat-1 images. The shadows in an image are a function of the solar elevation angle, azimuth angle and spatial resolution etc. The fine resolution image (Cartosat-2 building and their shadow pixel values are analysed by bimodal histogram splitting technique. The shadow boundaries are extracted. Finally Gamma filtering applied and with the Gaussian enhancement technique the shadows are eliminated from Cartosat-2 image. The building shadow under objectcan be identified in this method. The main application in shadow elimination is used for urban map preparation and the object oriented classification.

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

    Science.gov (United States)

    Skourikhine, Alexei N.

    2006-05-01

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

  6. Vehicle detection in WorldView-2 satellite imagery based on Gaussian modeling and contextual learning

    Science.gov (United States)

    Shen, Bichuan; Chen, Chi-Hau; Marchisio, Giovanni B.

    2012-06-01

    In this paper, we aim to study the detection of vehicles from WorldView-2 satellite imagery. For this purpose, accurate modeling of vehicle features and signatures and efficient learning of vehicle hypotheses are critical. We present a joint Gaussian and maximum likelihood based modeling and machine learning approach using SVM and neural network algorithms to describe the local appearance densities and classify vehicles from non-vehicle buildings, objects, and backgrounds. Vehicle hypotheses are fitted by elliptical Gaussians and the bottom-up features are grouped by Gabor orientation filtering based on multi-scale analysis and distance transform. Global contextual information such as road networks and vehicle distributions can be used to enhance the recognition. In consideration of the problem complexity the practical vehicle detection task faces due to dense and overlapping vehicle distributions, partial occlusion and clutters by building, shadows, and trees, we employ a spectral clustering strategy jointly combined with bootstrapped learning to estimate the parameters of centroid, orientation, and extents for local densities. We demonstrate a high detection rate 94.8%,with a missing rate 5.2% and a false alarm rate 5.3% on the WorldView-2 satellite imagery. Experimental results show that our method is quite effective to model and detect vehicles.

  7. Coral Reef environment reconstruction using small drones, new generation photogrammetry algorithms and satellite imagery

    Science.gov (United States)

    Elisa, Casella; Rovere, Alessio; Harris, Daniel; Parravicini, Valeriano

    2016-04-01

    Surveys based on Remotely Piloted Aircraft Systems (RPAS), together with new-generation Structure from Motion (SfM) and Multi-View Stereo (MVS) reconstruction algorithms have been employed to reconstruct the shallow bathymetry of the inner lagoon of a coral reef in Moorea, French Polinesia. This technique has already been used with a high rate of success on coastal environments (e.g. sandy beaches and rocky shorelines) reaching accuracy of the final Digital Elevation Model in the order of few centimeters. The application of such techniques to reconstruct shallow underwater environments is, though, still little reported. We then used the bathymetric dataset obtained from aerial pictures as ground-truth for relative bathymetry obtained from satellite imagery (WorldView-2) of a larger area within the same study site. The first results of our work suggest that RPAS coupled with SfM and MVS algorithms can be used to reconstruct shallow water environments with favorable weather conditions, and can be employed to ground-truth to satellite imagery.

  8. Convective cloud identification and classification in daytime satellite imagery using standard deviation limited adaptive clustering

    Science.gov (United States)

    Berendes, Todd A.; Mecikalski, John R.; MacKenzie, Wayne M.; Bedka, Kristopher M.; Nair, U. S.

    2008-10-01

    This paper describes a statistical clustering approach toward the classification of cloud types within meteorological satellite imagery, specifically, visible and infrared data. The method is based on the Standard Deviation Limited Adaptive Clustering (SDLAC) procedure, which has been used to classify a variety of features within both polar orbiting and geostationary imagery, including land cover, volcanic ash, dust, and clouds of various types. In this study, the focus is on classifying cumulus clouds of various types (e.g., "fair weather, "towering, and newly glaciated cumulus, in addition to cumulonimbus). The SDLAC algorithm is demonstrated by showing examples using Geostationary Operational Environmental Satellite (GOES) 12, Meteosat Second Generation's (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI), and the Moderate Resolution Infrared Spectrometer (MODIS). Results indicate that the method performs well, classifying cumulus similarly between MODIS, SEVIRI, and GOES, despite the obvious channel and resolution differences between these three sensors. The SDLAC methodology has been used in several research activities related to convective weather forecasting, which offers some proof of concept for its value.

  9. Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations

    Directory of Open Access Journals (Sweden)

    Checchi Francesco

    2013-01-01

    Full Text Available Abstract Background Estimating the size of forcibly displaced populations is key to documenting their plight and allocating sufficient resources to their assistance, but is often not done, particularly during the acute phase of displacement, due to methodological challenges and inaccessibility. In this study, we explored the potential use of very high resolution satellite imagery to remotely estimate forcibly displaced populations. Methods Our method consisted of multiplying (i manual counts of assumed residential structures on a satellite image and (ii estimates of the mean number of people per structure (structure occupancy obtained from publicly available reports. We computed population estimates for 11 sites in Bangladesh, Chad, Democratic Republic of Congo, Ethiopia, Haiti, Kenya and Mozambique (six refugee camps, three internally displaced persons’ camps and two urban neighbourhoods with a mixture of residents and displaced ranging in population from 1,969 to 90,547, and compared these to “gold standard” reference population figures from census or other robust methods. Results Structure counts by independent analysts were reasonably consistent. Between one and 11 occupancy reports were available per site and most of these reported people per household rather than per structure. The imagery-based method had a precision relative to reference population figures of Conclusions In settings with clearly distinguishable individual structures, the remote, imagery-based method had reasonable accuracy for the purposes of rapid estimation, was simple and quick to implement, and would likely perform better in more current application. However, it may have insurmountable limitations in settings featuring connected buildings or shelters, a complex pattern of roofs and multi-level buildings. Based on these results, we discuss possible ways forward for the method’s development.

  10. Application of satellite imagery to monitoring human rights abuse of vulnerable communities, with minimal risk to relief staff

    Science.gov (United States)

    Lavers, C.; Bishop, C.; Hawkins, O.; Grealey, E.; Cox, C.; Thomas, D.; Trimel, S.

    2009-07-01

    Space imagery offers remote surveillance of ethnic people groups at risk of human rights abuse. We highlight work in alleged violations in Burma and Sudan, using satellite imagery for verification with Amnesty International. We consider how imaging may effectively support small to medium-sized Non Governmental Organisations and charities, e.g. HART, working in dangerous zones on the ground. Satellite based sensing applications are now at a sufficiently mature stage for moderate Governmental funding levels to help prevent human rights abuse, rather than the greater cost of rebuilding communities and healing sectarian divisions after abuse has taken place.

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

    Science.gov (United States)

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

    2013-10-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  13. Environmental assessment for the Satellite Power System (SPS) Concept Development and Evaluation Program (CDEP). [Microwave and non-microwave health and ecological assessment

    Energy Technology Data Exchange (ETDEWEB)

    Valentino, A.R.

    1980-08-01

    In the satellite power system (SPS), satellites in geosynchronous earth orbit would collect solar energy in space, convert it to microwaves, and transmit the microwaves to receiving antennas (rectennas) on earth. At the rectennas, the microwave energy would be converted to electricity. This SPS environmental assessment considers the microwave and nonmicrowave effects on the terrestrial environment and human health, atmospheric effects, and effects on electromagnetic systems. No environmental problem has been identified that would preclude the continued study of SPS technology. To increase the certainty of the assessment, some research has been initiated and long-term research is being planned.

  14. The Role of Satellite Imagery to Improve Pastureland Estimates in South America

    Science.gov (United States)

    Graesser, J.

    2015-12-01

    Agriculture has changed substantially across the globe over the past half century. While much work has been done to improve spatial-temporal estimates of agricultural changes, we still know more about the extent of row-crop agriculture than livestock-grazed land. The gap between cropland and pastureland estimates exists largely because it is challenging to characterize natural versus grazed grasslands from a remote sensing perspective. However, the impasse of pastureland estimates is set to break, with an increasing number of spaceborne sensors and freely available satellite data. The Landsat satellite archive in particular provides researchers with immense amounts of data to improve pastureland information. Here we focus on South America, where pastureland expansion has been scrutinized for the past few decades. We explore the challenges of estimating pastureland using temporal Landsat imagery and focus on key agricultural countries, regions, and ecosystems. We focus on the suggested shift of pastureland from the Argentine Pampas to northern Argentina, and the mixing of small-scale and large-scale ranching in eastern Paraguay and how it could impact the Chaco forest to the west. Further, the Beni Savannahs of northern Bolivia and the Colombian Llanos—both grassland and savannah regions historically used for livestock grazing—have been hinted at as future areas for cropland expansion. There are certainly environmental concerns with pastureland expansion into forests; but what are the environmental implications when well-managed pasture systems are converted to intensive soybean or palm oil plantation? Tropical, grazed grasslands are important habitats for biodiversity, and pasturelands can mitigate soil erosion when well managed. Thus, we must improve estimates of grazed land before we can make informed policy and conservation decisions. This talk presents insights into pastureland estimates in South America and discusses the feasibility to improve current

  15. Mapping of land cover in northern California with simulated hyperspectral satellite imagery

    Science.gov (United States)

    Clark, Matthew L.; Kilham, Nina E.

    2016-09-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands

  16. A microwave satellite water vapour column retrieval for polar winter conditions

    Science.gov (United States)

    Perro, Christopher; Lesins, Glen; Duck, Thomas J.; Cadeddu, Maria

    2016-05-01

    A new microwave satellite water vapour retrieval for the polar winter atmosphere is presented. The retrieval builds on the work of Miao et al. (2001) and Melsheimer and Heygster (2008), employing auxiliary information for atmospheric conditions and numerical optimization. It was tested using simulated and actual measurements from the Microwave Humidity Sounder (MHS) satellite instruments. Ground truth was provided by the G-band vapour radiometer (GVR) at Barrow, Alaska. For water vapour columns less than 6 kg m-2, comparisons between the retrieval and GVR result in a root mean square (RMS) deviation of 0.39 kg m-2 and a systematic bias of 0.08 kg m-2. These results are compared with RMS deviations and biases at Barrow for the retrieval of Melsheimer and Heygster (2008), the AIRS and MIRS satellite data products, and the ERA-Interim, NCEP, JRA-55, and ASR reanalyses. When applied to MHS measurements, the new retrieval produces a smaller RMS deviation and bias than for the earlier retrieval and satellite data products. The RMS deviations for the new retrieval were comparable to those for the ERA-Interim, JRA-55, and ASR reanalyses; however, the MHS retrievals have much finer horizontal resolution (15 km at nadir) and reveal more structure. The new retrieval can be used to obtain pan-Arctic maps of water vapour columns of unprecedented quality. It may also be applied to measurements from the Special Sensor Microwave/Temperature 2 (SSM/T2), Advanced Microwave Sounding Unit B (AMSU-B), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Technology Microwave Sounder (ATMS), and Chinese MicroWave Humidity Sounder (MWHS) instruments.

  17. Estimating Uncertainties in Bio-Optical Products Derived from Satellite Ocean Color Imagery Using an Ensemble Approach

    Science.gov (United States)

    2011-01-01

    We propose a methodology to quantify errors and produce uncertainty maps for satellite-derived ocean color bio -optical products using ensemble...retrievals of bio -optical properties from satellite ocean color imagery are related to a variety of factors, including sensor calibration, atmospheric...correction, and the bio -optical inversion algorithms. Errors propagate, amplify, and intertwine along the processing path, so it is important to

  18. The Matsu Wheel: A Cloud-based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

    OpenAIRE

    Patterson, Maria T.; Anderson, Nikolas; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert; Handy, Matthew; Ly, Vuong; Mandl, Dan; Pederson, Shane; Pivarski, Jim; Powell, Ray; Spring, Jonathan; Wells, Walt

    2016-01-01

    Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for the cloud-based processing of Earth satellite imagery. A particular focus is the development of applications for detecting fires and floods to help support natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStac...

  19. Building high-performance system for processing a daily large volume of Chinese satellites imagery

    Science.gov (United States)

    Deng, Huawu; Huang, Shicun; Wang, Qi; Pan, Zhiqiang; Xin, Yubin

    2014-10-01

    The number of Earth observation satellites from China increases dramatically recently and those satellites are acquiring a large volume of imagery daily. As the main portal of image processing and distribution from those Chinese satellites, the China Centre for Resources Satellite Data and Application (CRESDA) has been working with PCI Geomatics during the last three years to solve two issues in this regard: processing the large volume of data (about 1,500 scenes or 1 TB per day) in a timely manner and generating geometrically accurate orthorectified products. After three-year research and development, a high performance system has been built and successfully delivered. The high performance system has a service oriented architecture and can be deployed to a cluster of computers that may be configured with high end computing power. The high performance is gained through, first, making image processing algorithms into parallel computing by using high performance graphic processing unit (GPU) cards and multiple cores from multiple CPUs, and, second, distributing processing tasks to a cluster of computing nodes. While achieving up to thirty (and even more) times faster in performance compared with the traditional practice, a particular methodology was developed to improve the geometric accuracy of images acquired from Chinese satellites (including HJ-1 A/B, ZY-1-02C, ZY-3, GF-1, etc.). The methodology consists of fully automatic collection of dense ground control points (GCP) from various resources and then application of those points to improve the photogrammetric model of the images. The delivered system is up running at CRESDA for pre-operational production and has been and is generating good return on investment by eliminating a great amount of manual labor and increasing more than ten times of data throughput daily with fewer operators. Future work, such as development of more performance-optimized algorithms, robust image matching methods and application

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

    Science.gov (United States)

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

    2014-11-01

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

  1. Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors technique

    Science.gov (United States)

    Ronald E. McRoberts; Mark D. Nelson; Daniel G. Wendt

    2002-01-01

    For two large study areas in Minnesota, USA, stratified estimation using classified Landsat Thematic Mapper satellite imagery as the basis for stratification was used to estimate forest area. Measurements of forest inventory plots obtained for a 12-month period in 1998 and 1999 were used as the source of data for within-stratum estimates. These measurements further...

  2. Estimation of Reservoir Discharges from Lake Nasser and Roseires Reservoir in the Nile Basin Using Satellite Altimetry and Imagery Data

    NARCIS (Netherlands)

    Muala, E.; Mohamed, Y.A.; Duan, Z.; Van der Zaag, P.

    2014-01-01

    This paper presents the feasibility of estimating discharges from Roseires Reservoir (Sudan) for the period from 2002 to 2010 and Aswan High Dam/Lake Nasser (Egypt) for the periods 1999–2002 and 2005–2009 using satellite altimetry and imagery with limited in situ data. Discharges were computed using

  3. Selecting Appropriate Spatial Scale for Mapping Plastic-Mulched Farmland with Satellite Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Hasituya

    2017-03-01

    Full Text Available In recent years, the area of plastic-mulched farmland (PMF has undergone rapid growth and raised remarkable environmental problems. Therefore, mapping the PMF plays a crucial role in agricultural production, environmental protection and resource management. However, appropriate data selection criteria are currently lacking. Thus, this study was carried out in two main plastic-mulching practice regions, Jizhou and Guyuan, to look for an appropriate spatial scale for mapping PMF with remote sensing. The average local variance (ALV function was used to obtain the appropriate spatial scale for mapping PMF based on the GaoFen-1 (GF-1 satellite imagery. Afterwards, in order to validate the effectiveness of the selected method and to interpret the relationship between the appropriate spatial scale derived from the ALV and the spatial scale with the highest classification accuracy, we classified the imagery with varying spatial resolution by the Support Vector Machine (SVM algorithm using the spectral features, textural features and the combined spectral and textural features respectively. The results indicated that the appropriate spatial scales from the ALV lie between 8 m and 20 m for mapping the PMF both in Jizhou and Guyuan. However, there is a proportional relation: the spatial scale with the highest classification accuracy is at the 1/2 location of the appropriate spatial scale generated from the ALV in Jizhou and at the 2/3 location of the appropriate spatial scale generated from the ALV in Guyuan. Therefore, the ALV method for quantitatively selecting the appropriate spatial scale for mapping PMF with remote sensing imagery has theoretical and practical significance.

  4. Monitoring and characterizing natural hazards with satellite InSAR imagery

    Science.gov (United States)

    Lu, Zhong; Zhang, Jixian; Zhang, Yonghong; Dzurisin, Daniel

    2010-01-01

    Interferometric synthetic aperture radar (InSAR) provides an all-weather imaging capability for measuring ground-surface deformation and inferring changes in land surface characteristics. InSAR enables scientists to monitor and characterize hazards posed by volcanic, seismic, and hydrogeologic processes, by landslides and wildfires, and by human activities such as mining and fluid extraction or injection. Measuring how a volcano’s surface deforms before, during, and after eruptions provides essential information about magma dynamics and a basis for mitigating volcanic hazards. Measuring spatial and temporal patterns of surface deformation in seismically active regions is extraordinarily useful for understanding rupture dynamics and estimating seismic risks. Measuring how landslides develop and activate is a prerequisite to minimizing associated hazards. Mapping surface subsidence or uplift related to extraction or injection of fluids during exploitation of groundwater aquifers or petroleum reservoirs provides fundamental data on aquifer or reservoir properties and improves our ability to mitigate undesired consequences. Monitoring dynamic water-level changes in wetlands improves hydrological modeling predictions and the assessment of future flood impacts. In addition, InSAR imagery can provide near-real-time estimates of fire scar extents and fire severity for wildfire management and control. All-weather satellite radar imagery is critical for studying various natural processes and is playing an increasingly important role in understanding and forecasting natural hazards.

  5. Geometric Potential of Pléiades 1A Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Postelniak Andrii

    2014-10-01

    Full Text Available In this paper, the geometrical characteristics of Pléiades 1A satellite imagery (both single and stereo are analysed. At first the process of digital surface model (DSM extraction from a Pléiades 1A stereo pair is described and analysed. After that geometric an accuracy of imagery, orthorectified using the extracted DSM and using the SRTM (Shuttle radar topographic mission was analysed. The Pléiades 1A stereo pair was acquired on October 22, 2012 from the same orbital pass over an urban zone (Kiev, Ukraine. The study area is heterogeneous: there are both built-up and flat areas. The iImage orientation, DSM extraction and orthorectified images generation were performed using the PCI Geomatica 2013 software. The results showed that a strong, positive correlation between reference-derived elevations and DSM-derived elevations can be observed, and the orthorectified image accuracy, generated using that DSM, approximately equal to 1 m can be achieved using a bias compensation sensor model. Different sensor models were used for orthorectification using the SRTM. In this case, the geometric accuracy is а function of a chosen sensor model and a number of ground control points (GCP.

  6. The Northeast Greenland Sirius Water Polynya dynamics and variability inferred from satellite imagery

    DEFF Research Database (Denmark)

    Pedersen, Jørn Bjarke Torp; Kaufmann, Laura Hauch; Kroon, Aart

    2010-01-01

    ’, and examines its spatial and temporal dynamics by analysis of recent satellite imagery, modelled meteorological data and historical data covering the last decade. The dominating mechanisms to form and sustain the polynya are inferred and the persistence and inter-annual variability of the phenomenon...... and summer regimes in the seasonal evolution of the polynya. During the winter regime, both the size of and the ice cover within the polynya varies significantly on a temporal and spatial scale. Intermittent wind-driven openings of the polynya alternate with periods of increasing ice cover. Some of the most...... persistent areas of open water in the polynya coincide with locations where significant concentrations of spring and summer settlements from the Thule Inuit culture (AD 1400-1850) are observed, indicating a connection between the presence of the polynya and the Thule Inuit living in the area in prehistoric...

  7. The Northeast Greenland Sirius Water Polynya dynamics and variability inferred from satellite imagery

    DEFF Research Database (Denmark)

    Pedersen, Jørn Bjarke Torp; Kaufmann, Laura Hauch; Kroon, Aart

    2010-01-01

    ’, and examines its spatial and temporal dynamics by analysis of recent satellite imagery, modelled meteorological data and historical data covering the last decade. The dominating mechanisms to form and sustain the polynya are inferred and the persistence and inter-annual variability of the phenomenon...... are estimated. The polynya formation is predominantly governed by mechanical forcing caused by northerly gales, and it is classified as a wind-driven shelf water polynya. A marked seasonal difference in the surface wind field, together with the obvious seasonal cycle in insolation, creates distinct winter...... and summer regimes in the seasonal evolution of the polynya. During the winter regime, both the size of and the ice cover within the polynya varies significantly on a temporal and spatial scale. Intermittent wind-driven openings of the polynya alternate with periods of increasing ice cover. Some of the most...

  8. Advancing Coastal Climate Adaptation in Denmark by Land Subsidence Mapping using Sentinel-1 Satellite Imagery

    DEFF Research Database (Denmark)

    Sørensen, Carlo Sass; Broge, Niels H.; Mølgaard, Mads R.

    2016-01-01

    There are still large uncertainties in projections of climate change and sea level rise. Here, land subsidence is an additional factor that may adversely affect the vulnerability towards floods in low-lying coastal communities. The presented study performs an initial assessment of subsidence...... mapping using Sentinel-1 satellite imagery and leveling at two coastal locations in Denmark. Within both investigated areas current subsidence rates of 5-10 millimeters per year are found. This subsidence is related to the local geology, and challenges and potentials in bringing land subsidence mapping...... and geology into climate adaptation are discussed in relation to perspectives of a national subsidence monitoring system partly based on the findings from the two coastal locations. The current lack of subsidence data and a fragmentation of geotechnical information are considered as hindrances to optimal...

  9. Coastal erosion and accretion in Pak Phanang, Thailand by GIS analysis of maps and satellite imagery

    Directory of Open Access Journals (Sweden)

    Sayedur Rahman Chowdhury

    2013-12-01

    Full Text Available Coastal erosion and accretion in Pak Phanang of southern Thailand between 1973 and 2003 was measured using multi-temporal topographic maps and Landsat satellite imageries. Within a GIS environment landward and seaward movements of shoreline was estimated by a transect-based analysis, and amounts of land accretion and erosion were estimated by a parcel-based geoprocessing. The whole longitudinal extent of the 58 kilometer coast was classified based on the erosion and accretion trends during this period using agglomerative hierarchical clustering approach. Erosion and accretion were found variable over time and space, and periodic reversal of status was also noticed in many places. Estimates of erosion were evaluated against field-survey based data, and found reasonably accurate where the rates were relatively great. Smoothing of shoreline datasets was found desirable as its impacts on the estimates remained within tolerable limits.

  10. Status of the microwave power transmission components for the solar power satellite

    Science.gov (United States)

    Brown, W. C.

    1981-01-01

    During the 1970-1980 time period a substantial advance has been made in developing all portions of a microwave power transmission system for the solar power satellite (SPS). The most recent advances pertain to the transmitting portion of the system in the satellite and are based upon experimental observations of the use of the magnetron combined with a passive directional device to convert it into a highly efficient directional amplifier with excellent low-noise properties and potentially very long life. The ability of its microwave output to track a phase reference makes it possible to combine it with many other radiating units to provide a highly coherent microwave beam. The ability of its output to track an amplitude reference while operating from a dc power source with varying voltage makes it possible to eliminate most of the power conditioning equipment that would otherwise be necessary.

  11. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2010-09-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved retrievals of surface soil moisture variations at global scales. Here we propose a technique to take advantage of retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates over sparse-to-moderately vegetated areas to obtain an improved soil moisture product. To do this, absolute soil moisture values from AMSR-E and relative soil moisture derived from ASCAT are rescaled against a reference land surface model date set using a cumulative distribution function (CDF matching approach. While this technique imposes the bias of the reference to the rescaled satellite products, it adjusts both satellite products to the same range and almost preserves the correlation between satellite products and in situ measurements. Comparisons with in situ data demonstrated that over the regions where the correlation coefficient between rescaled AMSR-E and ASCAT is above 0.65 (hereafter referred to as transitional regions, merging the different satellite products together increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT are respectively used in the merged product. Thus the merged product carries the advantages of better spatial coverage overall and increased number of observations particularly for the transitional regions. The combination approach developed in this study has the potential to be applied to existing microwave satellites as well as to new microwave missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  12. Glacier Fluctuations in the Western Himalaya: Multi-temporal Assessment Using Multi-sensor Satellite Imagery

    Science.gov (United States)

    Bishop, M. P.; Shroder, J. F.

    2004-12-01

    Alpine glaciers are retreating and downwasting in many mountain environments. Systematic and quantitative assessments are sorely needed, as regional mass-balance trends are not known, and many glaciers may disappear before we can study them and assess glacier sensitivity to climate forcing. This urgency dictates remote sensing and GIS-based studies to provide baseline information and estimates of mass balance. In the Western Himalaya there is a paucity of quantitative information on glacier fluctuations and meltwater contributions to rising sea level. As part of the Global Land Ice Measurements from Space (GLIMS) project, we conducted several glacier change-detection studies to assess ice fluctuations on selected glaciers. We compared SPOT imagery from the 1990's to ASTER satellite imagery from the 2000-2004 time period. Ground photography and satellite image analysis using artificial neural networks were used to compare glacier characteristics. Results indicate that some glaciers have retreated, while others exhibit very similar terminus positions to past positions, but have downwasted. Glacier retreat and downwasting have resulted in the disconnection of tributary glaciers to valley glaciers in the Hindu Kush and Nanga Parbat Himalaya. In addition, there are increases in meltwater production on some glaciers, as revealed by surging and variation in the frequency and size of supraglacial lakes. These results identify increased hazard potential in many areas, and suggest negative mass balance for some glaciers. Quantitative results from remote sensing studies, however, should be carefully interpreted, as climate, glacier, lithosphere interactions that dictate glacier fluctuations are not adequately accounted for in image-based analyses of supraglacial conditions. The integration of quantitative remote sensing/GIS information into numerical ice flow/mass balance models is required to obtain better estimates of mass balance and glacier sensitivity to climate forcing.

  13. Monitoring of oil pollution in the Arabian Gulf based on medium resolution satellite imagery

    Science.gov (United States)

    Zhao, J.; Ghedira, H.

    2013-12-01

    A large number of inland and offshore oil fields are located in the Arabian Gulf where about 25% of the world's oil is produced by the countries surrounding the Arabian Gulf region. Almost all of this oil production is shipped by sea worldwide through the Strait of Hormuz making the region vulnerable to environmental and ecological threats that might arise from accidental or intentional oil spills. Remote sensing technologies have the unique capability to detect and monitor oil pollutions over large temporal and spatial scales. Synoptic satellite imaging can date back to 1972 when Landsat-1 was launched. Landsat satellite missions provide long time series of imagery with a spatial resolution of 30 m. MODIS sensors onboard NASA's Terra and Aqua satellites provide a wide and frequent coverage at medium spatial resolution, i.e. 250 m and 500, twice a day. In this study, the capability of medium resolution MODIS and Landsat data in detecting and monitoring oil pollutions in the Arabian Gulf was tested. Oil spills and slicks show negative or positive contrasts in satellite derived RGB images compared with surrounding clean waters depending on the solar/viewing geometry, oil thickness and evolution, etc. Oil-contaminated areas show different spectral characteristics compared with surrounding waters. Rayleigh-corrected reflectance at the seven medium resolution bands of MODIS is lower in oil affected areas. This is caused by high light absorption of oil slicks. 30-m Landsat image indicated the occurrence of oil spill on May 26 2000 in the Arabian Gulf. The oil spill showed positive contrast and lower temperature than surrounding areas. Floating algae index (FAI) images are also used to detect oil pollution. Oil-contaminated areas were found to have lower FAI values. To track the movement of oil slicks found on October 21 2007, ocean circulations from a HYCOM model were examined and demonstrated that the oil slicks were advected toward the coastal areas of United Arab

  14. Using Satellite Imagery to Identify Tornado Damage Tracks and Recovery from the April 27, 2011 Severe Weather Outbreak

    Science.gov (United States)

    Cole, Tony A.; Molthan, Andrew L.; Bell, Jordan R.

    2014-01-01

    Emergency response to natural disasters requires coordination between multiple local, state, and federal agencies. Single, relatively weak tornado events may require comparatively simple response efforts; but larger "outbreak" events with multiple strong, long-track tornadoes can benefit from additional tools to help expedite these efforts. Meteorologists from NOAA's National Weather Service conduct field surveys to map tornado tracks, assess damage, and determine the tornado intensity following each event. Moderate and high resolution satellite imagery can support these surveys by providing a high-level view of the affected areas. Satellite imagery could then be used to target areas for immediate survey or to corroborate the results of the survey after it is completed. In this study, the feasibility of using satellite imagery to identify tornado damage tracks was determined by comparing the characteristics of tracks observed from low-earth orbit to tracks assessed during the official NWS storm survey process. Of the 68 NWS confirmed centerlines, 24 tracks (35.3%) could be distinguished from other surface features using satellite imagery. Within each EF category, 0% of EF-0, 3% of EF-1, 50% of EF-2, 77.7% of EF-3, 87.5% of EF-4 and 100% of EF-5 tornadoes were detected. It was shown that satellite data can be used to identify tornado damage tracks in MODIS and ASTER NDVI imagery, where damage to vegetation creates a sharp drop in values though the minimum EF-category which can be detected is dependent upon the type of sensor used and underlying vegetation. Near-real time data from moderate resolution sensors compare favorably to field surveys after the event and suggest that the data can provide some value in the assessment process.

  15. Satellite Microwave Communication Signal Degradation Due To Hall Thruster Plasma Plumes

    Science.gov (United States)

    Wiley, J. C.; Hallock, G. A.; Spencer, E. A.; Meyer, J. W.; Loane, J. T.

    2001-10-01

    We have developed a geometric optics vector ray-tracing code, BeamServer, for analyzing the effects of Hall thruster plasma plumes on satellite microwave communication signals. The possible effects include main beam attenuation and squinting, side lobe degradation, and induced cross-polarization. We report on a study of Hall current thruster (HCT) mounting positions on a realistic satellite configuration and a study with a highly shaped reflector. Results indicate HCT signal degradation can occur and should be considered in the satellite design process. Initial results of antenna pattern perturbations due to low frequency plume oscillations driven by thruster instabilities are also given.

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

    Science.gov (United States)

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

    2016-10-01

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

  17. The Satellite Passive-Microwave Record of Sea Ice in the Ross Sea Since Late 1978

    Science.gov (United States)

    Parkinson, Claire L.

    2009-01-01

    Satellites have provided us with a remarkable ability to monitor many aspects of the globe day-in and day-out and sea ice is one of numerous variables that by now have quite substantial satellite records. Passive-microwave data have been particularly valuable in sea ice monitoring, with a record that extends back to August 1987 on daily basis (for most of the period), to November 1970 on a less complete basis (again for most of the period), and to December 1972 on a less complete basis. For the period since November 1970, Ross Sea sea ice imagery is available at spatial resolution of approximately 25 km. This allows good depictions of the seasonal advance and retreat of the ice cover each year, along with its marked interannual variability. The Ross Sea ice extent typically reaches a minimum of approximately 0.7 x 10(exp 6) square kilometers in February, rising to a maximum of approximately 4.0 x 10(exp 6) square kilometers in September, with much variability among years for both those numbers. The Ross Sea images show clearly the day-by-day activity greatly from year to year. Animations of the data help to highlight the dynamic nature of the Ross Sea ice cover. The satellite data also allow calculation of trends in the ice cover over the period of the satellite record. Using linear least-squares fits, the Ross Sea ice extent increased at an average rate of 12,600 plus or minus 1,800 square kilometers per year between November 1978 and December 2007, with every month exhibiting increased ice extent and the rates of increase ranging from a low of 7,500 plus or minus 5,000 square kilometers per year for the February ice extents to a high of 20,300 plus or minus 6,100 kilometers per year for the October ice extents. On a yearly average basis, for 1979-2007 the Ross Sea ice extent increased at a rate of 4.8 plus or minus 1.6 % per decade. Placing the Ross Sea in the context of the Southern Ocean as a whole, over the November 1978-December 2007 period the Ross Sea had

  18. Routine Ocean Monitoring With Synthetic Aperture Radar Imagery Obtained From the Alaska Satellite Facility

    Science.gov (United States)

    Pichel, W. G.; Clemente-Colon, P.; Li, X.; Friedman, K.; Monaldo, F.; Thompson, D.; Wackerman, C.; Scott, C.; Jackson, C.; Beal, R.; McGuire, J.; Nicoll, J.

    2006-12-01

    The Alaska Satellite Facility (ASF) has been processing synthetic aperture radar (SAR) data for research and for near-real-time applications demonstrations since shortly after the launch of the European Space Agency's ERS-1 satellite in 1991. The long coastline of Alaska, the vast extent of ocean adjacent to Alaska, a scarcity of in-situ observations, and the persistence of cloud cover all contribute to the need for all-weather ocean observations in the Alaska region. Extensive experience with SAR product processing algorithms and SAR data analysis techniques, and a growing sophistication on the part of SAR data and product users have amply demonstrated the value of SAR instruments in providing this all-weather ocean observation capability. The National Oceanic and Atmospheric Administration (NOAA) has been conducting a near-real-time applications demonstration of SAR ocean and hydrologic products in Alaska since September 1999. This Alaska SAR Demonstration (AKDEMO) has shown the value of SAR-derived, high-resolution (sub kilometer) ocean surface winds to coastal weather forecasting and the understanding of coastal wind phenomena such as gap winds, barrier jets, vortex streets, and lee waves. Vessel positions and ice information derived from SAR imagery have been used for management of fisheries, protection of the fishing fleet, enforcement of fisheries regulations, and protection of endangered marine mammals. Other ocean measurements, with potentially valuable applications, include measurement of wave state (significant wave height, dominant wave direction and wavelength, and wave spectra), mapping of oil spills, and detection of shallow-water bathymetric features. In addition to the AKDEMO, ASF-processed SAR imagery is being used: (1) in the Gulf of Mexico for hurricane wind studies, and post-hurricane oil-spill and oil-platform analyses (the latter employing ship-detection algorithms for detection of changes in oil-platform locations); (2) in the North Pacific

  19. Microwave retrievals of terrestrial precipitation over snow-covered surfaces: A lesson from the GPM satellite

    Science.gov (United States)

    Ebtehaj, A. M.; Kummerow, C. D.

    2017-06-01

    Satellites are playing an ever-increasing role in estimating precipitation over remote areas. Improving satellite retrievals of precipitation requires increased understanding of its passive microwave signatures over different land surfaces. Snow-covered surfaces are notoriously difficult to interpret because they exhibit both emission from the land below and scattering from the ice crystals. Using data from the Global Precipitation Measurement (GPM) satellite, we demonstrate that microwave brightness temperatures of rain and snowfall transition from a scattering to an emission regime from summer to winter, due to expansion of less emissive snow cover. Evidence suggests that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The results demonstrate that, using a multifrequency matching method, the probability of snowfall detection can even be higher than rainfall—chiefly because of the information content of the low-frequency channels that respond to the (near) surface temperature.

  20. Sherlock Holmes' or Don Quixote`s certainty? Interpretations of cropmarks on satellite imageries in archaeological investigation

    Science.gov (United States)

    Wilgocka, Aleksandra; RÄ czkowski, Włodzimierz; Kostyrko, Mikołaj; Ruciński, Dominik

    2016-08-01

    Years of experience in air-photo interpretations provide us to conclusion that we know what we are looking at, we know why we can see cropmarks, we even can estimate, when are the best opportunities to observe them. But even today cropmarks may be a subject of misinterpretation or wishful thinking. The same problems appear when working with aerial photographs, satellite imageries, ALS, geophysics, etc. In the paper we present several case studies based on data acquired for and within ArchEO - archaeological applications of Earth Observation techniques project to discuss complexity and consequences of archaeological interpretations. While testing usefulness of satellite imagery in Poland on various types of sites, cropmarks were the most frequent indicators of past landscapes as well as archaeological and natural features. Hence, new archaeological sites have been discovered mainly thanks to cropmarks. This situation has given us an opportunity to test not only satellite imageries as a source of data but also confront them with results of other non-invasive methods of data acquisition. When working with variety of data we have met several issues which raised problems of interpretation. Consequently, questions related to the cognitive value of remote sensing data appear and should be discussed. What do the data represent? To what extent the imageries, cropmarks or other visualizations represent the past? How should we deal with ambiguity of data? What can we learn from pitfalls in the interpretation of cropmarks, soilmarks etc. to share more Sherlock's methodology rather than run around Don Quixote's delusions?

  1. Observing Red Tide Algal Blooms From Satellite Ocean Color Imagery: West Florida Shelf

    Science.gov (United States)

    Krueger, E. T.; Jose, F.

    2016-12-01

    Harmful algal blooms (HABs) from Karenia brevis occur along the west Florida shelf (WFS) almost every year, producing a brevetoxin that is harmful to birds, fish, marine mammals, shellfish, and humans. These HABs are commonly known as "red tide" from the reddish discoloration in the water, but color can vary from yellow to deep brown depending on other parameters. Ocean color data is a viable tool for monitoring the outbreak and persistence of these ecological phenomena. Also, the spatial extend of this outbreak could be evaluated effectively from satellite imagery. Chlorophyll (Chl) and sea surface temperature (SST) data from four satellites during the period from 2010 to 2013 were analyzed, and compared the monthly composite data with in situ observation on K. brevis cell counts collected by the Florida Fish and Wildlife Conservation Commission (FWC). Remote sensing data were extracted from the NASA Ocean Color data servers and were processed using WimSoft, a Windows-based remote sensing data analysis program. Based on the comparison of data from 26 transects from the WFS, which were extended from nearshore to 400 km offshore, highest Chl concentrations were observed in the sector from St. Petersburg to Sanibel Island. FWC data also showed that highest K. brevis cell counts were concentrated in this region during the 2011 to 2012 period. Additionally, a high Chl concentration was observed for the Big Bend region, particularly during the spring and early summer. The inter-annual variability of Chl, SST, and red tide occurrence are also discussed in this study.

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

    Science.gov (United States)

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

    2016-06-01

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

  3. Epipolar resampling of linear pushbroom satellite imagery by a new epipolarity model

    Science.gov (United States)

    Wang, Mi; Hu, Fen; Li, Jonathan

    This paper presents a practical epipolarity model for high-resolution linear pushbroom satellite images acquired in either along-track or cross-track mode, based on the projection reference plane in object space. A new method for epipolar resampling of satellite stereo imagery based on this model is then developed. In this method, the pixel-to-pixel relationship between the original image and the generated epipolar image is established directly by the geometric sensor model. The approximate epipolar images are generated in a manner similar to digital image rectification. In addition, by arranging the approximate epipolar lines on the defined projection reference plane, a stereoscopic model with consistent ground sampling distance and parallel to the object space is thus available, which is more convenient for three-dimensional measurement and interpretation. The results obtained from SPOT5, IKONOS, IRS-P5, and QuickBird stereo images indicate that the generated epipolar images all achieve high accuracy. Moreover, the vertical parallaxes at check points are at sub-pixel level, thus proving the feasibility, correctness, and applicability of the method.

  4. gProcess and ESIP Platforms for Satellite Imagery Processing over the Grid

    Science.gov (United States)

    Bacu, Victor; Gorgan, Dorian; Rodila, Denisa; Pop, Florin; Neagu, Gabriel; Petcu, Dana

    2010-05-01

    The Environment oriented Satellite Data Processing Platform (ESIP) is developed through the SEE-GRID-SCI (SEE-GRID eInfrastructure for regional eScience) co-funded by the European Commission through FP7 [1]. The gProcess Platform [2] is a set of tools and services supporting the development and the execution over the Grid of the workflow based processing, and particularly the satelite imagery processing. The ESIP [3], [4] is build on top of the gProcess platform by adding a set of satellite image processing software modules and meteorological algorithms. The satellite images can reveal and supply important information on earth surface parameters, climate data, pollution level, weather conditions that can be used in different research areas. Generally, the processing algorithms of the satellite images can be decomposed in a set of modules that forms a graph representation of the processing workflow. Two types of workflows can be defined in the gProcess platform: abstract workflow (PDG - Process Description Graph), in which the user defines conceptually the algorithm, and instantiated workflow (iPDG - instantiated PDG), which is the mapping of the PDG pattern on particular satellite image and meteorological data [5]. The gProcess platform allows the definition of complex workflows by combining data resources, operators, services and sub-graphs. The gProcess platform is developed for the gLite middleware that is available in EGEE and SEE-GRID infrastructures [6]. gProcess exposes the specific functionality through web services [7]. The Editor Web Service retrieves information on available resources that are used to develop complex workflows (available operators, sub-graphs, services, supported resources, etc.). The Manager Web Service deals with resources management (uploading new resources such as workflows, operators, services, data, etc.) and in addition retrieves information on workflows. The Executor Web Service manages the execution of the instantiated workflows

  5. Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

    Science.gov (United States)

    B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

    2014-02-01

    Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and

  6. Visual attention based detection of signs of anthropogenic activities in satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2010-10-13

    With increasing deployment of satellite imaging systems, only a small fraction of collected data can be subject to expert scrutiny. We present and evaluate a two-tier approach to broad area search for signs of anthropogenic activities in high-resolution commercial satellite imagery. The method filters image information using semantically oriented interest points by combining Harris corner detection and spatial pyramid matching. The idea is that anthropogenic structures, such as rooftop outlines, fence corners, road junctions, are locally arranged in specific angular relations to each other. They are often oriented at approximately right angles to each other (which is known as rectilinearity relation). Detecting the rectilinearity provides an opportunity to highlight regions most likely to contain anthropogenic activity. This is followed by supervised classification of regions surrounding the detected corner points as man-made vs. natural scenes. We consider, in particular, a search for anthropogenic activities in uncluttered areas. In this paper, we proposed and evaluated a two-tier approach to broad area search for signs of anthropogenic activities. Results from experiments on high-resolution ({approx}0.6m) commercial satellite image data showed the potential applicability of this approach and its ability of achieving both high precision and recall rates. The main advantage of combining corner-based cueing with general object recognition is that the incorporation of domain specific knowledge even in its more general form, such as presence of comers, provides a useful cue to narrow the focus of search for signs of anthropogenic activities. Combination of comer based cueing with spatial pyramid matching addressed the issue of comer categorization. An important practical issue for further research is optimizing the balance between false positive and false negative rates. While the results presented in the paper are encouraging, the problem of an automated broad area

  7. Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data

    OpenAIRE

    Smirnova, Julia E.; Golubkin, Pavel A.; Bobylev, Leonid P.; Zabolotskikh, Elizaveta; Chapron, Bertrand

    2015-01-01

    A new climatology of polar lows over the Nordic and Barents seas for 14 seasons (1995/1996-2008/2009) is presented. For the first time in climatological studies of polar lows an approach based on satellite passive microwave data was adopted for polar low identification. A total of 637 polar lows were found in 14 extended winter seasons by combining total atmospheric water vapor content and sea surface wind speed fields retrieved from Special Sensor Microwave/Imager data. As derived, the polar...

  8. Applicability of solid state microwave technology to solar power satellites

    Science.gov (United States)

    Nalos, E. J.; Fitzsimmons, G. W.; Sperber, B. R.

    1979-01-01

    A potential SPS design using antenna mounted GaAs FET's as the basic dc-RF converter is described, together with the rationale of why such a design may represent a viable cost effective complement to current SPS designs using tube type dc-RF converters such as klystrons or crossed field amplifiers. An initial description of a microwave antenna array module is given, together with a concept of how such a module is to be integrated into the SPS overall design. A comparison is made of several such designs using either antenna mounted or solar cell mounted dc-RF converters.

  9. LANDSAT imagery: Description of products available from the CSIR Satellite Remote Sensing Centre

    Science.gov (United States)

    1982-01-01

    An overview of the LANDSAT system is provided along with information to assist prospective users in establishing whether imagery for their areas of interest is available and how to obtain such imagery. Spectral bands, spatial resolution, and digital data are explained as well as worldwide reference system indexing and the identification number assigned to images. The sizes and scales of standard black and white imagery and of false color composite imagery are listed. The format is given for computer compatible tapes and standard enhanced imagery is described. Other information available to users include LANDSAT index maps, catalogs of available imagery, a schedule of overpass dates, and a list of product prices.

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

    Energy Technology Data Exchange (ETDEWEB)

    Newsam, S D; Kamath, C

    2004-01-22

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

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

    Science.gov (United States)

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

    2015-10-01

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

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

    Science.gov (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-05-01

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

  13. Ocean Wind Fields from Satellite Active Microwave Sensors

    OpenAIRE

    Zecchetto, S.

    2010-01-01

    Scatterometer QuikSCAT data have been downloaded from the Physical Oceanography Distributed Active Archive Center (PODAAC) of the Jet Propulsion Laboratory, Pasadena, USA. The ASCAT data have been obtained from the Koninklijk Nederlands Meteorologisch Instituut (Dutch Meteorological Service KNMI, www.knmi.nl) operating in the framework of the Ocean & Sea Ice Satellite Application Facility (www.osi-saf.org) of EUMETSAT. The Envisat ASAR Wide Swath image has been downloaded from the ESA web ser...

  14. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2011-02-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3 from AMSR-E and degree of saturation (% from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 ("transitional regions", merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  15. Land and Water Interface of Louisiana from 2002 Landsat Thematic Mapper Satellite Imagery, Geographic NAD83, LOSCO (2005) [landwater_interface_la_03ac_LOSCO_2002

    Data.gov (United States)

    Louisiana Geographic Information Center — These are polygon and raster data sets derived from 2002 Landsat Thematic Mapper Satellite Imagery that indicates areas of land and areas of water in Louisiana. The...

  16. Land and Water Interface of Louisiana from 2002 Landsat Thematic Mapper Satellite Imagery, Geographic NAD83, LOSCO (2004) [landwater_interface_la_25ac_LOSCO_2002

    Data.gov (United States)

    Louisiana Geographic Information Center — These are polygon and raster data sets derived from 2002 Landsat Thematic Mapper Satellite Imagery that indicates areas of land and areas of water in Louisiana. The...

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

  19. Land and Water Interface of Louisiana from 2002 Landsat Thematic Mapper Satellite Imagery, Geographic NAD83, LOSCO (2005) [landwater_interface_la_05ac_LOSCO_2002

    Data.gov (United States)

    Louisiana Geographic Information Center — These are polygon and raster data sets derived from 2002 Landsat Thematic Mapper Satellite Imagery that indicates areas of land and areas of water in Louisiana. The...

  20. Global Terrestrial Evapotranspiration from Optical and Microwave Satellite Observations

    Science.gov (United States)

    Jia, Li; Zhang, Chaolei; Hu, Guangcheng; Zhou, Jie; Cui, Yaokui; Lu, Jing; Wang, Kun; Liu, Qinhuo; Menenti, Massimo

    2016-08-01

    Terrestrial actual evapotranspiration (ET) is an important component of the terrestrial water cycle and links the hydrological, energy, and carbon cycles. Considering the diverse landscapes and multi-climatic features, a hybrid remotely sensed ET estimation model named ETMonitor was developed to estimate the daily actual evapotranspiration globally at a spatial resolution of 1 km. The ETMonitor model uses a variety of biophysical parameters derived from microwave and optical remote sensing observations as input data to estimate the daily ET for all sky conditions. This dataset provides important support to the large-scale evaluation of the environment, and some preliminary applications were conducted for regional- to global-scale mapping and monitoring of water consumption and drought severity.

  1. Phenological dynamics of arctic tundra vegetation and its implications on satellite imagery interpretation

    Science.gov (United States)

    Juutinen, Sari; Aurela, Mika; Mikola, Juha; Räsänen, Aleksi; Virtanen, Tarmo

    2016-04-01

    Remote sensing is a key methodology when monitoring the responses of arctic ecosystems to climatic warming. The short growing season and rapid vegetation development, however, set demands to the timing of image acquisition in the arctic. We used multispectral very high spatial resolution satellite images to study the effect of vegetation phenology on the spectral reflectance and image interpretation in the low arctic tundra in coastal Siberia (Tiksi, 71°35'39"N, 128°53'17"E). The study site mainly consists of peatlands, tussock, dwarf shrub, and grass tundra, and stony areas with some lichen and shrub patches. We tested the hypotheses that (1) plant phenology is responsive to the interannual weather variation and (2) the phenological state of vegetation has an impact on satellite image interpretation and the ability to distinguish between the plant communities. We used an empirical transfer function with temperature sums as drivers to reconstruct daily leaf area index (LAI) for the different plant communities for years 2005, and 2010-2014 based on measured LAI development in summer 2014. Satellite images, taken during growing seasons, were acquired for two years having late and early spring, and short and long growing season, respectively. LAI dynamics showed considerable interannual variation due to weather variation, and particularly the relative contribution of graminoid dominated communities was sensitive to these phenology shifts. We have also analyzed the differences in the reflectance values between the two satellite images taking account the LAI dynamics. These results will increase our understanding of the pitfalls that may arise from the timing of image acquisition when interpreting the vegetation structure in a heterogeneous tundra landscape. Very high spatial resolution multispectral images are available at reasonable cost, but not in high temporal resolution, which may lead to compromises when matching ground truth and the imagery. On the other hand

  2. Multi-decadal record of ice dynamics on Daugaard Jensen Gletscher, East Greenland, from satellite imagery and terrestrial measurements

    DEFF Research Database (Denmark)

    Stearns, L.A.; Hamilton, G.S.; Reeh, Niels

    2005-01-01

    The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained in approxima......The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained...... vs snow accumulation in the interior catchment show that Daugaard Jensen Gletscher has a small negative mass balance. This result is consistent with other mass-balance estimates for the inland region of the glacier....

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

    Directory of Open Access Journals (Sweden)

    CAO Yungang

    2016-10-01

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

  4. Choice of antenna geometry for microwave power transmission from solar power satellites

    Science.gov (United States)

    Potter, Seth D.

    1992-01-01

    A comparison is made between square and circular transmitting antennas for solar power satellite microwave power transmission. It is seen that the exclusion zone around the rectenna needed to protect populations from microwaves is smaller for a circular antenna operating at 2.45 GHz than it is for a square antenna at that frequency. If the frequency is increased, the exclusion zone size remains the same for a square antenna, but becomes even smaller for a circular antenna. Peak beam intensity is the same for both antennas if the frequency and antenna area are equal. The circular antenna puts a somewhat greater amount of power in the main lobe and somewhat less in the side lobes. Since rain attenuation and atmospheric heating remain problems above 10 GHz, it is recommended that future solar power satellite work concentrate on circular transmitting antennas at frequencies of roughly 10 GHz.

  5. Using Satellite Imagery to Monitor the Major Lakes; Case Study Lake Hamun

    Science.gov (United States)

    Norouzi, H.; Islam, R.; Bah, A.; AghaKouchak, A.

    2015-12-01

    Proper lakes function can ease the impact of floods and drought especially in arid and semi-arid regions. They are important environmentally and can directly affect human lives. Better understanding of the effect of climate change and human-driven changes on lakes would provide invaluable information for policy-makers and local people. As part of a comprehensive study, we aim to monitor the land-cover/ land-use changes in the world's major lakes using satellite observations. As a case study, Hamun Lake which is a pluvial Lake, also known as shallow Lake, located on the south-east of Iran and adjacent to Afghanistan, and Pakistan borders is investigated. The Lake is the main source of resources (agriculture, fishing and hunting) for the people around it and politically important in the region since it is shared among three different countries. The purpose of the research is to find the Lake's area from 1972 to 2015 and to see if any drought or water resources management has affected the lake. Analyzing satellites imagery from Landsat shows that the area of the Lake changes seasonally and intra-annually. Significant seasonal effects are found in 1975,1977, 1987, 1993, 1996, 1998, 2000, 2009 and 2011, as well as, substantial amount of shallow water is found throughout the years. The precipitation records as well as drought historical records are studied for the lake's basin. Meteorological studies suggest that the drought, decrease of rainfalls in the province and the improper management of the Lake have caused environmental, economic and geographical consequences. The results reveal that lake has experienced at least two prolong dryings since 1972 which drought cannot solely be blamed as main forcing factor.Proper lakes function can ease the impact of floods and drought especially in arid and semi-arid regions. They are important environmentally and can directly affect human lives. Better understanding of the effect of climate change and human-driven changes on lakes

  6. Subsurface Dynamical Properties of Variable Features Seen in Satellite IR Imagery off Point Sur and Their Acoustic Significance.

    Science.gov (United States)

    1980-06-01

    profile as in Fig. 87 except 60 foot source at 50 Hz -------------------------------. 205 90 Graph showing the difference between clima - tological PL...graph as in Fig. 90 except 300 foot source ---------------------------------------- 207 92 Graph showing the difference between clima - tological PL and... temporal scales, to make observations on the subsurface structure of features observed by satellite imagery, to investigate the diurnal variation of the sea

  7. Combining Satellite Ocean Color Imagery and Circulation Modeling to Forecast Bio-Optical Properties: Comparison of Models and Advection Schemes

    Science.gov (United States)

    2008-10-01

    Remote sensing of ocean color provides synoptic surface ocean bio -optical properties but is limited to real-time or climatological applications. Many...this, we couple satellite imagery with numerical circulation models to provide short-term (24-48 hr) forecasts of bio -optical properties. These are...physical processes control the bio -optical distribution patterns. We compare optical forecast results from three Navy models and two advection

  8. Exploring Land use and Land cover change in the mining areas of Wa East District, Ghana using Satellite Imagery

    Science.gov (United States)

    Basommi, Prosper Laari; Guan, Qingfeng; Cheng, Dandan

    2015-11-01

    Satellite imagery has been widely used to monitor the extent of environmental change in both mine and post mine areas. This study uses Remote sensing and Geographical Information System techniques for the assessment of land use/land cover dynamics of mine related areas in Wa East District of Ghana. Landsat satellite imageries of three different time periods, i.e., 1991, 2000 and 2014 were used to quantify the land use/cover changes in the area. Supervised Classification using Maximum Likelihood Technique in ERDAS was utilized. The images were categorized into five different classes: Open Savannah, Closed Savannah, Bare Areas, Settlement and Water. Image differencing method of change detection was used to investigate the changes. Normalized Differential Vegetative Index valueswere used to correlate the state of healthy vegetation. The image differencing showed a positive correlation to the changes in the Land use and Land cover classes. NDVI values reduced from 0.48 to 0.11. The land use change matrix also showed conversion of savannah areas into bare ground and settlement. Open and close savannah reduced from 50.80% to 36.5% and 27.80% to 22.67% respectively whiles bare land and settlement increased. Overall accuracy of classified 2014 image and kappa statistics was 83.20% and 0.761 respectively. The study revealed the declining nature of the vegetation and the significance of using satellite imagery. A higher resolution satellite Imagery is however needed to satisfactorily delineate mine areas from other bare areas in such Savannah zones.

  9. The Matsu Wheel: A Cloud-based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

    CERN Document Server

    Patterson, Maria T; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert; Handy, Matthew; Ly, Vuong; Mandl, Dan; Pederson, Shane; Pivarski, Jim; Powell, Ray; Spring, Jonathan; Wells, Walt

    2016-01-01

    Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for the cloud-based processing of Earth satellite imagery. A particular focus is the development of applications for detecting fires and floods to help support natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce, Storm and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework is designed to be able to support scanning queries using cloud computing applications, such as Hadoop and Accumulo. A scanning query processes all, or most of the data, in a database or data repository. We also descri...

  10. Monitoring of Conservation Tillage and Tillage Intensity by Ground and Satellite Imagery

    Directory of Open Access Journals (Sweden)

    M.A Rostami

    2014-09-01

    Full Text Available Local information about tillage intensity and ground residue coverage is useful for policies in agricultural extension, tillage implement design and upgrading management methods. The current methods for assessing crop residue coverage and tillage intensity such as residue weighing methods, line-transect and photo comparison methods are tedious and time-consuming. The present study was devoted to investigate accurate methods for monitoring residue management and tillage practices. The satellite imagery technique was used as a rapid and spatially explicit method for delineating crop residue coverage and as an estimator of conservation tillage adoption and intensity. The potential of multispectral high-spatial resolution WorldView-2 local data was evaluated using the total of eleven satellite spectral indices and Linear Spectral Unmixing Analysis (LSUA. The total of ninety locations was selected for this study and for each location the residue coverage was measured by the image processing method and recorded as ground control. The output of indices and LSUA method were individually correlated to the control and the relevant R2 was calculated. Results indicated that crop residue cover was related to IPVI, RVI1, RVI2 and GNDVI spectral indices and satisfactory correlations were established (0.74 - 0.81. The crop residue coverage estimated from the LSUA approach was found to be correlated with the ground residue data (0.75. Two effective indices named as Infrared Percentage Vegetation Index (IPVI and Ratio Vegetation Index (RVI with maximum R2 were considered for classification of tillage intensity. Results indicated that the classification accuracy with IPVI and RVI indices in different conditions varied from 78-100 percent and therefore in good agreement with ground measurement, observations and field records.

  11. The interpretation of SIR-B imagery of surface waves and other oceanographic features using in-situ, meteorological satellite, and infrared satellite data

    Science.gov (United States)

    Allan, T.; Guymer, T.; Muller, P.

    1984-01-01

    The overall aim is to interpret Shuttle Imaging Radar-B imagery of selected ocean areas near the United Kingdom using available data from ships and buoys, with particular emphasis on understanding the mechanisms involved in the backscattering of microwaves from the sea surface and their relationship to surface gravity waves. The secondary objective is to use a multispectral approach to study sea-surface expressions such as slicks, internal waves, and eddies. Data acquisition, handling, and analysis approaches and expected results are discussed.

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

    Directory of Open Access Journals (Sweden)

    Curt H. Davis

    2005-08-01

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

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

    Science.gov (United States)

    Sharghi, Elan

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

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

    Science.gov (United States)

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

    2016-12-01

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

  15. Urban thermal environment and its biophysical parameters derived from satellite remote sensing imagery

    Science.gov (United States)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

    2013-10-01

    In frame of global warming, the field of urbanization and urban thermal environment are important issues among scientists all over the world. This paper investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Bucharest metropolitan area of Romania based on satellite remote sensing imagery Landsat TM/ETM+, time series MODIS Terra/Aqua data and IKONOS acquired during 1990 - 2012 period. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also retrieved from thermal infrared band of Landsat TM/ETM+, from MODIS Terra/Aqua datasets. Based on these parameters, the urban growth, urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results indicated that the metropolitan area ratio of impervious surface in Bucharest increased significantly during two decades investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

  16. Monitoring the Urban Growth of Dhaka (bangladesh) by Satellite Imagery in Flooding Risk Management Perspective

    Science.gov (United States)

    Bitelli, G.; Franci, F.; Mandanici, E.

    2013-01-01

    There is large consensus that demographic changes, the lack of appropriate environmental policies and sprawling urbanization result in high vulnerability and exposure to the natural disasters. This work reports some experiences of using multispectral satellite imagery to produce landuse/cover maps for the Dhaka city, the capital of Bangladesh, which is subject to frequent flooding events.The activity was conducted in collaboration with the non-profit organization ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The Landsat images acquired in 2000, 2002 and 2009 were used to evaluate the urban growth in order to support risk assessment studies; to identify areas routinely flooded during the monsoon season, the image of October 2009 (the most critical month for the effects of rain) was compared with two images acquired in January and February 2010. The analysis between 2000 and 2009 was able to quantify a very rapid growth of the metropolis, with an increase in built-up areas from 75 to 111 km2. The analysis highlights also a sharp rise of Bare soil class, likely related to the construction of embankments for the creation of new building space; consequently a decrease of cultivated land was observed. In particular, these artificial islands have been invading flooding areas. The change detection procedure also showed that the flooding in October 2009 affected about 20% (115 out of 591 km2) of the entire study area; furthermore these areas became wetlands and farmland over the next three/four months.

  17. Flood mapping using VHR satellite imagery: a comparison between different classification approaches

    Science.gov (United States)

    Franci, Francesca; Boccardo, Piero; Mandanici, Emanuele; Roveri, Elena; Bitelli, Gabriele

    2016-10-01

    Various regions in Europe have suffered from severe flooding over the last decades. Flood disasters often have a broad extent and a high frequency. They are considered the most devastating natural hazards because of the tremendous fatalities, injuries, property damages, economic and social disruption that they cause. In this context, Earth Observation techniques have become a key tool for flood risk and damage assessment. In particular, remote sensing facilitates flood surveying, providing valuable information, e.g. flood occurrence, intensity and progress of flood inundation, spurs and embankments affected/threatened. The present work aims to investigate the use of Very High Resolution satellite imagery for mapping flood-affected areas. The case study is the November 2013 flood event which occurred in Sardinia region (Italy), affecting a total of 2,700 people and killing 18 persons. The investigated zone extends for 28 km2 along the Posada river, from the Maccheronis dam to the mouth in the Tyrrhenian sea. A post-event SPOT6 image was processed by means of different classification methods, in order to produce the flood map of the analysed area. The unsupervised classification algorithm ISODATA was tested. A pixel-based supervised technique was applied using the Maximum Likelihood algorithm; moreover, the SPOT 6 image was processed by means of object-oriented approaches. The produced flood maps were compared among each other and with an independent data source, in order to evaluate the performance of each method, also in terms of time demand.

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

    Science.gov (United States)

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

    2014-11-01

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

  19. Glacier changes in the Karakoram region mapped by multi-mission satellite imagery

    Directory of Open Access Journals (Sweden)

    M. Rankl

    2013-08-01

    Full Text Available Glaciers in the Karakoram region are known to show stable and advancing terminus positions or surging behavior, which contrasts the worldwide retreat of many mountain glaciers. The present study uses Landsat imagery to derive an updated and extended glacier inventory. Surging and advancing glaciers and their annual termini position changes are mapped in addition. Out of 1334 glaciers, 134 show advancing or surging behavior, with a marked increase since 2000. The length distribution of surging glaciers differs significantly from non-surging glaciers. More than 50% of the advancing/surging glaciers are shorter than 10 km. Besides a regional spatial coverage of ice dynamics, high-resolution SAR data allows to investigate very small and comparably fast flowing glaciers (up to 1.8 m day−1. Such data enables mapping of temporal changes of ice dynamics of individual small surging or advancing glaciers. In a further case study, glacier volume changes of three glaciers around Braldu Glacier are quantified during a surge event comparing digital elevation models from the Shuttle Radar Topography Mission (SRTM and the new TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X Mission. We recommend regular acquisitions of high resolution (bi-static SAR satellite data and further exploitation of the archives in order to generate an improved database for monitoring changes, and to at least partially compensate for the lack of in-situ and long-term climatological measurements in the Karakoram region.

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

    Science.gov (United States)

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2009-05-01

    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.

  2. Determination of mangrove change in Matang Mangrove Forest using multi temporal satellite imageries

    Science.gov (United States)

    Ibrahim, N. A.; Mustapha, M. A.; Lihan, T.; Ghaffar, M. A.

    2013-11-01

    Mangrove protects shorelines from damaging storm and hurricane winds, waves, and floods. Mangroves also help prevent erosion by stabilizing sediments with their tangled root systems. They maintain water quality and clarity, filtering pollutants and trapping sediments originating from land. However, mangrove has been reported to be threatened by land conversion for other activities. In this study, land use and land cover changes in Matang Mangrove Forest during the past 18 years (1993 to 2011) were determined using multi-temporal satellite imageries by Landsat TM and RapidEye. In this study, classification of land use and land cover approach was performed using the maximum likelihood classifier (MCL) method along with vegetation index differencing (NDVI) technique. Data obtained was evaluated through Kappa coefficient calculation for accuracy and results revealed that the classification accuracy was 81.25% with Kappa Statistics of 0.78. The results indicated changes in mangrove forest area to water body with 2,490.6 ha, aquaculture with 890.7 ha, horticulture with 1,646.1 ha, palm oil areas with 1,959.2 ha, dry land forest with 2,906.7 ha and urban settlement area with 224.1 ha. Combinations of these approaches were useful for change detection and for indication of the nature of these changes.

  3. GPU-based normalized cuts for road extraction using satellite imagery

    Indian Academy of Sciences (India)

    J Senthilnath; S Sindhu; S N Omkar

    2014-12-01

    This paper presents a GPU implementation of normalized cuts for road extraction problem using panchromatic satellite imagery. The roads have been extracted in three stages namely pre-processing, image segmentation and post-processing. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, vegetation, and fallow regions). The road regions are then extracted using the normalized cuts algorithm. Normalized cuts algorithm is a graph-based partitioning approach whose focus lies in extracting the global impression (perceptual grouping) of an image rather than local features. For the segmented image, post-processing is carried out using morphological operations – erosion and dilation. Finally, the road extracted image is overlaid on the original image. Here, a GPGPU (General Purpose Graphical Processing Unit) approach has been adopted to implement the same algorithm on the GPU for fast processing. A performance comparison of this proposed GPU implementation of normalized cuts algorithm with the earlier algorithm (CPU implementation) is presented. From the results, we conclude that the computational improvement in terms of time as the size of image increases for the proposed GPU implementation of normalized cuts. Also, a qualitative and quantitative assessment of the segmentation results has been projected.

  4. 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

    2009-01-01

    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.

  5. Object-oriented industrial solid waste identification using HJ satellite imagery: a case study of phosphogypsum

    Science.gov (United States)

    Fu, Zhuo; Shen, Wenming; Xiao, Rulin; Xiong, Wencheng; Shi, Yuanli; Chen, Baisong

    2012-10-01

    The increasing volume of industrial solid wastes presents a critical problem for the global environment. In the detection and monitoring of these industrial solid wastes, the traditional field methods are generally expensive and time consuming. With the advantages of quick observations taken at a large area, remote sensing provides an effective means for detecting and monitoring the industrial solid wastes in a large scale. In this paper, we employ an object-oriented method for detecting the industrial solid waste from HJ satellite imagery. We select phosphogypsum which is a typical industrial solid waste as our target. Our study area is located in Fuquan in Guizhou province of China. The object oriented method we adopted consists of the following steps: 1) Multiresolution segmentation method is adopted to segment the remote sensing images for obtaining the object-based images. 2) Build the feature knowledge set of the object types. 3) Detect the industrial solid wastes based on the object-oriented decision tree rule set. We analyze the heterogeneity in features of different objects. According to the feature heterogeneity, an object-oriented decision tree rule set is then built for aiding the identification of industrial solid waste. Then, based on this decision tree rule set, the industrial solid waste can be identified automatically from remote sensing images. Finally, the identified results are validated using ground survey data. Experiments and results indicate that the object-oriented method provides an effective method for detecting industrial solid wastes.

  6. Seasonally-managed wetland footprint delineation using Landsat ETM+ satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Quinn, Nigel W. T. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Epshtein, Olga [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Arizona State Univ., Tempe, AZ (United States). School of Sustainable Engineering and the Built Environment

    2014-01-09

    One major challenge in water resource management is the estimation of evapotranspiration losses from seasonally managed wetlands. Quantifying these losses is complicated by the dynamic nature of the wetlands' areal footprint during the periods of flood-up and drawdown. In this paper, we present a data-lean solution to this problem using an example application in the San Joaquin Basin, California. Through analysis of high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) satellite imagery, we develop a metric to better capture the extent of total flooded wetland area. The procedure is validated using year-long, continuously-logged field datasets for two wetlands within the study area. The proposed classification which uses a Landsat ETM + Band 5 (mid-IR wavelength) to Band 2 (visible green wavelength) ratio improves estimates by 30–50% relative to previous wetland delineation studies. Finally, requiring modest ancillary data, the study results provide a practical and efficient option for wetland management in data-sparse regions or un-gauged watersheds.

  7. Mapping snow depth in open alpine terrain from stereo satellite imagery

    Science.gov (United States)

    Marti, R.; Gascoin, S.; Berthier, E.; de Pinel, M.; Houet, T.; Laffly, D.

    2016-07-01

    To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. Here, we examine the potential of very-high-resolution (VHR) optical stereo satellites to this purpose. Two triplets of 0.70 m resolution images were acquired by the Pléiades satellite over an open alpine catchment (14.5 km2) under snow-free and snow-covered conditions. The open-source software Ame's Stereo Pipeline (ASP) was used to match the stereo pairs without ground control points to generate raw photogrammetric clouds and to convert them into high-resolution digital elevation models (DEMs) at 1, 2, and 4 m resolutions. The DEM differences (dDEMs) were computed after 3-D coregistration, including a correction of a -0.48 m vertical bias. The bias-corrected dDEM maps were compared to 451 snow-probe measurements. The results show a decimetric accuracy and precision in the Pléiades-derived snow depths. The median of the residuals is -0.16 m, with a standard deviation (SD) of 0.58 m at a pixel size of 2 m. We compared the 2 m Pléiades dDEM to a 2 m dDEM that was based on a winged unmanned aircraft vehicle (UAV) photogrammetric survey that was performed on the same winter date over a portion of the catchment (3.1 km2). The UAV-derived snow depth map exhibits the same patterns as the Pléiades-derived snow map, with a median of -0.11 m and a SD of 0.62 m when compared to the snow-probe measurements. The Pléiades images benefit from a very broad radiometric range (12 bits), allowing a high correlation success rate over the snow-covered areas. This study demonstrates the value of VHR stereo satellite imagery to map snow depth in remote mountainous areas even when no field data are available.

  8. Correcting bias in the rational polynomial coefficients of satellite imagery using thin-plate smoothing splines

    Science.gov (United States)

    Shen, Xiang; Liu, Bin; Li, Qing-Quan

    2017-03-01

    The Rational Function Model (RFM) has proven to be a viable alternative to the rigorous sensor models used for geo-processing of high-resolution satellite imagery. Because of various errors in the satellite ephemeris and instrument calibration, the Rational Polynomial Coefficients (RPCs) supplied by image vendors are often not sufficiently accurate, and there is therefore a clear need to correct the systematic biases in order to meet the requirements of high-precision topographic mapping. In this paper, we propose a new RPC bias-correction method using the thin-plate spline modeling technique. Benefiting from its excellent performance and high flexibility in data fitting, the thin-plate spline model has the potential to remove complex distortions in vendor-provided RPCs, such as the errors caused by short-period orbital perturbations. The performance of the new method was evaluated by using Ziyuan-3 satellite images and was compared against the recently developed least-squares collocation approach, as well as the classical affine-transformation and quadratic-polynomial based methods. The results show that the accuracies of the thin-plate spline and the least-squares collocation approaches were better than the other two methods, which indicates that strong non-rigid deformations exist in the test data because they cannot be adequately modeled by simple polynomial-based methods. The performance of the thin-plate spline method was close to that of the least-squares collocation approach when only a few Ground Control Points (GCPs) were used, and it improved more rapidly with an increase in the number of redundant observations. In the test scenario using 21 GCPs (some of them located at the four corners of the scene), the correction residuals of the thin-plate spline method were about 36%, 37%, and 19% smaller than those of the affine transformation method, the quadratic polynomial method, and the least-squares collocation algorithm, respectively, which demonstrates

  9. A robust method for removal of glint effects from satellite ocean colour imagery

    Directory of Open Access Journals (Sweden)

    R. K. Singh

    2014-12-01

    Full Text Available Removal of the glint effects from satellite imagery for accurate retrieval of water-leaving radiances is a complicated problem since its contribution in the measured signal is dependent on many factors such as viewing geometry, sun elevation and azimuth, illumination conditions, wind speed and direction, and the water refractive index. To simplify the situation, existing glint correction models describe the extent of the glint-contaminated region and its contribution to the radiance essentially as a function of the wind speed and sea surface slope that often lead to a tremendous loss of information with a considerable scientific and financial impact. Even with the glint-tilting capability of modern sensors, glint contamination is severe on the satellite-derived ocean colour products in the equatorial and sub-tropical regions. To rescue a significant portion of data presently discarded as "glint contaminated" and improving the accuracy of water-leaving radiances in the glint contaminated regions, we developed a glint correction algorithm which is dependent only on the satellite derived Rayleigh Corrected Radiance and absorption by clear waters. The new algorithm is capable of achieving meaningful retrievals of ocean radiances from the glint-contaminated pixels unless saturated by strong glint in any of the wavebands. It takes into consideration the combination of the background absorption of radiance by water and the spectral glint function, to accurately minimize the glint contamination effects and produce robust ocean colour products. The new algorithm is implemented along with an aerosol correction method and its performance is demonstrated for many MODIS-Aqua images over the Arabian Sea, one of the regions that are heavily affected by sunglint due to their geographical location. The results with and without sunglint correction are compared indicating major improvements in the derived products with sunglint correction. When compared to the

  10. Himalayan glaciers: understanding contrasting patterns of glacier behavior using multi-temporal satellite imagery

    Science.gov (United States)

    Racoviteanu, A.

    2014-12-01

    High rates of glacier retreat for the last decades are often reported, and believed to be induced by 20th century climate changes. However, regional glacier fluctuations are complex, and depend on a combination of climate and local topography. Furthermore, in ares such as the Hindu-Kush Himalaya, there are concerns about warming, decreasing monsoon precipitation and their impact on local glacier regimes. Currently, the challenge is in understanding the magnitude of feedbacks between large-scale climate forcing and small-scale glacier behavior. Spatio-temporal patterns of glacier distribution are still llimited in some areas of the high Hindu-Kush Himalaya, but multi-temporal satellite imagery has helped fill spatial and temporal gaps in regional glacier parameters in the last decade. Here I present a synopsis of the behavior of glaciers across the Himalaya, following a west to east gradient. In particular, I focus on spatial patterns of glacier parameters in the eastern Himalaya, which I investigate at multi-spatial scales using remote sensing data from declassified Corona, ASTER, Landsat ETM+, Quickbird and Worldview2 sensors. I also present the use of high-resolution imagery, including texture and thermal analysis for mapping glacier features at small scale, which are particularly useful in understanding surface trends of debris-covered glaciers, which are prevalent in the Himalaya. I compare and contrast spatial patterns of glacier area and élévation changes in the monsoon-influenced eastern Himalaya (the Everest region in the Nepal Himalaya and Sikkim in the Indian Himalaya) with other observations from the dry western Indian Himalaya (Ladakh and Lahul-Spiti), both field measurements and remote sensing-based. In the eastern Himalaya, results point to glacier area change of -0.24 % ± 0.08% per year from the 1960's to the 2006's, with a higher rate of retreat in the last decade (-0.43% /yr). Debris-covered glacier tongues show thinning trends of -30.8 m± 39 m

  11. Spatial Scaling of Snow Observations and Microwave Emission Modeling During CLPX and Appropriate Satellite Sensor Resolution

    Science.gov (United States)

    Kim, Edward J.; Tedesco, Marco

    2005-01-01

    Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.

  12. Quantifying the Value of Satellite Imagery in Agriculture and other Sectors

    Science.gov (United States)

    Brown, M. E.; Abbott, P. C.; Escobar, V. M.

    2013-12-01

    This study focused on quantifying the commercial value of satellite remote sensing for agriculture. Commercial value from satellite imagery arises when improved information leads to better economic decisions. We identified five areas of application of remote sensing to agriculture where there is this potential: crop management (precision agriculture), insurance, real estate assessment, crop forecasting, and environmental monitoring. These applications can be divided between public information (crop forecasting) and those that may generate private commercial value (crop management), with both public and private information dimensions in some categories. Public information applications of remote sensing have been more successful in the past, and are likely to generate more economic value in the future. It was found that several issues have limited realization of the potential to generate private value from remote sensing in agriculture. The scale of use is small to the high cost of acquiring and interpreting large images has limited the cost effectiveness to individual farmers. Insurance, environmental monitoring, and crop management services by cooperatives or consultants may be cases overcoming this limitation. The greatest opportunities for potential commercial value from agriculture are probably in the crop forecasting area, especially where agricultural statistics services are not as well developed, since public market information benefits a broad range of economic actors, not limited to countries where forecasts are made. We estimate here the value from components of USDA's World Agricultural Supply and Demand Estimates (WASDE) forecasts for corn, indicating potential value increasing in the range of 60 to 240 million if improved satellite based information enhances those forecasts. The research was conducted by agricultural economists at Purdue University, and will be the basis for further evaluation of the use of satellite data within the NASA Carbon

  13. The microwave noise environment at a geostationary satellite caused by the brightness of the earth

    Science.gov (United States)

    Smith, E. K.; Njoku, E. G.

    1985-01-01

    The microwave antenna temperature due to the earth in the satellite antenna beam has been computed for a series of longitudes for a satellite in geostationary orbit and for frequencies of 1 to 50 GHz. An earth-coverage beam is assumed for simplicity, but the technique is applicable to arbitrary beam shapes. Detailed calculations have been performed to account for varying land-ocean fractions within the field of view. Emission characteristics of the earth's atmosphere and surface are used with an accurate radiation transfer program to compute observed brightness temperatures. The value of 290 K commonly used for antenna temperature in satellite communication noise calculations is overly conservative, with more realistic values lying in the 60 to 240 K range.

  14. Signals of Opportunity Earth Reflectometry (SoOp-ER): Enabling new microwave observations from small satellites

    Science.gov (United States)

    Garrison, J. L.; Piepmeier, J. R.; Shah, R.; Lin, Y. C.; Du Toit, C. F.; Vega, M. A.; Knuble, J. J.

    2016-12-01

    Several recent experiments have demonstrated remote sensing by reutilizing communication satellite transmissions as sources in a bistatic radar configuration. This technique, referred to as "Signals of Opportunity Earth Reflectometry" (SoOp-ER), combines aspects of passive radiometry, active scatterometry and radar altimetry, but is essentially a new and alternative approach to microwave remote sensing. Reflectometry was first demonstrated with Global Navigation Satellite System (GNSS) signals, enabled by their use of pseudorandom noise (PRN) codes for ranging. Two decades of research in GNSS reflectometry has culminated in the upcoming launches of several satellite missions within the next few years (TechDemoSat-1, CYGNSS, and GEROS-ISS). GNSS signals, however, have low power and are confined to a few L-band frequencies allocated to radionavigation. Communication satellites, in contrast, transmit in nearly all bands penetrating the Earth's atmosphere at very high radiated powers to assure a low bit-error-rate. High transmission power and a forward scatter geometry result in a very high signal to noise ratio at the receiver. Surface resolution is determined by the signal bandwidth, not the antenna beam. In many applications, this will allow small, low gain antennas to be used to make scientifically useful measurements. These features indicate that SoOp-ER instruments would be an ideal technology for microwave remote sensing from small platforms. SoOp-ER observations are referenced at the specular point and a constellation of small satellites, evenly spaced in the same orbit, would provide global coverage through parallel specular point ground tracks. This presentation will summarize the current instrument development work by the authors on three different application of SoOp-ER: P-band (230-270 MHz) sensing of root-zone soil moisture (RZSM), S-band sensing of ocean winds and Ku/Ka-band altimetry. Potential mission scenarios using small satellite constellations

  15. Monitoring the frozen duration of Qinshai Lake using satellite passive microwave remote sensing low frequency data

    Institute of Scientific and Technical Information of China (English)

    CHE Tao; LI Xin; JIN Rui

    2009-01-01

    The Qinghai Lake is the largest inland lake in China.The significant difference of dielectric properties between water and ice suggests that a simple method of monitoring the Qinghai lake freeze-up and break-up dates using satellite passive microwave remote sensing data could be used.The freeze-up and break-up dates from the Qinghai Lake hydrological station and the MODIS L1B reflectance data were used to validate the passive microwave remote sensing results.The validation shows that passive microwave remote sensing data can accurately monitor the lake ice.Some uncertainty comes mainly from the revisit frequency of satellite overpass.The data from 1978 to 2006 show that lake ice duration is reduced by about 14-15 days.The freeze-up dates are about 4 days later and break-up dates about 10 days earlier.The regression analyses show that,at the 0.05 significance level,the correlations are 0.83,0.66 and 0.89 between monthly mean air temperature (MMAT) and lake ice duration days,freeze-up dates,break-up dates,respectively.Therefore,inter-annual variations of the Qinghai Lake ice duration days can significantly reflect the regional climate variation.

  16. Prototype of the Mexican spatial data infrastructure for climate raster models and satellite imagery (“VISTA-C”)

    Science.gov (United States)

    Couturier, S.; Osorno Covarrubias, J.; Magaña Rueda, V.; Martínez Zazueta, I.; Vázquez Cruz, G.

    2017-01-01

    In the face of climatic uncertainty and its impacts on agriculture yields, there is a growing need for public institutions of subtropical countries to access as reliable as possible meteorological models and transmit a representation of their results in an effective way to stakeholders in agriculture. In many of these countries however, broad climatic regions and point-based statistics remain the core of these representations. The use of satellite imagery is largely limited to visual assessment, although it could serve as complementary data to meteorological raster models and the basis for spatially consistent quantitative impact assessments of meteorological events. In view of this situation in Mexico, a project developed by the Institute of Geography at UNAM university, and promoted by the National Institute of Geography and Statistics, consisted in the development of a climate monitoring system, which includes three main features: 1) a modular array storage system containing NOAA and GOES satellite imagery acquired though a receiving station (ERISA), 2) a climate modeling squeme based on successive error corrections of climate raster maps and associated models using the above mentioned imagery, and 3) an online, dynamic geovisualization of the results of the models. We discuss the implemented technologies and illustrate the VISTA-C prototype which has been released.

  17. Estimation of hydraulic conductivity of a coastal aquifer using satellite imagery

    Science.gov (United States)

    Rebolledo-Vieyra, M.; Iglesias-Prieto, R.; Marino-Tapia, I.

    2012-12-01

    The northern Yucatan Peninsula is characterized by a young and dynamic karstic system that yields very high secondary porosity and permeability. However, we have little, if none, knowledge about the hydraulic conductivity and the amount of groundwater being discharged in to ocean. Here we present and estimation of the hydraulic conductivity and quantity of groundwater being discharged by the northern Yucatan Peninsula coastal aquifer into the Gulf of Mexico, using the Sea Surface Temperature (SST) Images offshore the Yucatan coast, where we have detected a thermal anomaly that appears few hours after heavy rainfall in northern Yucatan. We associated these thermal anomalies of the SST to the groundwater being discharged into the ocean. To test our hypothesis we conducted a review of extreme rainfall events in the last 10 years; in parallel we used data from pressure and flow direction gauges installed in a known submarine groundwater discharge (SGD) to estimate the hydraulic conductivity and the quantity of groundwater being discharged. The satellite imagery and the rainfall data, allowed us to estimate the time lag between the rainfall and the SGD beginning, along with the hydraulic data from the gauges we have estimated the hydrogeological parameters of the coastal aquifer. This data is very important to contribute to the understanding the hydrogeological setting of the Yucatan coastal aquifer and its implications of the impact of human activities on the water quality. July 29th, 2005, NOAA's Sea Surface Temperature (SST) image of the Gulf of Mexico taken a week after hurricane Emily (2005). A thermal low is present offshore northern Yucatan.

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

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

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

  19. EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

    Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

  20. Validation of the morphological compositing method for ZY-3 satellite imagery

    Science.gov (United States)

    Feng, Shuna; Zhao, Yindi

    2014-11-01

    Each scene of image generated from earth observation satellites can only cover a certain area. When one scene cannot cover a user's area of interest, two or more scenes are needed to be registered and combined into a single image, and this composition process is referred to as image mosaicking. The key issue in image composition is to decide where to place the seam line in overlapping region. The optimal seam line which joins several scenes of images covered the entire study area, is usually determined by texture and other characteristics of the overlap region for seamless quality. Recently, a morphological image compositing algorithm was proposed which is able to automatically delineate seam lines along salient image structures. And this algorithm uses the ideas of marker-controlled segmentation for image mosaicking and divides the overlap region into a determined number of areas. The resulting seam lines of the morphological image compositing algorithm cut along high gradient regions which are object edges in initial images. However, the morphological compositing method only applied to delineate the invisible seam line to the human eyes based on Landsat ETM+ data which is the representation of medium resolution data. In this paper, we test the validation of the morphological compositing method to generate visually pleasing seam line for image mosaic without changing the image radiometry and feasibility to handle two adjacent scenes simultaneously on high spatial resolution imagery by using ZY-3 multispectral image data. The focus of this paper is developing a quantitative evaluation measure which is usually formulated as the sum of morphological gradient of the image mosaic along the seam line divided by the length of the seam to quantitatively estimate the `quality' of the automatically delineate seam line.

  1. From Satellite Imagery to Peatland Vegetation Diversity: How Reliable Are Habitat Maps?

    Directory of Open Access Journals (Sweden)

    Monique F. Poulin

    2002-12-01

    Full Text Available Although satellite imagery is becoming a basic component of the work of ecologists and conservationists, its potential and reliability are still relatively unknown for a large number of ecosystems. Using Landsat 7/ETM+ (Enhanced Thematic Mapper Plus data, we tested the accuracy of two types of supervised classifications for mapping 13 peatland habitats in southern Quebec, Canada. Before classifying peatland habitats, we applied a mask procedure that revealed 629 peatlands covering a total of 18,103 ha; 26% of them were larger than 20 ha. We applied both a simple maximum likelihood (ML function and a weighted maximum likelihood (WML function that took into account the proportion of each habitat class within each peatland when classifying the habitats on the image. By validating 626 Global Positioning System locations within 92 peatlands, we showed that both classification procedures provided an accurate representation of the 13 peatland habitat classes. For all habitat classes except lawn with pools, the predominant classified habitat within 45 m of the center of the validation location was of the same type as the one observed in the field. There were differences in the performance of the two classification procedures: ML was a better tool for mapping rare habitats, whereas WML favored the most common habitats. Based on ordinations, peatland habitat classes were as effective as environmental variables such as humidity indicators and water chemistry components at explaining the distribution of plant species and performed 1.6 times better when it came to accounting for vegetation structure patterns. Peatland habitats with pools had the most distinct plant assemblages, and the habitats dominated by herbs were moderately distinct from those characterized by ericaceous shrubs. Habitats dominated by herbs were the most variable in terms of plant species assemblages. Because peatlands are economically valuable wetlands, the maps resulting from the new

  2. Quantifying ice loss in the eastern Himalayas since 1974 using declassified spy satellite imagery

    Science.gov (United States)

    Maurer, Joshua M.; Rupper, Summer B.; Schaefer, Joerg M.

    2016-09-01

    Himalayan glaciers are important natural resources and climate indicators for densely populated regions in Asia. Remote sensing methods are vital for evaluating glacier response to changing climate over the vast and rugged Himalayan region, yet many platforms capable of glacier mass balance quantification are somewhat temporally limited due to typical glacier response times. We here rely on declassified spy satellite imagery and ASTER data to quantify surface lowering, ice volume change, and geodetic mass balance during 1974-2006 for glaciers in the eastern Himalayas, centered on the Bhutan-China border. The wide range of glacier types allows for the first mass balance comparison between clean, debris, and lake-terminating (calving) glaciers in the region. Measured glaciers show significant ice loss, with an estimated mean annual geodetic mass balance of -0.13 ± 0.06 m w.e. yr-1 (meters of water equivalent per year) for 10 clean-ice glaciers, -0.19 ± 0.11 m w.e. yr-1 for 5 debris-covered glaciers, -0.28 ± 0.10 m w.e. yr-1 for 6 calving glaciers, and -0.17 ± 0.05 m w.e. yr-1 for all glaciers combined. Contrasting hypsometries along with melt pond, ice cliff, and englacial conduit mechanisms result in statistically similar mass balance values for both clean-ice and debris-covered glacier groups. Calving glaciers comprise 18 % (66 km2) of the glacierized area yet have contributed 30 % (-0.7 km3) to the total ice volume loss, highlighting the growing relevance of proglacial lake formation and associated calving for the future ice mass budget of the Himalayas as the number and size of glacial lakes increase.

  3. Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

    Directory of Open Access Journals (Sweden)

    Bin Yong

    2015-01-01

    Full Text Available The impact of one or two missing passive microwave (PMW input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA products were reproduced and re-released by National Aeronautics and Space Administration (NASA Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16 input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the “early” and “late” Version-7 TMPA real-time (TMPA-RT precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km2. The retrieval counts and retrieval frequency of various PMW and Infrared (IR sensors incorporated into the TMPA system were also analyzed to identify and diagnose the impacts of sensor availability on the TMPA-RT retrieval accuracy. Results show that the incorporation of AMSU-B and SSMIS-F16 has substantially reduced systematic errors. The improvement exhibits rather strong seasonal and topographic dependencies. Our analyses suggest that one or two single PMW sensors might play a key role in affecting the end product of current combined microwave-infrared precipitation estimates. This finding supports algorithm developers’ current endeavor in spatiotemporally incorporating as many PMW sensors as possible in the multi-satellite precipitation retrieval system called Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG. This study also recommends users of satellite precipitation products to switch to the newest Version-7 TMPA datasets and

  4. Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Latent Heating Profiles

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.; Shie, Chung-Lin; L'Ecuyer, Tristan S.; Tao, Wei-Kuo

    2009-01-01

    In this study, satellite passive microwave sensor observations from the TRMM Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1-QR) in regions of precipitation. The TMI heating algorithm (TRAIN) is calibrated, or "trained" using relatively accurate estimates of heating based upon spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based upon a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically-integrated condensation and surface precipitation. Estimates of Q1-QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1-QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structure with sharper and more intense heating peaks than the rawinsonde estimates. 2

  5. Evaluation of a physically-based snow model with infrared and microwave satellite-derived estimates

    Science.gov (United States)

    Wang, L.

    2013-05-01

    Snow (with high albedo, as well as low roughness and thermal conductivity) has significant influence on the land-atmosphere interactions in the cold climate and regions of high elevation. The spatial and temporal variability of the snow distribution on a basin scale greatly determines the timing and magnitude of spring snowmelt runoff. For improved water resources management, a physically-based distributed snow model has been developed and applied to the upper Yellow River Basin to provide the outputs of snow variables as well as streamflows from 2001 to 2005. Remotely-sensed infrared information from MODIS satellites has been used to evaluate the model's outputs of spatially-distributed snow cover extent (SCE) and land surface temperature (LST); while the simulated snow depth (SD) and snow water equivalent (SWE) have been compared with the microwave information from SSM/I and AMSR-E satellites. In general, the simulated streamflows (including spring snowmelt) agree fairly well with the gauge-based observations; while the modeled snow variables show acceptable accuracies through comparing to various satellite-derived estimates from infrared or microwave information.;

  6. Comparison of microwave satellite humidity data and radiosonde profiles: a survey of European stations

    Directory of Open Access Journals (Sweden)

    V. O. John

    2005-03-01

    Full Text Available A method to compare upper tropospheric humidity (UTH from satellite and radiosonde data has been applied to the European radiosonde stations. The method uses microwave data as a benchmark for monitoring the performance of the stations. The present study utilizes three years (2002–2003 of data from channel 18 (183.31±1.00 GHz of the Advanced Microwave Sounding Unit-B (AMSU-B aboard the satellites NOAA-15 and NOAA-16. The comparison is done in the radiance space, the radiosonde data were transformed to the channel radiances using a radiative transfer model. The comparison results confirm that there is a dry bias in the UTH measured by the radiosondes. This bias is highly variable among the stations and the years. This variability is attributed mainly to the differences in the radiosonde humidity measurements. The results also hint at a systematic difference between the two satellites, the channel 18 brightness temperature of NOAA-15 is on average 1.0 K higher than that of NOAA-16. The difference of 1 K corresponds to approximately 7% relative error in UTH which is significant for climatological applications.

  7. Passive microwave (SSM/I) satellite predictions of valley glacier hydrology, Matanuska Glacier, Alaska

    Science.gov (United States)

    Kopczynski, S.E.; Ramage, J.; Lawson, D.; Goetz, S.; Evenson, E.; Denner, J.; Larson, G.

    2008-01-01

    We advance an approach to use satellite passive microwave observations to track valley glacier snowmelt and predict timing of spring snowmelt-induced floods at the terminus. Using 37 V GHz brightness temperatures (Tb) from the Special Sensor Microwave hnager (SSM/I), we monitor snowmelt onset when both Tb and the difference between the ascending and descending overpasses exceed fixed thresholds established for Matanuska Glacier. Melt is confirmed by ground-measured air temperature and snow-wetness, while glacier hydrologic responses are monitored by a stream gauge, suspended-sediment sensors and terminus ice velocity measurements. Accumulation area snowmelt timing is correlated (R2 = 0.61) to timing of the annual snowmelt flood peak and can be predicted within ??5 days. Copyright 2008 by the American Geophysical Union.

  8. Compilation and assessment of microwave bioeffects. Final report. A selective review of the literature on biological effects of microwaves in relation to the Satellite Power System (SPS)

    Energy Technology Data Exchange (ETDEWEB)

    Justesen, D.R.; Ragan, H.A.; Rogers, L.E.; Guy, A.W.; Hjeresen, D.L.; Hinds, W.T.; Phillips, R.D.

    1978-05-01

    One of many alternate sources of electrical energy that are being considered by the Department of Energy is a microwave-mediated Satellite Power System (SPS). Once inserted into geosynchronous orbit at an altitude of more than 40,000 kilometers, a satellite would collect then convert the sun's energy to 2450-MHz microwaves, which would be beamed to the Earth's surface, where a rectifying antenna (rectenna) would convert the microwaves to electrical current suitable for industrial and domestic use. The expanse of each rectenna (about 10 by 13 kilometers), the power density of the continuous-wave microwave beam (approx. 23 mW/cm/sup 2/ at center, with fall off to 1 mW/cm/sup 2/ or less at the periphery of the rectenna), and the possibility that 20 or more satellite systems will eventually be operating, creates two sets of interrelated problems for biological/ecological assessment. These are 1) the effects of microwave fields of higher intensity on airborne biota (including human beings in aircraft) that may traffic the area above the rectenna and 2) the effects of virtually perpetual fields of much lower intensity on all forms of life at and beyond the rectennae's zone of exclusion. In this review, the scientific literature is examined, not only for biological effects that are pertinent to assessment of SPS, but for hiatuses of knowledge that will have to be filled before SPS can be vouched for operational safety.

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

    Science.gov (United States)

    Wang, Shifeng; So, Emily; Smith, Pete

    2015-04-01

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

  10. Pre-Launch Radiometric Performance Characterization of the Advanced Technology Microwave Sounder on the Joint Polar Satellite System-1 Satellite

    Science.gov (United States)

    Smith, Craig K.; Kim, Edward; Leslie, R. Vincent; Lyu, Joseph; McCormick, Lisa M.; Anderson, Kent

    2017-01-01

    The Advanced Technology Microwave Sounder (ATMS) is a space-based, cross-track radiometer for operational atmospheric temperature and humidity sounding, utilizing 22 channels over a frequency range from 23 to 183 gigahertz. The ATMS for the Joint Polar Satellite System-1 has undergone two rounds of re-work in 2014-2015 and 2016, following performance issues discovered during and following thermal vacuum chamber (TVAC) testing at the instrument and observatory level. Final shelf-level testing, including measurement of pass band characteristics and spectral response functions, was completed in December 2016. Final instrument-level TVAC testing and calibration occurred during February 2017. Here we will describe the instrument-level TVAC calibration process, and illustrate with results from the final TVAC calibration effort.

  11. Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics

    Science.gov (United States)

    Chuang, Ting-Wu; Henebry, Geoffrey M.; Kimball, John S.; VanRoekel-Patton, Denise L.; Hildreth, Michael B.; Wimberly, Michael C.

    2012-01-01

    Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems. PMID:23049143

  12. Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

    Science.gov (United States)

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

    2015-12-01

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

  13. Compilation and assessment of microwave bioeffects. Final report. A selective review of the literature on biological effects of microwaves in relation to the satellite power system

    Energy Technology Data Exchange (ETDEWEB)

    Justesen, D. R.; Ragan, H. A.; Rogers, L. E.; Guy, A. W.; Hjeresen, D. L.; Hinds, W. T.

    1978-05-01

    Potential biological and ecological problems are the focus of a review of the world's scientific literature on biological effects of microwave radiation. The emphasis is on recently reported data and on the 2450-MHz continuous-wave (CW) radiation that is envisioned for a Satellite Power System (SPS).

  14. Study of LEO-SAT microwave link for broad-band mobile satellite communication system

    Science.gov (United States)

    Fujise, Masayuki; Chujo, Wataru; Chiba, Isamu; Furuhama, Yoji; Kawabata, Kazuaki; Konishi, Yoshihiko

    1993-01-01

    In the field of mobile satellite communications, a system based on low-earth-orbit satellites (LEO-SAT's) such as the Iridium system has been proposed. The LEO-SAT system is able to offer mobile telecommunication services in high-latitude areas. Rain degradation, fading and shadowing are also expected to be decreased when the system is operated at a high elevation angle. Furthermore, the propagation delay generated in the LEO-SAT system is less pronounced than that in the geostationary orbit satellite (GEO-SAT) system and, in voice services, the effect of the delay is almost negligible. We proposed a concept of a broad-band mobile satellite communication system with LEO-SAT's and Optical ISL. In that system, a fixed L-band (1.6/1.5 GHz) multibeam is used to offer narrow band service to the mobile terminals in the entire area covered by a LEO-SAT and steerable Ka-band (30/20 GHz) spot beams are used for the wide band service. In this paper, we present results of a study of LEO-SAT microwave link between a satellite and a mobile terminal for a broad-band mobile satellite communication system. First, the results of link budget calculations are presented and the antennas mounted on satellites are shown. For a future mobile antenna technology, we also show digital beamforming (DBF) techniques. DBF, together with modulation and/or demodulation, is becoming a key technique for mobile antennas with advanced functions such as antenna pattern calibration, correction, and radio interference suppression. In this paper, efficient DBF techniques for transmitting and receiving are presented. Furthermore, an adaptive array antenna system suitable for this LEO-SAT is presented.

  15. Estimating Carbon STOCK Changes of Mangrove Forests Using Satellite Imagery and Airborne LiDAR Data in the South Sumatra State, Indonesia

    Science.gov (United States)

    Maeda, Y.; Fukushima, A.; Imai, Y.; Tanahashi, Y.; Nakama, E.; Ohta, S.; Kawazoe, K.; Akune, N.

    2016-06-01

    The purposes of this study were 1) to estimate the biomass in the mangrove forests using satellite imagery and airborne LiDAR data, and 2) to estimate the amount of carbon stock changes using biomass estimated. The study area is located in the coastal area of the South Sumatra state, Indonesia. This area is approximately 66,500 ha with mostly flat land features. In this study, the following procedures were carried out: (1) Classification of types of tree species using Satellite imagery in the study area, (2) Development of correlation equations between spatial volume based on LiDAR data and biomass stock based on field survey for each types of tree species, and estimation of total biomass stock and carbon stock using the equation, and (3) Estimation of carbon stock change using Chronological Satellite Imageries. The result showed the biomass and the amount of carbon stock changes can be estimated with high accuracy, by combining the spatial volume based on airborne LiDAR data with the tree species classification based on satellite imagery. Quantitative biomass monitoring is in demand for projects related to REDD+ in developing countries, and this study showed that combining airborne LiDAR data with satellite imagery is one of the effective methods of monitoring for REDD+ projects.

  16. ESTIMATING CARBON STOCK CHANGES OF MANGROVE FORESTS USING SATELLITE IMAGERY AND AIRBORNE LiDAR DATA IN THE SOUTH SUMATRA STATE, INDONESIA

    Directory of Open Access Journals (Sweden)

    Y. Maeda

    2016-06-01

    Full Text Available The purposes of this study were 1 to estimate the biomass in the mangrove forests using satellite imagery and airborne LiDAR data, and 2 to estimate the amount of carbon stock changes using biomass estimated. The study area is located in the coastal area of the South Sumatra state, Indonesia. This area is approximately 66,500 ha with mostly flat land features. In this study, the following procedures were carried out: (1 Classification of types of tree species using Satellite imagery in the study area, (2 Development of correlation equations between spatial volume based on LiDAR data and biomass stock based on field survey for each types of tree species, and estimation of total biomass stock and carbon stock using the equation, and (3 Estimation of carbon stock change using Chronological Satellite Imageries. The result showed the biomass and the amount of carbon stock changes can be estimated with high accuracy, by combining the spatial volume based on airborne LiDAR data with the tree species classification based on satellite imagery. Quantitative biomass monitoring is in demand for projects related to REDD+ in developing countries, and this study showed that combining airborne LiDAR data with satellite imagery is one of the effective methods of monitoring for REDD+ projects.

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

    Directory of Open Access Journals (Sweden)

    T. Alipour Fard

    2014-10-01

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

  18. 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

    Science.gov (United States)

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

    1975-01-01

    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.

  19. Validating Microwave-Based Satellite Rain Rate Retrievals Over TRMM Ground Validation Sites

    Science.gov (United States)

    Fisher, B. L.; Wolff, D. B.

    2008-12-01

    Multi-channel, passive microwave instruments are commonly used today to probe the structure of rain systems and to estimate surface rainfall from space. Until the advent of meteorological satellites and the development of remote sensing techniques for measuring precipitation from space, there was no observational system capable of providing accurate estimates of surface precipitation on global scales. Since the early 1970s, microwave measurements from satellites have provided quantitative estimates of surface rainfall by observing the emission and scattering processes due to the existence of clouds and precipitation in the atmosphere. This study assesses the relative performance of microwave precipitation estimates from seven polar-orbiting satellites and the TRMM TMI using four years (2003-2006) of instantaneous radar rain estimates obtained from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The seven polar orbiters include three different sensor types: SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), and AMSR-E. The TMI aboard the TRMM satellite flies in a sun asynchronous orbit between 35 S and 35 N latitudes. The rain information from these satellites are combined and used to generate several multi-satellite rain products, namely the Goddard TRMM Multi-satellite Precipitation Analysis (TMPA), NOAA's CPC Morphing Technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Instantaneous rain rates derived from each sensor were matched to the GV estimates in time and space at a resolution of 0.25 degrees. The study evaluates the measurement and error characteristics of the various satellite estimates through inter-comparisons with GV radar estimates. The GV rain observations provided an empirical ground-based reference for assessing the relative performance of each sensor and sensor

  20. Estimating soil moisture from satellite microwave observations: Past and ongoing projects, and relevance to GCIP

    Science.gov (United States)

    Owe, M.; Van de Griend, A. A.; de Jeu, R.; de Vries, J. J.; Seyhan, E.; Engman, E. T.

    1999-08-01

    On the basis of a series of studies conducted in Botswana and preliminary results from an ongoing study in Spain, developments in microwave remote sensing by satellite, which can be used to monitor near-real-time surface moisture and also study long-term soil moisture climatology, are described. A progression of methodologies beginning with single-polarization studies and leading to both dual polarization and multiple frequency techniques are described. Continuing analysis of a 9 year data set of satellite-derived surface moisture in Spain is ongoing. Preliminary results from this study appear to provide some evidence of long-term desertification in certain parts of this region. The methodologies developed during these investigations can be applied easily to other regions such as the GCIP area and could provide useful databases for simulation and validation studies. Additionally, they have strong potential for global applications such as climate change studies.

  1. Satellite microwave estimates of soil moisture and applications for desertification studies

    Science.gov (United States)

    Owe, Manfred; Van de Griend, Adriaan A.; de Jeu, Richard A.; de Vries, Jorrit; Seyhan, E.

    1998-12-01

    Based on a series of studies conducted in Botswana and preliminary results from an ongoing study in Spain, developments in microwave remote sensing by satellite which can be used to monitor near real-time surface moisture and also study long term soil moisture climatology are described. A progression of methodologies beginning with single polarization studies and leading to both dual polarization and multiple frequency techniques are described. Continuing analysis of a nine year data set of satellite-derived surface moisture in Spain is ongoing. Preliminary results from this study appear to provide some evidence of long term decertification in certain parts of this region. The methodologies developed during these investigations can be applied to other regions, and have the potential for providing modelers with extended data sets of independently derived surface moisture for simulation and validation studies, and climate change studies at the global scale.

  2. Portable Microwave Frequency Dissemination in Free Space and Implications on Ground-Satellite Synchronization

    CERN Document Server

    Wang, Bo; Bai, Yu; Yuan, Yibo; Gao, Chao; Wang, Lijun

    2015-01-01

    Frequency dissemination and synchronization in free space plays an important role in global navigation satellite system (GNSS), radio astronomy and synthetic aperture radar (SAR). In this paper, we demonstrate a portable radio frequency (RF) dissemination scheme via free space using microwave antennas. The setup has a good environment adaptability and high dissemination stability. The frequency signal is disseminated at different distances ranging from 10 to 640 m with a fixed 10 Hz locking bandwidth, and the scaling law of dissemination stability on distance and averaging time is discussed. The preliminary extrapolation shows that the dissemination stability may reach $1\\times10^{-12}/s$ in ground-to-satellite synchronization, which far exceeds all present methods, and is worthy for further study.

  3. Study of time-lapse processing for dynamic hydrologic conditions. [electronic satellite image analysis console for Earth Resources Technology Satellites imagery

    Science.gov (United States)

    Serebreny, S. M.; Evans, W. E.; Wiegman, E. J.

    1974-01-01

    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.

  4. Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

    Directory of Open Access Journals (Sweden)

    T. Lacava

    2005-01-01

    Full Text Available Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent hydro-geological hazards. Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV. Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. Recently, using data coming from AMSU (Advanced Microwave Sounding Unit, flying aboard NOAA (National Oceanic and Atmospheric Administration satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI, developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail

  5. Vectorized Shoreline of Guam, Derived from IKONOS Satellite Imagery, 2000 through 2003

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  6. Derived bathymetry from WorldView-2 satellite imagery of nearshore benthic habitats

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Methods used were adapted from a "cookbook" of instructions developed by Kyle Hogref for using IKONOS imagery data to derive seafloor elevations in optically clear...

  7. Vectorized Shoreline of Guam, Derived from IKONOS Satellite Imagery, 2000 through 2003

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  8. Environmental assessment for the satellite power system-concept development and evaluation program-microwave health and ecological effects

    Science.gov (United States)

    1980-01-01

    Potential health and ecological effects of the microwave beam from the microwave power transmission system (MPTS) of the satellite power system (SPS) are discussed. A detailed critical review of selected scientific articles from the published literature on the biological effects of nonionizing electromagnetic radiation is provided followed by an assessment of the possible effects of the SPS, based on exposure values for the reference system.

  9. Environmental assessment for the satellite power system-concept development and evaluation program-microwave health and ecological effects

    Energy Technology Data Exchange (ETDEWEB)

    1980-11-01

    This report is concerned with the potential health and ecological effects of the microwave beam from the microwave power transmission system (MPTS) of the satellite power system (SPS). The report is written in the form of a detailed critical review of selected scientific articles from the published literature on the biological effects of nonionizing electromagnetic radiation, followed by an assessment of the possible effects of the SPS, based on exposure values for the reference system (US DOE and NASA, 1978).

  10. Multi-decadal record of ice dynamics on Daugaard Jensen Gletscher, East Greenland, from satellite imagery and terrestrial measurements

    DEFF Research Database (Denmark)

    Stearns, L.A.; Hamilton, G.S.; Reeh, Niels

    2005-01-01

    The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained...... in approximately the same position over the past similar to 50 years. There is no evidence of a change in ice motion between 1968 and 2001, based on a comparison of velocities derived from terrestrial surveying and feature tracking using sequential satellite images. Estimates of flux near the entrance to the fjord...... vs snow accumulation in the interior catchment show that Daugaard Jensen Gletscher has a small negative mass balance. This result is consistent with other mass-balance estimates for the inland region of the glacier....

  11. Summit-to-sea mapping and change detection using satellite imagery: tools for conservation and management of coral reefs.

    Science.gov (United States)

    Shapiro, A C; Rohmann, S O

    2005-05-01

    Continuous summit-to-sea maps showing both land features and shallow-water coral reefs have been completed in Puerto Rico and the U.S. Virgin Islands, using circa 2000 Landsat 7 Enhanced Thematic Mapper (ETM+) Imagery. Continuous land/sea terrain was mapped by merging Digital Elevation Models (DEM) with satellite-derived bathymetry. Benthic habitat characterizations were created by unsupervised classifications of Landsat imagery clustered using field data, and produced maps with an estimated overall accuracy of>75% (Tau coefficient >0.65). These were merged with Geocover-LC (land use/land cover) data to create continuous land/ sea cover maps. Image pairs from different dates were analyzed using Principle Components Analysis (PCA) in order to detect areas of change in the marine environment over two different time intervals: 2000 to 2001, and 1991 to 2003. This activity demonstrates the capabilities of Landsat imagery to produce continuous summit-to-sea maps, as well as detect certain changes in the shallow-water marine environment, providing a valuable tool for efficient coastal zone monitoring and effective management and conservation.

  12. Spatio-Temporal Analysis of Urban Heat Island and Urban Metabolism by Satellite Imagery over the Phoenix Metropolitan Area

    Science.gov (United States)

    Zhao, Q.; Zhan, S.; Kuai, X.; Zhan, Q.

    2015-12-01

    The goal of this research is to combine DMSP-OLS nighttime light data with Landsat imagery and use spatio-temporal analysis methods to evaluate the relationships between urbanization processes and temperature variation in Phoenix metropolitan area. The urbanization process is a combination of both land use change within the existing urban environment as well as urban sprawl that enlarges the urban area through the transformation of rural areas to urban structures. These transformations modify the overall urban climate environment, resulting in higher nighttime temperatures in urban areas compared to the surrounding rural environment. This is a well-known and well-studied phenomenon referred to as the urban heat island effect (UHI). What is unknown is the direct relationship between the urbanization process and the mechanisms of the UHI. To better understand this interaction, this research focuses on using nighttime light satellite imagery to delineate and detect urban extent changes and utilizing existing land use/land cover map or newly classified imagery from Landsat to analyze the internal urban land use variations. These data are combined with summer and winter land surface temperature data extracted from Landsat. We developed a time series of these combined data for Phoenix, AZ from 1992 to 2013 to analyze the relationships among land use change, land surface temperature and urban growth.

  13. 3D high resolution tracking of ice flow using mutli-temporal stereo satellite imagery, Franz Josef Glacier, New Zealand

    Science.gov (United States)

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

    2013-12-01

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

  14. Probing orographic controls in the Himalayas during the monsoon using satellite imagery

    Directory of Open Access Journals (Sweden)

    A. P. Barros

    2004-01-01

    Full Text Available The linkages between the space-time variability of observed clouds, rainfall, large-circulation patterns and topography in northern India and the Himalayas were investigated using remote sensing data. The research purpose was to test the hypothesis that cloudiness patterns are dynamic tracers of rainstorms, and therefore their temporal and spatial evolution can be used as a proxy of the spatial and temporal organization of precipitation and precipitation processes in the Himalayan range during the monsoon. The results suggest that the space-time distribution of precipitation, the spatial variability of the diurnal cycle of convective activity, and the terrain (landform and altitudinal gradients are intertwined at spatial scales ranging from the order of a few kms (1–5km up to the continental-scale. Furthermore, this relationship is equally strong in the time domain with respect to the onset and intra-seasonal variability of the monsoon. Infrared and microwave imagery of cloud fields were analyzed to characterize the spatial and temporal evolution of mesoscale convective weather systems and short-lived convection in Northern India, the Himalayan range, and in the Tibetan Plateau during three monsoon seasons (1999, 2000 and 2001. The life cycle of convective systems suggests landform and orographic controls consistent with a convergence zone constrained to the valley of the Ganges and the Himalayan range, bounded in the west by the Aravalli range and the Garhwal mountains and in the East by the Khasi Hills and the Bay of Bengal, which we call the Northern India Convergence Zone (NICZ. The NICZ exhibits strong night-time activity along the south-facing slopes of the Himalayan range, which is characterized by the development of short-lived convection (1–3h aligned with protruding ridges between 1:00 and 3:00 AM. The intra-annual and inter-annual variability of convective activity in the NICZ were assessed with respect to large-scale synoptic

  15. Optimized Fast-FISH with a-satellite probes: acceleration by microwave activation

    Directory of Open Access Journals (Sweden)

    Durm M.

    1997-01-01

    Full Text Available It has been shown for several DNA probes that the recently introduced Fast-FISH (fluorescence in situ hybridization technique is well suited for quantitative microscopy. For highly repetitive DNA probes the hybridization (renaturation time and the number of subsequent washing steps were reduced considerably by omitting denaturing chemical agents (e.g., formamide. The appropriate hybridization temperature and time allow a clear discrimination between major and minor binding sites by quantitative fluorescence microscopy. The well-defined physical conditions for hybridization permit automatization of the procedure, e.g., by a programmable thermal cycler. Here, we present optimized conditions for a commercially available X-specific a-satellite probe. Highly fluorescent major binding sites were obtained for 74oC hybridization temperature and 60 min hybridization time. They were clearly discriminated from some low fluorescent minor binding sites on metaphase chromosomes as well as in interphase cell nuclei. On average, a total of 3.43 ± 1.59 binding sites were measured in metaphase spreads, and 2.69 ± 1.00 in interphase nuclei. Microwave activation for denaturation and hybridization was tested to accelerate the procedure. The slides with the target material and the hybridization buffer were placed in a standard microwave oven. After denaturation for 20 s at 900 W, hybridization was performed for 4 min at 90 W. The suitability of a microwave oven for Fast-FISH was confirmed by the application to a chromosome 1-specific a-satellite probe. In this case, denaturation was performed at 630 W for 60 s and hybridization at 90 W for 5 min. In all cases, the results were analyzed quantitatively and compared to the results obtained by Fast-FISH. The major binding sites were clearly discriminated by their brightness

  16. An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions

    Science.gov (United States)

    Kim, Edward

    2012-01-01

    Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.

  17. Application of satellite microwave remote sensed brightness temperature in the regional soil moisture simulation

    Directory of Open Access Journals (Sweden)

    X. K. Shi

    2009-02-01

    Full Text Available As the satellite microwave remote sensed brightness temperature is sensitive to land surface soil moisture (SM and SM is a basic output variable in model simulation, it is of great significance to use the brightness temperature data to improve SM numerical simulation. In this paper, the theory developed by Yan et al. (2004 about the relationship between satellite microwave remote sensing polarization index and SM was used to estimate the land surface SM from AMSR-E (Advanced Microwave Scanning Radiometer – Earth Observing System brightness temperature data. With consideration of land surface soil texture, surface roughness, vegetation optical thickness, and the AMSR-E monthly SM products, the regional daily land surface SM was estimated over the eastern part of the Qinghai-Tibet Plateau. The results show that the estimated SM is lower than the ground measurements and the NCEP (American National Centers for Environmental Prediction reanalysis data at the Maqu Station (33.85° N, 102.57° E and the Tanglha Station (33.07° N, 91.94° E, but its regional distribution is reasonable and somewhat better than that from the daily AMSR-E SM product, and its temporal variation shows a quick response to the ground daily precipitations. Furthermore, in order to improve the simulating ability of the WRF (Weather Research and Forecasting model to land surface SM, the estimated SM was assimilated into the Noah land surface model by the Newtonian relaxation (NR method. The results indicate that, by fine tuning of the quality factor in NR method, the simulated SM values are improved most in desert area, followed by grassland, shrub and grass mixed zone. At temporal scale, Root Mean Square Error (RMSE values between simulated and observed SM are decreased 0.03 and 0.07 m3/m3 by using the NR method in the Maqu Station and the Tanglha Station, respectively.

  18. Remote Estimation of Greenland Ice Sheet Supraglacial River Discharge using GIS Modeling and WorldView-2 Satellite Imagery

    Science.gov (United States)

    Chu, V. W.; Smith, L. C.; Yang, K.; Gleason, C. J.; Rennermalm, A. K.; Pitcher, L. H.; Legleiter, C. J.; Forster, R. R.

    2014-12-01

    Increasing surface melting on the Greenland ice sheet and rising sea level have heightened the need for understanding the complex pathways transporting meltwater from the ice sheet surface to the ice edge and the ocean. Satellite images show supraglacial rivers abundantly covering the western ablation zone throughout the melt season, transporting large volumes of meltwater into moulins and to the ice edge, yet these rivers remain poorly studied. Here, a GIS modeling framework is developed to estimate supraglacial river discharge by spatially adapting Manning's equation for use with remotely sensed imagery and is applied to supraglacial rivers on the Greenland Ice Sheet. This framework incorporates high-resolution visible/near-infrared WorldView-2 (WV2) satellite imagery, the Greenland Ice Mapping Project (GIMP) DEM, and a field-calibrated WV2 river bathymetry retrieval algorithm and channel roughness parameter. Orthogonal cross-sections are simulated along river centerlines to extract cross-sectional discharge using Manning's equation for open channel flow. A total of 1,629,502 reach-averaged points were retrieved over 465 river networks of western Greenland in 2012, including attributes of width, depth, velocity, slope, wetted perimeter, hydraulic radius, and discharge. This work provides a method for producing spatially extensive, high-resolution estimates of supraglacial meltwater flux in river networks and into the ice sheet.

  19. Extracting impervious surfaces from multi-source satellite imagery based on unified conceptual model by decision tree algorithm

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Extraction of impervious surfaces is one of the necessary processes in urban change detection.This paper derived a unified conceptual model (UCM) from the vegetation-impervious surface-soil (VIS) model to make the extraction more effective and accurate.UCM uses the decision tree algorithm with indices of spectrum and texture,etc.In this model,we found both dependent and independent indices for multi-source satellite imagery according to their similarity and dissimilarity.The purpose of the indices is to remove the other land-use and land-cover types (e.g.,vegetation and soil) from the imagery,and delineate the impervious surfaces as the result.UCM has the same steps conducted by decision tree algorithm.The Landsat-5 TM image (30 m) and the Satellite Probatoire d’Observation de la Terre (SPOT-4) image (20 m) from Chaoyang District (Beijing) in 2007 were used in this paper.The results show that the overall accuracy in Landsat-5 TM image is 88%,while 86.75% in SPOT-4 image.It is an appropriate method to meet the demand of urban change detection.

  20. A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

    Science.gov (United States)

    Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.; hide

    2009-01-01

    A joint U.S. Air Force/NASA blended, global snow product that utilizes Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and QuikSCAT (Quick Scatterometer) (QSCAT) data has been developed. Existing snow products derived from these sensors have been blended into a single, global, daily, user-friendly product by employing a newly-developed Air Force Weather Agency (AFWA)/National Aeronautics and Space Administration (NASA) Snow Algorithm (ANSA). This initial blended-snow product uses minimal modeling to expeditiously yield improved snow products, which include snow cover extent, fractional snow cover, snow water equivalent (SWE), onset of snowmelt, and identification of actively melting snow cover. The blended snow products are currently 25-km resolution. These products are validated with data from the lower Great Lakes region of the U.S., from Colorado during the Cold Lands Processes Experiment (CLPX), and from Finland. The AMSR-E product is especially useful in detecting snow through clouds; however, passive microwave data miss snow in those regions where the snow cover is thin, along the margins of the continental snowline, and on the lee side of the Rocky Mountains, for instance. In these regions, the MODIS product can map shallow snow cover under cloud-free conditions. The confidence for mapping snow cover extent is greater with the MODIS product than with the microwave product when cloud-free MODIS observations are available. Therefore, the MODIS product is used as the default for detecting snow cover. The passive microwave product is used as the default only in those areas where MODIS data are not applicable due to the presence of clouds and darkness. The AMSR-E snow product is used in association with the difference between ascending and descending satellite passes or Diurnal Amplitude Variations (DAV) to detect the onset of melt, and a QSCAT product will be used to

  1. Satellite geological and geophysical remote sensing of Iceland: Preliminary results from analysis of MSS imagery

    Science.gov (United States)

    Williams, R. S., Jr.; Boedvarsson, A.; Fridriksson, S.; Palmason, G.; Rist, S.; Sigtryggsson, H.; Thorarinsson, S.; Thorsteinsson, I.

    1973-01-01

    A binational, multidisciplinary research effort in Iceland is directed at an analysis of MSS imagery from ERTS-1 to study a variety of geologic, hydrologic, oceanographic, and agricultural phenomena. A preliminary evaluation of available MSS imagery of Iceland has yielded several significant results - some of which may have direct importance to the Icelandic economy. Initial findings can be summarized as follows: (1) recent lava flows can be delineated from older flows at Askja and Hekla; (2) MSS imagery from ERTS-1 and VHRR visible and infrared imagery from NOAA-2 recorded the vocanic eruption on Heimaey, Vestmann Islands; (3) coastline changes, particularly changes in the position of bars and beaches along the south coast are mappable; and (4) areas covered with new and residual snow can be mapped, and the appearance of newly fallen snow on ERTS-1, MSS band 7 appears dark where it is melting. ERTS-1 imagery provides a means of updating various types of maps of Iceland and will permit the compilation of special maps specifically aimed at those dynamic environmental phenomena which impact on the Icelandic economy.

  2. A Global Record of Daily Landscape Freeze-Thaw Status from Satellite Microwave Remote Sensing

    Science.gov (United States)

    Kimball, J. S.; Kim, Y.; Colliander, A.; McDonald, K. C.

    2011-12-01

    The freeze-thaw (FT) parameter from satellite microwave remote sensing quantifies the predominant landscape frozen or thawed state and is closely linked to surface energy budget and hydrologic activity, seasonal vegetation growth dynamics and terrestrial carbon budgets. A global Earth System Data Record (ESDR) of daily landscape FT status (FT-ESDR) was developed using a temporal change classification of 37 GHz brightness temperature (Tb) series from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I), and encompassing land areas where seasonal frozen temperatures influence ecosystem processes. A consistent, long-term (>30 yr) FT record was created by ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The product is designed to determine the FT status of the composite landscape vegetation-snow-soil medium with sufficient accuracy to characterize frozen temperature constraints to surface water mobility, vegetation productivity and land-atmosphere CO2 fluxes. A multi-tier product validation is applied using in situ temperature and tower carbon flux measurements, and other satellite FT retrievals. The FT-ESDR record shows mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals relative to surface air temperature measurements from global weather stations. Other comparisons against spatially dense temperature observations from an Alaska ecological transect reveal satellite sensor frequency dependence and variable FT sensitivity to surface air, vegetation, soil and snow properties. Other satellite sensor retrievals, including AMSR-E and SMOS show similar FT classification accuracies, but variable sensitivity to different landscape elements. Sensor FT classification differences reflect differences in microwave frequency, footprint resolution and satellite

  3. Exploring Google Earth Engine platform for big data processing: classification of multi-temporal satellite imagery for crop mapping

    Science.gov (United States)

    Shelestov, Andrii; Lavreniuk, Mykola; Kussul, Nataliia; Novikov, Alexei; Skakun, Sergii

    2017-02-01

    Many applied problems arising in agricultural monitoring and food security require reliable crop maps at national or global scale. Large scale crop mapping requires processing and management of large amount of heterogeneous satellite imagery acquired by various sensors that consequently leads to a “Big Data” problem. The main objective of this study is to explore efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger scale (e.g. country level) and multiple sensors (e.g. Landsat-8 and Sentinel-2). In particular, multiple state-of-the-art classifiers available in the GEE platform are compared to produce a high resolution (30 m) crop classification map for a large territory ( 28,100 km2 and 1.0 M ha of cropland). Though this study does not involve large volumes of data, it does address efficiency of the GEE platform to effectively execute complex workflows of satellite data processing required with large scale applications such as crop mapping. The study discusses strengths and weaknesses of classifiers, assesses accuracies that can be achieved with different classifiers for the Ukrainian landscape, and compares them to the benchmark classifier using a neural network approach that was developed in our previous studies. The study is carried out for the Joint Experiment of Crop Assessment and Monitoring (JECAM) test site in Ukraine covering the Kyiv region (North of Ukraine) in 2013. We found that Google Earth Engine (GEE) provides very good performance in terms of enabling access to the remote sensing products through the cloud platform and providing pre-processing; however, in terms of classification accuracy, the neural network based approach outperformed support vector machine (SVM), decision tree and random forest classifiers available in GEE.

  4. Validating a Satellite Microwave Remote Sensing Based Global Record of Daily Landscape Freeze-Thaw Dynamics

    Science.gov (United States)

    Kimball, J. S.; Kim, Y.; McDonald, K. C.

    2012-12-01

    The freeze-thaw (FT) parameter from satellite microwave remote sensing quantifies the predominant landscape frozen or thawed state and is closely linked to surface energy budget and hydrologic activity, vegetation growth, terrestrial carbon budgets and land-atmosphere trace gas exchange. A global Earth System Data Record of daily landscape FT status (FT-ESDR) was developed using a temporal change classification of overlapping 37 GHz brightness temperature (Tb) series from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I), and encompassing land areas where seasonal frozen temperatures influence ecosystem processes. A temporally consistent, long-term (>30 yr) FT record was created by ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The FT-ESDR is designed to determine the FT status of the composite landscape vegetation-snow-soil medium with sufficient accuracy to characterize frozen temperature constraints to surface water mobility, vegetation productivity and land-atmosphere CO2 fluxes. A multi-tier validation scheme was applied using in situ temperature measurements, other satellite FT retrievals and synergistic biophysical data. These results are incorporated into the product metadata structure, including mean daily spatial classification accuracies and annual quality assessment (QA) maps accounting for landscape heterogeneity, algorithm limitations and sensor retrieval gaps. The resulting FT-ESDR shows mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals. Accuracy is reduced during seasonal transition periods when FT heterogeneity is maximized within the relatively coarse (~25-km) satellite footprint. The QA rankings range from low (estimated accuracy 90%) categories; mean annual QA results for the 1979-2011 period show relative proportions of

  5. Seasonally Frozen Soil Monitoring Using Passive Microwave Satellite Data and Simulation Modeling

    Science.gov (United States)

    Toll, D. L.; Owe, M.; Levine, E.

    1998-01-01

    Satellite data and simulation modeling were used to assess seasonally frozen soils in the central US - Canada borders area (46-53 degrees N and 96-108 degrees). We used Scanning Multichannel Microwave Radiometer (SMMR) satellite data to delineate the top layer of frozen soils. SMMR is a passive microwave sensor having five channels (6.6, 10, 18, 21 and 37 GHz) with a horizontal and vertical polarization. SMRR data are available between 1978-1987 with noon and midnight overpass and footprint sizes between 25 km and 150 km. SMMR data were processed from resampled 1/4 degree grid cells during fall freeze-up and spring thaw (fall 1985 - spring 1987). The dielectric properties of a target may directly affect the satellite signal. The dielectric value is an order of magnitude smaller for frozen soil water. There are other significant changes to the emitted microwave signal from changes to the surface physical temperature, attenuation of the soil signal from plant water and soil moisture. We further characterized the temporal and spatial dynamic of frozen soils using the FroST (Frozen Soil Temperature) simulation model. The FroST model was used to further predict soil water and ice content, and soil temperature. SMMR results were compared versus 5-cm soil temperature data from available weather stations (14 in Canada and 11 for available months in the US). SMMR data were analyzed as a function of frequency, polarization, polarization difference, and "frequency gradient". In addition, vegetation density, physical temperature and snow depth were also considered. Preliminary analysis of SMMR derived frozen soil/thaw classification using a simple threshold classification indicates a mean overall classification accuracy by season of 85 percent. A sensitivity analysis for different soils with varying amounts of snow was conducted with FroST, which showed that the amount of snow, and the time of snow fall and melt affected the ice and water content, and depth of thaw. These

  6. Automatic Radiometric Normalization of Multitemporal Satellite Imagery with the Iteratively Re-weighted MAD Transformation

    DEFF Research Database (Denmark)

    Canty, Morton John; Nielsen, Allan Aasbjerg

    2008-01-01

    A recently proposed method for automatic radiometric normalization of multi- and hyper-spectral imagery based on the invariance property of the Multivariate Alteration Detection (MAD) transformation and orthogonal linear regression is extended by using an iterative re-weighting scheme involving no...

  7. Effects of atmospheric turbulence on microwave and millimeter wave satellite communications systems. [attenuation statistics and antenna design

    Science.gov (United States)

    Devasirvatham, D. M. J.; Hodge, D. B.

    1981-01-01

    A model of the microwave and millimeter wave link in the presence of atmospheric turbulence is presented with emphasis on satellite communications systems. The analysis is based on standard methods of statistical theory. The results are directly usable by the design engineer.

  8. The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

    Science.gov (United States)

    Patterson, Maria T.; Anderson, Nicholas; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert L.; Handy, Matthew; Ly, Vuong; Mandl, Daniel J.; Pederson, Shane; Pivarski, James; hide

    2016-01-01

    Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for

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

    Directory of Open Access Journals (Sweden)

    Marta Szulkin

    2015-10-01

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

  10. The users, uses, and value of Landsat and other moderate-resolution satellite imagery in the United States-Executive report

    Science.gov (United States)

    Miller, Holly M.; Sexton, Natalie R.; Koontz, Lynne; Loomis, John; Koontz, Stephen R.; Hermans, Caroline

    2011-01-01

    Moderate-resolution imagery (MRI), such as that provided by the Landsat satellites, provides unique spatial information for use by many people both within and outside of the United States (U.S.). However, exactly who these users are, how they use the imagery, and the value and benefits derived from the information are, to a large extent, unknown. To explore these issues, social scientists at the USGS Fort Collins Science Center conducted a study of U.S.-based MRI users from 2008 through 2010 in two parts: 1) a user identification and 2) a user survey. The objectives for this study were to: 1) identify and classify U.S.-based users of this imagery; 2) better understand how and why MRI, and specifically Landsat, is being used; and 3) qualitatively and quantitatively measure the value and societal benefits of MRI (focusing on Landsat specifically). The results of the survey revealed that respondents from multiple sectors use Landsat imagery in many different ways, as demonstrated by the breadth of project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance placed on the imagery, the numerous benefits received from projects using Landsat imagery, the negative impacts if Landsat imagery was no longer available, and the substantial willingness to pay for replacement imagery in the event of a data gap. The survey collected information from users who are both part of and apart from the known user community. The diversity of the sample delivered results that provide a baseline of knowledge about the users, uses, and value of Landsat imagery. While the results supply a wealth of information on their own, they can also be built upon through further research to generate a more complete picture of the population of Landsat users as a whole.

  11. A preliminary measurement of the cosmic microwave background spectrum by the Cosmic Background Explorer (COBE) satellite

    Energy Technology Data Exchange (ETDEWEB)

    Mather, J.C.; Cheng, E.S.; Shafer, R.A.; Bennett, C.L.; Boggess, N.W.; Dwek, E.; Hauser, M.G.; Kelsall, T.; Moseley, S.H. Jr.; Silverberg, R.F. (NASA, Goddard Space Flight Center, Greenbelt, MD (USA))

    1990-05-01

    A preliminary spectrum is presented of the background radiation between 1 and 20/cm from regions near the north Galactic pole, as observed by the FIRAS instrument on the COBE satellite. The spectral resolution is 1/cm. The spectrum is well fitted by a blackbody with a temperature of 2.735 + or - 0.06 K, and the deviation from a blackbody is less than 1 percent of the peak intensity over the range 1-20/cm. These new data show no evidence for the submillimeter excess previously reported by Matsumoto et al. (1988) in the cosmic microwave background. Further analysis and additional data are expected to improve the sensitivity to deviations from a blackbody spectrum by an order of magnitude. 31 refs.

  12. A preliminary measurement of the cosmic microwave background spectrum by the Cosmic Background Explorer (COBE) satellite

    Science.gov (United States)

    Mather, J. C.; Cheng, E. S.; Shafer, R. A.; Bennett, C. L.; Boggess, N. W.; Dwek, E.; Hauser, M. G.; Kelsall, T.; Moseley, S. H., Jr.; Silverberg, R. F.

    1990-01-01

    A preliminary spectrum is presented of the background radiation between 1 and 20/cm from regions near the north Galactic pole, as observed by the FIRAS instrument on the COBE satellite. The spectral resolution is 1/cm. The spectrum is well fitted by a blackbody with a temperature of 2.735 + or - 0.06 K, and the deviation from a blackbody is less than 1 percent of the peak intensity over the range 1-20/cm. These new data show no evidence for the submillimeter excess previously reported by Matsumoto et al. (1988) in the cosmic microwave background. Further analysis and additional data are expected to improve the sensitivity to deviations from a blackbody spectrum by an order of magnitude.

  13. A preliminary measurement of the cosmic microwave background spectrum by the Cosmic Background Explorer (COBE) satellite

    Science.gov (United States)

    Mather, J. C.; Cheng, E. S.; Shafer, R. A.; Bennett, C. L.; Boggess, N. W.; Dwek, E.; Hauser, M. G.; Kelsall, T.; Moseley, S. H., Jr.; Silverberg, R. F.

    1990-01-01

    A preliminary spectrum is presented of the background radiation between 1 and 20/cm from regions near the north Galactic pole, as observed by the FIRAS instrument on the COBE satellite. The spectral resolution is 1/cm. The spectrum is well fitted by a blackbody with a temperature of 2.735 + or - 0.06 K, and the deviation from a blackbody is less than 1 percent of the peak intensity over the range 1-20/cm. These new data show no evidence for the submillimeter excess previously reported by Matsumoto et al. (1988) in the cosmic microwave background. Further analysis and additional data are expected to improve the sensitivity to deviations from a blackbody spectrum by an order of magnitude.

  14. Calibration of the Microwave Limb Sounder on the Upper Atmosphere Research Satellite

    Science.gov (United States)

    Jarnot, R. F.; Cofield, R. E.; Waters, J. W.; Flower, D. A.; Peckham, G. E.

    1996-01-01

    The Microwave Limb Sounder (MLS) is a three-radiometer, passive, limb emission instrument onboard the Upper Atmosphere Research Satellite (UARS). Radiometric, spectral and field-of-view calibrations of the MLS instrument are described in this paper. In-orbit noise performance, gain stability, spectral baseline and dynamic range are described, as well as use of in-flight data for validation and refinement of prelaunch calibrations. Estimated systematic scaling uncertainties (3 sigma) on calibrated limb radiances from prelaunch calibrations are 2.6% in bands 1 through 3, 3.4% in band 4, and 6% in band 5. The observed systematic errors in band 6 are about 15%, consistent with prelaunch calibration uncertainties. Random uncertainties on individual limb radiance measurements are very close to the levels predicted from measured radiometer noise temperature, with negligible contribution from noise and drifts on the regular in-flight gain calibration measurements.

  15. Microwave maps of the polar ice of the earth. [from Nimbus-5 satellite

    Science.gov (United States)

    Gloersen, P.; Wilheit, T. T.; Chang, T. C.; Nordberg, W.; Campbell, W. J.

    1973-01-01

    Synoptic views of the entire polar regions of earth were obtained free of the usual persistent cloud cover using a scanning microwave radiometer operating at a wavelength of 1.55 cm on board the Nimbus-5 satellite. Three different views at each pole are presented utilizing data obtained at approximately one-month intervals during the winter of 1972-1973. The major discoveries resulting from an analysis of these data are as follows: (1) Large discrepancies exist between the climatic norm ice cover depicted in various atlases and the actual extent of the canopies. (2) The distribution of multiyear ice in the north polar region is markedly different from that predicted by existing ice dynamics models. (3) Irregularities in the edge of the Antarctic sea ice pack occur that have neither been observed previously nor anticipated. (4) The brightness temperatures of the Greenland and Antarctica glaciers show interesting contours probably related to the ice and snow morphologic structure.

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

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

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

  17. Mediterranean hurricanes: large-scale environment and convective and precipitating areas from satellite microwave observations

    Directory of Open Access Journals (Sweden)

    C. Claud

    2010-10-01

    Full Text Available Subsynoptic scale vortices that have been likened to tropical cyclones or polar lows (medicanes are occasionally observed over the Mediterranean Sea. Generated over the sea, they are usually associated with strong winds and heavy precipitation and thus can be highly destructive in islands and costal areas. Only an accurate forecasting of such systems could mitigate these effects. However, at the moment, the predictability of these systems remains limited.

    Due to the scarcity of conventional observations, use is made of NOAA/MetOp satellite observations, for which advantage can be taken of the time coverage differences between the platforms that carry it, to give a very complete temporal description of the disturbances. A combination of AMSU-B (Advanced Microwave Sounding Unit-B/MHS (Microwave Humidity Sounder observations permit to investigate precipitation associated with these systems while coincident AMSU-A (Advanced Microwave Sounding Unit-A observations give insights into the larger synoptic-scale environment in which they occur.

    Three different cases (in terms of intensity, location, trajectory, duration, and periods of the year – May, September and December, respectively were investigated. Throughout these time periods, AMSU-A observations show that the persisting deep outflow of cold air over the sea together with an upper-level trough upstream constituted a favourable environment for the development of medicanes. AMSU-B/MHS based diagnostics show that convection and precipitation areas are large in the early stage of the low, but significantly reduced afterwards. Convection is maximum just after the upper-level trough, located upstream of cold mid-tropospheric air, reached its maximum intensity and acquired a cyclonic orientation.

  18. Satellite microwave assessment of Northern Hemisphere lake ice phenology from 2002 to 2015

    Science.gov (United States)

    Du, Jinyang; Kimball, John S.; Duguay, Claude; Kim, Youngwook; Watts, Jennifer D.

    2017-01-01

    A new automated method enabling consistent satellite assessment of seasonal lake ice phenology at 5 km resolution was developed for all lake pixels (water coverage ≥ 90 %) in the Northern Hemisphere using 36.5 GHz H-polarized brightness temperature (Tb) observations from the Advanced Microwave Scanning Radiometer for EOS and Advanced Microwave Scanning Radiometer 2 (AMSR-E/2) sensors. The lake phenology metrics include seasonal timing and duration of annual ice cover. A moving t test (MTT) algorithm allows for automated lake ice retrievals with daily temporal fidelity and 5 km resolution gridding. The resulting ice phenology record shows strong agreement with available ground-based observations from the Global Lake and River Ice Phenology Database (95.4 % temporal agreement) and favorable correlations (R) with alternative ice phenology records from the Interactive Multisensor Snow and Ice Mapping System (R = 0.84 for water clear of ice (WCI) dates; R = 0.41 for complete freeze over (CFO) dates) and Canadian Ice Service (R = 0.86 for WCI dates; R = 0.69 for CFO dates). Analysis of the resulting 12-year (2002-2015) AMSR-E/2 ice record indicates increasingly shorter ice cover duration for 43 out of 71 (60.6 %) Northern Hemisphere lakes examined, with significant (p regional trends toward earlier ice melting for only five lakes. Higher-latitude lakes reveal more widespread and larger trends toward shorter ice cover duration than lower-latitude lakes, consistent with enhanced polar warming. This study documents a new satellite-based approach for rapid assessment and regional monitoring of seasonal ice cover changes over large lakes, with resulting accuracy suitable for global change studies.

  19. Preliminary study on direct assimilation of cloud-affected satellite microwave brightness temperatures

    Science.gov (United States)

    Zhang, Sibo; Guan, Li

    2017-02-01

    Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational (3D-Var) assimilation system is preliminarily studied in this paper. A combination of cloud microphysics parameters retrieved by the 1D-Var algorithm (including vertical profiles of cloud liquid water content, ice water content, and rain water content) and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters (cloud liquid water content, ice water content, and rain water content) are applied to the control variable. Typhoon Halong (2014) is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind analysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon, bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.

  20. Reference crop evapotranspiration derived from geo-stationary satellite imagery: a case study for the Fogera flood plain, NW-Ethiopia and the Jordan Valley, Jordan

    NARCIS (Netherlands)

    Bruin, de H.A.R.; Trigo, I.F.; Jitan, M.A.; Enku, N.T.; Tol, van der C.; Gieske, A.S.M.

    2010-01-01

    First results are shown of a project aiming to estimate daily values of reference crop evapotranspiration ET0 from geo-stationary satellite imagery. In particular, for Woreta, a site in the Ethiopian highland at an elevation of about 1800 m, we tested a radiation-temperature based approximate formul

  1. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop si...

  2. Reference crop evapotranspiration derived from geo-stationary satellite imagery: a case study for the Fogera flood plain, NW-Ethiopia and the Jordan Valley, Jordan

    NARCIS (Netherlands)

    Bruin, de H.A.R.; Trigo, I.F.; Jitan, M.A.; Enku, N.T.; Tol, van der C.; Gieske, A.S.M.

    2010-01-01

    First results are shown of a project aiming to estimate daily values of reference crop evapotranspiration ET0 from geo-stationary satellite imagery. In particular, for Woreta, a site in the Ethiopian highland at an elevation of about 1800 m, we tested a radiation-temperature based approximate

  3. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop si...

  4. Identifying and locating land irrigated by center-pivot irrigation systems using satellite imagery

    Science.gov (United States)

    Hoffman, R. O.

    1980-01-01

    A methodology for using Landsat imagery for the identification and location of land irrigated by center-pivot irrigation systems is presented. The procedure involves the use of sets of Landsat band 5 imagery taken separated in time by about three weeks during the irrigation season, a zoom transfer scope and mylar base maps to record the locations of center pivots. Further computer processing of the data has been used to obtain plots of center-pivot irrigation systems and tables indicating the distribution and growth of systems by county for the state of Nebraska, and has been found to be in 95% agreement with current high-altitude IR photography. The information obtainable can be used for models of ground-water aquifers or resource planning.

  5. USING OF THE MULTITEMPORAL THERMAL INFRARED SATELLITE IMAGERY FOR NATURAL AREAS MAPPING (CASE OF MENDELEEV VOLCANO

    Directory of Open Access Journals (Sweden)

    M. Y. Grishchenko

    2014-01-01

    Full Text Available In the paper authors examine the mountain group of Mendeleev volcano situated on the Kunashir island, Kuril archipelago, Russia. Ground observations were led to examine the vegetation cover of the area as well as its typical landscapes. The other type of used data is Landsat imagery. Images were combined into multitemporal thermal infrared and multispectral pictures, which were classified to reveal the heterogeneity of the study area. Ground observations and comparison of the classification results with landscape map derive that the multitemporal thermal infrared image classification result describes better the vegetation cover structure of the area and particularity of its typical landscapes distribution. It leads to the proposition that miltitemporal thermal infrared imagery can be used to refine landscape and vegetation cover contours. 

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

    Directory of Open Access Journals (Sweden)

    Shasha Jiang

    2016-05-01

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

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

    Science.gov (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-04-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  9. Application of Satellite Imagery to the Assessment and Exploitation of Oceanic Electromagnetic Ducting.

    Science.gov (United States)

    1981-03-01

    microwave refractometry , it provides assessment information only for the immediate task force environment. Furthermore, tactical operating con- straints will...openings, were obtained from an article written by Overbeck [Ref. 8] and from interviews with California and Hawaiian amateur radio operators who

  10. Diabatic initialization for improvement in the tropical analysis of divergence and moisture using satellite radiometric imagery data

    Science.gov (United States)

    Kasahara, Akira; Mizzi, Arthur P.; Donner, Leo J.

    1994-05-01

    To improve the quality of horizontal divergence and moisture analyses in the tropics, a diabatic initialization scheme is developed to incorporate information on convective activity and the proxy data of precipitation obtained from satellite radiometric imagery data. The tropical precipitation rates are estimated by developing a relationship between the pentad precipitation data of the Global Precipitation Climatology Project with daily outgoing longwave radiation data. The tropical belt from 35°S to 25°N (for January 1988) is divided into 3 parts: convective, convective fringe, and downward-motion (clear-air) areas. In the convective region, the algorithm adjusts the horizontal divergence and humidity fields such that a version of the Kuo cumulus parameterization will yield the precipitation rates closest to the proxy data. The temperature in the planetary boundary layer is also adjusted, if necessary, to ensure the initiation of cumulus convection. In the downward-motion region, the divergence field is adjusted to yield descending motion expected from the thermodynamic balance between radiative cooling and adiabatic warming. In the convective fringe region, where convective criteria are not met, the divergence field is adjusted only to satisfy the global conservation of divergence. The humidity field is left intact in both the downward-motion and convective fringe regions. This adjustment scheme will ameliorate problems associated with spinup of precipitation in a numerical prediction model with the same cumulus parameterization as used in the initialization. This initialization scheme may be used as a method of quality control for first-guess fields in four-dimensional data assimilation by means of satellite radiometric imagery data.

  11. Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

    Science.gov (United States)

    Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

    2016-10-01

    The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

  12. Assessing the population coverage of a health demographic surveillance system using satellite imagery and crowd-sourcing.

    Science.gov (United States)

    Di Pasquale, Aurelio; McCann, Robert S; Maire, Nicolas

    2017-01-01

    Remotely sensed data can serve as an independent source of information about the location of residential structures in areas under demographic and health surveillance. We report on results obtained combining satellite imagery, imported from Bing, with location data routinely collected using the built-in GPS sensors of tablet computers, to assess completeness of population coverage in a Health and Demographic Surveillance System in Malawi. The Majete Malaria Project Health and Demographic Surveillance System, in Malawi, started in 2014 to support a project with the aim of studying the reduction of malaria using an integrated control approach by rolling out insecticide treated nets and improved case management supplemented with house improvement and larval source management. In order to support the monitoring of the trial a Health and Demographic Surveillance System was established in the area that surrounds the Majete Wildlife Reserve (1600 km2), using the OpenHDS data system. We compared house locations obtained using GPS recordings on mobile devices during the demographic surveillance census round with those acquired from satellite imagery. Volunteers were recruited through the crowdcrafting.org platform to identify building structures on the images, which enabled the compilation of a database with coordinates of potential residences. For every building identified on these satellite images by the volunteers (11,046 buildings identified of which 3424 (ca. 30%) were part of the censused area), we calculated the distance to the nearest house enumerated on the ground by fieldworkers during the census round of the HDSS. A random sample of buildings (85 structures) identified on satellite images without a nearby location enrolled in the census were visited by a fieldworker to determine how many were missed during the baseline census survey, if any were missed. The findings from this ground-truthing effort suggest that a high population coverage was achieved in the

  13. Estimation of Reservoir Discharges from Lake Nasser and Roseires Reservoir in the Nile Basin Using Satellite Altimetry and Imagery Data

    Directory of Open Access Journals (Sweden)

    Eric Muala

    2014-08-01

    Full Text Available This paper presents the feasibility of estimating discharges from Roseires Reservoir (Sudan for the period from 2002 to 2010 and Aswan High Dam/Lake Nasser (Egypt for the periods 1999–2002 and 2005–2009 using satellite altimetry and imagery with limited in situ data. Discharges were computed using the water balance of the reservoirs. Rainfall and evaporation data were obtained from public domain data sources. In situ measurements of inflow and outflow (for validation were obtained, as well. The other water balance components, such as the water level and surface area, for derivation of the change of storage volume were derived from satellite measurements. Water levels were obtained from Hydroweb for Roseires Reservoir and Hydroweb and Global Reservoir and Lake Monitor (GRLM for Lake Nasser. Water surface areas were derived from Landsat TM/ETM+ images using the Normalized Difference Water Index (NDWI. The water volume variations were estimated by integrating the area-level relationship of each reservoir. For Roseires Reservoir, the water levels from Hydroweb agreed well with in situ water levels (RMSE = 0.92 m; R2 = 0.96. Good agreement with in situ measurements were also obtained for estimated water volume (RMSE = 23%; R2 = 0.94 and computed discharge (RMSE = 18%; R2 = 0.98. The accuracy of the computed discharge was considered acceptable for typical reservoir operation applications. For Lake Nasser, the altimetry water levels also agreed well with in situ levels, both for Hydroweb (RMSE = 0.72 m; R2 = 0.81 and GRLM (RMSE = 0.62 m; R2 = 0.96 data. Similar agreements were also observed for the estimated water volumes (RMSE = 10%–15%. However, the estimated discharge from satellite data agreed poorly with observed discharge, Hydroweb (RMSE = 70%; R2 = 0.09 and GRLM (RMSE = 139%; R2 = 0.36. The error could be attributed to the high sensitivity of discharge to errors in storage volume because of the immense reservoir compared to inflow

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiao Ling

    2016-08-01

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

  16. Statistical Analysis of the Correlation between Microwave Emission Anomalies and Seismic Activity Based on AMSR-E Satellite Data

    Science.gov (United States)

    qin, kai; Wu, Lixin; De Santis, Angelo; Zhang, Bin

    2016-04-01

    Pre-seismic thermal IR anomalies and ionosphere disturbances have been widely reported by using the Earth observation system (EOS). To investigate the possible physical mechanisms, a series of detecting experiments on rock loaded to fracturing were conducted. Some experiments studies have demonstrated that microwave radiation energy will increase under the loaded rock in specific frequency and the feature of radiation property can reflect the deformation process of rock fracture. This experimental result indicates the possibility that microwaves are emitted before earthquakes. Such microwaves signals are recently found to be detectable before some earthquake cases from the brightness temperature data obtained by the microwave-radiometer Advanced Microwave-Scanning Radiometer for the EOS (AMSR-E) aboard the satellite Aqua. This suggested that AMSR-E with vertical- and horizontal-polarization capability for six frequency bands (6.925, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz) would be feasible to detect an earthquake which is associated with rock crash or plate slip. However, the statistical analysis of the correlation between satellite-observed microwave emission anomalies and seismic activity are firstly required. Here, we focus on the Kamchatka peninsula to carry out a statistical study, considering its high seismicity activity and the dense orbits covering of AMSR-E in high latitudes. 8-years (2003-2010) AMSR-E microwave brightness temperature data were used to reveal the spatio-temporal association between microwave emission anomalies and 17 earthquake events (M>5). Firstly, obvious spatial difference of microwave brightness temperatures between the seismic zone at the eastern side and the non-seismic zone the western side within the Kamchatka peninsula are found. Secondly, using both vertical- and horizontal-polarization to extract the temporal association, it is found that abnormal changes of microwave brightness temperatures appear generally 2 months before the

  17. Use and Assessment of Multi-Spectral Satellite Imagery in NWS Operational Forecasting Environments

    Science.gov (United States)

    Molthan, Andrew; Fuell, Kevin; Stano, Geoffrey; McGrath, Kevin; Schultz, Lori; LeRoy, Anita

    2015-01-01

    NOAA's Satellite Proving Grounds have established partnerships between product developers and NWS WFOs for the evaluation of new capabilities from the GOES-R and JPSS satellite systems. SPoRT has partnered with various WFOs to evaluate multispectral (RGB) products from MODIS, VIIRS and Himawari/AHI to prepare for GOES-R/ABI. Assisted through partnerships with GINA, UW/CIMSS, NOAA, and NASA Direct Broadcast capabilities.

  18. Methodology of satellite microwave diagnostics of latitudinal-zonal and seasonal variations of frozen soil and sea ice

    Directory of Open Access Journals (Sweden)

    V. V. Melentiev

    2013-01-01

    Full Text Available In the frame of the work we have had investigated the utility of 6.9GHz dual polarization passive microwave data from the sensor AMSR-E for quantitative assessment of spatial and temporal variations of permafrost, seasonally frozen grounds and sea ice properties along the transect 70° E in 2005–2008 years. Analysis of the factors which could be detected with using study of the spatial-temporal variations of the microwave emissivity (brightness temperatures of the system «Earth-atmosphere» was carried out with using in situ data obtained from meteorological stations situated along the investigated transect of the Western Siberia and geocryologic station Marre-Sale (Yamal Peninsula. A new method of visualization of the brightness temperatures in spatial-temporal dimensions was suggested and practical applied. Eight latitudinal zones with intrinsic peculiarities of the spatial and seasonal variability of the brightness temperatures were revealed and investigated in many details. Comparison of the location of these zones with geographic distribution of biomes in Western Siberia was provided and it shows that satellite passive microwave information can be used for classification of the territories inside biomes. In frame of this study the annual brightness temperatures course for tundra zone area has been strictly divided into four periods (seasons characterized by different types of microwave emissivity variations. For boreal needle-leaved forest zone these seasons are manifested weaker. Comprehensive analysis of the satellite microwave survey data and corresponding the in situ data has shown satisfactory correlation between the brightness temperatures of the tundra areas on the Yamal Peninsula and their thermodynamic ground-trough temperatures at the square of geocryologic station Marre-Sale during winter period of stable frozen conditions and vegetation period. In these periods one-channel satellite microwave survey could be applied for the

  19. Building damage assessment after the earthquake in Haiti using two postevent satellite stereo imagery and DSMs

    DEFF Research Database (Denmark)

    Tian, Jiaojiao; Nielsen, Allan Aasbjerg; Reinartz, Peter

    2015-01-01

    In this article, a novel after-disaster building damage monitoring method is presented. This method combines the multispectral imagery and digital surface models (DSMs) from stereo matching of two dates to obtain three kinds of changes: collapsed buildings, newly built buildings and temporary...... shelters. The proposed method contains three basic steps. The first step is to focus on the DSMs and orthorectified images preparation. The second step is to segment the panchromatic images in obtaining small homogeneous regions. In the last step, a rule-based classification is built on the change...

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

    Science.gov (United States)

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

    2013-12-01

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

  1. RPC Stereo Processor (rsp) - a Software Package for Digital Surface Model and Orthophoto Generation from Satellite Stereo Imagery

    Science.gov (United States)

    Qin, R.

    2016-06-01

    Large-scale Digital Surface Models (DSM) are very useful for many geoscience and urban applications. Recently developed dense image matching methods have popularized the use of image-based very high resolution DSM. Many commercial/public tools that implement matching methods are available for perspective images, but there are rare handy tools for satellite stereo images. In this paper, a software package, RPC (rational polynomial coefficient) stereo processor (RSP), is introduced for this purpose. RSP implements a full pipeline of DSM and orthophoto generation based on RPC modelled satellite imagery (level 1+), including level 2 rectification, geo-referencing, point cloud generation, pan-sharpen, DSM resampling and ortho-rectification. A modified hierarchical semi-global matching method is used as the current matching strategy. Due to its high memory efficiency and optimized implementation, RSP can be used in normal PC to produce large format DSM and orthophotos. This tool was developed for internal use, and may be acquired by researchers for academic and non-commercial purpose to promote the 3D remote sensing applications.

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

    Directory of Open Access Journals (Sweden)

    Phillippa K Bricher

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

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

    Directory of Open Access Journals (Sweden)

    Kabir Uddin

    2015-08-01

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

  4. Precipitation effects on the selection of suitable non-variant targets intended for atmospheric correction of satellite remotely sensed imagery

    Science.gov (United States)

    Themistocleous, Kyriacos; Hadjimitsis, Diofantos G.; Retalis, Adrianos; Chrysoulakis, Nektarios; Michaelides, Silas

    2013-09-01

    One of the most well-established atmospheric correction methods of satellite imagery is the use of the empirical line method using non-variant targets. Non-variant targets serve as pseudo-invariant targets since their reflectance values are stable across time. A recent adaptation of the empirical line method incorporates the use of ground reflectance measurements of selected non-variant targets. Most of the users are not aware of the existing conditions of the pseudo-invariant targets; i.e., whether they are dry or wet. Any omission of such effects may cause erroneous results; therefore, remote sensing users must be aware of such effects. This study assessed the effects of precipitation on five types of commonly located surfaces, including asphalt, concrete and sand, intended as pseudo-invariant targets for atmospheric correction. Spectroradiometric measurements were taken in wet and dry conditions to obtain the spectral signatures of the targets, from January 2010 to May 2011 (46 campaigns). An atmospheric correction of eleven Landsat TM/ETM + satellite images using the empirical line method was conducted. To identify the effects of precipitation, a comparison was conducted of the atmospheric path radiance component for wet and dry conditions. It was found that precipitation conditions such as rainfall affected the reflectance values of the surfaces, especially sand. Therefore, precipitation conditions need to be considered when using non-variant targets in atmospheric correction methods.

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-01-01

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

  7. Land Use Changes of Mata Lake Using Multi-temporal Satellite Imageries

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Land use and protection has become a global hotspot. How to use land resources is an important topic for the future socio-economic sustainable development. This paper analyzes the land use changes of Mata lake of Shandong province in China, from 1985's to 2000's using multi-temporal remotely sensed data including TM in the 1985s, ETM+ in the 2000s and ancillary data such as soil use map, water map etc. The remote sensing imageries were calibrated, registered and geo-referenced, then classified by multi-source information data and remote sensing image interpretation expert system based on knowledge base. Five land use types were extracted from remote sensing imageries, that is, water body, agriculture land, rural settlement, bare land and none use land. The total precision is 80.7% and Kappa index is 0.825. The analysis result of the remote sensing showsthat during the past 15 years, water resource dropped off very promptly from 51.77 km2 to 16. 65 km2 and bare land reduced greatly more than 60% in Mata lake region. With the development of the economy and agriculture areas, more and more water body and bare land converted to agriculture land use and rural settlement areas. Since last years, the Mata lake has been affected by natural factor, human activity and increasing population. So its land use pattern greatly changed from 1985 to 2000.The information of land use changes provided scientific supports for land planning and environmental protection.

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

    Science.gov (United States)

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

    2017-04-01

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

  9. Changes in the Earth's largest surge glacier system from satellite and airborne altimetry and imagery

    Science.gov (United States)

    Trantow, T.; Herzfeld, U. C.

    2015-12-01

    The Bering-Bagley Glacier System (BBGS), Alaska, one of the largest ice systems outside of Greenland and Antarctica, has recently surged (2011-2013), providing a rare opportunity to study the surge phenomenon in a large and complex system. Understanding fast-flowing glaciers and accelerations in ice flow, of which surging is one type, is critical to understanding changes in the cryosphere and ultimately changes in sea level. It is important to distinguish between types of accelerations and their consequences, especially between reversible or quasi-cyclic and irreversible forms of glacial acceleration, but current icesheet models treat all accelerating ice identically. Additionally, the surge provides an exceptional opportunity to study the influence of surface roughness and water content on return signals of altimeter systems. In this presentation, we analyze radar and laser altimeter data from CryoSat-2, NASA's Operation IceBridge (OIB), the ICESat Geoscience Laser Altimeter System (GLAS), ICESat-2's predecessor the Multiple Altimeter Beam Experimental Lidar (MABEL), and airborne laser altimeter and imagery campaigns by our research group. These measurements are used to study elevation, elevation change and crevassing throughout the glacier system. Analysis of the imagery from our airborne campaigns provides comprehensive characterizations of the BBGS surface over the course of the surge. Results from the data analysis are compared to numerical modeling experiments.

  10. The UNOSAT-GRID Project: Access to Satellite Imagery through the Grid Environment

    CERN Document Server

    Méndez-Lorenzo, P; Lamanna, M; Meyer, X; Lazeyras, M; Bjorgo, E; Retiere, A; Falzone, A; Venuti, N; Maccarone, S; Ugolotti, B

    2007-01-01

    UNOSAT is a United Nations activity to provide access to satellite images and geographic system services for humanitarian operations for rescue or aid activities. UNOSAT is implemented by the UN Institute for Training and Research (UNITAR) and managed by the UN Office for Project Services (UNOPS). In addition, partners from different organizations constitute the UNOSAT consortium. Among these partners, CERN participates actively providing the required computational and storage resources. The critical part of the UNOSAT activity is the storage and processing of large quantities of satellite images. The fast and secure access to these images from any part of the world is mandatory during these activities. Based on two successful CERN-GRID/UNOSAT pilot projects (data storage/compression/download and image access through mobile phone), the GRIDUNOSAT project has consolidated the considerable work undertaken so far in the present activity. The main use case already demonstrated is the delivery of satellite images ...

  11. GHRSST Level 2P Global Subskin Sea Surface Temperature from the Advanced Microwave Scanning Radiometer 2 on the GCOM-W satellite (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Advanced Microwave Scanning Radiometer 2 (AMSR2) was launched on 18 May 2012, onboard the Global Change Observation Mission - Water (GCOM-W) satellite developed...

  12. Application of satellite imagery to analyse the distribution and recruitment of sardinella - Annual Report 2002

    NARCIS (Netherlands)

    Zeeberg, J.J.

    2003-01-01

    Remote sensing studies at the Netherlands Institute for Fisheries Research (RIVO) aim to stimulate the use of satellite images on board of Dutch freezer-trawlers in the Mauritanian Exclusive Economic Zone (MEEZ). During four research missions (5-12 July 2002, 23-30 August 2002, 13-20 October 2002, a

  13. The Final Frontier: News Media’s Use of Commercial Satellite Imagery during Wartime

    Science.gov (United States)

    2006-04-01

    Political Communication . Vol. 9, 1992, p. 192. 5 “An orbit is sun-synchronous when the spacecraft is constantly interposed between the earth and the sun...government: The media, remote-sensing satellites, and U.S. national security policy.” Political Communication . Vol. 9, 1992. DeSelding, P.B. and Lawler

  14. Remote Sensing of Tropical Cyclones: Applications from Microwave Radiometry and Global Navigation Satellite System Reflectometry

    Science.gov (United States)

    Morris, Mary

    Tropical cyclones (TCs) are important to observe, especially over the course of their lifetimes, most of which is spent over the ocean. Very few in situ observations are available. Remote sensing has afforded researchers and forecasters the ability to observe and understand TCs better. Every remote sensing platform used to observe TCs has benefits and disadvantages. Some remote sensing instruments are more sensitive to clouds, precipitation, and other atmospheric constituents. Some remote sensing instruments are insensitive to the atmosphere, which allows for unobstructed observations of the ocean surface. Observations of the ocean surface, either of surface roughness or emission can be used to estimate ocean surface wind speed. Estimates of surface wind speed can help determine the intensity, structure, and destructive potential of TCs. While there are many methods by which TCs are observed, this thesis focuses on two main types of remote sensing techniques: passive microwave radiometry and Global Navigation Satellite System reflectometry (GNSS-R). First, we develop and apply a rain rate and ocean surface wind speed retrieval algorithm for the Hurricane Imaging Radiometer (HIRAD). HIRAD, an airborne passive microwave radiometer, operates at C-band frequencies, and is sensitive to rain absorption and emission, as well as ocean surface emission. Motivated by the unique observing geometry and high gradient rain scenes that HIRAD typically observes, a more robust rain rate and wind speed retrieval algorithm is developed. HIRAD's observing geometry must be accounted for in the forward model and retrieval algorithm, if high rain gradients are to be estimated from HIRAD's observations, with the ultimate goal of improving surface wind speed estimation. Lastly, TC science data products are developed for the Cyclone Global Navigation Satellite System (CYGNSS). The CYGNSS constellation employs GNSS-R techniques to estimate ocean surface wind speed in all precipitating

  15. Inversion Technique for Estimating Emissions of Volcanic Ash from Satellite Imagery

    Science.gov (United States)

    Pelley, Rachel; Cooke, Michael; Manning, Alistair; Thomson, David; Witham, Claire; Hort, Matthew

    2014-05-01

    When using dispersion models such as NAME (Numerical Atmospheric-dispersion Modelling Environment) to predict the dispersion of volcanic ash, a source term defining the mass release rate of ash is required. Inversion modelling using observations of the ash plume provides a method of estimating the source term for use in NAME. Our inversion technique makes use of satellite retrievals, calculated using data from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) instrument on-board the MSG (Meteosat Second Generation) satellite, as the ash observations. InTEM (Inversion Technique for Emission Modelling) is the UK Met Office's inversion modelling system. Recently the capability to estimate time and height varying source terms has been implemented and applied to volcanic ash. InTEM uses a probabilistic approach to fit NAME model concentrations to satellite retrievals. This is achieved by applying Bayes Theorem to give a cost function for the source term. Source term profiles with lower costs generate model concentrations that better fit the satellite retrievals. InTEM uses the global optimisation technique, simulated annealing, to find the minimum of the cost function. The use of a probabilistic approach allows the uncertainty in the satellite retrievals to be incorporated into the inversion technique. InTEM makes use of satellite retrievals of both ash column loadings and of cloud free regions. We present a system that allows InTEM to be used during an eruption. The system is automated and can produce source term updates up to four times a day. To allow automation hourly satellite retrievals of ash are routinely produced using conservative detection limits. The conservative detection limits provide good detection of the ash plume while limiting the number of false alarms. Regions which are flagged as ash contaminated or free from cloud (both meteorological and ash) are used in the InTEM system. This approach is shown to improve the concentrations in the

  16. Comparison of Orbit-Based and Time-Offset-Based Geometric Correction Models for SAR Satellite Imagery Based on Error Simulation.

    Science.gov (United States)

    Hong, Seunghwan; Choi, Yoonjo; Park, Ilsuk; Sohn, Hong-Gyoo

    2017-01-17

    Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various geometric correction models have been developed and applied. However, it is still difficult for general users to adopt a suitable geometric correction models having sufficient precision. In this regard, this paper evaluated the orbit-based and time-offset-based models with an error simulation. To evaluate the geometric correction models, Radarsat-1 images that have large errors in satellite orbit information and TerraSAR-X images that have a reportedly high accuracy in satellite orbit and sensor information were utilized. For Radarsat-1 imagery, the geometric correction model based on the satellite position parameters has a better performance than the model based on time-offset parameters. In the case of the TerraSAR-X imagery, two geometric correction models had similar performance and could ensure sub-pixel geolocation accuracy.

  17. Comparison of Orbit-Based and Time-Offset-Based Geometric Correction Models for SAR Satellite Imagery Based on Error Simulation

    Science.gov (United States)

    Hong, Seunghwan; Choi, Yoonjo; Park, Ilsuk; Sohn, Hong-Gyoo

    2017-01-01

    Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various geometric correction models have been developed and applied. However, it is still difficult for general users to adopt a suitable geometric correction models having sufficient precision. In this regard, this paper evaluated the orbit-based and time-offset-based models with an error simulation. To evaluate the geometric correction models, Radarsat-1 images that have large errors in satellite orbit information and TerraSAR-X images that have a reportedly high accuracy in satellite orbit and sensor information were utilized. For Radarsat-1 imagery, the geometric correction model based on the satellite position parameters has a better performance than the model based on time-offset parameters. In the case of the TerraSAR-X imagery, two geometric correction models had similar performance and could ensure sub-pixel geolocation accuracy. PMID:28106729

  18. Comparison of Orbit-Based and Time-Offset-Based Geometric Correction Models for SAR Satellite Imagery Based on Error Simulation

    Directory of Open Access Journals (Sweden)

    Seunghwan Hong

    2017-01-01

    Full Text Available Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various geometric correction models have been developed and applied. However, it is still difficult for general users to adopt a suitable geometric correction models having sufficient precision. In this regard, this paper evaluated the orbit-based and time-offset-based models with an error simulation. To evaluate the geometric correction models, Radarsat-1 images that have large errors in satellite orbit information and TerraSAR-X images that have a reportedly high accuracy in satellite orbit and sensor information were utilized. For Radarsat-1 imagery, the geometric correction model based on the satellite position parameters has a better performance than the model based on time-offset parameters. In the case of the TerraSAR-X imagery, two geometric correction models had similar performance and could ensure sub-pixel geolocation accuracy.

  19. An Assessment of the Capabilities of the ERS Satellites' Active Microwave Instruments for Monitoring Soil Moisture Change

    Directory of Open Access Journals (Sweden)

    K. Blyth

    1997-01-01

    Full Text Available The launch of the European Remote sensing Satellite (ERS-1 in July 1991 represented an important turning point in the development of Earth observation as it was the first of a series of satellites which would carry high resolution active microwave (radar sensors which could operate through the thickest cloudeover and provide continuity of data for at least a decade. This was of particular relevance to hydrological applications, such as soil moisture monitoring, which generally require frequent satellite observations to monitor changes in state. ERS-1 and its successor ERS-2 carry the active microwave instrument (AMI which operates in 3 modes (synthetic aperture radar, wind scatterometer and wave seatterometer together with the radar altimeter which may all be useful for the observation of soil moisture. This paper assesses the utility of these sensors through a comprehensive review of work in this field. Two approaches to soil moisture retrieval are identified: 1 inversion modelling, where the physical effects of vegetation and soil roughness on radar backscatter are quantified through the use of multi-frequency and/or multi-polarization sensors and 2 change detection where these effects are normalized through frequent satellite observation, the residual effects being attributed to short-term changes in soil moisture. Both approaches will be better supported by the future European Envisat-l satellite which will provide both multi-polarization SAR and low resolution products which should facilitate more frequent temporal observation.

  20. Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird satellite imagery.

    Science.gov (United States)

    Stow, Douglas A; Lippitt, Christopher D; Weeks, John R

    2010-08-01

    The objective was to test GEographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregating census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (1) merging adjacent EAs according to vegetation measures and (2) image segmentation. Both approaches exploit readily available functions within commercial GEOBIA software. Image-derived neighborhood maps were compared to a reference map derived by spatial clustering of slum index values (from census data), to provide a relative assessment of potential map utility. A size-constrained iterative segmentation approach to aggregation was more successful than standard image segmentation or feature merge techniques. The segmentation approaches account for size and shape characteristics, enabling more realistic neighborhood boundaries to be delineated. The percentage of vegetation patches within each EA yielded more realistic delineation of potential neighborhoods than mean vegetation patch size per EA.

  1. Do clouds save the great barrier reef? satellite imagery elucidates the cloud-SST relationship at the local scale.

    Directory of Open Access Journals (Sweden)

    Susannah M Leahy

    Full Text Available Evidence of global climate change and rising sea surface temperatures (SSTs is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an "ocean thermostat" and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006 and two relatively cool summers (2007 and 2008. Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005 and La Niña (2008 study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs.

  2. Do clouds save the great barrier reef? satellite imagery elucidates the cloud-SST relationship at the local scale.

    Science.gov (United States)

    Leahy, Susannah M; Kingsford, Michael J; Steinberg, Craig R

    2013-01-01

    Evidence of global climate change and rising sea surface temperatures (SSTs) is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an "ocean thermostat" and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR) shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006) and two relatively cool summers (2007 and 2008). Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005) and La Niña (2008) study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs.

  3. Title: Rice Crop Monitoring by Fusing Microwave and Optical Satellite Data

    Science.gov (United States)

    Oyoshi, K.; Takeuchi, W.; LE Toan, T.; Sobue, S.

    2015-12-01

    Rapid population and economic growth, and the increase in extreme weather events, are destabilizing global food security. In Asia, rice is a staple cereal crop, and the continent accounts for about 90% of global rice production and consumption. The Group on Earth Observations (GEO) Global Agricultural Monitoring (GLAM) was launched in 2011 to utilize remote sensing tools to enhance crop production projections in order to promote food security and foster sustainable economic growth. Asia---‒Rice Crop Estimation & Monitoring (Asia---‒RiCE) is a component of GEOGLAM, and aims to use remote sensing tools to develop rice---‒related information such as maps of paddy fields, rice growing conditions, yield, and production. However, in some regions in Southeast Asia, rice is planted and harvested more than twice a year, and the crop calendar is quite complicated. In addition, rice is mainly cultivated in the rainy season, and the high density of cloud cover during that season limits the observations that can be made from space using only optical sensors. In contrast, Synthetic Aperture Radar (SAR) is a robust tool because it penetrates cloud cover; however, the revisit frequency of a single SAR satellite is limited, making it difficult to capture the complicated rice crop calendar in Asia. In this research, time---‒series SAR data were fused with optical data to monitor rice crops in Southeast Asia with complicated crop calendars. In addition, a microwave radiometer that also penetrates clouds and has a high revisit frequency but a coarse spatial resolution (greater than several kilometers), was used. The integrated use of a large variety of satellite data enables us to periodically monitor surface conditions such as water inundation, transplanting, and rice crop growth and harvesting, which in turn enables us to examine rice planted areas, rice crop calendars, and rice growing conditions in order to estimate rice production.

  4. UNOSAT at CERN – 15 years of satellite imagery support to the humanitarian and development community

    CERN Document Server

    CERN. Geneva

    2017-01-01

    Abstract: UNOSAT is part of the United Nations Institute for Training and Research (UNITAR) and has been hosted at CERN since 2001. This partnership allows UNOSAT to benefit from CERN's IT infrastructure whenever the situation requires, allowing the UN to be at the forefront of satellite-analysis technology. Specialists in geographic information systems (GIS) and in the analysis of satellite data, supported by IT engineers and policy experts, ensure a dedicated service to the international humanitarian and development communities 24 hours a day, seven days a week. The presentation will give an overview of the variety of activities carried out by UNOSAT over the last 15 years including support to humanitarian assistance and protection of cultural heritage, sustainable water management in Chad and training & capacity development in East Africa and Asia. The talk will be followed at 12:00 by the inauguration of the UNOSAT exhibition, in front of the Users' office. Speaker: Einar Bjor...

  5. Becoming Bombs: 3D Animated Satellite Imagery and the Weaponization of the Civic Eye

    Directory of Open Access Journals (Sweden)

    Roger Stahl

    2010-02-01

    Full Text Available This essay traces the recent history of 3D satellite animation from its military origins to its visibility in the civic sphere. Specifically, technologies unveiled in 2004 as Google Earth first received widespread public visibility in the television coverage of the 2003 U.S. invasion of Iraq. The essay first maps the political economy of the “military-media-geotech” complex, focusing mainly on the coverage of the Iraq War as an nexus of interests. Second, the essay analyzes the aesthetic uses of 3D satellite animation on the news during this period, including how these imaging practices meshed with existing discourses such as the clean war, the weaponization of the civic gaze, and others. The essay concludes with thoughts regarding what these practices mean for the efficacy of the deliberative citizen, public life, and the meaning of war.

  6. Detection of the urban heat island in Beijing using HJ-1B satellite imagery

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Satellite images are used extensively in studying the urban heat island(UHI) phenomenon.We evaluated the suitability of thermal infrared(TIR) data from the HJ-1B satellite for detecting UHI using a case study in Beijing.Two modified algorithms for retrieving the land surface temperature(LST) from HJ-1B data were tested.The results were compared with LST images derived from a Landsat TM thermal band and the MODIS LST output.The spatial pattern of UHI generated using HJ-1B data matched well with that produced using TM and MODIS data.Of the two algorithms,the mono-window algorithm performed better but further tests are necessary.With more frequent coverage than TM and higher spatial resolution than MODIS,the HJ-1B TIR data present a unique opportunity to study thermal environments in cities in China and neighboring countries.

  7. Land use change detection based on multi-date imagery from different satellite sensor systems

    Science.gov (United States)

    Stow, Douglas A.; Collins, Doretta; Mckinsey, David

    1990-01-01

    An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

  8. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery.

    Directory of Open Access Journals (Sweden)

    Takuto Sakamoto

    Full Text Available Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level.

  9. A fast radiative transfer method for the simulation of visible satellite imagery

    Science.gov (United States)

    Scheck, Leonhard; Frèrebeau, Pascal; Buras-Schnell, Robert; Mayer, Bernhard

    2016-05-01

    A computationally efficient radiative transfer method for the simulation of visible satellite images is presented. The top of atmosphere reflectance is approximated by a function depending on vertically integrated optical depths and effective particle sizes for water and ice clouds, the surface albedo, the sun and satellite zenith angles and the scattering angle. A look-up table (LUT) for this reflectance function is generated by means of the discrete ordinate method (DISORT). For a constant scattering angle the reflectance is a relatively smooth and symmetric function of the two zenith angles, which can be well approximated by the lowest-order terms of a 2D Fourier series. By storing only the lowest Fourier coefficients and adopting a non-equidistant grid for the scattering angle, the LUT is reduced to a size of 21 MB per satellite channel. The computation of the top of atmosphere reflectance requires only the calculation of the cloud parameters from the model state and the evaluation and interpolation of the reflectance function using the compressed LUT and is thus orders of magnitude faster than DISORT. The accuracy of the method is tested by generating synthetic satellite images for the 0.6 μm and 0.8 μm channels of the SEVIRI instrument for operational COSMO-DE model forecasts from the German Weather Service (DWD) and comparing them to DISORT results. For a test period in June the root mean squared absolute reflectance error is about 10-2 and the mean relative reflectance error is less than 2% for both channels. For scattering angles larger than 170 ° the rapid variation of reflectance with the particle size related to the backscatter glory reduces the accuracy and the errors increase by a factor of 3-4. Speed and accuracy of the new method are sufficient for operational data assimilation and high-resolution model verification applications.

  10. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting

    Science.gov (United States)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.

    2014-12-01

    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  11. Content-Aware Adaptive Compression of Satellite Imagery Using Artificial Vision

    Science.gov (United States)

    2013-09-01

    Figure 3.2 An example of a vector-based Digital Nautical Chart ( DNC ) which could be used to automatically remove most of the terrain from a satellite...Transform DNC Digital Nautical Chart DWT Discrete Wavelet Transform DSP Digital Signal Processor FPGA Field-Programmable Gate Array IEC International...order to automate this step. Figure 3.2: An example of a vector-based Digital Nautical Chart ( DNC ) which could be used to automatically remove most of

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

    OpenAIRE

    Dowdeswell, Julian A.; Benham, Toby J.

    2003-01-01

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

  13. OVERVIEW OF MODERN RESEARCH OF LANDSLIDES ACCORDING TO AERIAL AND SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    K. M. Lyapishev

    2015-01-01

    Full Text Available This article is an overview of researches of landslides using remote sensing methods such as aerial photography, satellite images, radar interferometry, and their combination with the use of GIS technology. Modern methods of investigation of landslides are very diverse. The authors propose different approaches to the identification, classification and monitoring of landslides. Data analysis techniques can help in creating more sophisticated approach to the analysis of landslides.

  14. Use of Commercial Satellite Imagery for Surveillance of the Canadian North by the Canadian Armed Forces

    Science.gov (United States)

    1988-12-01

    by M. Dobson. New York: IEEE Press, 1988. 9. Bodin , P. and J-F. Reulet. "A New Channel for SPOT Satellite in the SWIR Band," Focal Plane Arra@s...TecholgqoandAic@igtns, edited by Jean -Pierre Chartard. Proc. SPIE 865, 142-1Li9 (1987). 10. Burrows, W.E. eep apck _Sacesionage_and National SecuritU. New

  15. Using ISERV and Commercial Satellite Imagery to Assess and Monitor Recovery Efforts in Urban Damaged Areas

    Science.gov (United States)

    Bell, Jordan R.; Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.

    2014-01-01

    NASA's Short-term Prediction, Research, and Transition (SPoRT) Center uses a wide array of satellites to monitor and assess the impacts of natural disasters, with support from NASA's Applied Sciences Program. One of the newest sensors SPoRT is utilizing in these activities is the International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. ISERV provides a unique view of the areas impacted and will play a big role in monitoring the recovery these areas. High-resolution commercial satellite data is also used to monitor urban areas that have been impacted by natural disasters. SPoRT is developing techniques to measure the extent of these disasters and to monitor recovery. Several of these techniques include semi-automatic feature detection and change as well as developing an experimental damage assessment based upon the visible damage observed by the satellites. Furthermore, throughout these activities SPoRT hopes to provide additional data to the NOAA National Weather Service Damage Assessment Toolkit, which will help to supplement those activities being performed in the field.

  16. An improved technique for global daily sunshine duration estimation using satellite imagery

    Institute of Scientific and Technical Information of China (English)

    Muhammad Ali SHAMIM; Renji REMESAN; Da-wei HAN; Naeem EJAZ; Ayub ELAHI

    2012-01-01

    This paper presents an improved model for global sunshine duration estimation.The methodology incorporates geostationary satellite images by including snow cover information,sun and satellite angles and a trend correction factor for seasons,for the determination of cloud cover index.The effectiveness of the proposed methodology has been tested using Meteosat geostationary satellite images in the visible band with a temporal resolution of 1 h and spatial resolution of 2.5 km×2.5 km,for the Brue Catchment in the southwest of England.Validation results show a significant improvement in the estimation of global sunshine duration by the proposed method as compared to its predecessor (R2 is improved from 0.68 to 0.83,root mean squared error (RMSE) from 2.37 h/d to 1.19 h/d and the mean biased error (MBE) from 0.21 h/d to 0.08 h/d).Further studies are needed to test this method in other parts of the world with different climate and geographical conditions.

  17. Classification of mangroves vegetation species using texture analysis on Rapideye satellite imagery

    Science.gov (United States)

    Roslani, M. A.; Mustapha, M. A.; Lihan, T.; Juliana, W. A. Wan

    2013-11-01

    Mangroves are unique ecosystem structures that are typically made up of salt tolerant species of vegetation that can be found in tropical and subtropical climate country. Mangrove ecosystem plays important role and also is known as highly productive ecosystem with high diversity of flora and fauna. However, these ecosystems have been declining over time due to the various kinds of direct and indirect pressures. Thus, there is an increasing need to monitor and assess this ecosystem for better conservation and management efforts. The multispectral RapidEye satellite image was used to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia using texture analysis. Classification was implemented using the maximum likelihood classifier (MLC) method. Total of eleven main mangrove species were found in the satellite image of the study site which includes Rhizophora mucronata, Rhizophora apiculata, Bruguiera parviflora, Bruguiera cylindrica, Bruguiera gymnorrhiza, Avicennia alba, Avicennia officinalis, Sonneratia alba, Sonneratia caseolaris, Sonneratia ovata and Xylocarpus granatum. The classification results showed that the textured image produced high overall classification assessment recorded at 84% and kappa statistic of 0.8016. Meanwhile, the non-textured image produces 80% of overall accuracy and kappa statistic of 0.7061. The classification result indicated the capability of high resolution satellite image to classify the mangrove species and inclusion of texture information in the classification increased the classification accuracy.

  18. Aerial Photography and Imagery, Ortho-Corrected, 2004 Satellite Imagery, Published in 2004, 1:12000 (1in=1000ft) scale, Anne Arundel County, OIT GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

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

    Directory of Open Access Journals (Sweden)

    A. Nascetti

    2015-07-01

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

  20. Assessment of the Impact of Reservoirs in the Upper Mekong River Using Satellite Radar Altimetry and Remote Sensing Imageries

    Directory of Open Access Journals (Sweden)

    Kuan-Ting Liu

    2016-04-01

    Full Text Available Water level (WL and water volume (WV of surface-water bodies are among the most crucial variables used in water-resources assessment and management. They fluctuate as a result of climatic forcing, and they are considered as indicators of climatic impacts on water resources. Quantifying riverine WL and WV, however, usually requires the availability of timely and continuous in situ data, which could be a challenge for rivers in remote regions, including the Mekong River basin. As one of the most developed rivers in the world, with more than 20 dams built or under construction, Mekong River is in need of a monitoring system that could facilitate basin-scale management of water resources facing future climate change. This study used spaceborne sensors to investigate two dams in the upper Mekong River, Xiaowan and Jinghong Dams within China, to examine river flow dynamics after these dams became operational. We integrated multi-mission satellite radar altimetry (RA, Envisat and Jason-2 and Landsat-5/-7/-8 Thematic Mapper (TM/Enhanced Thematic Mapper plus (ETM+/Operational  Land Imager (OLI optical remote sensing (RS imageries to construct composite WL time series with enhanced spatial resolutions and substantially extended WL data records. An empirical relationship between WL variation and water extent was first established for each dam, and then the combined long-term WL time series from Landsat images are reconstructed for the dams. The R2 between altimetry WL and Landsat water area measurements is >0.95. Next, the Tropical Rainfall Measuring Mission (TRMM data were used to diagnose and determine water variation caused by the precipitation anomaly within the basin. Finally, the impact of hydrologic dynamics caused by the impoundment of the dams is assessed. The discrepancy between satellite-derived WL and available in situ gauge data, in term of root-mean-square error (RMSE is at 2–5 m level. The estimated WV variations derived from combined RA

  1. Use of open source information and commercial satellite imagery for nuclear nonproliferation regime compliance verification by a community of academics

    Science.gov (United States)

    Solodov, Alexander

    The proliferation of nuclear weapons is a great threat to world peace and stability. The question of strengthening the nonproliferation regime has been open for a long period of time. In 1997 the International Atomic Energy Agency (IAEA) Board of Governors (BOG) adopted the Additional Safeguards Protocol. The purpose of the protocol is to enhance the IAEA's ability to detect undeclared production of fissile materials in member states. However, the IAEA does not always have sufficient human and financial resources to accomplish this task. Developed here is a concept for making use of human and technical resources available in academia that could be used to enhance the IAEA's mission. The objective of this research was to study the feasibility of an academic community using commercially or publicly available sources of information and products for the purpose of detecting covert facilities and activities intended for the unlawful acquisition of fissile materials or production of nuclear weapons. In this study, the availability and use of commercial satellite imagery systems, commercial computer codes for satellite imagery analysis, Comprehensive Test Ban Treaty (CTBT) verification International Monitoring System (IMS), publicly available information sources such as watchdog groups and press reports, and Customs Services information were explored. A system for integrating these data sources to form conclusions was also developed. The results proved that publicly and commercially available sources of information and data analysis can be a powerful tool in tracking violations in the international nuclear nonproliferation regime and a framework for implementing these tools in academic community was developed. As a result of this study a formation of an International Nonproliferation Monitoring Academic Community (INMAC) is proposed. This would be an independent organization consisting of academics (faculty, staff and students) from both nuclear weapon states (NWS) and

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

    Science.gov (United States)

    Necsoiu, M.; Onaca, A.

    2015-12-01

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

  3. A general framework of TOPSIS method for integration of airborne geophysics, satellite imagery, geochemical and geological data

    Science.gov (United States)

    Abedi, Maysam; Norouzi, Gholam-Hossain

    2016-04-01

    This work presents the promising application of three variants of TOPSIS method (namely the conventional, adjusted and modified versions) as a straightforward knowledge-driven technique in multi criteria decision making processes for data fusion of a broad exploratory geo-dataset in mineral potential/prospectivity mapping. The method is implemented to airborne geophysical data (e.g. potassium radiometry, aeromagnetic and frequency domain electromagnetic data), surface geological layers (fault and host rock zones), extracted alteration layers from remote sensing satellite imagery data, and five evidential attributes from stream sediment geochemical data. The central Iranian volcanic-sedimentary belt in Kerman province at the SE of Iran that is embedded in the Urumieh-Dokhtar Magmatic Assemblage arc (UDMA) is chosen to integrate broad evidential layers in the region of prospect. The studied area has high potential of ore mineral occurrences especially porphyry copper/molybdenum and the generated mineral potential maps aim to outline new prospect zones for further investigation in future. Two evidential layers of the downward continued aeromagnetic data and its analytic signal filter are prepared to be incorporated in fusion process as geophysical plausible footprints of the porphyry type mineralization. The low values of the apparent resistivity layer calculated from the airborne frequency domain electromagnetic data are also used as an electrical criterion in this investigation. Four remote sensing evidential layers of argillic, phyllic, propylitic and hydroxyl alterations were extracted from ASTER images in order to map the altered areas associated with porphyry type deposits, whilst the ETM+ satellite imagery data were used as well to map iron oxide layer. Since potassium alteration is generally the mainstay of porphyry ore mineralization, the airborne potassium radiometry data was used. The geochemical layers of Cu/B/Pb/Zn elements and the first component of PCA

  4. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and Quantitative mapping of salinity stress in sugarcane fields

    Science.gov (United States)

    Hamzeh, Saeid; Naseri, Abd Ali; AlaviPanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

    2016-10-01

    This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image acquired on September 7, 2010 were used as hyperspectral and multispectral satellite imagery. Field data including soil salinity in the sugarcane root zone was collected at 191 locations in 25 fields during September 2010. In the first section of the paper, based on the yield potential of sugarcane as influenced by different soil salinity levels provided by FAO, soil salinity was classified into three classes, low salinity (1.7-3.4 dS/m), moderate salinity (3.5-5.9 dS/m) and high salinity (6-9.5) by applying different classification methods including Support Vector Machine (SVM), Spectral Angle Mapper (SAM), Minimum Distance (MD) and Maximum Likelihood (ML) on Hyperion and Landsat images. In the second part of the paper the performance of nine vegetation indices (eight indices from literature and a new developed index in this study) extracted from Hyperion and Landsat data was evaluated for quantitative mapping of salinity stress. The experimental results indicated that for categorical classification of salinity stress, Landsat data resulted in a higher overall accuracy (OA) and Kappa coefficient (KC) than Hyperion, of which the MD classifier using all bands or PCA (1-5) as an input performed best with an overall accuracy and kappa coefficient of 84.84% and 0.77 respectively. Vice versa for the quantitative estimation of salinity stress, Hyperion outperformed Landsat. In this case, the salinity and water stress index (SWSI) has the best prediction of salinity stress with an R2 of 0.68 and RMSE of 1.15 dS/m for Hyperion followed by Landsat data with an R2 and RMSE of 0.56 and 1.75 dS/m respectively. It was concluded that categorical mapping of salinity stress is the best option

  5. Forest Tree Species Distribution Mapping Using Landsat Satellite Imagery and Topographic Variables with the Maximum Entropy Method in Mongolia

    Science.gov (United States)

    Hao Chiang, Shou; Valdez, Miguel; Chen, Chi-Farn

    2016-06-01

    Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled

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

    Science.gov (United States)

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

    2015-12-01

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

  7. FOREST TREE SPECIES DISTRIBUTION MAPPING USING LANDSAT SATELLITE IMAGERY AND TOPOGRAPHIC VARIABLES WITH THE MAXIMUM ENTROPY METHOD IN MONGOLIA

    Directory of Open Access Journals (Sweden)

    S. H. Chiang

    2016-06-01

    Full Text Available Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface

  8. Investigation of multipactor breakdown in communication satellite microwave co-axial systems

    Indian Academy of Sciences (India)

    S K Nagesh; D Revannasiddiah; S V K Shastry

    2005-01-01

    Multipactor breakdown or multipactor discharge is a form of high frequency discharge that may occur in microwave components operating at very low pressures. Some RF components of multi-channel communication satellites have co-axial geometry and handle high RF power under near-vacuum conditions. The breakdown occurs due to secondary electron resonance, wherein electrons move back and forth in synchronism with the RF voltage across the gap between the inner and outer conductors of the co-axial structure. If the yield of secondary electrons from the walls of the co-axial structure is greater than unity, then the electron density increases with time and eventually leads to the breakdown. In this paper, the current due to the oscillating electrons in the co-axial geometry has been treated as a radially oriented Hertzian dipole. The electric field, due to this dipole, at any point in the coaxial structure, may then be determined by employing the dyadic Green’s function technique. This field has been compared with the field that would exist in the absence of multipactor.

  9. Optical frequency comb based multi-band microwave frequency conversion for satellite applications.

    Science.gov (United States)

    Yang, Xinwu; Xu, Kun; Yin, Jie; Dai, Yitang; Yin, Feifei; Li, Jianqiang; Lu, Hua; Liu, Tao; Ji, Yuefeng

    2014-01-13

    Based on optical frequency combs (OFC), we propose an efficient and flexible multi-band frequency conversion scheme for satellite repeater applications. The underlying principle is to mix dual coherent OFCs with one of which carrying the input signal. By optically channelizing the mixed OFCs, the converted signal in different bands can be obtained in different channels. Alternatively, the scheme can be configured to generate multi-band local oscillators (LO) for widely distribution. Moreover, the scheme realizes simultaneous inter- and intra-band frequency conversion just in a single structure and needs only three frequency-fixed microwave sources. We carry out a proof of concept experiment in which multiple LOs with 2 GHz, 10 GHz, 18 GHz, and 26 GHz are generated. A C-band signal of 6.1 GHz input to the proposed scheme is successfully converted to 4.1 GHz (C band), 3.9 GHz (C band) and 11.9 GHz (X band), etc. Compared with the back-to-back (B2B) case measured at 0 dBm input power, the proposed scheme shows a 9.3% error vector magnitude (EVM) degradation at each output channel. Furthermore, all channels satisfy the EVM limit in a very wide input power range.

  10. Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Benjamin T. Tuttle

    2010-12-01

    Full Text Available The potential use of satellite observed nighttime lights for estimating carbon-dioxide (CO2 emissions has been demonstrated in several previous studies. However, the procedures for a moderate resolution (1 km2 grid cells global map of fossil fuel CO2 emissions based on nighttime lights are still in the developmental phase. We report on the development of a method for mapping distributed fossil fuel CO2 emissions (excluding electric power utilities at 30 arc-seconds or approximately 1 km2 resolution using nighttime lights data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS. A regression model, Model 1, was initially developed based on carbon emissions from five sectors of the Vulcan data produced by the Purdue University and a nighttime satellite image of the U.S. The coefficient derived through Model 1 was applied to the global nighttime image but it resulted in underestimation of CO2 emissions for most of the world’s countries, and the states of the U.S. Thus, a second model, Model 2 was developed by allocating the distributed CO2 emissions (excluding emissions from utilities using a combination of DMSP-OLS nighttime image and population count data from the U.S. Department of Energy's (DOE LandScan grid. The CO2 emissions were distributed in proportion to the brightness of the DMSP nighttime lights in areas where lighting was detected. In areas with no DMSP detected lighting, the CO2 emissions were distributed based on population count, with the assumption that people who live in these areas emit half as much CO2 as people who live in the areas with DMSP detected lighting. The results indicate that the relationship between satellite observed nighttime lights and CO2 emissions is complex, with differences between sectors and variations in lighting practices between countries. As a result it is not possible to make independent estimates of CO2 emissions with currently available coarse

  11. Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

  12. Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.

    2006-01-01

    Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal

  13. SNOW DEPTH ESTIMATION USING TIME SERIES PASSIVE MICROWAVE IMAGERY VIA GENETICALLY SUPPORT VECTOR REGRESSION (CASE STUDY URMIA LAKE BASIN

    Directory of Open Access Journals (Sweden)

    N. Zahir

    2015-12-01

    Full Text Available Lake Urmia is one of the most important ecosystems of the country which is on the verge of elimination. Many factors contribute to this crisis among them is the precipitation, paly important roll. Precipitation has many forms one of them is in the form of snow. The snow on Sahand Mountain is one of the main and important sources of the Lake Urmia’s water. Snow Depth (SD is vital parameters for estimating water balance for future year. In this regards, this study is focused on SD parameter using Special Sensor Microwave/Imager (SSM/I instruments on board the Defence Meteorological Satellite Program (DMSP F16. The usual statistical methods for retrieving SD include linear and non-linear ones. These methods used least square procedure to estimate SD model. Recently, kernel base methods widely used for modelling statistical problem. From these methods, the support vector regression (SVR is achieved the high performance for modelling the statistical problem. Examination of the obtained data shows the existence of outlier in them. For omitting these outliers, wavelet denoising method is applied. After the omission of the outliers it is needed to select the optimum bands and parameters for SVR. To overcome these issues, feature selection methods have shown a direct effect on improving the regression performance. We used genetic algorithm (GA for selecting suitable features of the SSMI bands in order to estimate SD model. The results for the training and testing data in Sahand mountain is [R²_TEST=0.9049 and RMSE= 6.9654] that show the high SVR performance.

  14. Assessing the Performance of a Northern Gulf of Mexico Tidal Model Using Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Stephen C. Medeiros

    2013-11-01

    Full Text Available Tidal harmonic analysis simulations along with simulations spanning four specific historical time periods in 2003 and 2004 were conducted to test the performance of a northern Gulf of Mexico tidal model. A recently developed method for detecting inundated areas based on integrated remotely sensed data (i.e., Radarsat-1, aerial imagery, LiDAR, Landsat 7 ETM+ was applied to assess the performance of the tidal model. The analysis demonstrates the applicability of the method and its agreement with traditional performance assessment techniques such as harmonic resynthesis and water level time series analysis. Based on the flooded/non-flooded coastal areas estimated by the integrated remotely sensed data, the model is able to adequately reproduce the extent of inundation within four sample areas from the coast along the Florida panhandle, correctly identifying areas as wet or dry over 85% of the time. Comparisons of the tidal model inundation to synoptic (point-in-time inundation areas generated from the remotely sensed data generally agree with the results of the traditional performance assessment techniques. Moreover, this approach is able to illustrate the spatial distribution of model inundation accuracy allowing for targeted refinement of model parameters.

  15. Improvements to Lunar BRDF-Corrected Nighttime Satellite Imagery: Uses and Applications

    Science.gov (United States)

    Cole, T.; Molthan, A.; Schultz, L. A.; Roman, M. O.; Wanik, D. W.

    2016-12-01

    Observations made by the VIIRS day/night band (DNB) provide daily, nighttime measurements to monitor Earth surface processes. However, these observations are impacted by variations in reflected solar radiation on the moon's surface. As the moon transitions from new to full phase, increasing radiance is reflected to the Earth's surface and contributes additional reflected moonlight from clouds and land surface, in addition to emissions from other light sources observed by the DNB. The introduction of a bi-directional reflectance distribution function (BRDF) algorithm serves to remove these lunar variations and normalize observed radiances. Provided by the Terrestrial Information Systems Laboratory at Goddard Space Flight Center, a 1 km gridded lunar BRDF-corrected DNB product and VIIRS cloud mask can be used for a multitude of nighttime applications without influence from the moon. Such applications include the detection of power outages following severe weather events using pre- and post-event DNB imagery, as well as the identification of boat features to curtail illegal fishing practices. This presentation will provide context on the importance of the lunar BRDF correction algorithm and explore the aforementioned uses of this improved DNB product for applied science applications.

  16. Detection of Neolithic Settlements in Thessaly (Greece Through Multispectral and Hyperspectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Dimitrios Alexakis

    2009-02-01

    Full Text Available Thessaly is a low relief region in Greece where hundreds of Neolithic settlements/tells called magoules were established from the Early Neolithic period until the Bronze Age (6,000 – 3,000 BC. Multi-sensor remote sensing was applied to the study area in order to evaluate its potential to detect Neolithic settlements. Hundreds of sites were geo-referenced through systematic GPS surveying throughout the region. Data from four primary sensors were used, namely Landsat ETM, ASTER, EO1 - HYPERION and IKONOS. A range of image processing techniques were originally applied to the hyperspectral imagery in order to detect the settlements and validate the results of GPS surveying. Although specific difficulties were encountered in the automatic classification of archaeological features composed by a similar parent material with the surrounding landscape, the results of the research suggested a different response of each sensor to the detection of the Neolithic settlements, according to their spectral and spatial resolution.

  17. Impact of Atmospheric Attenuations Time Resolutions in Solar Radiation Derived from Satellite Imagery

    Science.gov (United States)

    Cony, Marco; Liria, Juan; Weisenberg, Ralf; Serrano, Enrique

    2014-05-01

    Accurate knowledge of solar irradiance components at the earth surface is of highly interest in many scientific and technology branches concerning meteorology, climate, agriculture and solar energy applications. In the specific case of solar energy systems the solar resource analysis with accuracy is a first step in every project since it is a required data for design, power output estimations, systems simulations and risk assessments. Solar radiation measurement availability is increasing both in spatial density and in historical archiving. However, it is still quite limited and most of the situations cannot make use of a long term ground database of high quality since solar irradiance is not generally measured where users need data. Satellite-derived solar radiation estimations are a powerful and valuable tool for solar resource assessment studies that have achieved a relatively high maturity due to years of developments and improvements. However, several sources of uncertainty are still present in satellite-derived methods. In particular, the strong influence of atmospheric attenuation information as input to the method is one of the main topics of improvement. Since solar radiation attenuation by atmospheric aerosols, and water vapor in a second place, is, after clouds, the second most important factor determining solar radiation, and particularly direct normal irradiance, the accurate knowledge of aerosol optical depth and water vapor content is relevant in the final output of satellite-derived methods. This present work, two different datasets we are used for extract atmospheric attenuation information. On the one hand the monthly mean values of the Linke turbidity factor from Meteotest database, which are twelve unique values of the Linke turbidity worldwide with a spatial resolution of 1/12º. On the other hand, daily values of AOD (Aerosol Optical Depth) at 550 nm, Angstrom alpha exponent and water vapor column were taken from a gridded database that

  18. Satellite geological and geophysical remote sensing of Iceland: Preliminary results of geologic, hydrologic, oceanographic, and agricultural studies with ERTS-1 imagery

    Science.gov (United States)

    Williams, R. S., Jr. (Principal Investigator); Boeovarsson, A.; Frioriksson, S.; Palmason, G.; Rist, S.; Sigtryggsson, H.; Saemundsson, K.; Thorarinsson, S.; Thorsteinsson, I.

    1973-01-01

    The author has identified the following significant results. The wide variety of geological and geophysical phenomena which can be observed in Iceland, and particularly their very direct relation to the management of the country's natural resources, has provided great impetus to the use of ERTS-1 imagery to measure and map the dynamic natural phenomena in Iceland. MSS imagery is being used to study a large variety of geological and geophysical eruptive products, geologic structure, volcanic geomorphology, hydrologic, oceanographic, and agricultural phenomena of Iceland. Some of the preliminary results from this research projects are: (1) a large number of geological and volcanic features can be studied from ERTS-1 imagery, particularly imagery acquired at low sun angle, which had not previously been recognized; (2) under optimum conditions the ERTS-1 satellite can discern geothermal areas by their snow melt pattern or warm spring discharge into frozen lakes; (3) various maps at scales of 1:1 million and 1:500,000 can be updated and made more accurate with ERTS-1 imagery; (4) the correlation of water reserves with snowcover can improve the basis for planning electrical production in the management of water resources; (5) false-color composites (MSS) permitted the mapping of four types of vegetation: forested; grasslands, reclaimed, and cultivated areas, and the seasonal change of the vegetation, all of high value to rangeland management.

  19. Monitoring powdery mildew of winter wheat by using moderate resolution multi-temporal satellite imagery.

    Directory of Open Access Journals (Sweden)

    Jingcheng Zhang

    Full Text Available Powdery mildew is one of the most serious diseases that have a significant impact on the production of winter wheat. As an effective alternative to traditional sampling methods, remote sensing can be a useful tool in disease detection. This study attempted to use multi-temporal moderate resolution satellite-based data of surface reflectances in blue (B, green (G, red (R and near infrared (NIR bands from HJ-CCD (CCD sensor on Huanjing satellite to monitor disease at a regional scale. In a suburban area in Beijing, China, an extensive field campaign for disease intensity survey was conducted at key growth stages of winter wheat in 2010. Meanwhile, corresponding time series of HJ-CCD images were acquired over the study area. In this study, a number of single-stage and multi-stage spectral features, which were sensitive to powdery mildew, were selected by using an independent t-test. With the selected spectral features, four advanced methods: mahalanobis distance, maximum likelihood classifier, partial least square regression and mixture tuned matched filtering were tested and evaluated for their performances in disease mapping. The experimental results showed that all four algorithms could generate disease maps with a generally correct distribution pattern of powdery mildew at the grain filling stage (Zadoks 72. However, by comparing these disease maps with ground survey data (validation samples, all of the four algorithms also produced a variable degree of error in estimating the disease occurrence and severity. Further, we found that the integration of MTMF and PLSR algorithms could result in a significant accuracy improvement of identifying and determining the disease intensity (overall accuracy of 72% increased to 78% and kappa coefficient of 0.49 increased to 0.59. The experimental results also demonstrated that the multi-temporal satellite images have a great potential in crop diseases mapping at a regional scale.

  20. Application of LANDSAT satellite imagery for iron ore prospecting in the Western Desert of Egypt

    Science.gov (United States)

    Elshazly, E. M.; Abdelhady, M. A.; Elghawaby, M. A.; Khawasik, S. M.

    1977-01-01

    Prospecting for iron ore occurrences was conducted by the Remote Sensing Center in Bahariya Oasis-El Faiyum area covering some 100,000 km squared in the Western Desert of Egypt. LANDSAT-1 satellite images were utilized as the main tool in the regional prospecting of the iron ores. The delineation of the geological units and geological structure through the interpretation of the images corroborated by field observations and structural analysis led to the discovery of new iron ore occurrences in the area of investigation.

  1. Determination of Land Use from Satellite Imagery for Input to Hydrologic Models.

    Science.gov (United States)

    1980-04-01

    Symposium on Remote Sensing of thieK Environment, 23-30 April 1980, San Jose, Costa Rica 19. KEY WORDS - C=Wm*. eO I.W. EII..e.wvm I*FS Week atfm...Fourteenth International Symposium on Remote Sensing of the Environment, 23-30 April 1980, San Jose, Costa Rica DETERMINATION OF LAND USE FROM SATELLITE...Factors in Small Hydropower Planning, Darryl W. Davis, February 1979, 38 pages. #62 Flood Hydrograph and Peak Flow Frequency Analysis, Arlen D. Feldman

  2. REFLECTIONS ON THE USO OF SATELLITE IMAGERY FOR THE TEACHING-LEARNING OF URBAN GEOGRAPHY CONTENTS IN FORTALEZA/CEARÁ

    Directory of Open Access Journals (Sweden)

    Rosilene Aires

    2016-06-01

    Full Text Available This paper exposes a didactic experience realized in 2012 with 80 students of the daytime secondary education from school E.E.F.M Senador Osires Pontes in Fortaleza - Ceará. This experience demonstrated how the school use of satellite imagery can aid in the geography teaching. The methodology was based on study and analysis of satellite images of urban areas, making drawings and application of questionnaires by students in the neighborhood. After that, discussed about the cognitive responses of students from didactic resources and teaching method chosen to approach of the contents. This practice improved learning of all students about its reality. Este artigo expõe uma experiência pedagógica realizada em 2012 com 80 alunos do 2o ano do Ensino Médio diurno da Escola de Ensino Fundamental e Médio Senador Osires Pontes em Fortaleza- Ceará. Esta vivência demonstrou como o uso pedagógico de imagens pode auxiliar no ensino de conteúdos geográficos. A metodologia baseou-se em estudo e análise de imagens de satélite de áreas urbanas, confecção e interpretação de croquis e elaboração e aplicação de questionários pelos estudantes no bairro. Em seguida, dialogou-se sobre as respostas do público-alvo, diante dos recursos didáticos e do método de ensino escolhido na abordagem dos conteúdos. Esta prática melhorou a aprendizagem dos participantes sobre sua realidade.

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

    Directory of Open Access Journals (Sweden)

    Timothy Shields

    2016-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Panu Srestasathiern

    2014-10-01

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

  5. Mapping species distribution of Canarian Monteverde forest by field spectroradiometry and satellite imagery

    Science.gov (United States)

    Martín-Luis, Antonio; Arbelo, Manuel; Hernández-Leal, Pedro; Arbelo-Bayó, Manuel

    2016-10-01

    Reliable and updated maps of vegetation in protected natural areas are essential for a proper management and conservation. Remote sensing is a valid tool for this purpose. In this study, a methodology based on a WorldView-2 (WV-2) satellite image and in situ spectral signatures measurements was applied to map the Canarian Monteverde ecosystem located in the north of the Tenerife Island (Canary Islands, Spain). Due to the high spectral similarity of vegetation species in the study zone, a Multiple Endmember Spectral Mixture Analysis (MESMA) was performed. MESMA determines the fractional cover of different components within one pixel and it allows for a pixel-by-pixel variation of endmembers. Two libraries of endmembers were collected for the most abundant species in the test area. The first library was collected from in situ spectral signatures measured with an ASD spectroradiometer during a field campaign in June 2015. The second library was obtained from pure pixels identified in the satellite image for the same species. The accuracy of the mapping process was assessed from a set of independent validation plots. The overall accuracy for the ASD-based method was 60.51 % compared to the 86.67 % reached for the WV-2 based mapping. The results suggest the possibility of using WV-2 images for monitoring and regularly updating the maps of the Monteverde forest on the island of Tenerife.

  6. Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China

    Science.gov (United States)

    Wang, Wen; Cheng, Hui; Zhang, Li

    2012-04-01

    All countries around the world and many international bodies, including the United Nations Development Program (UNDP), United Nations Food and Agricultural Organization (FAO), the International Fund for Agricultural Development (IFAD) and the International Labor Organization (ILO), have to eliminate rural poverty. Estimation of regional poverty level is a key issue for making strategies to eradicate poverty. Most of previous studies on regional poverty evaluations are based on statistics collected typically in administrative units. This paper has discussed the deficiencies of traditional studies, and attempted to research regional poverty evaluation issues using 3-year DMSP/OLS night-time light satellite imagery. In this study, we adopted 17 socio-economic indexes to establish an integrated poverty index (IPI) using principal component analysis (PCA), which was proven to provide a good descriptor of poverty levels in 31 regions at a provincial scale in China. We also explored the relationship between DMSP/OLS night-time average light index and the poverty index using regression analysis in SPSS and a good positive linear correlation was modelled, with R2 equal to 0.854. We then looked at provincial poverty problems in China based on this correlation. The research results indicated that the DMSP/OLS night-time light data can assist analysing provincial poverty evaluation issues.

  7. Atmospheric Correction of Satellite GF-1/WFV Imagery and Quantitative Estimation of Suspended Particulate Matter in the Yangtze Estuary

    Directory of Open Access Journals (Sweden)

    Pei Shang

    2016-11-01

    Full Text Available The Multispectral Wide Field of View (WFV camera on the Chinese GF-1 satellite, launched in 2013, has advantages of high spatial resolution (16 m, short revisit period (4 days and wide scene swath (800 km compared to the Landsat-8/OLI, which make it an ideal means of monitoring spatial-temporal changes of Suspended Particulate Matter (SPM in large estuaries like the Yangtze Estuary. However, a lack of proper atmospheric correction methods has limited its application in water quality assessment. We propose an atmospheric correction method based on a look up table coupled by the atmosphere radiative transfer model (6S and the water semi-empirical radiative transfer (SERT model for inversion of water-leaving reflectance from GF-1 top-of-atmosphere radiance, and then retrieving SPM concentration from water-leaving radiance reflectance of the Yangtze Estuary and its adjacent sea. Results are validated by the Landsat-8/OLI imagery together with autonomous fixed station data, and influences of human activities (e.g., waterway construction and shipping on SPM distribution are analyzed.

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

    Science.gov (United States)

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

    2017-05-01

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

  9. ANALYSIS OF AMBIENT FIELDS AND SATELLITE IMAGERY CHARACTERISTICS OF EFFECT OF BAY OF BENGAL STORMS ON LOW-LATITUDE PLATEAU

    Institute of Scientific and Technical Information of China (English)

    XU Mei-ling; ZHANG Xiu-nian; YANG Su-yu

    2007-01-01

    Based on the composite analysis method, 12 rainstorms triggered by Bay of Bengal storms(shortened as B-storms hereafter) across the whole province of Yunnan were studied, and some interesting results of rain and circulation characteristics influenced by the storms were obtained for low-latitude plateau.Usually, when a rainstorm weather occurs in low-latitude plateau, the B-storm center locates in the central,east or north parts of the Bay of Bengal. At the same time, the subtropical high ridge moves to 15°N - 20°Nand the west ridge point moves to the Indo-china Peninsula from the South China Sea and the low-latitude plateau is controlled by southwest air streams coming from the front of the trough and the periphery of the subtropical high. The southwest low-level jet stream from the east side of the bay storm has great effect on heavy rains. On the one hand, the southwest low-level jet stream is playing the role of transporting water vapor and energy. On the other hand, the southwest low-level jet stream is helpful to keep essential dynamical condition. From the analysis of the satellite cloud imagery, it is found that mesoscale convection cloud clusters will keep growing and moving into the low-latitude plateau to cause heavy rains when a storm forms in the Bay of Bengal.

  10. Atmospheric Correction of Satellite GF-1/WFV Imagery and Quantitative Estimation of Suspended Particulate Matter in the Yangtze Estuary.

    Science.gov (United States)

    Shang, Pei; Shen, Fang

    2016-11-25

    The Multispectral Wide Field of View (WFV) camera on the Chinese GF-1 satellite, launched in 2013, has advantages of high spatial resolution (16 m), short revisit period (4 days) and wide scene swath (800 km) compared to the Landsat-8/OLI, which make it an ideal means of monitoring spatial-temporal changes of Suspended Particulate Matter (SPM) in large estuaries like the Yangtze Estuary. However, a lack of proper atmospheric correction methods has limited its application in water quality assessment. We propose an atmospheric correction method based on a look up table coupled by the atmosphere radiative transfer model (6S) and the water semi-empirical radiative transfer (SERT) model for inversion of water-leaving reflectance from GF-1 top-of-atmosphere radiance, and then retrieving SPM concentration from water-leaving radiance reflectance of the Yangtze Estuary and its adjacent sea. Results are validated by the Landsat-8/OLI imagery together with autonomous fixed station data, and influences of human activities (e.g., waterway construction and shipping) on SPM distribution are analyzed.

  11. Mapping seagrass and colonized hard bottom in Springs Coast, Florida using WorldView-2 satellite imagery

    Science.gov (United States)

    Baumstark, René; Duffey, Renee; Pu, Ruiliang

    2016-11-01

    The offshore extent of seagrass habitat along the West Florida (USA) coast represents an important corridor for inshore-offshore migration of economically important fish and shellfish. Surviving at the fringe of light requirements, offshore seagrass beds are sensitive to changes in water clarity. Beyond and intermingled with the offshore seagrass areas are large swaths of colonized hard bottom. These offshore habitats of the West Florida coast have lacked mapping efforts needed for status and trends monitoring. The objective of this study was to propose an object-based classification method for mapping offshore habitats and to compare results to traditional photo-interpreted maps. Benthic maps were created from WorldView-2 satellite imagery using an Object Based Image Analysis (OBIA) method and a visual photo-interpretation method. A logistic regression analysis identified depth and distance from shore as significant parameters for discriminating spectrally similar seagrass and colonized hard bottom features. Seagrass, colonized hard bottom and unconsolidated sediment (sand) were mapped with 78% overall accuracy using the OBIA method compared to 71% overall accuracy using the photo-interpretation method. This study suggests an alternative for mapping deeper, offshore habitats capable of producing higher thematic and spatial resolution maps compared to those created with the traditional photo-interpretation method.

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

    Science.gov (United States)

    Kim, J. W.; Lu, Z.

    2016-12-01

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

  13. Fine-scale features on the sea surface in SAR satellite imagery – Part 1: Simultaneous in-situ measurements

    Directory of Open Access Journals (Sweden)

    S. Brusch

    2012-09-01

    Full Text Available This work is aimed at identifying the origin of fine-scale features on the sea surface in synthetic aperture radar (SAR imagery with the help of in-situ measurements as well as numerical models (presented in a companion paper. We are interested in natural and artificial features starting from the horizontal scale of the upper ocean mixed layer, around 30–50 m. These features are often associated with three-dimensional upper ocean dynamics. We have conducted a number of studies involving in-situ observations in the Straits of Florida during SAR satellite overpass. The data include examples of sharp frontal interfaces, wakes of surface ships, internal wave signatures, as well as slicks of artificial and natural origin. Atmospheric processes, such as squall lines and rain cells, produced prominent signatures on the sea surface. This data has allowed us to test an approach for distinguishing between natural and artificial features and atmospheric influences in SAR images that is based on a co-polarized phase difference filter.

  14. Estimating trends of urban residential irrigation extent and rate using satellite imagery in the city of Los Angeles, CA

    Science.gov (United States)

    Chen, Y. J.; McFadden, J. P.; Clarke, K. C.; Roberts, D. A.

    2015-12-01

    Urban residential irrigation is a large component of urban water budgets in Mediterranean climate cities, and plays a significant role for managing landscape vegetation and water resources. This is particularly occurring at cities such as Los Angeles, where water availability is limited during dry summers. This study applied 10-m SPOT 5 satellite imagery and a database of monthly water use records for residential water customers in Los Angeles in order to examine the interactions between vegetation water demand and residential water consumption. Here, we identify the spatial distribution of vegetation greenness and the extent of irrigation rates through water year 2005-2007, including normal, dry, and wet extremes of annual rainfall. Additionally, the water conservation ratio, which is between rates of irrigation and vegetation water demand, is used to assess over-irrigation. Although residential outdoor water usage was found as highest in the dry year, landscape vegetation under water stress that cannot maintain greenness condition as well as in wetter years. However, the decreasing trend of over-irrigation occurred from wet to drier years, since vegetation water demand increased significantly but irrigation rates changed little, implying over-irrigation in urbanized areas. This over watering issue can be implemented by water resource management, and urban planning, especially in current severe California drought.

  15. Mapping invasive Phragmites australis in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support

    Science.gov (United States)

    Bourgeau-Chavez, Laura L.; Kowalski, Kurt P.; Carlson Mazur, Martha L.; Scarbrough, Kirk A.; Powell, Richard B.; Brooks, Colin N.; Huberty, Brian; Jenkins, Liza K.; Banda, Elizabeth C.; Galbraith, David M.; Laubach, Zachary M.; Riordan, Kevin

    2013-01-01

    The invasive variety of Phragmites australis (common reed) forms dense stands that can cause negative impacts on coastal Great Lakes wetlands including habitat degradation and reduced biological diversity. Early treatment is key to controlling Phragmites, therefore a map of the current distribution is needed. ALOS PALSAR imagery was used to produce the first basin-wide distribution map showing the extent of large, dense invasive Phragmites-dominated habitats in wetlands and other coastal ecosystems along the U.S. shore of the Great Lakes. PALSAR is a satellite imaging radar sensor that is sensitive to differences in plant biomass and inundation patterns, allowing for the detection and delineation of these tall (up to 5 m), high density, high biomass invasive Phragmites stands. Classification was based on multi-season ALOS PALSAR L-band (23 cm wavelength) HH and HV polarization data. Seasonal (spring, summer, and fall) datasets were used to improve discrimination of Phragmites by taking advantage of phenological changes in vegetation and inundation patterns over the seasons. Extensive field collections of training and randomly selected validation data were conducted in 2010–2011 to aid in mapping and for accuracy assessments. Overall basin-wide map accuracy was 87%, with 86% producer's accuracy and 43% user's accuracy for invasive Phragmites. The invasive Phragmites maps are being used to identify major environmental drivers of this invader's distribution, to assess areas vulnerable to new invasion, and to provide information to regional stakeholders through a decision support tool.

  16. Assessing the Spatial Variability of Alfalfa Yield Using Satellite Imagery and Ground-Based Data

    Science.gov (United States)

    Kayad, Ahmed G.; Al-Gaadi, Khalid A.; Tola, ElKamil; Madugundu, Rangaswamy; Zeyada, Ahmed M.; Kalaitzidis, Chariton

    2016-01-01

    Understanding the temporal and spatial variability in a crop yield is viewed as one of the key steps in the implementation of precision agriculture practices. Therefore, a study on a center pivot irrigated 23.5 ha field in Saudi Arabia was conducted to assess the variability in alfalfa yield using Landsat-8 imagery and a hay yield monitor data. In addition, the study was designed to also explore the potential of predicting the alfalfa yield using vegetation indices. A calibrated yield monitor mounted on a large rectangular hay baler was used to measure the actual alfalfa yield for four alfalfa harvests performed in the period from October 2013 to May 2014. A total of 18 Landsat-8 images, representing different crop growth stages, were used to derive different vegetation indices (VIs). Data from the yield monitor was used to generate yield maps, which illustrated a definite spatial variation in alfalfa yield across the experimental field for the four studied harvests as indicated by the high spatial correlation values (0.75 to 0.97) and the low P-values (4.7E-103 to 8.9E-27). The yield monitor-measured alfalfa actual yield was compared to the predicted yield form the Vis. Results of the study showed that there was a correlation between actual and predicted yield. The highest correlations were observed between actual yield and the predicted using NIR reflectance, SAVI and NDVI with maximum correlation coefficients of 0.69, 0.68 and 0.63, respectively. PMID:27281189

  17. Mapping Aquatic Vegetation in a Tropical Wetland Using High Spatial Resolution Multispectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Timothy G. Whiteside

    2015-09-01

    Full Text Available Vegetation plays a key role in the environmental function of wetlands. The Ramsar-listed wetlands of the Magela Creek floodplain in Northern Australia are identified as being at risk from weeds, fire and climate change. In addition, the floodplain is a downstream receiving environment for the Ranger Uranium Mine. Accurate methods for mapping wetland vegetation are required to provide contemporary baselines of annual vegetation dynamics on the floodplain to assist with analysing any potential change during and after minesite rehabilitation. The aim of this study was to develop and test the applicability of geographic object-based image analysis including decision tree classification to classify WorldView-2 imagery and LiDAR-derived ancillary data to map the aquatic vegetation communities of the Magela Creek floodplain. Results of the decision tree classification were compared against a Random Forests classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010. The decision tree classification method provided an overall accuracy of 78% which was significantly higher than the overall accuracy of the Random Forests classification (67%. Most of the error in both classifications was associated with confusion between spectrally similar classes dominated by grasses, such as Hymenachne and Pseudoraphis. In addition, the extent of the sedge Eleocharis was under-estimated in both cases. This suggests the method could be useful for mapping wetlands where statistical-based supervised classifications have achieved less than satisfactory results. Based upon the results, the decision tree method will form part of an ongoing operational monitoring program.

  18. Verification of sectoral cloud motion based direct normal irradiance nowcasting from satellite imagery

    Science.gov (United States)

    Schroedter-Homscheidt, Marion; Gesell, Gerhard

    2016-05-01

    The successful integration of solar electricity from photovoltaics or concentrating solar power plants into the existing electricity supply requires an electricity production forecast for 48 hours, while any improved surface irradiance forecast over the next upcoming hours is relevant for an optimized operation of the power plant. While numerical weather prediction has been widely assessed and is in commercial use, the short-term nowcasting is still a major field of development. European Commission's FP7 DNICast project is especially focusing on this task and this paper reports about parts of DNICast results. A nowcasting scheme based on Meteosat Second Generation cloud imagery and cloud movement tracking has been developed for Southern Spain as part of a solar production forecasting tool (CSP-FoSyS). It avoids the well-known, but not really satisfying standard cloud motion vector approach by using a sectoral approach and asking the question at which time any cloud structure will affect the power plant. It distinguishes between thin cirrus clouds and other clouds, which typically occur in different heights in the atmosphere and move in different directions. Also, their optical properties are very different - especially for the calculation of direct normal irradiances as required by concentrating solar power plants. Results for Southern Spain show a positive impact of up to 8 hours depending of the time of the day and a RMSD reduction of up to 10% in hourly DNI irradiation compared to day ahead forecasts. This paper presents the verification of this scheme at other locations in Europe and Northern Africa (BSRN and EnerMENA stations) with different cloud conditions. Especially for Jordan and Tunisia as the most relevant countries for CSP in this station list, we also find a positive impact of up to 8 hours.

  19. Program on application of communications satellites to educational development: Design of a 12 channel FM microwave receiver. [color television from communication satellites

    Science.gov (United States)

    Risch, C. O.; Rosenbaum, F. J.; Gregory, R. O.

    1974-01-01

    The design, fabrication, and performance of elements of a low cost FM microwave satellite ground station receiver is described. It is capable of accepting 12 contiguous color television equivalent bandwidth channels in the 11.72 to 12.2 GHz band. Each channel is 40 MHz wide and incorporates a 4 MHz guard band. The modulation format is wideband FM and the channels are frequency division multiplexed. Twelve independent CATV compatible baseband outputs are provided. The overall system specifications are first discussed, then consideration is given to the receiver subsystems and the signal branching network.

  20. Rectification of single and multiple frames of satellite scanner imagery using points and edges as control

    Science.gov (United States)

    Paderes, F. C., Jr.; Mikhail, E. M.; Foerstner, W.

    1984-01-01

    Rectification of single and overlapping multiple scanner frames produced by such satellite-borne scanners as the LANDSAT MSS was carried out using a newly developed comprehensive parametric model. Tests with both simulated and real image data demonstrate conclusively that this model in general is superior to the widely used polynomial model, and that the simultaneous rectification of overlapping frames using least squares techniques yields a high accuracy than sngle frame rectification due to the inclusion of tie points between the image frames. Used to control, edges or lines, whic are much more likely to be found in images, can replace conventional control points and can easily be implemented into the least squares approach. An efficient algorithm for findng corresponding points in image paris was developed which can be used for determining tie points between image frames and thus increase the ecnomy of the whole rectification procedure.

  1. Subpixel Accuracy Analysis of Phase Correlation Shift Measurement Methods Applied to Satellite Imagery

    Directory of Open Access Journals (Sweden)

    S.M. Badwai

    2013-01-01

    Full Text Available the key point of super resolution process is the accurate measuring of sub-pixel shift. Any tiny error in measuring such shift leads to an incorrect image focusing. In this paper, methodology of measuring sub-pixel shift using Phase correlation (PC are evaluated using different window functions, then modified version of (PC method using high pass filter (HPF is introduced . Comprehensive analysis and assessment of (PC methods shows that different natural features yield different shift measurements. It is concluded that there is no universal window function for measuring shift; it mainly depends on the features in the satellite images. Even the question of which window is optimal of particular feature is generally remains open. This paper presents the design of a method for obtaining high accuracy sub pixel shift phase correlation using (HPF.The proposed method makes the change in the different locations that lack of edges easy.

  2. Dynamics modeling for sugar cane sucrose estimation using time series satellite imagery

    Science.gov (United States)

    Zhao, Yu; Justina, Diego Della; Kazama, Yoriko; Rocha, Jansle Vieira; Graziano, Paulo Sergio; Lamparelli, Rubens Augusto Camargo

    2016-10-01

    Sugarcane, as one of the most mainstay crop in Brazil, plays an essential role in ethanol production. To monitor sugarcane crop growth and predict sugarcane sucrose content, remote sensing technology plays an essential role while accurate and timely crop growth information is significant, in particularly for large scale farming. We focused on the issues of sugarcane sucrose content estimation using time-series satellite image. Firstly, we calculated the spectral features and vegetation indices to make them be correspondence to the sucrose accumulation biological mechanism. Secondly, we improved the statistical regression model considering more other factors. The evaluation was performed and we got precision of 90% which is about 20% higher than the conventional method. The validation results showed that prediction accuracy using our sugarcane growth modeling and improved mix model is satisfied.

  3. A new method to determine eroded areas in arid environment using Landsat satellite imagery

    Science.gov (United States)

    A, Aydda; Ah, Algouti; Ab, Algouti; M, Essemani; Y, Taghya

    2014-06-01

    Erosion (by water or wind) is an increasing problem for many local authorities and government agencies throughout the world. The identification of eroded areas in arid and humid regions can be very useful for environmental planning and can help reduce soil and sediment degradation in these regions. In this work we present a new method to determine eroded areas in arid environment. In this method were explored lithological data to determine eroded areas. These data were collected in the field using GPS (Global Positioning System) checkpoints and geological maps. For that, two lithological maps of the study areas were analysed to determine lithological data change. Those two maps were obtained from the classification algorithm by applying the maximum likelihood on two Landsat satellite images. After images classification and validation a change detection technique was adopted to determine eroded areas. This method was applied in northern part of Atlantic Sahara desert to confirm their potentiality.

  4. LAND USE LAND COVER DYNAMICS OF NILGIRIS DISTRICT, INDIA INFERRED FROM SATELLITE IMAGERIES

    Directory of Open Access Journals (Sweden)

    P. Nalina

    2014-01-01

    Full Text Available Land use Land cover changes are critical components in managing natural resources especially in hilly region as they trigger the erosion of soil and thus making the zone highly vulnerable to landslides. The Nilgiris district of Tamilnadu state in India is the first biosphere in Western Ghats region with rare species of flora and fauna and often suffered by frequent landslides. Therefore in this present study land use land cover dynamics of Nilgiri district has been studied from 1990 to 2010 using Satellite Remote Sensing Technique. The temporal changes of land use and land cover changes of Nilgiris district over the period of 1990 to 2010 were monitored using LISS I and LISS III of IRS 1A and IRS-P6 satellites. Land use dynamics were identified using Maximum likelihood classification under supervised classification technique. From the remote sensing study, it is found that during the study period of 1990 to 2010, area of dense forest increased by 27.17%, forest plantation area decreased by 54.64%. Conversion of forest plantation, Range land and open forest by agriculture and settlement leading to soil erosion and landslides. Tea plantation increased by 33.95% and agricultural area for plantation of vegetables increased rapidly to 217.56% in the mountain steep area. The accuracy of classification has been assessed by forming confusion matrix and evaluating kappa coefficient. The overall accuracy has been obtained as 83.7 and 89.48% for the years 1990 and 2010 respectively. The kappa coefficients were reported as 0.80 and 0.88 respectively for the years 1990 and 2010.

  5. Automatic geolocation of targets tracked by aerial imaging platforms using satellite imagery

    Science.gov (United States)

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

    2014-11-01

    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.

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Directory of Open Access Journals (Sweden)

    H. Rastiveis

    2015-12-01

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

  8. Mapping plant functional type distributions in Arctic ecosystems using WorldView-2 satellite imagery and unsupervised clustering

    Science.gov (United States)

    Langford, Z.; Kumar, J.; Hoffman, F. M.; Sloan, V. L.; Norby, R. J.; Wullschleger, S. D.

    2014-12-01

    The Arctic has emerged as an important focal point for the study of climate change. Arctic vegetation is particularly sensitive to warming conditions and likely to exhibit shifts in species composition, phenology and productivity under changing climate. Modeling of Arctic tundra vegetation requires representation of the heterogeneous tundra landscape, which includes representation of individual plant functional types (PFT). Vegetation exhibits unique spectral characteristics that can be harnessed to discriminate plant types and develop quantitative vegetation indices, such as the Normalized Difference Vegetation Index. We have combined high resolution multi-spectral remote sensing from the WorldView-2 satellite with LiDAR-derived digital elevation models to characterize the tundra landscape in four 100m X 100m sites within the Barrow Environmental Observatory, a 3021 hectare research reserve located at the northern most location on the Alaskan Arctic Coastal Plain. Classification of landscape PFT's using spectral and topographic characteristics yields spatial regions with expectedly similar vegetation characteristics. A field campaign was conducted during peak growing season (June - August) to collect vegetation surveys from a number of 1m x 1m plots in the study region, which were then analyzed for distribution of vegetation types in the plots. Statistical relationships were developed between spectral and topographic characteristics and vegetation type distributions at the vegetation plots. These derived relationships were employed to statistically upscale the vegetation distributions for the landscape based on spectral characteristics. We will describe two versions of PFT upscaling from WorldView-2 imagery: 1) a version computed from multiple imagery through the growing season and 2) a version computed from a single image in the middle of the growing season. This approach allowed us to test the degree to which including phenology helps predict PFT distribution

  9. Object-based approach to national land cover mapping using HJ satellite imagery

    Science.gov (United States)

    Zhang, Lei; Li, Xiaosong; Yuan, Quanzhi; Liu, Yu

    2014-01-01

    To meet the carbon storage estimate in ecosystems for a national carbon strategy, we introduce a consistent database of China land cover. The Chinese Huan Jing (HJ) satellite is proven efficient in the cloud-free acquisition of seasonal image series in a monsoon region and in vegetation identification for mesoscale land cover mapping. Thirty-eight classes of level II land cover are generated based on the Land Cover Classification System of the United Nations Food and Agriculture Organization that follows a standard and quantitative definition. Twenty-four layers of derivative spectral, environmental, and spatial features compose the classification database. Object-based approach characterizing additional nonspectral features is conducted through mapping, and multiscale segmentations are applied on object boundary match to target real-world conditions. This method sufficiently employs spatial information, in addition to spectral characteristics, to improve classification accuracy. The algorithm of hierarchical classification is employed to follow step-by-step procedures that effectively control classification quality. This algorithm divides the dual structures of universal and local trees. Consistent universal trees suitable to most regions are performed first, followed by local trees that depend on specific features of nine climate stratifications. The independent validation indicates the overall accuracy reaches 86%.

  10. Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

    Directory of Open Access Journals (Sweden)

    Jochen Zschau

    2012-05-01

    Full Text Available Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types. At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free- and open-source basis and aim at being transparent, usable and transferable.

  11. Estimating the global surface area of rivers and streams using satellite imagery

    Science.gov (United States)

    Allen, George; Pavelsky, Tamlin

    2017-04-01

    Global observational assessments of river and stream systems are based largely on gauge station data, which are fragmented and often limited to country-level statistics. This limitation severely impedes our understanding of global-scale hydrologic, geomorphic, and biogeochemical fluvial processes. In contrast, satellite remote sensing data provide a globally-consistent and spatially-continuous tool for studying rivers. Here we present a novel method estimate the total surface area of all rivers and stream globally using measurements from the recently-developed Global River Widths from Landsat (GRWL) database and field surveys. The surface area of rivers and streams is a key model parameter in global evaluations of greenhouse gas emissions from inland waters. Preliminary analysis suggests that rivers occupy a total area of 80 thousand square kilometers, or 0.58% of Earth's land surface. This result is 30% greater than the previous best estimate that is based on digital elevation models and gauge station measurements. Compared to previous regional assessments, we find that rivers and streams occupy a greater proportion of the land surface in the arctic and in the tropics, and a lower proportion of land surface in the United States and in Europe. Our results suggest that current estimates of greenhouse gas emissions from inland waters should be revised upwards to account for the greater abundance of river and stream surface area.

  12. Monitoring agricultural crop growth: comparison of high spatial-temporal satellite imagery versus UAV-based imaging spectrometer time series measurements

    Science.gov (United States)

    Mucher, Sander; Roerink, Gerbert; Franke, Jappe; Suomalainen, Juha; Kooistra, Lammert

    2014-05-01

    In 2012, the Dutch National Satellite Data Portal (NSD) was launched as a preparation to the launch of the European SENTINEL satellites in the framework of the Copernicus Programme. At the same time the Unmanned Aerial Remote Sensing Facility (UARSF: www.wageningenUR.nl/uarsf) has been established as research facility at Wageningen University and Research Centre. The NSD became available for the development of services and advice through an investment from the Dutch government in collaboration with the Netherlands Space Office (NSO) in order to develop new services for precision agriculture. The NSD contains Formosat, Radarsat as well as DMC satellite imagery. The processing of the DMC imagery resulted in the Greenmonitor service (www.groenmonitor.nl). The Greenmonitor is an unique product that covers the Netherlands with a high spatial and temporal resolution. The Greenmonitor is now being exploited for various applications, amongst others crop identification, crop phenology, and identification of management activities. The UARSF of Wageningen UR has three objectives: 1) to develop innovation in the field of remote sensing science using Unmanned Aerial Vehicles (UAV) by providing a platform for dedicated and high-quality experiments; 2) to support high quality UAV services by providing calibration facilities and disseminating processing procedures to the UAV user community; 3) to promote and test the use of UAV in a broad range of application fields such as precision agriculture and habitat monitoring. Through this coincidence of new developments the goal of our study was to compare the information for the measurements of spatial variation in crops and soils as derived from high spatial-temporal satellite imagery from the national data portal compared to the exploitation of UAVs, in our case an Altura octocopter with a hyperspectral camera. As such, the focus is on the applications in precision agriculture. Both primary producers and chain partners and service

  13. Drought resistance across California ecosystems: Evaluating changes in carbon dynamics using satellite imagery

    Science.gov (United States)

    Malone, Sparkle; Tulbure, Mirela; Pérez-Luque, Antonio J.; Assal, Timothy J.; Bremer, Leah; Drucker, Debora; Hillis, Vicken; Varela, Sara; Goulden, Michael

    2016-01-01

    Drought is a global issue that is exacerbated by climate change and increasing anthropogenic water demands. The recent occurrence of drought in California provides an important opportunity to examine drought response across ecosystem classes (forests, shrublands, grasslands, and wetlands), which is essential to understand how climate influences ecosystem structure and function. We quantified ecosystem resistance to drought by comparing changes in satellite-derived estimates of water-use efficiency (WUE = net primary productivity [NPP]/evapotranspiration [ET]) under normal (i.e., baseline) and drought conditions (ΔWUE = WUE2014 − baseline WUE). With this method, areas with increasing WUE under drought conditions are considered more resilient than systems with declining WUE. Baseline WUE varied across California (0.08 to 3.85 g C/mm H2O) and WUE generally increased under severe drought conditions in 2014. Strong correlations between ΔWUE, precipitation, and leaf area index (LAI) indicate that ecosystems with a lower average LAI (i.e., grasslands) also had greater C-uptake rates when water was limiting and higher rates of carbon-uptake efficiency (CUE = NPP/LAI) under drought conditions. We also found that systems with a baseline WUE ≤ 0.4 exhibited a decline in WUE under drought conditions, suggesting that a baseline WUE ≤ 0.4 might be indicative of low drought resistance. Drought severity, precipitation, and WUE were identified as important drivers of shifts in ecosystem classes over the study period. These findings have important implications for understanding climate change effects on primary productivity and C sequestration across ecosystems and how this may influence ecosystem resistance in the future.

  14. Online Access to Weather Satellite Imagery Through the World Wide Web

    Science.gov (United States)

    Emery, W.; Baldwin, D.

    1998-01-01

    Both global area coverage (GAC) and high-resolution picture transmission (HRTP) data from the Advanced Very High Resolution Radiometer (AVHRR) are made available to laternet users through an online data access system. Older GOES-7 data am also available. Created as a "testbed" data system for NASA's future Earth Observing System Data and Information System (EOSDIS), this testbed provides an opportunity to test both the technical requirements of an onune'd;ta system and the different ways in which the -general user, community would employ such a system. Initiated in December 1991, the basic data system experienced five major evolutionary changes In response to user requests and requirements. Features added with these changes were the addition of online browse, user subsetting, dynamic image Processing/navigation, a stand-alone data storage system, and movement,from an X-windows graphical user Interface (GUI) to a World Wide Web (WWW) interface. Over Its lifetime, the system has had as many as 2500 registered users. The system on the WWW has had over 2500 hits since October 1995. Many of these hits are by casual users that only take the GIF images directly from the interface screens and do not specifically order digital data. Still, there b a consistent stream of users ordering the navigated image data and related products (maps and so forth). We have recently added a real-time, seven- day, northwestern United States normalized difference vegetation index (NDVI) composite that has generated considerable Interest. Index Terms-Data system, earth science, online access, satellite data.

  15. Surface chlorophyll distributions in the upper Gulf of Thailand investigated using satellite imagery and ecosystem model

    Science.gov (United States)

    Buranapratheprat, Anukul

    MERIS data and Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) ecosystem model coupled with the Princeton Ocean Model (POM), were used to investigate seasonal variations in surface chlorophyll distributions and their controlling factors to clarify phytoplankton dynamics in the upper Gulf of Thailand. Chlorophyll maps were produced by application on MERIS Level 2 data an empirical algorithm derived from the regression analysis of the relationship between chlorophyll-a concentration and remote sensing reflectance ratio. The results indicated that the patterns of seasonal chlorophyll distributions corresponded to local wind and water circulations. The model simulation highlighted the importance of river water as a significant nutrient source, and its movement after discharge into the sea is controlled by seasonal circulations. High chlorophyll concentration located along the western coast following the direction of counter-clockwise circulation, forced by the northeast winds, while chlorophyll accumulation was observed in the northeastern corner of the gulf due to clockwise circulation, driven by the southwest winds. These key simulated results are consistent with those of field observations and satellite images captured in the same periods of time, and also described seasonal shifting of blooming areas previously reported. Sensitivity analysis of simulated chlorophyll distributions suggested that not only nutrients but also wind-induced vertical movement plays a significant role in controlling phytoplankton growth. Plankton blooms occur in zones of upwelling or where vertical diffusivities are low. Increasing nutrients in the water column due to river loads leads to increasing potential for severe plankton blooms when other photosynthetic factors, such as water stability and light, are optimized. The knowledge of seasonal patterns of blooming can be used to construct environmental risk maps which are very useful for planning to mitigate the eutrophic problems

  16. Detecting the changes in rural communities in Taiwan by applying multiphase segmentation on FORMOSA-2 satellite imagery

    Science.gov (United States)

    Huang, Yishuo

    2015-09-01

    regions containing roads, buildings, and other manmade construction works and the class with high values of NDVI indicates that those regions contain vegetation in good health. In order to verify the processed results, the regional boundaries were extracted and laid down on the given images to check whether the extracted boundaries were laid down on buildings, roads, or other artificial constructions. In addition to the proposed approach, another approach called statistical region merging was employed by grouping sets of pixels with homogeneous properties such that those sets are iteratively grown by combining smaller regions or pixels. In doing so, the segmented NDVI map can be generated. By comparing the areas of the merged classes in different years, the changes occurring in the rural communities of Taiwan can be detected. The satellite imagery of FORMOSA-2 with 2-m ground resolution is employed to evaluate the performance of the proposed approach. The satellite imagery of two rural communities (Jhumen and Taomi communities) is chosen to evaluate environmental changes between 2005 and 2010. The change maps of 2005-2010 show that a high density of green on a patch of land is increased by 19.62 ha in Jhumen community and conversely a similar patch of land is significantly decreased by 236.59 ha in Taomi community. Furthermore, the change maps created by another image segmentation method called statistical region merging generate similar processed results to multiphase segmentation.

  17. Assimilation of microwave, infrared, and radio occultation satellite observations with a weather research and forecasting model for heavy rainfall forecasting

    Science.gov (United States)

    Boonyuen, Pakornpop; Wu, Falin; Phunthirawuth, Parwapath; Zhao, Yan

    2016-10-01

    In this research, satellite observation data were assimilated into Weather Research and Forecasting Model (WRF) by using Three-dimensional Variational Data Assimilation System (3DVAR) to analyze its impacts on heavy rainfall forecasts. The weather case for this research was during 13-18 September 2015. Tropical cyclone VAMCO, forming in South China Sea near with Vietnam, moved on west direction to the Northeast of Thailand. After passed through Vietnam, the tropical cyclone was become to depression and there was heavy rainfall throughout the area of Thailand. Observation data, used in this research, included microwave radiance observations from the Advanced Microwave Sounding Unit-A (AMSU-A), infrared radiance observations from Infrared Atmospheric Sounding Interferometer (IASI), and GPS radio occultation (RO) from the COSMIC and CHAMP missions. The experiments were designed in five cases, namely, 1) without data assimilation (CTRL); 2) with only RO data (RO); 3) with only AMSU-A data (AMSUA); 4) with only IASI data (IASI); and 5) with all of RO, AMSU-A and IASI data assimilation (ALL). Then all experiment results would be compared with both NCEP FNL (Final) Operational Global Analysis and the observation data from Thai Meteorological Department weather stations. The experiments result demonstrated that with microwave (AMSU-A), infrared (IASI) and GPS radio occultation (RO) data assimilation can produce the positive impact on analyses and forecast. All of satellite data assimilations have corresponding positive effects in term of temperature and humidity forecasting, and the GPS-RO assimilation produces the best of temperature and humidity forecast biases. The satellite data assimilation has a good impact on temperature and humidity in lower troposphere and vertical distribution that very helpful for heavy rainfall forecast improvement.

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

    Science.gov (United States)

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

    2013-12-01

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

  19. Mapping daily and seasonal evapotranspiration from irrigated crops using global climate grids and satellite imagery: Automation and methods comparison

    Science.gov (United States)

    Biggs, Trent W.; Marshall, Michael; Messina, Alex

    2016-09-01

    The surface energy balance algorithm for land (SEBAL) estimates land surface evapotranspiration (ET) from radiometric surface temperature (TR), but requires manual selection of calibration pixels, which can be impractical for mapping seasonal ET. Here pixel selection is automated and SEBAL implemented using global climate grids and satellite imagery. SEBAL is compared with the MOD16 algorithm, which uses remotely sensed data on vegetation condition to constrain reference ET from the Penman-Monteith equation. The difference between the evaporative fraction (Λ, range 0-1) from SEBAL and six eddy flux correlation towers was less than 0.10 for three of six towers, and less than 0.24 for all towers. SEBAL ET was moderately sensitive to surface roughness length and implementation over regions smaller than ˜10,000 km2 provided lower error than larger regions. Pixel selection based on TR had similar errors as those based on a vegetation index. For maize, MOD16 had lower error in mean seasonal evaporative fraction (-0.02) compared to SEBAL Λ (0.23), but MOD16 significantly underestimated the evaporative fraction from rice (-0.52) and cotton fields (-0.67) compared with SEBAL (-0.09 rice, -0.09 cotton). MOD16 had the largest error over short crops in the early growing season when vegetation cover was low but land surface was wet. Temperature-based methods like SEBAL can be automated and likely outperform vegetation-based methods in irrigated areas, especially under conditions of low vegetation cover and high soil evaporation.

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

    Science.gov (United States)

    Debats, Stephanie Renee

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

  1. Integration of satellite imagery and forest inventory in mapping dominant and associated species at a regional scale.

    Science.gov (United States)

    Zhang, Yangjian; He, Hong S; Dijak, William D; Yang, Jian; Shifley, Stephen R; Palik, Brian J

    2009-08-01

    To achieve the overall objective of restoring natural environment and sustainable resource usability, each forest management practice effect needs to be predicted using a simulation model. Previous simulation efforts were typically confined to public land. Comprehensive forest management practices entail incorporating interactions between public and private land. To make inclusion of private land into management planning feasible at the regional scale, this study uses a new method of combining Forest Inventory and Analysis (FIA) data with remotely sensed forest group data to retrieve detailed species composition and age information for the Missouri Ozark Highlands. Remote sensed forest group and land form data inferred from topography were integrated to produce distinct combinations (ecotypes). Forest types and size classes were assigned to ecotypes based on their proportions in the FIA data. Then tree species and tree age determined from FIA subplots stratified by forest type and size class were assigned to pixels for the entire study area. The resulting species composition map can improve simulation model performance in that it has spatially explicit and continuous information of dominant and associated species, and tree ages that are unavailable from either satellite imagery or forest inventory data. In addition, the resulting species map revealed that public land and private land in Ozark Highlands differ in species composition and stand size. Shortleaf pine is a co-dominant species in public land, whereas it becomes a minor species in private land. Public forest is older than private forest. Both public and private forests have deviated from historical forest condition in terms of species composition. Based on possible reasons causing the deviation discussed in this study, corresponding management avenues that can assist in restoring natural environment were recommended.

  2. Multiscale assessment of progress of electrification in Indonesia based on brightness level derived from nighttime satellite imagery.

    Science.gov (United States)

    Ramdani, Fatwa; Setiani, Putri

    2017-06-01

    Availability of electricity can be used as an indicator to proximate parameters related to human well-being. Overall, the electrification process in Indonesia has been accelerating in the past two decades. Unfortunately, monitoring the country's progress on its effort to provide wider access to electricity poses challenges due to inconsistency of data provided by each national bureau, and limited availability of information. This study attempts to provide a reliable measure by employing nighttime satellite imagery to observe and to map the progress of electrification within a duration of 20 years, from 1993 to 2013. Brightness of 67,021 settlement-size points in 1993, 2003, and 2013 was assessed using data from DMSP/OLS instruments to study the electrification progress in the three service regions (Sumatera, Java-Bali, and East Indonesia) of the country's public electricity company, PLN. Observation of all service areas shows that the increase in brightness, which correspond with higher electricity development and consumption, has positive correlation with both population density (R(2) = 0.70) and urban change (R(2) = 0.79). Moreover, urban change has a stronger correlation with brightness, which is probably due to the high energy consumption in urban area per capita. This study also found that the brightness in Java-Bali region is very dominant, while the brightness in other areas has been lagging during the period of analysis. The slow development of electricity infrastructure, particularly in major parts of East Indonesia region, affects the low economic growth in some areas and formed vicious cycle.

  3. Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

    Science.gov (United States)

    Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

    2014-10-01

    The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure

  4. Daily Area of Snow Melt Onset on Arctic Sea Ice from Passive Microwave Satellite Observations 1979–2012

    OpenAIRE

    Angela C. Bliss; Anderson, Mark R

    2014-01-01

    Variability in snow melt onset (MO) on Arctic sea ice since 1979 is examined by determining the area of sea ice experiencing the onset of melting during the melt season on a daily basis. The daily MO area of the snow and ice surface is determined from passive microwave satellite-derived MO dates for the Arctic Ocean and sub-regions. Annual accumulations of MO area are determined by summing the time series of daily MO area through the melt season. Daily areas and annual accumulations of MO are...

  5. Inferring Species Richness and Turnover by Statistical Multiresolution Texture Analysis of Satellite Imagery

    Science.gov (United States)

    Convertino, Matteo; Mangoubi, Rami S.; Linkov, Igor; Lowry, Nathan C.; Desai, Mukund

    2012-01-01

    Background The quantification of species-richness and species-turnover is essential to effective monitoring of ecosystems. Wetland ecosystems are particularly in need of such monitoring due to their sensitivity to rainfall, water management and other external factors that affect hydrology, soil, and species patterns. A key challenge for environmental scientists is determining the linkage between natural and human stressors, and the effect of that linkage at the species level in space and time. We propose pixel intensity based Shannon entropy for estimating species-richness, and introduce a method based on statistical wavelet multiresolution texture analysis to quantitatively assess interseasonal and interannual species turnover. Methodology/Principal Findings We model satellite images of regions of interest as textures. We define a texture in an image as a spatial domain where the variations in pixel intensity across the image are both stochastic and multiscale. To compare two textures quantitatively, we first obtain a multiresolution wavelet decomposition of each. Either an appropriate probability density function (pdf) model for the coefficients at each subband is selected, and its parameters estimated, or, a non-parametric approach using histograms is adopted. We choose the former, where the wavelet coefficients of the multiresolution decomposition at each subband are modeled as samples from the generalized Gaussian pdf. We then obtain the joint pdf for the coefficients for all subbands, assuming independence across subbands; an approximation that simplifies the computational burden significantly without sacrificing the ability to statistically distinguish textures. We measure the difference between two textures' representative pdf's via the Kullback-Leibler divergence (KL). Species turnover, or diversity, is estimated using both this KL divergence and the difference in Shannon entropy. Additionally, we predict species richness, or diversity, based on the

  6. Inferring species richness and turnover by statistical multiresolution texture analysis of satellite imagery.

    Directory of Open Access Journals (Sweden)

    Matteo Convertino

    Full Text Available BACKGROUND: The quantification of species-richness and species-turnover is essential to effective monitoring of ecosystems. Wetland ecosystems are particularly in need of such monitoring due to their sensitivity to rainfall, water management and other external factors that affect hydrology, soil, and species patterns. A key challenge for environmental scientists is determining the linkage between natural and human stressors, and the effect of that linkage at the species level in space and time. We propose pixel intensity based Shannon entropy for estimating species-richness, and introduce a method based on statistical wavelet multiresolution texture analysis to quantitatively assess interseasonal and interannual species turnover. METHODOLOGY/PRINCIPAL FINDINGS: We model satellite images of regions of interest as textures. We define a texture in an image as a spatial domain where the variations in pixel intensity across the image are both stochastic and multiscale. To compare two textures quantitatively, we first obtain a multiresolution wavelet decomposition of each. Either an appropriate probability density function (pdf model for the coefficients at each subband is selected, and its parameters estimated, or, a non-parametric approach using histograms is adopted. We choose the former, where the wavelet coefficients of the multiresolution decomposition at each subband are modeled as samples from the generalized Gaussian pdf. We then obtain the joint pdf for the coefficients for all subbands, assuming independence across subbands; an approximation that simplifies the computational burden significantly without sacrificing the ability to statistically distinguish textures. We measure the difference between two textures' representative pdf's via the Kullback-Leibler divergence (KL. Species turnover, or [Formula: see text] diversity, is estimated using both this KL divergence and the difference in Shannon entropy. Additionally, we predict species

  7. Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

    Science.gov (United States)

    Wolff, David B.; Fisher, Brad L.

    2011-01-01

    Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU

  8. Detecting snowfall over land by satellite high-frequency microwave observations: The lack of scattering signature and a statistical approach

    Science.gov (United States)

    Liu, Guosheng; Seo, Eun-Kyoung

    2013-02-01

    has been long believed that the dominant microwave signature of snowfall over land is the brightness temperature decrease caused by ice scattering. However, our analysis of multiyear satellite data revealed that on most of occasions, brightness temperatures are rather higher under snowfall than nonsnowfall conditions, likely due to the emission by cloud liquid water. This brightness temperature increase masks the scattering signature and complicates the snowfall detection problem. In this study, we propose a statistical method for snowfall detection, which is developed by using CloudSat radar to train high-frequency passive microwave observations. To capture the major variations of the brightness temperatures and reduce the dimensionality of independent variables, the detection algorithm is designed to use the information contained in the first three principal components resulted from Empirical Orthogonal Function (EOF) analysis, which capture ~99% of the total variances of brightness temperatures. Given a multichannel microwave observation, the algorithm first transforms the brightness temperature vector into EOF space and then retrieves a probability of snowfall by using the CloudSat radar-trained look-up table. Validation has been carried out by case studies and averaged horizontal snowfall fraction maps. The result indicated that the algorithm has clear skills in identifying snowfall areas even over mountainous regions.

  9. The influence of snow depth and surface air temperature on satellite-derived microwave brightness temperature. [central Russian steppes, and high plains of Montana, North Dakota, and Canada

    Science.gov (United States)

    Foster, J. L.; Hall, D. K.; Chang, A. T. C.; Rango, A.; Allison, L. J.; Diesen, B. C., III

    1980-01-01

    Areas of the steppes of central Russia, the high plains of Montana and North Dakota, and the high plains of Canada were studied in an effort to determine the relationship between passive microwave satellite brightness temperature, surface air temperature, and snow depth. Significant regression relationships were developed in each of these homogeneous areas. Results show that sq R values obtained for air temperature versus snow depth and the ratio of microwave brightness temperature and air temperature versus snow depth were not as the sq R values obtained by simply plotting microwave brightness temperature versus snow depth. Multiple regression analysis provided only marginal improvement over the results obtained by using simple linear regression.

  10. An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

    Science.gov (United States)

    Kim, E. J.

    2011-12-01

    surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 2011. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

  11. Use of satellite imagery to identify vegetation cover changes following the Waldo Canyon Fire event, Colorado, 2012-2013

    Science.gov (United States)

    Cole, Christopher J.; Friesen, Beverly A.; Wilson, Earl M.

    2014-01-01

    The Waldo Canyon Fire of 2012 was one of the most destructive wildfire events in Colorado history. The fire burned a total of 18,247 acres, claimed 2 lives, and destroyed 347 homes. The Waldo Canyon Fire continues to pose challenges to nearby communities. In a preliminary emergency assessment conducted in 2012, the U.S. Geological Survey (USGS) concluded that drainage basins within and near the area affected by the Waldo Canyon Fire pose a risk for future debris flow events. Rainfall over burned, formerly vegetated surfaces resulted in multiple flood and debris flow events that affected the cities of Colorado Springs and Manitou Springs in 2013. One fatality resulted from a mudslide near Manitou Springs in August 2013. Federal, State, and local governments continue to monitor these hazards and other post-fire effects, along with the region’s ecological recovery. At the request of the Colorado Springs Office of Emergency Management, the USGS Special Applications Science Center developed a geospatial product to identify vegetation cover changes following the 2012 Waldo Canyon Fire event. Vegetation cover was derived from July 2012 WorldView-2 and September 2013 QuickBird multispectral imagery at a spatial resolution of two meters. The 2012 image was collected after the fire had reached its maximum extent. Per-pixel increases and decreases in vegetation cover were identified by measuring spectral changes that occurred between the 2012 and 2013 image dates. A Normalized Difference Vegetation Index (NDVI), and Green-Near Infrared Index (GRNIR) were computed from each image. These spectral indices are commonly used to characterize vegetation cover and health condition, due to their sensitivity to detect foliar chlorophyll content. Vector polygons identifying surface-cover feature boundaries were derived from the 2013 imagery using image segmentation software. This geographic software groups similar image pixels into vector objects based upon their spatial and spectral

  12. The 2010 MW 6.9 Yushu (Qinghai, China) earthquake: constraints from InSAR, bodywave modeling and satellite imagery

    Science.gov (United States)

    Parsons, B. E.; Li, Z.; Elliott, J. R.; Barisin, I.; Feng, W.; Jackson, J. A.; Song, X.; Walters, R. J.; Zhang, P.

    2010-12-01

    A large earthquake (MW = 6.9) struck the county of Yushu, Qinghai, China on 13 April 2010, causing 2,220 fatalities and over 12,000 injured. We have used a combination of ALOS and Envisat SAR data to model the fault geometry and slip distribution of this event, using high-resolution satellite imagery and bodywave modelling to provide further information. Preliminary observations were first posted on the internet on 20 April 2010. The fault on which the earthquake occurred can be traced precisely using SPOT 5 (2.5 m resolution) imagery and SAR image offsets, interferometric coherence and phase discontinuities. On this basis the fault was most simply divided into three segments. The dips of the fault segments were obtained from elastic dislocation models with uniform slip; the southeast segment, on which the largest slip occurred, and northwest segment are near vertical, with the central segment dipping about 75° to the southwest. Slip was almost pure left-lateral. The fault geometry was then fixed and the slip distribution that best-fits the InSAR phase measurements determined. Slip occurs mainly in the upper 10 km, with a maximum slip of ~2 m at a depth of 3 km on the southeast segment. Near-surface slip (upper 1 km of the model) agrees well with field observations of offsets on the southeast segment. The geodetically-determined and seismic moments are in reasonable agreement (2.1 ± 0.2 × 1019 N m). However, rupture lengths of 35-40 km were estimated immediately after the earthquake from the seismic moment together with a magnitude of slip from surface observations and assumed seismogenic layer thicknesses, whereas the interferograms showed slip must have occurred over a length of 70-75 km. The apparent discrepancy can be explained in terms of the non-uniform distribution of moment release on the fault. There are three main patches of moment release along the length of the fault. We believe the northwest patch may be due to the aftershock (M0 = ~0.2 × 1019 N m

  13. Rainfall measurements from cellular networks microwave links : an alternative ground reference for satellite validation and hydrology in Africa .

    Science.gov (United States)

    Gosset, Marielle; cazenave, frederic; Zougmore, françois; Doumounia, Ali; kacou, Modeste

    2015-04-01

    In many part of the Tropics the ground based gauge networks are sparse, often degrading and accessing this data for monitoring rainfall or for validating satellite products is sometime difficult. Here, an alternative rainfall measuring technique is proposed and tested in West Africa. It is based on using commercial microwave links from cellular telephone networks to detect and quantify rainfall. Rainfall monitoring based on commercial terrestrial microwave links has been tested for the first time in Burkina Faso, in Sahel. The rainfall regime is characterized by intense rainfall intensities brought by mesoscale Convective systems (MCS), generated by deep organized convection. The region is subjected to drought as well as dramatic floods associated with the intense rainfall provided by a few MCSs. The hydrometeorological risk is increasing and need to be monitored. In collaboration with the national cellular phone operator, Telecel Faso, the attenuation on 29 km long microwave links operating at 7 GHz was monitored at 1s time rate for the monsoon season 2012. The time series of attenuation is transformed into rain rates and compared with rain gauge data. The method is successful in quantifying rainfall: 95% of the rainy days are detected. The correlation with the daily raingauge series is 0.8 and the season bias is 5%. The correlation at the 5 min time step within each event is also high. We will present the quantitative results, discuss the uncertainties and compare the time series and the 2D maps with those derived from a polarimetric radar. The results demonstrate the potential interest of exploiting national and regional wireless telecommunication networks to provide rainfall maps for various applications : urban hydrology, agro-hydrological risk monitoring, satellite validation and development of combined rainfall products. We will also present the outcome of the first international Rain Cell Africa workshop held in Ouagadougou early 2015.

  14. An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

    Science.gov (United States)

    Kim, Edward

    2011-01-01

    Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

  15. Hoar crystal development and disappearance at Dome C, Antarctica: observation by near-infrared photography and passive microwave satellite

    Directory of Open Access Journals (Sweden)

    N. Champollion

    2013-08-01

    Full Text Available Hoar crystals episodically cover the snow surface in Antarctica and affect the roughness and reflective properties of the air–snow interface. However, little is known about their evolution and the processes responsible for their development and disappearance despite a probable influence on the surface mass balance and energy budget. To investigate hoar evolution, we use continuous observations of the surface by in situ near-infrared photography and by passive microwave remote sensing at Dome C in Antarctica. From the photography data, we retrieved a daily indicator of the presence/absence of hoar crystals using a texture analysis algorithm. The analysis of this 2 yr long time series shows that Dome C surface is covered almost half of the time by hoar. The development of hoar crystals takes a few days and seems to occur whatever the meteorological conditions. In contrast, the disappearance of hoar is rapid (a few hours and coincident with either strong winds or with moderate winds associated with a change in wind direction from southwest (the prevailing direction to southeast. From the microwave satellite data, we computed the polarisation ratio (i.e. horizontal over vertical polarised brightness temperatures, an indicator known to be sensitive to hoar in Greenland. Photography data and microwave polarisation ratio are correlated, i.e. high values of polarisation ratio which theoretically correspond to low snow density values near the surface are associated with the presence of hoar crystals in the photography data. Satellite data over nearly ten years (2002–2011 confirm that a strong decrease of the polarisation ratio (i.e. signature of hoar disappearance is associated with an increase of wind speed or a change in wind direction from the prevailing direction. The photography data provides, in addition, evidence of interactions between hoar and snowfall. Further adding the combined influence of wind speed and wind direction results in a

  16. Contribution of MODIS satellite imagery in modelling the flooding patterns of the coastal wetlands of the Tana River, Kenya

    Science.gov (United States)

    Leauthaud, C.; Duvail, S.; Belaud, G.; Albergel, J.; Moussa, R.; Grunberger, O.

    2012-04-01

    -scale flooding as well as differences between the long and short rainy-seasons. We also show that the total flooded surface was mainly correlated to upstream river-flow data and not local rainfall nor evaporation. The inundation maps were then used to construct a simplified hydrological model of the zone in order to 1/ further characterize the major processes that determine flood extent and duration and 2/ assess whether there have been temporal and spatial changes of the latter in the past decade. As such, MODIS products have proved useful in understanding the seasonal inundation dynamics in the TRD. The calibrated hydrological model will provide insight on how new hydroelectric infrastructure will impact the water resources and the associated ecosystem services of the delta. These high temporal and medium-range spatial resolution satellite imagery provide a free-of-cost and rapid solution in monitoring water distribution and environmental changes in tropical, coastal or semi-arid areas.

  17. Optimizing available water capacity using microwave satellite data for improving irrigation management

    Science.gov (United States)

    Gupta, Manika; Bolten, John; Lakshmi, Venkat

    2015-04-01

    This work addresses the improvement of available water capacity by developing a technique for estimating soil hydraulic parameters through the utilization of satellite-retrieved near surface soil moisture. The prototype involves the usage of Monte Carlo analysis to assimilate historical remote sensing soil moisture data available from the Advanced Microwave Scanning Radiometer (AMSR-E) within the hydrological model. The main hypothesis used in this study is that near-surface soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately In the method followed in this study the hydraulic parameters are derived directly from information on the soil moisture state at the AMSR-E footprint scale and the available water capacity is derived for the root zone by coupling of AMSR-E soil moisture with the physically-based hydrological model. The available capacity water, which refers to difference between the field capacity and wilting point of the soil and represent the soil moisture content at 0.33 bar and 15 bar respectively is estimated from the soil hydraulic parameters using the van Genuchten equation. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on Soil Survey Geographic (SSURGO) database within the particular AMSR-E footprint. Using the Monte Carlo simulation, the ranges are narrowed in the region where simulation shows a good match between predicted and near-surface soil moisture from AMSR-E. In this study, the uncertainties in accurately determining the parameters of the nonlinear soil water retention function for large-scale hydrological modeling is the focus of the development of the Bayesian framework. Thus, the model forecasting has been combined with the observational information to optimize the model state and the soil hydraulic parameters simultaneously. The optimization process is divided into

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

    Directory of Open Access Journals (Sweden)

    E. Fundisi

    2017-09-01

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

  19. Assessment of depth and turbidity with airborne Lidar bathymetry and multiband satellite imagery in shallow water bodies of the Alaskan North Slope

    Science.gov (United States)

    Saylam, Kutalmis; Brown, Rebecca A.; Hupp, John R.

    2017-06-01

    Airborne Lidar bathymetry (ALB) is an effective and a rapidly advancing technology for mapping and characterizing shallow coastal water zones as well as inland fresh-water basins such as rivers and lakes. The ability of light beams to detect and traverse shallow water columns has provided valuable information about unmapped and often poorly understood coastal and inland water bodies of the world. Estimating ALB survey results at varying water clarity and depth conditions is essential for realizing project expectations and preparing budgets accordingly. In remote locations of the world where in situ water clarity measurements are not feasible or possible, using multiband satellite imagery can be an effective tool for estimating and addressing such considerations. For this purpose, we studied and classified reflected electromagnetic energy from selected water bodies acquired by RapidEye sensor and then correlated findings with ALB survey results. This study was focused not on accurately measuring depth from optical bathymetry but rather on using multiband satellite imagery to quickly predict ALB survey results and identify potentially turbid water bodies with limited depth penetration. For this study, we constructed an in-house algorithm to confirm ALB survey findings using bathymetric waveform information. The study findings are expected to contribute to the ongoing understanding of forecasting ALB survey expectations in unknown and varying water conditions, especially in remote and inaccessible parts of the world.

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

    Science.gov (United States)

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

    2015-12-01

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

  1. The 4-Day Wave as Obvserved from the Upper Atmosphere Research Satellite Microwave Limb Sounder

    Science.gov (United States)

    Allen, D. R.; Stanford, J. L.

    1996-01-01

    The 4-day wave is an eastward moving quasi-nondispersive feature with period near 4 days occurring near the winter polar stratopause. This paper presents evidence of the 4-day feature in Microwave Limb Sounder (MLS) temperature, geopotential height and ozone data from the late Southern winters of 1992 and 1993.

  2. The RISCO RapidIce Viewer: An application for monitoring the polar ice sheets with multi-resolution, multi-temporal, multi-sensor satellite imagery

    Science.gov (United States)

    Herried, B.; Porter, C. C.; Morin, P. J.; Howat, I. M.

    2013-12-01

    The Rapid Ice Sheet Change Observatory (RISCO) is a NASA-funded, inter-organizational collaboration created to provide a systematic framework for gathering, processing, analyzing, and distributing consistent satellite imagery of polar ice sheet change for Antarctica and Greenland. RISCO gathers observations over areas of rapid change and makes them easily accessible to investigators, media, and the general public. As opposed to existing data centers, which are structured to archive and distribute diverse types of raw data to end users with the specialized software and skills to analyze them, RISCO distributes processed georeferenced raster image data products in JPEG and GeoTIFF formats, making them immediately viewable in a browser-based application. Currently, the archive includes 16 sensors including: MODIS Terra, MODIS Aqua, MODIS Terra Bands 3-6-7, Landsat MSS, Landsat TM, Landsat ETM+, Landsat 8 OLI, EO-1, SPOT, ASTER VNIR, Operation IceBridge ATM and LVIS, and commercial satellites such as WorldView-1, WorldView-2, QuickBird-2, GeoEye-1 and IKONOS. The RISCO RapidIce Viewer is a lightweight JavaScript application that provides an interface to viewing and downloading the satellite imagery from predefined areas-of-interest (or 'subsets'), which are normally between 10,000 and 20,000 sq km. Users select a subset (from a map or drop-down) and the archive of individual granules is loaded in a thumbnail grid, sorted chronologically (newest first). For each thumbnail, users can choose to view a larger preview JPG, download a GeoTIFF, or be redirected back to the original data center to see the original imagery or view metadata. There are several options for filtering displayed including by sensor, by date range, by month, or by cloud cover. Last, users can select multiple images to play back as an animation. The RapidIce Viewer is an easy-to-use, software independent application for researchers to quickly monitor daily changes in ice sheets or download historical

  3. Comparing the Accuracy of AMSRE, AMSR2, SSMI and SSMIS Satellite Radiometer Ice Concentration Products with One-Meter Resolution Visible Imagery in the Arctic

    Science.gov (United States)

    Peterson, E. R.; Stanton, T. P.

    2016-12-01

    Determining ice concentration in the Arctic is necessary to track significant changes in sea ice edge extent. Sea ice concentrations are also needed to interpret data collected by in-situ instruments like buoys, as the amount of ice versus water in a given area determines local solar heating. Ice concentration products are now routinely derived from satellite radiometers including the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Special Sensor Microwave Imager (SSMI), and the Special Sensor Microwave Imager/Sounder (SSMIS). While these radiometers are viewed as reliable to monitor long-term changes in sea ice extent, their accuracy should be analyzed, and compared to determine which radiometer performs best over smaller features such as melt ponds, and how seasonal conditions affect accuracy. Knowledge of the accuracy of radiometers at high resolution can help future researchers determine which radiometer to use, and be aware of radiometer shortcomings in different ice conditions. This will be especially useful when interpreting data from in-situ instruments which deal with small scale measurements. In order to compare these passive microwave radiometers, selected high spatial resolution one-meter resolution Medea images, archived at the Unites States Geological Survey, are used for ground truth comparison. Sea ice concentrations are derived from these images in an interactive process, although estimates are not perfect ground truth due to exposure of images, shadowing and cloud cover. 68 images are retrieved from the USGS website and compared with 9 useable, collocated SSMI, 33 SSMIS, 36 AMSRE, and 14 AMSR2 ice concentrations in the Arctic Ocean. We analyze and compare the accuracy of radiometer instrumentation in differing ice conditions.

  4. Geostationary Satellite (GOES) Images

    Data.gov (United States)

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

  5. Building damage assessment after the earthquake in Haiti using two post-event satellite stereo imagery and DSMs

    DEFF Research Database (Denmark)

    Reinartz, Peter; Tian, Jiaojiao; Nielsen, Allan Aasbjerg

    2013-01-01

    In this paper, a novel disaster building damage monitoring method is presented. This method combines the multispectral imagery and DSMs from stereo matching to obtain three kinds of changes. The proposed method contains three basic steps. The first step is to segment the panchromatic images to get...

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

    Science.gov (United States)

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

    2017-08-01

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

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

    OpenAIRE

    B. De Mol; Ruddick, K

    2004-01-01

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

  8. Frequency and distribution of winter melt events from passive microwave satellite data in the pan-Arctic, 1988-2013

    Science.gov (United States)

    Wang, Libo; Toose, Peter; Brown, Ross; Derksen, Chris

    2016-11-01

    This study presents an algorithm for detecting winter melt events in seasonal snow cover based on temporal variations in the brightness temperature difference between 19 and 37 GHz from satellite passive microwave measurements. An advantage of the passive microwave approach is that it is based on the physical presence of liquid water in the snowpack, which may not be the case with melt events inferred from surface air temperature data. The algorithm is validated using in situ observations from weather stations, snow pit measurements, and a surface-based passive microwave radiometer. The validation results indicate the algorithm has a high success rate for melt durations lasting multiple hours/days and where the melt event is preceded by warm air temperatures. The algorithm does not reliably identify short-duration events or events that occur immediately after or before periods with extremely cold air temperatures due to the thermal inertia of the snowpack and/or overpass and resolution limitations of the satellite data. The results of running the algorithm over the pan-Arctic region (north of 50° N) for the 1988-2013 period show that winter melt events are relatively rare, totaling less than 1 week per winter over most areas, with higher numbers of melt days (around two weeks per winter) occurring in more temperate regions of the Arctic (e.g., central Québec and Labrador, southern Alaska and Scandinavia). The observed spatial pattern is similar to winter melt events inferred with surface air temperatures from the ERA-Interim (ERA-I) and Modern Era-Retrospective Analysis for Research and Applications (MERRA) reanalysis datasets. There was little evidence of trends in winter melt event frequency over 1988-2013 with the exception of negative trends over northern Europe attributed to a shortening of the duration of the winter period. The frequency of winter melt events is shown to be strongly correlated to the duration of winter period. This must be taken into

  9. Linking the Presence of Surfactant Associated Bacteria on the Sea Surface and in the Near Surface Layer of the Ocean to Satellite Imagery

    Science.gov (United States)

    Hamilton, Bryan; Dean, Cayla; Kurata, Naoko; Soloviev, Alex; Tartar, Aurelien; Shivji, Mahmood; Perrie, William; Lehner, Susanne

    2015-04-01

    Several genera of bacteria residing on the sea surface and in the near-surface layer of the ocean have been found to be involved in the production and decay of surfactants. Under low wind speed conditions, these surfactants can suppress short gravity capillary waves at the sea surface and form natural sea slicks. These features can be observed with both airborne and satellite-based synthetic aperture radar (SAR). We have developed a new method for sampling the sea surface microlayer that has reduced contamination from the boat and during lab handling of samples. Using this new method, a series of experiments have been conducted to establish a connection between the presence of surfactant-associated bacteria in the upper layer of the ocean and sea slicks. DNA analysis of in situ samples taken during a RADARSAT-2 satellite overpass in the Straits of Florida during the 2010 Deepwater Horizon oil spill showed a higher abundance of surfactant-associated bacterial genera in the slick area as compared to the non-slick area. These genera were found to be more abundant in the subsurface water samples collected as compared to samples taken from the sea surface. The experiment was repeated in the Straits of Florida in September 2013 and was coordinated with TerraSAR-X satellite overpasses. The observations suggest that the surfactants contributing to sea slick formation are produced by marine bacteria in the organic matter-rich water column and move to the sea surface by diffusion or advection. Thus, within a range of wind-wave conditions, the organic materials present in the water column (such as dissolved oil spills) can be monitored with SAR satellite imagery. In situ sampling was also performed in the Gulf of Mexico in December 2013 during RADARSAT-2 and TerraSAR-X satellite overpasses. Areas near natural oil seeps identified from archived TerraSAR-X imagery were targeted for in situ sampling. A number of samples from this location have been analyzed to determine the

  10. Use of stereoscopic satellite imagery for 3D mapping of bedrock structure in West Antarctica: An example from the northern Ford Ranges

    Science.gov (United States)

    Contreras, A.; Siddoway, C. S.; Porter, C.; Gottfried, M.

    2012-12-01

    In coastal West Antarctica, crustal-scale faults have been minimally mapped using traditional ground-based methods but regional scale structures are inferred mainly on the basis of low resolution potential fields data from airborne geophysical surveys (15 km flightline spacing). We use a new approach to detailed mapping of faults, shear zones, and intrusive relationships using panchromatic and multispectral imagery draped upon a digital elevation model (DEM). Our work focuses on the Fosdick Mountains, a culmination of lower middle crustal rocks exhumed at c. 100 Ma by dextral oblique detachment faulting. Ground truth exists for extensive areas visited during field studies in 2005-2011, providing a basis for spectral analysis of 8-band WorldView-02 imagery for detailed mapping of complex granite- migmatite relationships on the north side of the Fosdick range. A primary aim is the creation of a 3D geological map using the results of spectral analysis merged with a DEM computed from a stereographic pair of high resolution panchromatic images (sequential scenes, acquired 45 seconds apart). DEMs were computed using ERDAS Imagine™ LPS eATE, refined by MATLAB-based interpolation scripts to remove artifacts in the terrain model according to procedures developed by the Polar Geospatial Center (U. Minnesota). Orthorectified satellite imagery that covers the area of the DEMs was subjected to principal component analysis in ESRI ArcGIS™ 10.1, then the different rock types were identified using various combinations of spectral bands in order to map the geology of rock exposures that could not be accessed directly from the ground. Renderings in 3D