WorldWideScience

Sample records for models satellite imagery

  1. Burn severity mapping using simulation modeling and satellite imagery

    Science.gov (United States)

    Eva C. Karau; Robert E. Keane

    2010-01-01

    Although burn severity maps derived from satellite imagery provide a landscape view of fire impacts, fire effects simulation models can provide spatial fire severity estimates and add a biotic context in which to interpret severity. In this project, we evaluated two methods of mapping burn severity in the context of rapid post-fire assessment for four wildfires in...

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

    Science.gov (United States)

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

    2014-01-01

    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...

  3. VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    J. Octariady

    2017-05-01

    Full Text Available 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. The significance of using satellite imagery data only in Ecological Niche Modelling of Iberian herps

    Directory of Open Access Journals (Sweden)

    Neftalí Sillero

    2012-12-01

    Full Text Available The environmental data used to calculate ecological niche models (ENM are obtained mainly from ground-based maps (e.g., climatic interpolated surfaces. These data are often not available for less developed areas, or may be at an inappropriate scale, and thus to obtain this information requires fieldwork. An alternative source of eco-geographical data comes from satellite imagery. Three sets of ENM were calculated exclusively with variables obtained (1 from optical and radar images only and (2 from climatic and altitude maps obtained by ground-based methods. These models were compared to evaluate whether satellite imagery can accurately generate ENM. These comparisons must be made in areas with well-known species distribution and with available satellite imagery and ground-based data. Thus, the study area was the south-western part of Salamanca (Spain, using amphibian and reptiles as species models. Models’ discrimination capacity was measured with ROC plots. Models’ covariation was measured with a Spatial Spearman correlation. Four modelling techniques were used (Bioclim, Mahalanobis distance, GARP and Maxent. The results of this comparison showed that there were no significant differences between models generated using remotely sensed imagery or ground-based data. However, the models built with satellite imagery data exhibited a larger diversity of values, probably related to the higher spatial resolution of the satellite imagery. Satellite imagery can produce accurate ENM, independently of the modelling technique or the dataset used. Therefore, biogeographical analysis of species distribution in remote areas can be accurately developed only with variables from satellite imagery.

  5. Modelling avian biodiversity using raw, unclassified satellite imagery.

    Science.gov (United States)

    St-Louis, Véronique; Pidgeon, Anna M; Kuemmerle, Tobias; Sonnenschein, Ruth; Radeloff, Volker C; Clayton, Murray K; Locke, Brian A; Bash, Dallas; Hostert, Patrick

    2014-01-01

    Applications of remote sensing for biodiversity conservation typically rely on image classifications that do not capture variability within coarse land cover classes. Here, we compare two measures derived from unclassified remotely sensed data, a measure of habitat heterogeneity and a measure of habitat composition, for explaining bird species richness and the spatial distribution of 10 species in a semi-arid landscape of New Mexico. We surveyed bird abundance from 1996 to 1998 at 42 plots located in the McGregor Range of Fort Bliss Army Reserve. Normalized Difference Vegetation Index values of two May 1997 Landsat scenes were the basis for among-pixel habitat heterogeneity (image texture), and we used the raw imagery to decompose each pixel into different habitat components (spectral mixture analysis). We used model averaging to relate measures of avian biodiversity to measures of image texture and spectral mixture analysis fractions. Measures of habitat heterogeneity, particularly angular second moment and standard deviation, provide higher explanatory power for bird species richness and the abundance of most species than measures of habitat composition. Using image texture, alone or in combination with other classified imagery-based approaches, for monitoring statuses and trends in biological diversity can greatly improve conservation efforts and habitat management.

  6. 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.

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

    OpenAIRE

    Miliaresis, George

    2014-01-01

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

  8. 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....

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

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    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.

  10. 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

  11. ROI-ORIENTATED SENSOR CORRECTION BASED ON VIRTUAL STEADY REIMAGING MODEL FOR WIDE SWATH HIGH RESOLUTION OPTICAL SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    Y. Zhu

    2017-09-01

    Full Text Available To meet the requirement of high accuracy and high speed processing for wide swath high resolution optical satellite imagery under emergency situation in both ground processing system and on-board processing system. This paper proposed a ROI-orientated sensor correction algorithm based on virtual steady reimaging model for wide swath high resolution optical satellite imagery. Firstly, the imaging time and spatial window of the ROI is determined by a dynamic search method. Then, the dynamic ROI sensor correction model based on virtual steady reimaging model is constructed. Finally, the corrected image corresponding to the ROI is generated based on the coordinates mapping relationship which is established by the dynamic sensor correction model for corrected image and rigours imaging model for original image. Two experimental results show that the image registration between panchromatic and multispectral images can be well achieved and the image distortion caused by satellite jitter can be also corrected efficiently.

  12. FULLY AUTOMATED GENERATION OF ACCURATE DIGITAL SURFACE MODELS WITH SUB-METER RESOLUTION FROM SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    J. Wohlfeil

    2012-07-01

    Full Text Available Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images’ relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.

  13. Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

    Science.gov (United States)

    Wittke, S.; Karila, K.; Puttonen, E.; Hellsten, A.; Auvinen, M.; Karjalainen, M.

    2017-05-01

    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).

  14. Comparison of Flood Inundation Mapping Techniques between Different Modeling Approaches and Satellite Imagery

    Science.gov (United States)

    Zhang, J.; Munasinghe, D.; Huang, Y. F.; Lin, P.; Fang, N. Z.; Cohen, S.; Tsang, Y. P.

    2016-12-01

    Flood inundation extent serves as a crucial information source for both hydrologists and decision makers. Accurate and timely inundation mapping can potentially improve flood risk management and reduce flood damage. In this study, the authors applied two modeling approaches to estimate flood inundation area for a large flooding event that occurred in May 2016 in the Brazos River: The Height Above the Nearest Drainage combined with National Hydrograph Dataset (NHD-HAND) and the International River Interface Cooperative - Flow and Sediment Transport with Morphological Evolution of Channels (iRIC-FaSTMECH). NHD-HAND features a terrain model that simplifies the dynamic flood inundation mapping process while iRIC-FaSTMECH is a hydrodynamic model that simulates flood extent under quasi-steady approximation. In terms of data sources, HAND and iRIC utilized the National Water Model (NWM) output and the United States Geological Survey (USGS) stream gage data, respectively. The flood inundation extents generated from these two approaches were validated against Landsat 8 Satellite Imagery. Four remote sensing classification techniques were used to provide alternative observations: supervised, unsupervised, normalized difference water index and delta-cue change detection of water. According to the quantitative analysis that compares simulated areas with different remote sensing classifications, the advanced fitness index of iRIC simulation ranges from 57.5% to 69.9% while that of HAND ranges from 49.4% to 55.5%. We found that even though HAND better captures some details than iRIC in the inundation extent, it has problems in certain areas where subcatchments are not behaving independently, especially for extreme flooding events. The iRIC model performs better in this case, however, we cannot simply conclude iRIC is a better-suited approach than HAND considering the uncertainties in remote sensing observations and iRIC model parameters. Further research will include more

  15. An estimation model of population in China using time series DMSP night-time satellite imagery from 2002-2010

    Science.gov (United States)

    Zhang, Xiaoyong; Zhang, Zhijie; Chang, Yuguang; Chen, Zhengchao

    2015-12-01

    Accurate data on the spatial distribution and potential growth estimation of human population are playing pivotal role in addressing and mitigating heavy lose caused by earthquake. Traditional demographic data is limited in its spatial resolution and is extremely hard to update. With the accessibility of massive DMSP/OLS night time imagery, it is possible to model population distribution at the county level across China. In order to compare and improve the continuity and consistency of time-series DMSP night-time satellite imagery obtained by different satellites in same year or different years by the same satellite from 2002-2010, normalized method was deployed for the inter-correction among imageries. And we referred to the reference F162007 Jixi city, whose social-economic has been relatively stable. Through binomial model, with average R2 0.90, then derived the correction factor of each year. The normalization obviously improved consistency comparing to previous data, which enhanced the correspondent accuracy of model. Then conducted the model of population density between average night-time light intensity in eight-economic districts. According to the two parameters variation law of consecutive years, established the prediction model of next following years with R2of slope and constant typically 0.85 to 0.95 in different regions. To validate the model, taking the year of 2005 as example, retrieved quantitatively population distribution in per square kilometer based on the model, then compared the results to the statistical data based on census, the difference of the result is acceptable. In summary, the estimation model facilitates the quick estimation and prediction in relieving the damage to people, which is significant in decision-making.

  16. 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.

  17. 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.

  18. Satellite imagery in safeguards: progress and prospects

    International Nuclear Information System (INIS)

    Niemeyer, I.; Listner, C.

    2013-01-01

    The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)

  19. Using satellite imagery for qualitative evaluation of plume transport in modeling the effects of the Kuwait oil fire smoke plumes

    International Nuclear Information System (INIS)

    Bass, A.; Janota, P.

    1992-01-01

    To forecast the behavior of the Kuwait oil fire smoke plumes and their possible acute or chronic health effects over the Arabian Gulf region, TASC created a comprehensive health and environmental impacts modeling system. A specially-adapted Lagrangian puff transport model was used to create (a) short-term (multiday) forecasts of plume transport and ground-level concentrations of soot and SO 2 ; and (b) long-term (seasonal and longer) estimates of average surface concentrations and depositions. EPA-approved algorithms were used to transform exposures to SO 2 and soot (as PAH/BaP) into morbidity, mortality and crop damage risks. Absent any ground truth, satellite imagery from the NOAA Polar Orbiter and the ESA Geostationary Meteosat offered the only opportunity for timely qualitative evaluation of the long-range plume transport and diffusion predictions. This paper shows the use of actual satellite images (including animated loops of hourly Meteosat images) to evaluate plume forecasts in near-real-time, and to sanity-check the meso- and long-range plume transport projections for the long-term estimates. Example modeled concentrations, depositions and health effects are shown

  20. 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.

  1. Satellite imagery in a nuclear age

    International Nuclear Information System (INIS)

    Baines, P.J.

    1998-01-01

    Increasingly, high resolution satellite imaging systems are becoming available from multiple and diverse sources with capabilities useful for answering security questions. With increased supply, data availability and data authenticity may be assured. In a commercial market a supplier can ill afford the loss in market share that would result from any falsification of data. Similarly rising competitors willing to sell imagery of national security sites will decrease the tendency to endure self-imposed restrictions on sales of those sites. International organizations operating in the security interests of all nations might also gain preferential access. Costa for imagery will also fall to the point were individuals can afford purchases of satellite images. International organizations will find utility in exploiting imagery for solving international security problems. Housed within international organizations possessing competent staff, procedures, and 'shared destiny' stakes in resolving compliance discrepancies, the use of satellite imagery may provide a degree of stability in a world in which individuals, non-governmental organizations and governments may choose to exploit the available information for political gain. The use of satellite imagery outside these international organizations might not necessarily be aimed at seeking mutually beneficial solutions for international problems

  2. 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.

  3. 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.

  4. 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 of...

  5. Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

    Science.gov (United States)

    García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

    2018-04-01

    Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important

  6. Quantifying unpredictability: A multiple-model approach based on satellite imagery data from Mediterranean ponds.

    Directory of Open Access Journals (Sweden)

    Lluis Franch-Gras

    Full Text Available Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1 gathering long-term data and (2 handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+ to assess a set of environmental models for estimating environmental predictability. The case study included 20 Mediterranean saline ponds and lakes, and the focal variable was the water-surface area. This study first aimed to produce a method for accurately estimating the water-surface area from satellite images. Saline ponds can develop salt-crusted areas that make it difficult to distinguish between soil and water. This challenge was addressed using a novel pipeline that combines band ratio water indices and the short near-infrared band as a salt filter. The study then extracted the predictable and unpredictable components of variation in the water-surface area. Two different approaches, each showing variations in the parameters, were used to obtain the stochastic variation around a regular pattern with the objective of dissecting the effect of assumptions on predictability estimations. The first approach, which is based on Colwell's predictability metrics, transforms the focal variable into a nominal one. The resulting discrete categories define the relevant variations in the water-surface area. In the second approach, we introduced General Additive Model (GAM fitting as a new metric for quantifying predictability. Both approaches produced a wide range of predictability for the studied ponds. Some model assumptions-which are considered very different a priori

  7. Satellite imagery and the Department of Safeguards

    International Nuclear Information System (INIS)

    Chitumbo, K.; Bunney, J.; Leve, G.; Robb, S.

    2001-01-01

    Full text: The presentation examines some of the challenges the Satellite Imagery and Analysis Laboratory (SIAL) is facing in supporting Strengthened Safeguards. It focuses on the analytical process, starting with specifying initial tasking and continuing through to end products that are a direct result of in-house analysis. In addition it also evaluates the advantages and disadvantages of SIAL's mission and introduces external forces that the agency must consider, but cannot itself, predict or control. Although SIAL's contribution to tasks relating to Article 2a(iii) of the Additional Protocol are known and are presently of great benefit to operations areas, this is only one aspect of its work. SIAL's ability to identify and analyze historical satellite imagery data has the advantage of permitting operations to take a more in depth view of a particular area of interest's (AOI) development, and thus may permit operations to confirm or refute specific assertions relating to the AOI's function or abilities. These assertions may originate in-house or may be open source reports the agency feels it is obligated to explore. SIAL's mission is unique in the world of imagery analysis. Its aim is to support all operations areas equally and in doing so it must maintain global focus. The task is tremendous, but the resultant coverage and concentration of unique expertise will allow SIAL to develop and provide operations with datasets that can be exploited in standalone mode or be incorporated into new cutting edge tools to be developed in SGIT. At present SIAL relies on two remote sensors, IKONOS-2 and EROS-AI, for present high- resolution imagery data and is using numerous sources for historical, pre 1999, data. A multiplicity of sources for high-resolution data is very important to SIAL, but is something that it cannot influence. It is hoped that the planned launch of two new sensors by Summer 2002 will be successful and will offer greater flexibility for image collection

  8. Estimating Evapotranspiration from an Improved Two-Source Energy Balance Model Using ASTER Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Qifeng Zhuang

    2015-11-01

    Full Text Available Reliably estimating the turbulent fluxes of latent and sensible heat at the Earth’s surface by remote sensing is important for research on the terrestrial hydrological cycle. This paper presents a practical approach for mapping surface energy fluxes using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER images from an improved two-source energy balance (TSEB model. The original TSEB approach may overestimate latent heat flux under vegetative stress conditions, as has also been reported in recent research. We replaced the Priestley-Taylor equation used in the original TSEB model with one that uses plant moisture and temperature constraints based on the PT-JPL model to obtain a more accurate canopy latent heat flux for model solving. The collected ASTER data and field observations employed in this study are over corn fields in arid regions of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER area, China. The results were validated by measurements from eddy covariance (EC systems, and the surface energy flux estimates of the improved TSEB model are similar to the ground truth. A comparison of the results from the original and improved TSEB models indicates that the improved method more accurately estimates the sensible and latent heat fluxes, generating more precise daily evapotranspiration (ET estimate under vegetative stress conditions.

  9. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    Science.gov (United States)

    Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

    2011-01-01

    The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data

  10. Big data - modelling of midges in Europa using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Cuellar, Ana Carolina; Kjær, Lene Jung; Skovgaard, Henrik

    2017-01-01

    coordinates of each trap, start and end dates of trapping. We used 120 environmental predictor variables together with Random Forest machine learning algorithms to predict the overall species distribution (probability of occurrence) and monthly abundance in Europe. We generated maps for every month...... and the Obsoletus group, although abundance was generally higher for a longer period of time for C. imicula than for the Obsoletus group. Using machine learning techniques, we were able to model the spatial distribution in Europe for C. imicola and the Obsoletus group in terms of abundance and suitability...

  11. 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.

  12. 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

  13. 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

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

    International Nuclear Information System (INIS)

    Andersson, Christer

    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

  15. 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

  16. Generative Street Addresses from Satellite Imagery

    Directory of Open Access Journals (Sweden)

    İlke Demir

    2018-03-01

    Full Text Available We describe our automatic generative algorithm to create street addresses from satellite images by learning and labeling roads, regions, and address cells. Currently, 75% of the world’s roads lack adequate street addressing systems. Recent geocoding initiatives tend to convert pure latitude and longitude information into a memorable form for unknown areas. However, settlements are identified by streets, and such addressing schemes are not coherent with the road topology. Instead, we propose a generative address design that maps the globe in accordance with streets. Our algorithm starts with extracting roads from satellite imagery by utilizing deep learning. Then, it uniquely labels the regions, roads, and structures using some graph- and proximity-based algorithms. We also extend our addressing scheme to (i cover inaccessible areas following similar design principles; (ii be inclusive and flexible for changes on the ground; and (iii lead as a pioneer for a unified street-based global geodatabase. We present our results on an example of a developed city and multiple undeveloped cities. We also compare productivity on the basis of current ad hoc and new complete addresses. We conclude by contrasting our generative addresses to current industrial and open solutions.

  17. Gravity current model of the volumetric growth of volcanic clouds: remote assessment with satellite imagery and estimation of mass eruption rate

    Science.gov (United States)

    Pouget, S.; Bursik, M. I.; Sparks, R. S.; Hogg, A. J.; Johnson, C. G.; Singh, T.; Pavolonis, M. J.

    2013-12-01

    The eruption of Eyjafjallajökull, Iceland in April and May, 2010, brought to light the hazards of airborne volcanic ash and the importance of being able to estimate the concentration of ash with time. This can be done using Volcanic Ash Transport and Dispersion models (VATD). These models require Eruption Source Parameters (ESP) such as the mass eruption rate (MER), as input. MER can be estimated from volumetric flux assuming gravity current behavior of the atmospheric intrusion. We used a gravity current model for the umbrella cloud and downwind plume in which the predominantly horizontal spreading through the atmosphere is driven by buoyancy forces and wind drag. Ash is advected by these atmospheric motions and settles out relatively slowly under the action of gravity. Given the importance of knowing ESP for VATD, we explored the use of the gravity current model applied to satellite imagery, using the geometric characteristics of ash clouds. To test the gravity current model on the use of satellite imagery, we estimated ESP from five well-studied and well-characterized historical eruptions: Mount St. Helens, 1980; Pinatubo, 1991, Redoubt, 1990; Hekla, 2000 and Eyjafjallajökull, 2010. These tests show that the methodologies yield results comparable to currently accepted methodologies of ESP estimation. We then applied the methodology to umbrella clouds produced by the eruptions of Okmok, 12 July 2008, and Sarychev Peak, 12 June 2009, and to the downwind plume produced by the eruptions of Hekla, 2000; Kliuchevsko'i, 1 October 1994; Kasatochi 7-8 August 2008 and Bezymianny, 1 September 2012; none of which had previous estimates of MER.

  18. 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...

  19. Soil depth modelling using terrain analysis and satellite imagery: the case study of Qeshlaq mountainous watershed (Kurdistan, Iran

    Directory of Open Access Journals (Sweden)

    Salahudin Zahedi

    2017-09-01

    Full Text Available Soil depth is a major soil characteristic, which is commonly used in distributed hydrological modelling in order to present watershed subsurface attributes. This study aims at developing a statistical model for predicting the spatial pattern of soil depth over the mountainous watershed from environmental variables derived from a digital elevation model (DEM and remote sensing data. Among the explanatory variables used in the models, seven are derived from a 10 m resolution DEM, namely specific catchment area, wetness index, aspect, slope, plan curvature, elevation and sediment transport index. Three variables landuse, NDVI and pca1 are derived from Landsat8 imagery, and are used for predicting soil depth by the models. Soil attributes, soil moisture, topographic curvature, training samples for each landuse and major vegetation types are considered at 429 profiles within four subwatersheds. Random forests (RF, support vector machine (SVM and artificial neural network (ANN are used to predict soil depth using the explanatory variables. The models are run using 336 data points in the calibration dataset with all 31 explanatory variables, and soil depth as the response of the models. Mean decrease permutation accuracy is performed on Variable selection. Testing dataset is done with the model soil depth values at testing locations (93 points using different efficiency criteria. Prediction error is computed for both the calibration and testing datasets. Results show that the variables landuse, specific surface area, slope, pca1, NDVI and aspect are the most important explanatory variables in predicting soil depth. RF and SVM models are appropriate for the mountainous watershed areas that have been limited in the depth of the soil and ANN model is more suitable for watershed with the fields of agricultural and deep soil depth.

  20. Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

    Science.gov (United States)

    Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

    2017-12-01

    Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and

  1. Towards the objective analysis of clouds from satellite imagery data

    Science.gov (United States)

    Coakley, J. A., Jr.; Baldwin, D. G.

    1984-01-01

    It is suspected that clouds play a major role in climate dynamics. However, conclusive studies regarding the effects related to the cloud cover appear difficult because there is a lack of objective data. The present investigation is concerned with an objective scheme for deriving clouds and their properties from satellite imagery data for the oceans. The objective analysis makes use of the spatial coherence method for retrieving cloud cover from satellite imagery data. This method has advantages over other techniques often applied to imagery data. It is not necessary that clouds fill completely the observing instrument's field-of-view, and a priori or satellite derived knowledge of the cloud radiative properties is not needed.

  2. September 3rd, 2017 underground nuclear test in North Korea: Results from satellite radar imagery and dislocation modeling

    Science.gov (United States)

    Wang, T.; Nikkhoo, M.; Motagh, M.; Wei, S.; Barbot, S.; Burgmann, R.

    2017-12-01

    On September 3rd 2017, two seismic events were detected in the Democratic People's Republic of Korea (North Korea)'s Punggye-ri nuclear test site. US Geological Survey and China Earthquake Networks Center determined a body wave magnitude of Mb 6.3 for the first and larger event. Underground explosions have been well studied using seismic waveforms, the surface displacement associated with this kind of source is, however, poorly known due to the lack of geodetic measurements. Here, we use satellite observations to determine the first-ever complete (3D) surface displacement characterization associated with North Korea's sixth underground nuclear test. We measure the surface displacement by cross-correlating high-resolution radar images (2.5 m in azimuth and 0.5 m in the range direction) acquired by the German TerraSAR-X satellite. We combine azimuth and range offsets from two ascending and two descending tracks to map the 3D surface displacements. The horizontal motions of up to 3.5 m show a divergent pattern centered at the top of Mt. Mantap with a central zone of subsidence of 0.5 m, indicating the surface projection of the source (epicenter). The horizontal motions are distributed asymmetrically with larger displacements on the west and south flanks than the east and north flanks, suggesting a strong topographic control on the surface displacement pattern. We infer the location, depth and geometry of the deformation sources through applying the compound dislocation model (CDM) and the boundary element method (BEM) to the surface displacements. We show that the significant topographic effect on the near field displacements is due to the shallow depth and large radius of the explosion cavity and the steep slopes of the ground zero. The simulated surface displacements in our model consist of the contributions of two consecutive deformation sources, which are represented by two inflating and contracting finite cavities, respectively. The exposed characteristics of the

  3. Biomass burning - Combustion emissions, satellite imagery, and biogenic emissions

    Science.gov (United States)

    Levine, Joel S.; Cofer, Wesley R., III; Winstead, Edward L.; Rhinehart, Robert P.; Cahoon, Donald R., Jr.; Sebacher, Daniel I.; Sebacher, Shirley; Stocks, Brian J.

    1991-01-01

    After detailing a technique for the estimation of the instantaneous emission of trace gases produced by biomass burning, using satellite imagery, attention is given to the recent discovery that burning results in significant enhancement of biogenic emissions of N2O, NO, and CH4. Biomass burning accordingly has an immediate and long-term impact on the production of atmospheric trace gases. It is presently demonstrated that satellite imagery of fires may be used to estimate combustion emissions, and could be used to estimate long-term postburn biogenic emission of trace gases to the atmosphere.

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

    Science.gov (United States)

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

    2013-04-01

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

  5. Establishing a Commercial Reserve Imagery Fleet Obtaining Surge Imagery Capacity from Commercial Remote Sensing Satellite Systems During Crisis

    National Research Council Canada - National Science Library

    Rider, Douglas

    2000-01-01

    .... Congress directed the National Reconnaissance Office and National Imagery and Mapping Agency to investigate commercial satellite imaging systems as a supplement to national reconnaissance systems...

  6. Tamarisk Mapping and Monitoring Using High Resolution Satellite Imagery

    Science.gov (United States)

    Jason W. San Souci; John T. Doyle

    2006-01-01

    QuickBird high resolution multispectral satellite imagery (60 cm GSD, 4 spectral bands) and calibrated products from DigitalGlobe’s AgroWatch program were used as inputs to Visual Learning System’s Feature Analyst automated feature extraction software to map localized occurrences of pervasive and aggressive Tamarisk (Tamarix ramosissima), an invasive...

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

    Science.gov (United States)

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

    1988-01-01

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

  8. Satellite Imagery Analysis for Automated Global Food Security Forecasting

    Science.gov (United States)

    Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

    2017-12-01

    The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. 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. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

  9. 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...

  10. TESTFIELD TRENTO: GEOMETRIC EVALUATION OF VERY HIGH RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    G. Agugiaro

    2012-07-01

    Full Text Available Today the use of spaceborne Very High Spatial Resolution (VHSR optical sensors for automatic 3D information extraction is increasing in the scientific and civil communities. The 3D Optical Metrology (3DOM Unit of the Bruno Kessler Foundation (FBK in Trento (Italy has collected stereo VHSR satellite imagery, as well as aerial and terrestrial data over Trento, with the aim to create a complete data collection with state-of-the-art datasets for investigations on image analysis, automatic digital surface model (DSM generation, 2D/3D feature extraction, city modelling and data fusion. The testfield region covers the city of Trento, characterised by very dense urban (historical centre, residential and industrial areas, and the surrounding hills and steep mountains (approximate height range 200-2100 m with cultivations, forests and bare soil. This paper reports the analysis conducted in FBK on the VHSR spaceborne imagery of Trento testfield for 3D information extraction. The data include two stereo-pairs acquired by WorldView-2 in August 2010 and by GeoEye-1 in September 2011 in panchromatic and multispectral mode, together with their original Rational Polynomial Coefficients (RPC, and the position and description of well distributed ground points. For reference and validation, a DSM from airborne LiDAR acquisition is used. The paper gives details on the project and the dataset characteristics. The results achieved by 3DOM on DSM extraction from WorldView-2 and GeoEye-1 stereo-pairs are shown and commented.

  11. Biomass burning: Combustion emissions, satellite imagery, and biogenic emissions

    International Nuclear Information System (INIS)

    Levine, J.S.; Cofer, W.R III; Rhinehart, R.P.; Cahoon, D.R. J.; Winstead, E.L.; Sebacher, S.; Sebacher, D.I.; Stocks, B.J.

    1991-01-01

    This chapter deals with two different, but related, aspects of biomass burning. The first part of the chapter deals with a technique to estimate the instantaneous emissions of trace gases produced by biomass burning using satellite imagery. The second part of the chapter concerns the recent discovery that burning results in significantly enhanced biogenic emissions of N 2 O, NO, and CH 4 . Hence, biomass burning has both an immediate and long-term impact on the production of trace gases to the atmosphere. The objective of this research is to better assess and quantify the role of this research is to better assess and quantify the role and impact of biomass as a driver for global change. It will be demonstrated that satellite imagery of fires may be used to estimate combustion emissions and may in the future be used to estimate the long-term postburn biogenic emissions of trace gases to the atmosphere

  12. Combining Landsat TM multispectral satellite imagery and different modelling approaches for mapping post-fire erosion changes in a Mediterranean site

    Science.gov (United States)

    Petropoulos, George P.; Kairis, Orestis; Karamesouti, Mina; Papanikolaou, Ioannis D.; Kosmas, Constantinos

    2013-04-01

    South European countries are naturally vulnerable to wildfires. Their natural resources such as soil, vegetation and water may be severely affected by wildfires, causing an imminent environmental deterioration due to the complex interdependence among biophysical components. Soil surface water erosion is a natural process essential for soil formation that is affected by such interdependences. Accelerated erosion due to wildfires, constitutes a major restrictive factor for ecosystem sustainability. In 2007, South European countries were severely affected by wildfires, with more than 500,000 hectares of land burnt in that year alone, well above the average of the last 30 years. The present work examines the changes in spatial variability of soil erosion rates as a result of a wildfire event that took place in Greece in 2007, one of the most devastating years in terms of wildfire hazards. Regional estimates of soil erosion rates before and after the fire outbreak were derived from the Revised Universal Soil Loss Equation (RUSLE, Renard et al. 1991) and the Pan-European Soil Erosion Risk Assessment model (PESERA, Kirkby, 1999; Kirkby et al., 2000). Inputs for both models included climatic, land-use, soil type, topography and land use management data. Where appropriate, both models were also fed with input data derived from the analysis of LANDSAT TM satellite imagery available in our study area, acquired before and shortly after the fire suppression. Our study was compiled and performed in a GIS environment. In overall, the loss of vegetation from the fire outbreak caused a substantial increase of soil erosion rates in the affected area, particularly towards the steep slopes. Both tested models were compared to each other and noticeable differences were observed in the soil erosion predictions before and after the fire event. These are attributed to the different parameterization requirements of the 2 models. This quantification of sediment supply through the river

  13. VHR satellite imagery for humanitarian crisis management: a case study

    Science.gov (United States)

    Bitelli, Gabriele; Eleias, Magdalena; Franci, Francesca; Mandanici, Emanuele

    2017-09-01

    During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

  14. Modelling risk of tick exposure in southern Scandinavia using machine learning techniques, satellite imagery, and human population density maps

    OpenAIRE

    Kjær, Lene Jung; Korslund, L.; Kjelland, V.; Slettan, A.; Andreassen, Å. K.; Paulsen, K. M.; Christensson, M.; Kjellander, P.; Teräväinen, M.; Soleng, A.; Edgar, K. S.; Lindstedt, H. H.; Schou, Kirstine Klitgaard; Bødker, Rene

    2017-01-01

    Vector-borne diseases such as Lyme disease and tick-borne encephalitis have become more common in recent decades and present a real health problem in many parts of Europe. Risk assessment, control, and prevention of these diseases require a better understanding of vector abundance as well as risk factors determining human exposure to ticks. There is a great need for analyses and models that can predict how vectors and their associated diseases are distributed and how this relates to high risk...

  15. Modelling risk of tick exposure in southern Scandinavia using machine learning techniques, satellite imagery, and human population density maps

    DEFF Research Database (Denmark)

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

    distribution (probability of presence) in southern Scandinavia. Together with the predicted distribution maps, we used human density maps to determine areas with high risk of exposure to ticks. For nymphs, the predicted distribution found corresponded well with known distributions of ticks in Scandinavia......Vector-borne diseases such as Lyme disease and tick-borne encephalitis have become more common in recent decades and present a real health problem in many parts of Europe. Risk assessment, control, and prevention of these diseases require a better understanding of vector abundance as well as risk...... factors determining human exposure to ticks. There is a great need for analyses and models that can predict how vectors and their associated diseases are distributed and how this relates to high risk areas for human exposure.As a part of the ScandTick Innovation project, we surveyed ticks at approximately...

  16. Strengthening IAEA safeguards using high-resolution commercial satellite imagery

    International Nuclear Information System (INIS)

    Zhang Hui

    2001-01-01

    Full text: In May 1997, the IAEA Board of Governors adopted the Additional Safeguards Protocol to improve its ability to detect the undeclared production of fissile material. This new strengthened safeguards system has opened the door for the IAEA to use of all types of information, including the potential use of commercial satellite imagery. We have therefore been investigating the feasibility of strengthening IAEA safeguards using commercial satellite imagery. Based on our analysis on a number of one-meter resolution IKONOS satellite images of military nuclear production facilities at nuclear states including Russia, China, India, Pakistan and Israel, we found that the new high-resolution commercial satellite imagery would play a new and valuable role in strengthening IAEA safeguards. Since 1999, images with a resolution of one meter have been available commercially from Space Imaging's IKONOS satellite. One-meter images from other companies are expected to enter the market soon. Although still an order of magnitude less capable than military imaging satellites, the capabilities of these new high-resolution commercial satellites are good enough to detect and identify the major visible characteristics of nuclear production facilities and sites. Unlike the classified spy satellite photos limited to few countries, the commercial satellite imagery is commercially available to anyone who wants to purchase it. Therefore, the new commercial satellite open a new chance that each state, international organizations, and non-governmental groups could use the commercial images to play a more proactive role in monitoring the nuclear activities in related countries and verifying the compliance of non-proliferation agreements. This could help galvanize support for intensified efforts to slow the pace of nuclear proliferation. To produce fissile materials (plutonium and highly enriched uranium) for weapons, a country would operate dedicated plutonium-production reactors and the

  17. Satellite Imagery Production and Processing Using Apache Hadoop

    Science.gov (United States)

    Hill, D. V.; Werpy, J.

    2011-12-01

    The United States Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center Land Science Research and Development (LSRD) project has devised a method to fulfill its processing needs for Essential Climate Variable (ECV) production from the Landsat archive using Apache Hadoop. Apache Hadoop is the distributed processing technology at the heart of many large-scale, processing solutions implemented at well-known companies such as Yahoo, Amazon, and Facebook. It is a proven framework and can be used to process petabytes of data on thousands of processors concurrently. It is a natural fit for producing satellite imagery and requires only a few simple modifications to serve the needs of science data processing. This presentation provides an invaluable learning opportunity and should be heard by anyone doing large scale image processing today. The session will cover a description of the problem space, evaluation of alternatives, feature set overview, configuration of Hadoop for satellite image processing, real-world performance results, tuning recommendations and finally challenges and ongoing activities. It will also present how the LSRD project built a 102 core processing cluster with no financial hardware investment and achieved ten times the initial daily throughput requirements with a full time staff of only one engineer. Satellite Imagery Production and Processing Using Apache Hadoop is presented by David V. Hill, Principal Software Architect for USGS LSRD.

  18. Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery

    Directory of Open Access Journals (Sweden)

    M. C. Anderson

    2011-01-01

    Full Text Available Thermal infrared (TIR remote sensing of land-surface temperature (LST provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil + canopy land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5 to 10-km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions on the order of 10 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe, Africa

  19. Pattern recognition of satellite cloud imagery for improved weather prediction

    Science.gov (United States)

    Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

    1986-01-01

    The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

  20. 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

  1. A statistical model for determining impact of wildland fires on Particulate Matter (PM2.5) in Central California aided by satellite imagery of smoke

    International Nuclear Information System (INIS)

    Preisler, Haiganoush K.; Schweizer, Donald; Cisneros, Ricardo; Procter, Trent; Ruminski, Mark; Tarnay, Leland

    2015-01-01

    As the climate in California warms and wildfires become larger and more severe, satellite-based observational tools are frequently used for studying impact of those fires on air quality. However little objective work has been done to quantify the skill these satellite observations of smoke plumes have in predicting impacts to PM 2.5 concentrations at ground level monitors, especially those monitors used to determine attainment values for air quality under the Clean Air Act. Using PM 2.5 monitoring data from a suite of monitors throughout the Central California area, we found a significant, but weak relationship between satellite-observed smoke plumes and PM 2.5 concentrations measured at the surface. However, when combined with an autoregressive statistical model that uses weather and seasonal factors to identify thresholds for flagging unusual events at these sites, we found that the presence of smoke plumes could reliably identify periods of wildfire influence with 95% accuracy. - Highlights: • Satellite observed smoke is useful for predicting wildfire impacts on Particulate Matter. • A metric was developed to flag ‘exceptional events’ days as defined by EPA. • We found significant impact of wildfires on PM 2.5 at various sites in Central California. • Fires in most years had no significant impact on compliance with EPA standards. - This work quantifies the skill of satellite observations of smoke plumes in predicting wildfire impacts on PM 2.5 concentrations at ground level monitors

  2. 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.

  3. 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.

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

    Science.gov (United States)

    Stapleton, Seth; LaRue, Michelle; Lecomte, Nicolas; Atkinson, Stephen; Garshelis, David; Porter, Claire; Atwood, Todd

    2014-01-01

    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.

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

    Science.gov (United States)

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

    2016-06-01

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

  6. Users, uses, and value of Landsat satellite imagery: results from the 2012 survey of users

    Science.gov (United States)

    Miller, Holly M.; Richardson, Leslie A.; Koontz, Stephen R.; Loomis, John; Koontz, Lynne

    2013-01-01

    Landsat satellites have been operating since 1972, providing a continuous global record of the Earth’s land surface. The imagery is currently available at no cost through the U.S. Geological Survey (USGS). Social scientists at the USGS Fort Collins Science Center conducted an extensive survey in early 2012 to explore who uses Landsat imagery, how they use the imagery, and what the value of the imagery is to them. The survey was sent to all users registered with USGS who had accessed Landsat imagery in the year prior to the survey and over 11,000 current Landsat imagery users responded. The results of the survey revealed that respondents from many sectors use Landsat imagery in myriad project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance of and dependence on the imagery, the numerous environmental and societal benefits observed from projects using Landsat imagery, the potential negative impacts on users’ work if Landsat imagery was no longer available, and the substantial aggregated annual economic benefit from the imagery. These results represent only the value of Landsat to users registered with USGS; further research would help to determine what the value of the imagery is to a greater segment of the population, such as downstream users of the imagery and imagery-derived products.

  7. Properties of multilayered cloud systems from satellite imagery

    Science.gov (United States)

    Coakley, J. A., Jr.

    1983-01-01

    The spatial coherence method for obtaining fractional cloud cover from satellite imagery is extended to the case of multilayered cloud systems. Examples are presented in which simultaneous observations at 3.7 microns and 11 microns are used to solve a system of linear equations for the nonoverlapped fractional cover contributed by each of two layers. The retrieval relies on the assumption that the clouds reside in distinct, well-defined layers and are optically thick at the wavelengths of observation. Simultaneous observations at 3.7 microns and 11 microns of the separate layers indicate that the assumptions are generally valid. Owing to the reflection of solar radiation at 3.7 microns by low-level water clouds, the method is limited to nighttime observations.

  8. 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.

  9. 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.

  10. 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

  11. Automatic Cloud Detection for Chinese High Resolution Remote Sensing Satellite Imagery

    Directory of Open Access Journals (Sweden)

    TAN Kai

    2016-05-01

    Full Text Available Cloud detection is always an arduous problem in satellite imagery processing, especially the thin cloud which has the similar spectral characteristics as ground surfacehas long been the obstacle of the production of imagery product. In this paper, an automatic cloud detection method for Chinese high resolution remote sensing satellite imagery is introduced to overcome this problem.Firstly, the image is transformed from RGB to HIS color space by an improved color transformation model. The basic cloud coverage figure is obtained by using the information of intensity and saturation,followed by getting the modified figure with the information of near-infrared band and hue. Methods of histogram equalization and bilateral filtering, combined with conditioned Otsu thresholding are adopted to generate texture information. Then the cloud seed figureis obtained by using texture information to eliminate the existed errors in the modified figure. Finally, cloud covered areas are accurately extracted by integration of intensity information from the HIS color space and cloud seed figure. Compared to the detection results of other automatic and interactive methods, the overall accuracy of our proposed method achieves nearly 10% improvement, and it is capable of improving the efficiency of cloud detection significantly.

  12. 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.

  13. Development of a Model for Estimation of Acacia Senegal Tree Biomass Using Allometry and Aster Satellite Imagery at Ennuhud, West Kordofan State, Sudan

    Science.gov (United States)

    Elamin, Hatim; Elnour Adam, Hassan; Csaplovics, Elmar

    The current paper deals with the development of a biomass model for Acacia senegal trees by applying allometric equations for ground data combined with ASTER satellite data sets. The current study is conducted around Ennuhud area which is located in Ennuhud locality in West Kordofan State, Sudan. Primary data are obtained by application of random sampling around Ennuhud town where Acacia senegal tree species is abundant. Ten sample units are taken. Each unit contains five sample plots (15x15 m), one in the centre and the others in the four directions 100 m away from the centre forming a total of 50 sample plots. The tree coordinates, diameter/diameters (diameter at breast height ≥ 5 cm), height and crown diameters will be recorded. Sensor data were acquired from ASTER remote sensing satellite (29.03.2007 & 26.01.2011) and integrated with the in-situ data. The expected findings allow for the calculation of the mean diameter of trees. The tree above ground biomass (TAGB), tree below ground biomass (TBGB) and the tree total biomass (TTB) of Acacia senegal are computed consequently. Remotely sensed data are integrated with the ground data for creating the data base for calculating the correlation of the relationship between the two methods of data collection. The application of allometric equations is useful as a non-destructive method for biomass estimation by the application of remote sensing is recommended for biomass modelling over large areas. Keywords: Biomass model, Acacia senegal tree, remote sensing, Ennuhud, North Kordofan

  14. Shallow water bathymetry correction using sea bottom classification with multispectral satellite imagery

    Science.gov (United States)

    Kazama, Yoriko; Yamamoto, Tomonori

    2017-10-01

    Bathymetry at shallow water especially shallower than 15m is an important area for environmental monitoring and national defense. Because the depth of shallow water is changeable by the sediment deposition and the ocean waves, the periodic monitoring at shoe area is needed. Utilization of satellite images are well matched for widely and repeatedly monitoring at sea area. Sea bottom terrain model using by remote sensing data have been developed and these methods based on the radiative transfer model of the sun irradiance which is affected by the atmosphere, water, and sea bottom. We adopted that general method of the sea depth extraction to the satellite imagery, WorldView-2; which has very fine spatial resolution (50cm/pix) and eight bands at visible to near-infrared wavelengths. From high-spatial resolution satellite images, there is possibility to know the coral reefs and the rock area's detail terrain model which offers important information for the amphibious landing. In addition, the WorldView-2 satellite sensor has the band at near the ultraviolet wavelength that is transmitted through the water. On the other hand, the previous study showed that the estimation error by the satellite imagery was related to the sea bottom materials such as sand, coral reef, sea alga, and rocks. Therefore, in this study, we focused on sea bottom materials, and tried to improve the depth estimation accuracy. First, we classified the sea bottom materials by the SVM method, which used the depth data acquired by multi-beam sonar as supervised data. Then correction values in the depth estimation equation were calculated applying the classification results. As a result, the classification accuracy of sea bottom materials was 93%, and the depth estimation error using the correction by the classification result was within 1.2m.

  15. 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 (< 20 m depths) around Timor-Leste from DigitalGlobe WorldView-2 satellite imagery, acquired from Jan 26...

  16. A Verification of Optical Depth Retrievals From High Resolution Satellite Imagery

    National Research Council Canada - National Science Library

    Evans, Jack R

    2007-01-01

    A new technique has been developed using high resolution satellite imagery to derive aerosol optical depths by measuring the difference of the radiances inside and outside of shaded regions Vincent (2006...

  17. 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...

  18. Using Airborne and Satellite Imagery to Distinguish and Map Black Mangrove

    Science.gov (United States)

    This paper reports the results of studies evaluating color-infrared (CIR) aerial photography, CIR aerial true digital imagery, and high resolution QuickBird multispectral satellite imagery for distinguishing and mapping black mangrove [Avicennia germinans (L.) L.] populations along the lower Texas g...

  19. Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

    Science.gov (United States)

    Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

    2017-05-01

    This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

  20. Vessel and oil spill early detection using COSMO satellite imagery

    Science.gov (United States)

    Revollo, Natalia V.; Delrieux, Claudio A.

    2017-10-01

    Oil spillage is one of the most common sources of environmental damage in places where coastal wild life is found in natural reservoirs. This is especially the case in the Patagonian coast, with a littoral more than 5000 km long and a surface above a million and half square km. In addition, furtive fishery activities in Argentine waters are depleting the food supplies of several species, altering the ecological equilibrium. For this reason, early oil spills and vessel detection is an imperative surveillance task for environmental and governmental authorities. However, given the huge geographical extension, human assisted monitoring is unfeasible, and therefore real time remote sensing technologies are the only operative and economically feasible solution. In this work we describe the theoretical foundations and implementation details of a system specifically designed to take advantage of the SAR imagery delivered by two satellite constellations (the SAOCOM mission, developed by the Argentine Space Agency, and the COSMO mission, developed by the Italian Space Agency), to provide real-time detection of vessels and oil spills. The core of the system is based on pattern recognition over a statistical characterization of the texture patterns arising in the positive and negative conditions (i.e., vessel, oil, or plain sea surfaces). Training patterns were collected from a large number of previously reported contacts tagged by experts in the National Commission on Space Activities (CONAE). The resulting system performs well above the sensitivity and specificity of other avalilable systems.

  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. Detection and Prediction of Hail Storms in Satellite Imagery using Deep Learning

    Science.gov (United States)

    Pullman, M.; Gurung, I.; Ramachandran, R.; Maskey, M.

    2017-12-01

    Natural hazards, such as damaging hail storms, dramatically disrupt both industry and agriculture, having significant socio-economic impacts in the United States. In 2016, hail was responsible for 3.5 billion and 23 million dollars in damage to property and crops, respectively, making it the second costliest 2016 weather phenomenon in the United States. The destructive nature and high cost of hail storms has driven research into the development of more accurate hail-prediction algorithms in an effort to mitigate societal impacts. Recently, weather forecasting efforts have turned to deep learning neural networks because neural networks can more effectively model complex, nonlinear, dynamical phenomenon that exist in large datasets through multiple stages of transformation and representation. In an effort to improve hail-prediction techniques, we propose a deep learning technique that leverages satellite imagery to detect and predict the occurrence of hail storms. The technique is applied to satellite imagery from 2006 to 2016 for the contiguous United States and incorporates hail reports obtained from the National Center for Environmental Information Storm Events Database for training and validation purposes. In this presentation, we describe a novel approach to predicting hail via a neural network model that creates a large labeled dataset of hail storms, the accuracy and results of the model, and its applications for improving hail forecasting.

  3. Wide area change detection with satellite imagery for locating underground nuclear testing

    International Nuclear Information System (INIS)

    Canty, M.J.; Jasani, B.; Schlittenhardt, J.

    2001-01-01

    nicest aspects of the MAD method: It sorts different categories of change into different image components. Another very important characteristic of the MAD transformation is that it is invariant to linear transformations of the data. This means that if for example the sensors used for the two images have different gains, or if atmospheric haze attenuates the reflectance measurement in one of the images but not in the other, the results of the analysis will be unaffected. A Bayesian model of the probability distribution of the MAD components intensities is applied to determine automatically the decision thresholds for change and no change. The prerequisite image-to-image registration is carried out automatically with the help contour and comer matching to determine ground control points, followed by nearest-neighbor resampling. The inclusion of higher resolution panchromatic information into the procedure without loss of spectral discrimination is accomplished via wavelet fusion with the multispectral channels. A computer program CDSAT (Change Detection with SATellite imagery), which implements a user-friendly graphical environment for performing the various steps involved, is described briefly. The technique has been applied successfully to detect the exact position of an underground nuclear test in Rajasthan in 1998. In the present paper we discuss further results for tests carried out in Lop Nor, China in the 1990's and at the Nevada test site in the 1980's. Historical LANDSAT TM satellite images are used for change detection. Results are correlated with seismic and ground truth data and conclusions are drawn regarding the applicability of wide area change detection to complement seismic verification of the Comprehensive Test Ban Treaty

  4. Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

    Science.gov (United States)

    Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

    2015-06-01

    Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

  5. Extraction of Airport Features from High Resolution Satellite Imagery for Design and Risk Assessment

    Science.gov (United States)

    Robinson, Chris; Qiu, You-Liang; Jensen, John R.; Schill, Steven R.; Floyd, Mike

    2001-01-01

    The LPA Group, consisting of 17 offices located throughout the eastern and central United States is an architectural, engineering and planning firm specializing in the development of Airports, Roads and Bridges. The primary focus of this ARC project is concerned with assisting their aviation specialists who work in the areas of Airport Planning, Airfield Design, Landside Design, Terminal Building Planning and design, and various other construction services. The LPA Group wanted to test the utility of high-resolution commercial satellite imagery for the purpose of extracting airport elevation features in the glide path areas surrounding the Columbia Metropolitan Airport. By incorporating remote sensing techniques into their airport planning process, LPA wanted to investigate whether or not it is possible to save time and money while achieving the equivalent accuracy as traditional planning methods. The Affiliate Research Center (ARC) at the University of South Carolina investigated the use of remotely sensed imagery for the extraction of feature elevations in the glide path zone. A stereo pair of IKONOS panchromatic satellite images, which has a spatial resolution of 1 x 1 m, was used to determine elevations of aviation obstructions such as buildings, trees, towers and fence-lines. A validation dataset was provided by the LPA Group to assess the accuracy of the measurements derived from the IKONOS imagery. The initial goal of this project was to test the utility of IKONOS imagery in feature extraction using ERDAS Stereo Analyst. This goal was never achieved due to problems with ERDAS software support of the IKONOS sensor model and the unavailability of imperative sensor model information from Space Imaging. The obstacles encountered in this project pertaining to ERDAS Stereo Analyst and IKONOS imagery will be reviewed in more detail later in this report. As a result of the technical difficulties with Stereo Analyst, ERDAS OrthoBASE was used to derive aviation

  6. A statistical model for determining impact of wildland fires on Particulate Matter (PM2.5) in Central California aided by satellite imagery of smoke

    Science.gov (United States)

    Haiganoush K. Preisler; Donald Schweizer; Ricardo Cisneros; Trent Procter; Mark Ruminski; Leland Tarnay

    2015-01-01

    As the climate in California warms and wildfires become larger and more severe, satellite-based observational tools are frequently used for studying impact of those fires on air quality. However little objective work has been done to quantify the skill these satellite observations of smoke plumes have in predicting impacts to PM2.5 concentrations...

  7. A NEW OPTIMIZED RFM OF HIGH-RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    C. Li

    2016-06-01

    Full Text Available Over-parameterization and over-correction are two of the major problems in the rational function model (RFM. A new approach of optimized RFM (ORFM is proposed in this paper. By synthesizing stepwise selection, orthogonal distance regression, and residual systematic error correction model, the proposed ORFM can solve the ill-posed problem and over-correction problem caused by constant term. The least square, orthogonal distance, and the ORFM are evaluated with control and check grids generated from satellite observation Terre (SPOT-5 high-resolution satellite data. Experimental results show that the accuracy of the proposed ORFM, with 37 essential RFM parameters, is more accurate than the other two methods, which contain 78 parameters, in cross-track and along-track plane. Moreover, the over-parameterization and over-correction problems have been efficiently alleviated by the proposed ORFM, so the stability of the estimated RFM parameters and its accuracy have been significantly improved.

  8. Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Oscar Rojas

    2013-04-01

    Full Text Available Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regional scales. Several qualitative and quantitative approaches can be clearly distinguished, going from the use of low resolution satellite imagery as the main predictor of final crop yield to complex crop growth models where remote sensing-derived indicators play different roles, depending on the nature of the model and on the availability of data measured on the ground. Vegetation performance anomaly detection with low resolution images continues to be a fundamental component of early warning and drought monitoring systems at the regional scale. For applications at more detailed scales, the limitations created by the mixed nature of low resolution pixels are being progressively reduced by the higher resolution offered by new sensors, while the continuity of existing systems remains crucial for ensuring the availability of long time series as needed by the majority of the yield prediction methods used today.

  9. Heterogeneous benefits of precision nitrogen management over the Midwestern US: evidence from 1,000 fields derived by satellite imagery and crop modeling

    Science.gov (United States)

    Jin, Z.; Archontoulis, S.; Lobell, D. B.

    2017-12-01

    The wise management of nitrogen (N) fertilizer is important for both economic and environmental considerations. The variable rate technology (VRT) that applies different rates of N fertilizer by fully taking account of the spatial heterogeneity within fields has gained popularity with the recent advent of high-resolution satellites and spectrometers, but its profitability is still uncertain given the dependence of corn-nitrogen responses to soil and climate. To our knowledge, the benefits of adopting VRT in the vast Midwestern US agricultural zones have only been assessed at a very limited number of fields based on labor-costing on-farm samplings. Here we present a study that integrates a range of geospatial tools and data to quantifying the economic benefit of VRT versus uniform N application over 1,000 randomly selected corn fields in the US Midwest. We employed the Google Earth Engine (GEE) and Landsat-5, 7 and 8 collections to derive 30m-resolution yield map for years 2007-2015, and used the multi-year averaged yields to characterize the yield variation and hence the management zones for each field and zone-specific yield goal. The yield goals as well as the Soil Survey Geographic Database (SSURGO) data were then used to calibrate the Agricultural Production Systems sIMulator (APSIM) model, which generated a range of variables such as yields, N balance and leaching. Our preliminary results showed that the calibrated APSIM model was able to capture about 60% of the variation in the satellite-based yield estimates, and more than 70% of the yield spread (i.e. maximum - minimum yield). Regardless of the overall environmental benefits of less N loss through leaching, the economic difference between adopting VRT and uniform application ranged from -50 to 200 per acre, with the majority lay between -10 and 40 per acre. Fields with a wider range of yield spread benefited more from adopting VRT, yet the conclusion varies upon weather, especially the precipitation. Our

  10. Satellite imagery-based monitoring of archaeological site damage in the Syrian civil war.

    Directory of Open Access Journals (Sweden)

    Jesse Casana

    Full Text Available Since the start of the Syrian civil war in 2011, the rich archaeological heritage of Syria and northern Iraq has faced severe threats, including looting, combat-related damage, and intentional demolition of monuments. However, the inaccessibility of the conflict zone to archaeologists or cultural heritage specialists has made it difficult to produce accurate damage assessments, impeding efforts to develop mitigation strategies and policies. This paper presents results of a project, undertaken in collaboration with the American Schools of Oriental Research (ASOR and the US Department of State, to monitor damage to archaeological sites in Syria, northern Iraq, and southern Turkey using recent, high-resolution satellite imagery. Leveraging a large database of archaeological and heritage sites throughout the region, as well as access to continually updated satellite imagery from DigitalGlobe, this project has developed a flexible and efficient methodology to log observations of damage in a manner that facilitates spatial and temporal queries. With nearly 5000 sites carefully evaluated, analysis reveals unexpected patterns in the timing, severity, and location of damage, helping us to better understand the evolving cultural heritage crisis in Syria and Iraq. Results also offer a model for future remote sensing-based archaeological and heritage monitoring efforts in the Middle East and beyond.

  11. Satellite imagery-based monitoring of archaeological site damage in the Syrian civil war.

    Science.gov (United States)

    Casana, Jesse; Laugier, Elise Jakoby

    2017-01-01

    Since the start of the Syrian civil war in 2011, the rich archaeological heritage of Syria and northern Iraq has faced severe threats, including looting, combat-related damage, and intentional demolition of monuments. However, the inaccessibility of the conflict zone to archaeologists or cultural heritage specialists has made it difficult to produce accurate damage assessments, impeding efforts to develop mitigation strategies and policies. This paper presents results of a project, undertaken in collaboration with the American Schools of Oriental Research (ASOR) and the US Department of State, to monitor damage to archaeological sites in Syria, northern Iraq, and southern Turkey using recent, high-resolution satellite imagery. Leveraging a large database of archaeological and heritage sites throughout the region, as well as access to continually updated satellite imagery from DigitalGlobe, this project has developed a flexible and efficient methodology to log observations of damage in a manner that facilitates spatial and temporal queries. With nearly 5000 sites carefully evaluated, analysis reveals unexpected patterns in the timing, severity, and location of damage, helping us to better understand the evolving cultural heritage crisis in Syria and Iraq. Results also offer a model for future remote sensing-based archaeological and heritage monitoring efforts in the Middle East and beyond.

  12. 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.

  13. Visualizing Cloud Properties and Satellite Imagery: A Tool for Visualization and Information Integration

    Science.gov (United States)

    Chee, T.; Nguyen, L.; Smith, W. L., Jr.; Spangenberg, D.; Palikonda, R.; Bedka, K. M.; Minnis, P.; Thieman, M. M.; Nordeen, M.

    2017-12-01

    Providing public access to research products including cloud macro and microphysical properties and satellite imagery are a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a web based visualization tool and API that allows end users to easily create customized cloud product and satellite imagery, ground site data and satellite ground track information that is generated dynamically. The tool has two uses, one to visualize the dynamically created imagery and the other to provide access to the dynamically generated imagery directly at a later time. Internally, we leverage our practical experience with large, scalable application practices to develop a system that has the largest potential for scalability as well as the ability to be deployed on the cloud to accommodate scalability issues. We build upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product information, satellite imagery, ground site data and satellite track information accessible and easily searchable. This tool is the culmination of our prior experience with dynamic imagery generation and provides a way to build a "mash-up" of dynamically generated imagery and related kinds of information that are visualized together to add value to disparate but related information. In support of NASA strategic goals, our group aims to make as much scientific knowledge, observations and products available to the citizen science, research and interested communities as well as for automated systems to acquire the same information for data mining or other analytic purposes. This tool and the underlying API's provide a valuable research tool to a wide audience both as a standalone research tool and also as an easily accessed data source that can easily be mined or used with existing tools.

  14. 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

  15. CLPX-Satellite: Radarsat Synthetic Aperture Radar Imagery

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of time-series spaceborne Synthetic Aperture Radar (SAR) imagery of the three Cold Land Processes Field Experiment (CLPX) Meso-cell Study...

  16. 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...

  17. 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.

  18. The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities

    Directory of Open Access Journals (Sweden)

    G. Broquet

    2018-02-01

    Full Text Available This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the shortwave infrared measurements of a space-borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA. This assessment is based on observing system simulation experiments (OSSEs with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 h before a given satellite overpass. These 6 h correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge with 50 % uncertainty on the hourly or sectorial emissions, and with ∼ 25 % uncertainty on the 6 h mean emissions, from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbiting missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system

  19. The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities

    Science.gov (United States)

    Broquet, Grégoire; Bréon, François-Marie; Renault, Emmanuel; Buchwitz, Michael; Reuter, Maximilian; Bovensmann, Heinrich; Chevallier, Frédéric; Wu, Lin; Ciais, Philippe

    2018-02-01

    This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the shortwave infrared measurements of a space-borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on observing system simulation experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 h before a given satellite overpass. These 6 h correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge with 50 % uncertainty on the hourly or sectorial emissions, and with ˜ 25 % uncertainty on the 6 h mean emissions, from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbiting missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the

  20. Trophic state index of a lake system using IRS (P6-LISS III) satellite imagery.

    Science.gov (United States)

    Sheela, A M; Letha, J; Joseph, Sabu; Ramachandran, K K; Sanalkumar, S P

    2011-06-01

    Water pollution has now become a major threat to the existence of living beings and water quality monitoring is an effective step towards the restoration of water quality. Lakes are versatile ecosystems and their eutrophication is a serious problem. Carlson Trophic State Index (CTSI) provides an insight into the trophic condition of a lake. CTSI has been modified for the study area and is used in this study. Satellite imagery analysis now plays a prominent role in the quick assessment of water quality in a vast area. This study is an attempt to assess the trophic state index based on secchi disk depth and chlorophyll a of a lake system (Akkulam-Veli lake, Kerala, India) using Indian Remote Sensing (IRS) P6 LISS III imagery. Field data were collected on the date of the overpass of the satellite. Multiple regression equation is found to yield superior results than the simple regression equations using spectral ratios and radiance from the individual bands, for the prediction of trophic state index from satellite imagery. The trophic state index based on secchi disk depth, derived from the satellite imagery, provides an accurate prediction of the trophic status of the lake. IRS P6-LISS III imagery can be effectively used for the assessment of the trophic condition of a lake system.

  1. Measurement of Sun Induced Chlorophyll Fluorescence Using Hyperspectral Satellite Imagery

    Science.gov (United States)

    Irteza, S. M.; Nichol, J. E.

    2016-06-01

    Solar Induced Chlorophyll Fluorescence (SIF), can be used as an indicator of stress in vegetation. Several scientific approaches have been made and there is considerable evidence that steady state Chlorophyll fluorescence is an accurate indicator of plant stress hence a reliable tool to monitor vegetation health status. Retrieval of Chlorophyll fluorescence provides an insight into photochemical and carbon sequestration processes within vegetation. Detection of Chlorophyll fluorescence has been well understood in the laboratory and field measurement. Fluorescence retrieval methods were applied in and around the atmospheric absorption bands 02B (Red wavelength) approximately 690 nm and 02A (Far red wavelengths) 740 nm. Hyperion satellite images were acquired for the years 2012 to 2015 in different seasons. Atmospheric corrections were applied using the 6S Model. The Fraunhofer Line Discrimanator (FLD) method was applied for retrieval of SIF from the Hyperion images by measuring the signal around the absorption bands in both vegetated and non vegetated land cover types. Absorption values were extracted in all the selected bands and the fluorescence signal was detected. The relationships between NDVI and Fluorescence derived from the satellite images are investigated to understand vegetation response within the absorption bands.

  2. Imagery Intelligence (IMINT) Production Model

    Science.gov (United States)

    1980-01-01

    IkINT instructor teaches his students the ’LST’ principle, whici he sums up in the toll owi ny terms o L - Look at all the imagery. o S - See what is...8217 C)C4-)’~ >-.CC)C 4s- a -C-4 4-’, a)C W 5Wc- eSl C3 LE )A -.-0 E. S C r- C C C - C 0rC C u -S- U S-- S- 41 (n C : 2 F- 2- W 4tio (, C*- S t4- C C E

  3. Using satellite imagery to identify and analyze tumuli on Earth and Mars

    Science.gov (United States)

    Diniega, Serina; Sangha, Simran; Browne, Brandon

    2018-01-01

    Tumuli are small, dome-like features that form when magmatic pressures build within a subsurface lava pathway, causing the overlying crust to bulge upwards. As the appearance of these features has been linked to lava flow structure (e.g., underlying lava flow tubes) and conditions, there is interest in identifying such features in satellite images so they can be used to expand our understanding of lava flows within regions difficult to access (such as on other planets). Here, we define a methodology for identifying (and measuring) tumuli within satellite imagery, and validate it by comparing our results with fieldwork results of terrestrial tumuli reported in the literature and with independent measurements we made within Amboy Field, CA. In addition, we present aggregated results from the application of our methodology to satellite images of six terrestrial fields and seven martian fields (with >2100 tumuli identified, per planet). Comparisons of tumuli morphometrics on Earth and Mars yield similarities in size and overall shape, which were surprising given the many differences in the environmental and planetary conditions within which these features have formed. Given our measurements, we identify constraints for tumulus formation models and drivers that would yield similar shapes and sizes on two different planets. Furthermore, we test a published hypothesis regarding the number of tumuli that form per a square kilometer, and find it unlikely that a diagnostic "tumuli density" value exists.

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

    Science.gov (United States)

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

    2016-01-01

    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. PMID:27999261

  5. 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.

  6. 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.

  7. Polar Bears from Space: Assessing Satellite Imagery as a Tool to Track Arctic Wildlife

    OpenAIRE

    Stapleton, Seth; LaRue, Michelle; Lecomte, Nicolas; Atkinson, Stephen; Garshelis, David; Porter, Claire; Atwood, Todd

    2014-01-01

    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 s...

  8. "Data Day" and "Data Night" Definitions - Towards Producing Seamless Global Satellite Imagery

    Science.gov (United States)

    Schmaltz, J. E.

    2017-12-01

    For centuries, the art and science of cartography has struggled with the challenge of mapping the round earth on to a flat page, or a flat computer monitor. Earth observing satellites with continuous monitoring of our planet have added the additional complexity of the time dimension to this procedure. The most common current practice is to segment this data by 24-hour Coordinated Universal Time (UTC) day and then split the day into sun side "Data Day" and shadow side "Data Night" global imagery that spans from dateline to dateline. Due to the nature of satellite orbits, simply binning the data by UTC date produces significant discontinuities at the dateline for day images and at Greenwich for night images. Instead, imagery could be generated in a fashion that follows the spatial and temporal progression of the satellite which would produce seamless imagery everywhere on the globe for all times. This presentation will explore approaches to produce such imagery but will also address some of the practical and logistical difficulties in implementing such changes. Topics will include composites versus granule/orbit based imagery, day/night versus ascending/descending definitions, and polar versus global projections.

  9. 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.

  10. 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

  11. 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...

  12. 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.

  13. Improved wetland classification using eight-band high-resolution satellite imagery and a hybrid approach

    Science.gov (United States)

    Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of derived wetland maps were limited or often unsatisfactory largely due to the relatively coarse spatial resolution of conventional satellite imagery. This re...

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

    Indian Academy of Sciences (India)

    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 ...

  15. Identification of High-Variation Fields based on Open Satellite Imagery

    DEFF Research Database (Denmark)

    Jeppesen, Jacob Høxbroe; Jacobsen, Rune Hylsberg; Nyholm Jørgensen, Rasmus

    2017-01-01

    This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective. The categorizat...... of satellite imagery, hence coupling the geospatial data analysis to direct improvements for the farmers, contractors, and consultants....

  16. Visualization of Surface Processes over Space and Time using a Long Series of Satellite Based Imagery

    Science.gov (United States)

    Harris, T.; Schafer, R.; Hulslander, D.; O'Connor, A. S.; Wolfe, J.

    2014-12-01

    With the increasing diversity and long temporal record of satellite-based Earth imagery, we have new opportunities to better understand and predict Earth surface processes and activities. Satellite-based imagery is an increasingly important resource for analyzing changes in vegetation and land use, as well as monitoring the evolution of hazards and environmental conditions. A key requirement for exploitation of this imagery is visualization and extraction of multimodal data over space and time. Analysis of this imagery requires four primary components: 1) Assignment of acquisition time, spatial reference, and parameter descriptions, 2) Preprocessing including radiometric calibration, generation of derived parameters such as NDVI, and normalization to a common spatial grid, 3) Cataloging and access for discovering and extracting data through space, parameter, and time, and 4) Visualization techniques including animation, parameter-time, space-time, and space-frequency plots. Using ENVI, we will demonstrate how Landsat, MODIS, and Suomi NPP VIIRS data products can be prepared and visualized for exploring the evolution of processes and activities. Visual animation through a temporal stack of imagery is used to quickly understand trends in urban growth, vegetation, and land use. After exploring the temporal stack of images, spatio-temporal and periodic relationships are visualized using space-time and space-frequency representations of the data. Satellite-based imagery is a primary source of data for understanding global changes over time. To understand processes and activities, it is now increasingly important for data exploitation tools such as ENVI to easily extract data from multiple satellite-based sensors and visualize this multimodal data in both space and time.

  17. Nonlinear bias compensation of ZiYuan-3 satellite imagery with cubic splines

    Science.gov (United States)

    Cao, Jinshan; Fu, Jianhong; Yuan, Xiuxiao; Gong, Jianya

    2017-11-01

    Like many high-resolution satellites such as the ALOS, MOMS-2P, QuickBird, and ZiYuan1-02C satellites, the ZiYuan-3 satellite suffers from different levels of attitude oscillations. As a result of such oscillations, the rational polynomial coefficients (RPCs) obtained using a terrain-independent scenario often have nonlinear biases. In the sensor orientation of ZiYuan-3 imagery based on a rational function model (RFM), these nonlinear biases cannot be effectively compensated by an affine transformation. The sensor orientation accuracy is thereby worse than expected. In order to eliminate the influence of attitude oscillations on the RFM-based sensor orientation, a feasible nonlinear bias compensation approach for ZiYuan-3 imagery with cubic splines is proposed. In this approach, no actual ground control points (GCPs) are required to determine the cubic splines. First, the RPCs are calculated using a three-dimensional virtual control grid generated based on a physical sensor model. Second, one cubic spline is used to model the residual errors of the virtual control points in the row direction and another cubic spline is used to model the residual errors in the column direction. Then, the estimated cubic splines are used to compensate the nonlinear biases in the RPCs. Finally, the affine transformation parameters are used to compensate the residual biases in the RPCs. Three ZiYuan-3 images were tested. The experimental results showed that before the nonlinear bias compensation, the residual errors of the independent check points were nonlinearly biased. Even if the number of GCPs used to determine the affine transformation parameters was increased from 4 to 16, these nonlinear biases could not be effectively compensated. After the nonlinear bias compensation with the estimated cubic splines, the influence of the attitude oscillations could be eliminated. The RFM-based sensor orientation accuracies of the three ZiYuan-3 images reached 0.981 pixels, 0.890 pixels, and 1

  18. 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...

  19. 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...

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

    International Nuclear Information System (INIS)

    Andersson, Christer

    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

  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. Creating soil moisture maps based on radar satellite imagery

    Science.gov (United States)

    Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

    2017-10-01

    The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

  3. Evaluation of non-point source pollution reduction by applying best management practices using a SWAT model and QuickBird high resolution satellite imagery.

    Science.gov (United States)

    Lee, MiSeon; Park, GeunAe; Park, MinJi; Park, JongYoon; Lee, JiWan; Kim, SeongJoon

    2010-01-01

    This study evaluated the reduction effect of non-point source pollution by applying best management practices (BMPs) to a 1.21 km2 small agricultural watershed using a SWAT (Soil and Water Assessment Tool) model. Two meter QuickBird land use data were prepared for the watershed. The SWAT was calibrated and validated using daily streamflow and monthly water quality (total phosphorus (TP), total nitrogen (TN), and suspended solids (SS)) records from 1999 to 2000 and from 2001 to 2002. The average Nash and Sutcliffe model efficiency was 0.63 for the streamflow and the coefficients of determination were 0.88, 0.72, and 0.68 for SS, TN, and TP, respectively. Four BMP scenarios viz. the application of vegetation filter strip and riparian buffer system, the regulation of Universal Soil Loss Equation P factor, and the fertilizing control amount for crops were applied and analyzed.

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

    International Nuclear Information System (INIS)

    Zimmerman, P.D.

    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

  5. Connecting Swath Satellite Data With Imagery in Mapping Applications

    Science.gov (United States)

    Thompson, C. K.; Hall, J. R.; Penteado, P. F.; Roberts, J. T.; Zhou, A. Y.

    2016-12-01

    Visualizations of gridded science data products (referred to as Level 3 or Level 4) typically provide a straightforward correlation between image pixels and the source science data. This direct relationship allows users to make initial inferences based on imagery values, facilitating additional operations on the underlying data values, such as data subsetting and analysis. However, that same pixel-to-data relationship for ungridded science data products (referred to as Level 2) is significantly more challenging. These products, also referred to as "swath products", are in orbital "instrument space" and raster visualization pixels do not directly correlate to science data values. Interpolation algorithms are often employed during the gridding or projection of a science dataset prior to image generation, introducing intermediary values that separate the image from the source data values. NASA's Global Imagery Browse Services (GIBS) is researching techniques for efficiently serving "image-ready" data allowing client-side dynamic visualization and analysis capabilities. This presentation will cover some GIBS prototyping work designed to maintain connectivity between Level 2 swath data and its corresponding raster visualizations. Specifically, we discuss the DAta-to-Image-SYstem (DAISY), an indexing approach for Level 2 swath data, and the mechanisms whereby a client may dynamically visualize the data in raster form.

  6. Accessing Cloud Properties and Satellite Imagery: A tool for visualization and data mining

    Science.gov (United States)

    Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.

    2016-12-01

    Providing public access to imagery of cloud macro and microphysical properties and the underlying satellite imagery is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and system that allows end users to easily browse cloud information and satellite imagery that is otherwise difficult to acquire and manipulate. The tool has two uses, one to visualize the data and the other to access the data directly. It uses a widely used access protocol, the Open Geospatial Consortium's Web Map and Processing Services, to encourage user to access the data we produce. Internally, we leverage our practical experience with large, scalable application practices to develop a system that has the largest potential for scalability as well as the ability to be deployed on the cloud. One goal of the tool is to provide a demonstration of the back end capability to end users so that they can use the dynamically generated imagery and data as an input to their own work flows or to set up data mining constraints. We build upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product information and satellite imagery accessible and easily searchable. Increasingly, information is used in a "mash-up" form where multiple sources of information are combined to add value to disparate but related information. In support of NASA strategic goals, our group aims to make as much cutting edge scientific knowledge, observations and products available to the citizen science, research and interested communities for these kinds of "mash-ups" as well as provide a means for automated systems to data mine our information. This tool and access method provides a valuable research tool to a wide audience both as a standalone research tool and also as an easily accessed data source that can easily be mined or used with existing tools.

  7. Comparison of different digital elevation models and satellite imagery for lineament analysis: Implications for identification and spatial arrangement of fault zones in crystalline basement rocks of the southern Black Forest (Germany)

    Science.gov (United States)

    Meixner, J.; Grimmer, J. C.; Becker, A.; Schill, E.; Kohl, T.

    2018-03-01

    GIS-based remote sensing techniques and lineament mapping provide additional information on the spatial arrangement of faults and fractures in large areas with variable outcrop conditions. Due to inherent censoring and truncation bias mapping of lineaments is still a challenging task. In this study we show how statistical evaluations help to improve the reliability of lineament mappings by comparing two digital elevation models (ASTER, LIDAR) and satellite imagery data sets in the seismically active southern Black Forest. A statistical assessment of the orientation, average length, and the total length of mapped lineaments reveals an impact of the different resolutions of the data sets that allow to define maximum (censoring bias) and minimum (truncation bias) observable lineament length for each data set. The increase of the spatial resolution of the digital elevation model from 30 m × 30 m to 5 m × 5 m results in a decrease of total lineament length by about 40% whereby the average lineament lengths decrease by about 60%. Lineament length distributions of both data sets follow a power law distribution as documented elsewhere for fault and fracture systems. Predominant NE-, N-, NNW-, and NW-directions of the lineaments are observed in all data sets and correlate with well-known, mappable large-scale structures in the southern Black Forest. Therefore, mapped lineaments can be correlated with faults and hence display geological significance. Lineament density in the granite-dominated areas is apparently higher than in the gneiss-dominated areas. Application of a slip- and dilation tendency analysis on the fault pattern reveals largest reactivation potentials for WNW-ESE and N-S striking faults as strike-slip faults whereas normal faulting may occur along NW-striking faults within the ambient stress field. Remote sensing techniques in combination with highly resolved digital elevation models and a slip- and dilation tendency analysis thus can be used to quickly get

  8. Spatiotemporal estimation of air temperature patterns at the street level using high resolution satellite imagery.

    Science.gov (United States)

    Pelta, Ran; Chudnovsky, Alexandra A

    2017-02-01

    Although meteorological monitoring stations provide accurate measurements of Air Temperature (AT), their spatial coverage within a given region is limited and thus is often insufficient for exposure and epidemiological studies. In many applications, satellite imagery measures energy flux, which is spatially continuous, and calculates Brightness Temperature (BT) that used as an input parameter. Although both quantities (AT-BT) are physically related, the correlation between them is not straightforward, and varies daily due to parameters such as meteorological conditions, surface moisture, land use, satellite-surface geometry and others. In this paper we first investigate the relationship between AT and BT as measured by 39 meteorological stations in Israel during 1984-2015. Thereafter, we apply mixed regression models with daily random slopes to calibrate Landsat BT data with monitored AT measurements for the period 1984-2015. Results show that AT can be predicted with high accuracy by using BT with high spatial resolution. The model shows relatively high accuracy estimation of AT (R 2 =0.92, RMSE=1.58°C, slope=0.90). Incorporating meteorological parameters into the model generates better accuracy (R 2 =0.935) than the AT-BT model (R 2 =0.92). Furthermore, based on the relatively high model accuracy, we investigated the spatial patterns of AT within the study domain. In the latter we focused on July-August, as these two months are characterized by relativity stable synoptic conditions in the study area. In addition, a temporal change in AT during the last 30years was estimated and verified using available meteorological stations and two additional remote sensing platforms. Finally, the impact of different land coverage on AT were estimated, as an example of future application of the presented approach. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Diurnal changes in ocean color sensed in satellite imagery

    Science.gov (United States)

    Arnone, Robert; Vandermuelen, Ryan; Soto, Inia; Ladner, Sherwin; Ondrusek, Michael; Yang, Haoping

    2017-07-01

    Measurements of diurnal changes in ocean color in turbid coastal regions in the Gulf of Mexico were characterized using above water spectral radiometry from a National Aeronautics and Space Administration (aerosol robotic network-WaveCIS CSI-06) site that can provide 8 to 10 observations per day. Satellite capability to detect diurnal changes in ocean color was characterized using hourly overlapping afternoon orbits of the visual infrared imaging radiometer suite (VIIRS) Suomi National Polar-orbiting Partnership ocean color sensor and validated with in situ observations. The monthly cycle of diurnal changes was investigated for different water masses using VIIRS overlaps. Results showed the capability of satellite observations to monitor hourly color changes in coastal regions that can be impacted by vertical movement of optical layers, in response to tides, resuspension, and river plume dispersion. The spatial variability of VIIRS diurnal changes showed the occurrence and displacement of phytoplankton blooming and decaying processes. The diurnal change in ocean color was above 20%, which represents a 30% change in chlorophyll-a. Seasonal changes in diurnal ocean color for different water masses suggest differences in summer and winter responses to surface processes. The diurnal changes observed using satellite ocean color can be used to define the following: surface processes associated with biological activity, vertical changes in optical depth, and advection of water masses.

  10. Satellite estimates of urban development for hydrological modelling

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin

    We investigate the applicability of medium resolution Landsat satellite imagery for mapping temporal changes in urban land cover in European cities for direct use in urban flood models. The overarching aim is to provide accurate and costand resource-efficient quantification of temporal changes...

  11. Monitoring Trends in Light Pollution in China Based on Nighttime Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Pengpeng Han

    2014-06-01

    Full Text Available China is the largest developing country worldwide, with rapid economic growth and the highest population. Light pollution is an environmental factor that significantly influences the quality and health of wildlife, as well as the people of any country. The objective of this study is to model the light pollution spatial pattern, and monitor changes in trends of spatial distribution from 1992 to 2012 in China using nighttime light imagery from the Defense Meteorological Satellite Program Operational Linescan System. Based on the intercalibration of nighttime light imageries of the study area from 1992 to 2012, this study obtained the change trends map. This result shows an increase in light pollution of the study area; light pollution in the spatial scale increased from 2.08% in the period from 1992–1996 to 2000–2004, to 5.64% in the period from 2000–2004 to 2008–2012. However, light pollution change trends presented varying styles in different regions and times. In the 1990s, the increasing trend in light pollution regions mostly occurred in larger urban cities, which are mainly located in eastern and coastal areas, whereas the decreasing trend areas were chiefly industrial and mining cities rich in mineral resources, in addition to the central parts of large cities. Similarly, the increasing trend regions dominated urban cities of the study area, and the expanded direction changed from larger cities to small and middle-sized cities and towns in the 2000s. The percentages of regions where light pollution transformed to severe and slight were 5.64% and 0.39%, respectively. The results can inform and help identify how local economic and environmental decisions influence our global nighttime environment, and assist government agencies in creating environmental protection measures.

  12. 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...

  13. MODIS Rapid Response: On-the-ground, real time applications of scientific satellite imagery

    Science.gov (United States)

    Schmaltz, J. E.; Riebeek, H.; Kendall, J. D.

    2009-12-01

    Since 2001, NASA’s MODIS Rapid Response Project has been providing fire detections and imagery in near real time for a wide variety of application users. The project web site provides MODIS imagery in true color and false color band combinations, a vegetation index, and land surface temperature - in both uncorrected swath format and geographically corrected subset regions within a few hours of data acquisition. The uncorrected swath format data is available worldwide. Geographically corrected subset images cover the world's land areas and adjoining waters, as well as the entire Arctic and Antarctic. Images are available twice daily, in the morning from the Terra satellite and in the afternoon from the Aqua satellite. A wide range of user communities access this information to get a rapid, 250 meter-resolution overview of ground conditions for fire management, crop and famine monitoring and forecasting, disaster response (floods, storms), dust and aerosol monitoring, aviation (tracking volcanic ash), monitoring sea ice conditions, environmental monitoring, and more. The scientific community uses imagery to locate phenomena of interest prior to ordering and processing data and to support the day-to-day planning of field campaigns. Rapid Response imagery is used extensively to support education and public outreach, both by NASA and other organizations, and is frequently found in newspapers, books, TV, and the web. California wildfires, 26 October 2003, Terra MODIS

  14. Evaluation of Distribution and Display Systems for Satellite Imagery. Phase I.

    Science.gov (United States)

    1982-03-01

    and Display Systems for Satellite Imagery (Phase 1) John Henline James Talotta rmuif Pepared by FAA Technical Center Atlantic City Airport, N.J...operational procedures, and system configurations. in accomplishing these objectives, the question of cathode-ray tube (CRT) versus hardcopy display of...All questions were phrased so that careful reading would result in fair responses, thus precluding stereotype answers. Also, response categories

  15. Inferring Species Richness and Turnover by Statistical Multiresolution Texture Analysis of Satellite Imagery

    Science.gov (United States)

    2012-10-24

    ecosystem characterization. Biogeoscience 54: 511–521. 42. Jeffreys C (2004) Support vector machine and parametric wavelet-based texture... machine classification of human embryonic stem cells. International Symposium on Biomedical Imaging: 284–287. 44. Mangoubi R, Desai M, Sammak P (2008) Non...spectral resolution in estimating ecosystem a-diversity by satellite imagery. Remote Sensing of Environment 111: 423–434. 62. Wang C, Menenti M, Stoll MP

  16. Some Aspects of Satellite Imagery Integration from Eros B and Landsat 8

    Science.gov (United States)

    Fryskowska, A.; Wojtkowska, M.; Delis, P.; Grochala, A.

    2016-06-01

    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.

  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. Geometric Positioning for Satellite Imagery without Ground Control Points by Exploiting Repeated Observation

    Directory of Open Access Journals (Sweden)

    Zhenling Ma

    2017-01-01

    Full Text Available With the development of space technology and the performance of remote sensors, high-resolution satellites are continuously launched by countries around the world. Due to high efficiency, large coverage and not being limited by the spatial regulation, satellite imagery becomes one of the important means to acquire geospatial information. This paper explores geometric processing using satellite imagery without ground control points (GCPs. The outcome of spatial triangulation is introduced for geo-positioning as repeated observation. Results from combining block adjustment with non-oriented new images indicate the feasibility of geometric positioning with the repeated observation. GCPs are a must when high accuracy is demanded in conventional block adjustment; the accuracy of direct georeferencing with repeated observation without GCPs is superior to conventional forward intersection and even approximate to conventional block adjustment with GCPs. The conclusion is drawn that taking the existing oriented imagery as repeated observation enhances the effective utilization of previous spatial triangulation achievement, which makes the breakthrough for repeated observation to improve accuracy by increasing the base-height ratio and redundant observation. Georeferencing tests using data from multiple sensors and platforms with the repeated observation will be carried out in the follow-up research.

  19. Satellite Imagery and In-situ Data Overlay Approach for Fishery Zonation

    Directory of Open Access Journals (Sweden)

    Fardhi Adria

    2010-12-01

    Full Text Available Remote sensing technology can be used to better understand the earth’s characteristics. SeaWiFS (sea-viewing wide field-of-view sensor is one of remote sensors used to observe global ocean phenomena. Previous studies showed that the distribution of chlorophyll-a in the ocean indicates the presence of fish. However, only a few studies tried to directly relate the chlorophyll-a distribution obtained through interpretation of satellite imagery to in-situ data of fish distribution. This paper investigates the relation between chlorophyll-a distribution and fish-capturing points in Aceh Province sea waters using overlay image analysis. The results are then used to identify the potential fishing ground in Aceh. The profile of chlorophyll-a concentration is derived from SeaWIFS satellite imagery. Fish-capturing points data is obtained from the fisherman communities of Banda Aceh, starting from June to November 2008. The results showed that the chlorophyll-a profile derived from satellite imagery has a positive relationship to fish-capturing point data. The most potential fish-capturing zone in Aceh sea waters is identified at 5-8º north latitude (N and 96-99º east longitude (E.

  20. 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.

  1. Best practice approaches for applying satellite imagery for landscape archaeological applications: a case study from the world heritage site of Sanchi, India

    Science.gov (United States)

    Beck, A.; Shaw, J.; Stott, D.

    2007-10-01

    Satellite imagery is an increasingly important tool for cultural and natural heritage management. It has particular relevance in those areas of the world where the heritage resource is poorly understood. In these areas what is known may be significantly biased: i.e. heritage management strategies may have been skewed towards a specific type of remain (normally monumental architecture). This paper will present work undertaken in the landscape around the UNESCO World Heritage site of Sanchi, a major early-historic Buddhist site in Madhya Pradesh, India. Rather than discuss the merits of individual sensors this paper takes a more holistic approach and examines the 'life-cycle' of satellite imagery for an archaeological project. This means that satellite imagery is viewed not just as a source of archaeological information but also as a data source that can be used to contextualise and interpret the archaeological resource. Hence this paper provides a framework which should allow archaeological investigators to select, manipulate and integrate different satellite sensors to provide information which is fit for purpose. This paper discusses the implications of satellite sensors for different activities, including archaeological prospection, landuse mapping and terrain modeling and considers how the synergies of different satellite and archaeological data can be exploited.

  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. Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring

    Directory of Open Access Journals (Sweden)

    Jana Müllerová

    2017-05-01

    Full Text Available The rapid spread of invasive plants makes their management increasingly difficult. Remote sensing offers a means of fast and efficient monitoring, but still the optimal methodologies remain to be defined. The seasonal dynamics and spectral characteristics of the target invasive species are important factors, since, at certain time of the vegetation season (e.g., at flowering or senescing, plants are often more distinct (or more visible beneath the canopy. Our aim was to establish fast, repeatable and a cost-efficient, computer-assisted method applicable over larger areas, to reduce the costs of extensive field campaigns. To achieve this goal, we examined how the timing of monitoring affects the detection of noxious plant invaders in Central Europe, using two model herbaceous species with markedly different phenological, structural, and spectral characteristics. They are giant hogweed (Heracleum mantegazzianum, a species with very distinct flowering phase, and the less distinct knotweeds (Fallopia japonica, F. sachalinensis, and their hybrid F. × bohemica. The variety of data generated, such as imagery from purposely-designed, unmanned aircraft vehicle (UAV, and VHR satellite, and aerial color orthophotos enabled us to assess the effects of spectral, spatial, and temporal resolution (i.e., the target species' phenological state for successful recognition. The demands for both spatial and spectral resolution depended largely on the target plant species. In the case that a species was sampled at the most distinct phenological phase, high accuracy was achieved even with lower spectral resolution of our low-cost UAV. This demonstrates that proper timing can to some extent compensate for the lower spectral resolution. The results of our study could serve as a basis for identifying priorities for management, targeted at localities with the greatest risk of invasive species' spread and, once eradicated, to monitor over time any return. The best mapping

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    P. Fischer

    2018-04-01

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

  6. Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution

    Science.gov (United States)

    LaRue, Michelle A.; Stapleton, Seth P.; Porter, Claire; Atkinson, Stephen N.; Atwood, Todd C.; Dyck, Markus; Lecomte, Nicolas

    2015-01-01

    High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. Forecasting Transplanted Rice Yield at the Farm Scale Using Moderate-Resolution Satellite Imagery and the AquaCrop Model: A Case Study of a Rice Seed Production Community in Thailand

    OpenAIRE

    Kulapramote Prathumchai; Masahiko Nagai; Nitin K. Tripathi; Nophea Sasaki

    2018-01-01

    Thailand has recently introduced agricultural policies to promote large-scale rice farming through supporting and integrating small-scale farmers. However, achieving these policies requires agricultural tools that can assist farmers in rice farming planning and management. Crop models, along with remote sensing technologies, can be useful for farmers and field managers in this regard. In this study, we used the AquaCrop model along with moderate-resolution satellite images (30 m) to simulate ...

  14. Portable devices for delivering imagery and modelling interventions ...

    African Journals Online (AJOL)

    The main objective of this study was to investigate the effectiveness of portable devices (MP4) and a stationary device (DVD and fixed point stationary computer) in delivering imagery and modelling training among female netball players, examining the effect on imagery adherence, performance, self-efficacy, and the relative ...

  15. Assessing the Effects of Forest Fragmentation Using Satellite Imagery and Forest Inventory Data

    Science.gov (United States)

    Ronald E. McRoberts; Greg C. Liknes

    2005-01-01

    For a study area in the North Central region of the USA, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and forest attributes observed on...

  16. A fuzzy decision making system for building damage map creation using high resolution satellite imagery

    Science.gov (United States)

    Rastiveis, H.; Samadzadegan, F.; Reinartz, P.

    2013-02-01

    Recent studies have shown high resolution satellite imagery to be a powerful data source for post-earthquake damage assessment of buildings. Manual interpretation of these images, while being a reliable method for finding damaged buildings, is a subjective and time-consuming endeavor, rendering it unviable at times of emergency. The present research, proposes a new state-of-the-art method for automatic damage assessment of buildings using high resolution satellite imagery. In this method, at the first step a set of pre-processing algorithms are performed on the images. Then, extracting a candidate building from both pre- and post-event images, the intact roof part after an earthquake is found. Afterwards, by considering the shape and other structural properties of this roof part with its pre-event condition in a fuzzy inference system, the rate of damage for each candidate building is estimated. The results obtained from evaluation of this algorithm using QuickBird images of the December 2003 Bam, Iran, earthquake prove the ability of this method for post-earthquake damage assessment of buildings.

  17. Using Online Citizen Science to Assess Giant Kelp Abundances Across the Globe with Satellite Imagery

    Science.gov (United States)

    Byrnes, J.; Cavanaugh, K. C.; Haupt, A. J.; Trouille, L.; Rosenthal, I.; Bell, T. W.; Rassweiler, A.; Pérez-Matus, A.; Assis, J.

    2017-12-01

    Global scale long-term data sets that document the patterns and variability of human impacts on marine ecosystems are rare. This lack is particularly glaring for underwater species - even moreso for ecologically important ones. Here we demonstrate how online Citizen Science combined with Landsat satellite imagery can help build a picture of change in the dynamics of giant kelp, an important coastal foundation species around the globe, from the 1984 to the present. Giant kelp canopy is visible from Landsat images, but these images defy easy machine classification. To get useful data, images must be processed by hand. While academic researchers have applied this method successfully at sub-regional scales, unlocking the value of the full global dataset has not been possible until given the massive effort required. Here we present Floating Forests (http://floatingforests.org), an international collaboration between kelp forest researchers and the citizen science organization Zooniverse. Floating Forests provides an interface that allows citizen scientists to identify canopy cover of giant kelp on Landsat images, enabling us to scale up the dataset to the globe. We discuss lessons learned from the initial version of the project launched in 2014, a prototype of an image processing pipeline to bring Landsat imagery to citizen science platforms, methods of assessing accuracy of citizen scientists, and preliminary data from our relaunch of the project. Through this project we have developed generalizable tools to facilitate citizen science-based analysis of Landsat and other satellite and aerial imagery. We hope that this create a powerful dataset to unlock our understanding of how global change has altered these critically important species in the sea.

  18. 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.

  19. Super-Resolution for “Jilin-1” Satellite Video Imagery via a Convolutional Network

    Directory of Open Access Journals (Sweden)

    Aoran Xiao

    2018-04-01

    Full Text Available Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method’s practicality. Experimental results on “Jilin-1” satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

  20. Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.

    Science.gov (United States)

    Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian

    2018-04-13

    Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

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

    Energy Technology Data Exchange (ETDEWEB)

    Lavers, C; Bishop, C; Hawkins, O; Grealey, E; Cox, C; Thomas, D; Trimel, S, E-mail: brnc-radarcomms1@nrta.mod.u [Sensors Team, Plymouth University at Britannia Royal Naval College, Dartmouth (United Kingdom); DMC International Imaging, Tycho House, Surrey Research Park, Guildford (United Kingdom); Qinetiq, Cody Technology Park, Cody Building, Ively Road, Farnborough (United Kingdom); Humanitarian Aid Relief Trust (HART), 3 Arnellan House, Kingsbury, London (United Kingdom); Amnesty International USA, 5 Penn Plaza, New York (United States)

    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.

  2. Assessing Building Vulnerability to Tsunami Hazards using Very High Resolution Satellite Imagery (Case : Cilacap, Indonesia)

    Science.gov (United States)

    Sumaryono, S.; Strunz, G.; Ludwig, R.; Post, J.; Zosseder, K.; Mück, M.

    2009-04-01

    The big tsunami disaster occurring on 26 December 2004 has destroyed many cities along the Indian Ocean rim and killed approximately 300,000 people and destroyed buildings and city infrastructures making it the deadliest tsunami as well as one of the deadliest natural disasters in recorded history. Furthermore, there are large numbers of world's cities located near coastal lines prone to tsunami hazard. Anticipation measures and disaster mitigation must be taken in order to minimize the negative impacts that may hit those living and built in the cities. The assessment of building vulnerability is an important measure in order to minimize disaster risks to the city. Measuring vulnerability for large number of buildings using conventional method is time consuming and costly. This paper offers a comprehensive framework in assessing building vulnerability by combining field assessment and remote sensing techniques. Field assessment was based on quantitative and qualitative building structural analysis and remote sensing technique was undertaken using object-oriented classification. Very high resolution satellite imagery (quickbird) and elevation data were employed in the remote sensing technique. Each building in the study area was classified automatically into 4 classes (Class A, B, C and Vertical Evacuation) based on their level of vulnerability to tsunami hazard using parameters extracted from remotely sensed data. This paper presents results from Cilacap City, South coast of Java, Indonesia. The research work was performed in the framework of the GITEWS project. The results show that remote sensing and GIS approaches are promising to be applied to measure building vulnerability to tsunami hazards. Outcomes of the research consist of : new concepts in assessing urban vulnerability to tsunami hazard, new algorithm for extracting information from very high resolution satellite images, map of building vulnerability and recommendations concerning to urban vulnerability

  3. 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

  4. Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

    Science.gov (United States)

    Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

    2018-03-01

    High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

  5. 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

  6. Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas

    Science.gov (United States)

    Wu, Bo; Xie, Linfu; Hu, Han; Zhu, Qing; Yau, Eric

    2018-05-01

    Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies. Recent developments in aerial oblique photogrammetry based on aircraft or unmanned aerial vehicles (UAVs) offer promising techniques for 3D modeling. However, 3D models generated from aerial oblique imagery in urban areas with densely distributed high-rise buildings may show geometric defects and blurred textures, especially on building façades, due to problems such as occlusion and large camera tilt angles. Meanwhile, mobile mapping systems (MMSs) can capture terrestrial images of close-range objects from a complementary view on the ground at a high level of detail, but do not offer full coverage. The integration of aerial oblique imagery with terrestrial imagery offers promising opportunities to optimize 3D modeling in urban areas. This paper presents a novel method of integrating these two image types through automatic feature matching and combined bundle adjustment between them, and based on the integrated results to optimize the geometry and texture of the 3D models generated from aerial oblique imagery. Experimental analyses were conducted on two datasets of aerial and terrestrial images collected in Dortmund, Germany and in Hong Kong. The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas.

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

    NARCIS (Netherlands)

    Pasquale, Di Aurelio; Mc Cann, Robert; 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

  8. 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.

  9. Location of irrigated land classified from satellite imagery - High Plains Area, nominal date 1992

    Science.gov (United States)

    Qi, Sharon L.; Konduris, Alexandria; Litke, David W.; Dupree, Jean

    2002-01-01

    Satellite imagery from the Landsat Thematic Mapper (nominal date 1992) was used to classify and map the location of irrigated land overlying the High Plains aquifer. The High Plains aquifer underlies 174,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. The U.S. Geological Survey is conducting a water-quality study of the High Plains aquifer as part of the National Water-Quality Assessment Program. To help interpret data and select sites for the study, it is helpful to know the location of irrigated land within the study area. To date, the only information available for the entire area is 20 years old. To update the data on irrigated land, 40 summer and 40 spring images (nominal date 1992) were acquired from the National Land Cover Data set and processed using a band-ratio method (Landsat Thematic Mapper band 4 divided by band 3) to enhance the vegetation signatures. The study area was divided into nine subregions with similar environmental characteristics, and a band-ratio threshold was selected from imagery in each subregion that differentiated the cutoff between irrigated and nonirrigated land. The classified images for each subregion were mosaicked to produce an irrigated-land map for the study area. The total amount of irrigated land classified from the 1992 imagery was 13.1 million acres, or about 12 percent of the total land in the High Plains. This estimate is approximately 1.5 percent greater than the amount of irrigated land reported in the 1992 Census of Agriculture (12.8 millions acres).

  10. 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.

  11. 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...

  12. 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.

  13. Monitoring Termite-Mediated Ecosystem Processes Using Moderate and High Resolution Satellite Imagery

    Science.gov (United States)

    Lind, B. M.; Hanan, N. P.

    2016-12-01

    Termites are considered dominant decomposers and prominent ecosystem engineers in the global tropics and they build some of the largest and architecturally most complex non-human-made structures in the world. Termite mounds significantly alter soil texture, structure, and nutrients, and have major implications for local hydrological dynamics, vegetation characteristics, and biological diversity. An understanding of how these processes change across large scales has been limited by our ability to detect termite mounds at high spatial resolutions. Our research develops methods to detect large termite mounds in savannas across extensive geographic areas using moderate and high resolution satellite imagery. We also investigate the effect of termite mounds on vegetation productivity using Landsat-8 maximum composite NDVI data as a proxy for production. Large termite mounds in arid and semi-arid Senegal generate highly reflective `mound scars' with diameters ranging from 10 m at minimum to greater than 30 m. As Sentinel-2 has several bands with 10 m resolution and Landsat-8 has improved calibration, higher radiometric resolution, 15 m spatial resolution (pansharpened), and improved contrast between vegetated and bare surfaces compared to previous Landsat missions, we found that the largest and most influential mounds in the landscape can be detected. Because mounds as small as 4 m in diameter are easily detected in high resolution imagery we used these data to validate detection results and quantify omission errors for smaller mounds.

  14. Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

    Science.gov (United States)

    Freire, S.; Santos, T.; Navarro, A.; Soares, F.; Silva, J. D.; Afonso, N.; Fonseca, A.; Tenedório, J.

    2014-04-01

    Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000.

  15. 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.

  16. Classification of irrigated land using satellite imagery, the High Plains aquifer, nominal date 1992

    Science.gov (United States)

    Qi, Sharon L.; Konduris, Alexandria; Litke, David W.; Dupree, Jean

    2002-01-01

    Satellite imagery from the Landsat Thematic Mapper (nominal date 1992) was used to classify and map the location of irrigated land across the High Plains aquifer. The High Plains aquifer underlies 174,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. The U.S. Geological Survey is conducting a waterquality study of the High Plains aquifer as part of the National Water-Quality Assessment Program. To help interpret data and select sites for the study, it is helpful to know the location of irrigated land within the study area. To date, the only information available for the entire area is 20 years old. To update the data on irrigated land, 40 summer and 40 spring images (nominal date 1992) were acquired from the National Land Cover Data set and processed using a band-ratio method (Landsat Thematic Mapper band 4 divided by band 3) to enhance the vegetation signatures. The study area was divided into nine subregions with similar environmental characteristics, and a band-ratio threshold was selected from imagery in each subregion that differentiated the cutoff between irrigated and nonirrigated land. The classified images for each subregion were mosaicked to produce an irrigated land map for the study area. The total amount of irrigated land classified from the 1992 imagery was 13.1 million acres, or about 12 percent of the total land in the High Plains. This estimate is approximately 1.5 percent greater than the amount of irrigated land reported in the 1992 Census of Agriculture (12.8 millions acres). This information was also compared to a similar data set based on 1980 imagery. The 1980 data classified 13.7 million acres as irrigated. Although the change in the amount of irrigated land between the two times was not substantial, the location of the irrigated land did shift from areas where there were large ground-water-level declines to other areas where ground-water levels were static or rising.

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

    Science.gov (United States)

    Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

    2017-10-01

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

  18. BOTTOM TYPES IDENTIFICATION IN SHALLOW CORAL REEF ECOSYSTEMS USING IMAGERY SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    MASITA DWI MANDINI MANESSA

    2015-06-01

    Full Text Available Satellite data provide information about spectral signatures of objects in detail, based on the wide range of spectral wavelengths. Bottom types in a coral reef Ecosystems are diverse and each object has a different spectral signature. The aim of this research is to define bottom types using Multispectral and Hyperspectral imagery satellite data. Six processes were applied to Hyperspectral Images to identified bottom types using modification of Analytical Imaging and Geophysics LLC (AIG hyperspectral analysis. The multispectral analysis was focused on correcting water column noise by applying the radiative water column algorithm (Lyzenga, 1978, 1981 and the modified image correction algorithm (Lyzenga et al., 2006. The results showed that multispectral image analysis was able to identify a fine complexity of b bottom types classes with 68.57% overall accuracy. In contrast, Hyperion image identified a coarse complexity of bottom types classes with 61.57% overall accuracy. This low result was caused by low spatial resolution which created a mixing pixel around image of thin and narrow shallow coral reef ecosystem. Spatial resolution, atmosphere and water scattering played an important role in bottom types identification.

  19. Assessment on spatiotemporal relationship between rainfall and cloud top temperature from new generation weather satellite imagery

    Science.gov (United States)

    Wei, Chiang; Yeh, Hui-Chung; Chen, Yen-Chang

    2017-04-01

    This study addressed the relationship between rainfall and cloud top temperature (CCT) from new generation satellite Himawari-8 imagery at different spatiotemporal scale. This satellite provides higher band, more bits for data format, spatial and temporal resolution compared with previous GMS series. The multi-infrared channels with 10-minute and 1-2 km resolution make it possible for rainfall estimating/forecasting in small/medium watershed. The preliminary result investigated at Chenyulan watershed (443.6 square kilometer) of Central Taiwan in 2016 Typhoon Megi shows the regression coefficient fitted by negative exponential equation of largest rainfall vs. CCT (B8 band) at pixel scale increases as time scales enlarges and reach 0.462 for 120-minute accumulative rainfall; the value (CTT of B15 band) decreases from 0.635 for 10-minute to 0.423 for 120-minute accumulative rainfall at basin-wide scale. More rainfall events for different regime are yet to evaluate to get solid results.

  20. Satellite Imagery Application: An Experience In Environmental Sensitivity Index Mapping In Nigeria

    International Nuclear Information System (INIS)

    Abolarin, A.A.O.

    1995-01-01

    Pre-planning for response to emergency, most often, dictates the degree of actual response success, within the region of 'certainty' in risk management. Contingency planning against oil spillage has been recognised as a vital tool in the oil spillage has been recognised as a vital tool in the oil industry. A number of inputs are necessary for an effective Contingency Planning. One of such inputs is the identification of priority areas to be protected or to be allowed only the minimum exposure in the event of a spillage. A modern tool for this prioritizing activity, which is constantly gaining patronage, is the Environmental Sensitivity Index (ESI) Mapping. Satellites have become invaluable sources of information for the indexing and classification purpose. They provide remotely sensed data which could otherwise be obtained at greater costs, at least, in time and money. This paper summarises the Elf Petroleum Nigeria's experience with satellite imagery application for environmental sensitivity indexing purposes. This includes the case studies of the NNPC/Elf OML's 57 (swamp), 58 (land) and 100 (offshore). It provides some background to the technology's data acquisition, and the dilemma of indexing. It is expected that the paper would serve educational and corporate purposes in the industry

  1. 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?

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  3. A technique for determining cloud free vs cloud contaminated pixels in satellite imagery

    Science.gov (United States)

    Wohlman, Richard A.

    1996-01-01

    Since the first earth orbiting satellite sent pictures of the earth back to them, atmospheric scientists have been focused on the possibilities of using that information as both a forecasting tool and as a meteorological research tool. With the latest generation of Geostationary Operational Environmental Satellites (GOES) now entering service, that view of the earth yields views at a frequency and resolution never before available. These satellites have imagers with a five band multi-spectral capability with high spatial resolution. In addition, the sounder has eighteen thermal infrared (IR) channels plus one low-resolution visible band. With a resolution as small as one kilometer, GOES provides scientists with a powerful eye on the atmosphere. Menzel and Purdom (1994) detail both the imager and sounder capability as well as other systems on the GOES satellites. Immediately apparent in the visible channel are the patterns of clouds swirling over both oceans and continents. These clouds range in size from huge planetary systems covering thousands of kilometers to puffy fair weather cumulus clouds on the order of half a kilometer in size. With the IR sensors temperature patterns are observed. High clouds appear very cold, while low stratus field show temperatures near that of the surface. The surface, in turn, generally appears warmer than the clouds. It would seem then a simple manner to determine cloud and surface temperature from the imagery, but such is not the case. While most of the atmospheric constituents are well mixed and homogeneous, water vapor is not. The water molecule, because of its unique structure and vibration modes, affects the transmittance of the atmosphere most notably in the infrared regions. There are regions of the IR spectrum where water vapor acts as a strong absorber, and at others it is nearly transparent. The transparent wavelengths are called windows, and one such window occurs at 11.2 microns. Adjacent to this window at 12.7 microns

  4. 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

  5. Limitations and potential of satellite imagery to monitor environmental response to coastal flooding

    Science.gov (United States)

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

    2012-01-01

    Storm-surge flooding and marsh response throughout the coastal wetlands of Louisiana were mapped using several types of remote sensing data collected before and after Hurricanes Gustav and Ike in 2008. These included synthetic aperture radar (SAR) data obtained from the (1) C-band advance SAR (ASAR) aboard the Environmental Satellite, (2) phased-array type L-band SAR (PALSAR) aboard the Advanced Land Observing Satellite, and (3) optical data obtained from Thematic Mapper (TM) sensor aboard the Land Satellite (Landsat). In estuarine marshes, L-band SAR and C-band ASAR provided accurate flood extent information when depths averaged at least 80 cm, but only L-band SAR provided consistent subcanopy detection when depths averaged 50 cm or less. Low performance of inundation mapping based on C-band ASAR was attributed to an apparent inundation detection limit (>30 cm deep) in tall Spartina alterniflora marshes, a possible canopy collapse of shoreline fresh marsh exposed to repeated storm-surge inundations, wind-roughened water surfaces where water levels reached marsh canopy heights, and relatively high backscatter in the near-range portion of the SAR imagery. A TM-based vegetation index of live biomass indicated that the severity of marsh dieback was linked to differences in dominant species. The severest impacts were not necessarily caused by longer inundation but rather could be caused by repeated exposure of the palustrine marsh to elevated salinity floodwaters. Differential impacts occurred in estuarine marshes. The more brackish marshes on average suffered higher impacts than the more saline marshes, particularly the nearshore coastal marshes occupied by S. alterniflora.

  6. Automated estimation of mass eruption rate of volcanic eruption on satellite imagery using a cloud pattern recognition algorithm

    Science.gov (United States)

    Pouget, Solene; Jansons, Emile; Bursik, Marcus; Tupper, Andrew; Patra, Abani; Pitman, Bruce; Carn, Simon

    2014-05-01

    The need to detect and track the position of ash in the atmosphere has been highlighted in the past few years following the eruption Eyjafjallajokull. As a result, Volcanic Ash Advisory Centers (VAACs) are using Volcanic Ash Transport and Dispersion models (VATD) to estimate and predict the whereabouts of the ash in the atmosphere. However, these models require inputs of eruption source parameters, such as the mass eruption rate (MER), and wind fields, which are vital to properly model the ash movements. These inputs might change with time as the eruption enters different phases. This implies tracking the ash movement as conditions change, and new satellite imagery comes in. Thus, ultimately, the eruption must be detectable, regardless of changing eruption source and meteorological conditions. Volcanic cloud recognition can be particularly challenging, especially when meteorological clouds are present, which is typically the case in the tropics. Given the fact that a large fraction of the eruptions in the world happen in a tropical environment, we have based an automated volcanic cloud recognition algorithm on the fact that meteorological clouds and volcanic clouds behave differently. As a result, the pattern definition algorithm detects and defines volcanic clouds as different object types from meteorological clouds on satellite imagery. Following detection and definition, the algorithm then estimates the area covered by the ash. The area is then analyzed with respect to a plume growth rate methodology to get estimation of the volumetric and mass growth with time. This way, we were able to get an estimation of the MER with time, as plume growth is dependent on MER. To test our approach, we used the examples of two eruptions of different source strength, in two different climatic regimes, and for which therefore the weather during the eruption was quite different: Manam (Papua New Guinea) January 27 2005, which produced a stratospheric umbrella cloud and was

  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. 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...

  9. Identifying Small Mine Blasts and Earthquakes in Eastern Kazakhstan using Bulletins, Waveform Correlation and Satellite Imagery

    Science.gov (United States)

    Euler, G. G.; Hartse, H. E.; MacCarthy, J.

    2016-12-01

    Using waveform cross-correlation, 1000 repeating events in the seismic bulletin published by the Kazakhstan National Data Center from 2002 to 2007 were identified. Most of these repeating events could be grouped into 17 clusters that we then relocated by picking phases on the stacked waveforms of seismic stations KURK, MKAR, KKAR, BVAR and ZALV. Inspection of satellite imagery near the relocations identified visual evidence of open-pit mining within 10 km of most of our seismic locations. We then demonstrate that once waveform templates are established for a given mine, continuous data can be scanned to find additional, unreported events from the same mine. In particular, we detect several unreported Kara-Zhyra coal mine explosions from the first half of 2004, and we also find a November, 2009 explosion at the same mine used for the Comprehensive Test-Ban Treaty Organization's National Data Center Preparedness Exercise known as NPE2009. From time-of-day analysis we learned that mine shots in eastern Kazakhstan typically occurred between noon and 1 pm and between 6 and 7 pm local time while less frequent shooting occurred anytime from 6 am up through 8 pm. We also identified one mine that shoots frequently near midnight on Saturdays, which is the first reported seismic evidence in this region of prevalent non-daytime mining activity. Consistent with expectations for mining activity, all reported magnitudes for the mining events were mb ≤ 3.5. We subsequently used this information to create a ground-truth earthquake dataset by selecting (1) events of any magnitude when they occur during hours 21, 22, and 23 UTC (3, 4, and 5 am local time), (2) events of mb ≥ 4.0 regardless of origin time, and (3) any events displaying significant waveform correlation with an event of mb ≥ 4.0. These results show that combining bulletin information, waveform correlation results, and satellite imagery can improve ground-truth data set quality used in seismic research for

  10. Monitoring vegetation change in Abu Dhabi Emirate from 1996 to 2000 and 2004 using Landsat Satellite Imagery

    International Nuclear Information System (INIS)

    Starbuck, M.J.; Tamayo, J.

    2007-01-01

    In the fall of 2001, a study was initiated to investigate vegetation changes in the Abu Dhabi Emirates. The vast majority of vegetation present in the region is irrigated and analysis of vegetation change will support groundwater investigations in the region by indicating areas of increased water use. Satellite-based imaging systems provide a good source of data for such an analysis. The recent analysis was completed between February and November 2002 using Landsat 5 Thematic Mapper satellite imagery acquired in 1996 and Landsat 7 Enhanced Thematic Mapper Plus imagery acquired in 2000. These assessments were augmented in 2004with the study of Landsat 7 imagery acquired in early 2004. The total area of vegetation for each of seven study areas was calculated using the Normalized Difference Vegetation Index (NDVI) technique. Multiband image classification was used to differentiate general vegetation types. Change analysis consisted of simple NDVI image differencing and post-classification change matrices. Measurements of total vegetation are for the Abu Dhabi Emirate indicate an increase from 77,200 hectares in 1996 to 162,700 hectares in 2000 (110% increase). Based on comparison with manual interpretation of satellite imagery, the amount of under-reporting of irrigated land is estimated at about 15% of the actual area. From the assessment of 2004 Landset imagery, it was found that the growth of irrigated vegetation in most areas of Emirate had stabilized and had actually slightly decreased in some cases. The decreases are probably due to variability in the measurement technique and not due to actual decreases in area of vegetation. (author)

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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

  1. DIORAMA Model of Satellite Body Orientation

    Energy Technology Data Exchange (ETDEWEB)

    Werley, Kenneth Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-03-04

    The DIORAMA GPS satellite platform orientation model is described. Satellites need to keep sensors pointed towards the earth and solar panels oriented to face the sun (when not in the earth’s shadow) while they orbit the earth.

  2. 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.

  3. Assessment of building heights from pléiades satellite imagery for ...

    African Journals Online (AJOL)

    A tri-stereoscopic Pléiades satellite scene was used to process a digital surface model. An object-based image analysis provided the basic geometries and respective variables, which served as input features for a Support Vector Machine based classification. The comparison of the building footprints with ground reference ...

  4. Harmonizing estimates of forest land area from national-level forest inventory and satellite imagery

    Science.gov (United States)

    Bonnie Ruefenacht; Mark D. Nelson; Mark Finco

    2009-01-01

    Estimates of forest land area are derived both from national-level forest inventories and satellite image-based map products. These estimates can differ substantially within subregional extents (e.g., states or provinces) primarily due to differences in definitions of forest land between inventory- and image-based approaches. We present a geospatial modeling approach...

  5. 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.

  6. 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

    2016-12-21

    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.

  7. 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, D.; Funk, C.; Galu, G.

    2008-07-01

    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.

  8. A FUZZY AUTOMATIC CAR DETECTION METHOD BASED ON HIGH RESOLUTION SATELLITE IMAGERY AND GEODESIC MORPHOLOGY

    Directory of Open Access Journals (Sweden)

    N. Zarrinpanjeh

    2017-09-01

    Full Text Available Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  9. a Fuzzy Automatic CAR Detection Method Based on High Resolution Satellite Imagery and Geodesic Morphology

    Science.gov (United States)

    Zarrinpanjeh, N.; Dadrassjavan, F.

    2017-09-01

    Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  10. Coastline changes in North Bengkalis Island, Indonesia: satellite imagery analysis and observation

    Directory of Open Access Journals (Sweden)

    M Mubarak

    2018-01-01

    Full Text Available Coastal area activity on human exploitation greatly affected aquatic ecosystems. Land changes disturbed the level of soil stability, soil will be easily eroded by the flow of water, the surface tide ran off to the sea. North waters of the island of Bengkalis is a place boiling down to several rivers, including the river Jangkang and river Liung. The rivers have affected the concentration of total suspended solid (TSS in the strait waters of North Bengkalis Island. This research demonstrated water sampling by using sampling point determined by purposive sampling method mixing the layer of water depth ratio. The results based on satellite imagery data showed that TSS was quite high in the West season period until the transition period I (West to East with a large concentration value of 200 mg / L. For the lowest TSS concentration occurred in the East season i.e., between 0 - 200 mg/L. TSS concentrations that dominated in the East season ranged from 51 to 75 mg/L This value was higher than the TSS concentration of field data analysis, i.e., between 23 - 39 mg/L. Changes of coastal coastline of North Bengkalis during the last 20 years continue to change the size of the land area, with a land area of 131 ha lost.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. Modeling woody vegetation resources using Landsat TM imagery in ...

    African Journals Online (AJOL)

    Modeling woody vegetation resources using Landsat TM imagery in northern Namibia. Alex Verlinden, Risto Laamanen. Abstract. In 1995 a forest inventory covering northern Namibia was initiated, based on stratified systematic field sampling of plots with a radius of up to 30 m. In these plots detailed tree parameters were ...

  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. Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

    Directory of Open Access Journals (Sweden)

    J. G. Williams

    2018-01-01

    Full Text Available Landslides triggered by large earthquakes in mountainous regions contribute significantly to overall earthquake losses and pose a major secondary hazard that can persist for months or years. While scientific investigations of coseismic landsliding are increasingly common, there is no protocol for rapid (hours-to-days humanitarian-facing landslide assessment and no published recognition of what is possible and what is useful to compile immediately after the event. Drawing on the 2015 Mw 7.8 Gorkha earthquake in Nepal, we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated. We find that, at present, many forms of landslide assessment are too slow to generate relative to the speed of a humanitarian response, despite increasingly rapid access to high-quality imagery. Importantly, the value of information on landslides evolves rapidly as a disaster response develops, so identifying the purpose, timescales, and end users of a post-earthquake landslide assessment is essential to inform the approach taken. It is clear that discussions are needed on the form and timing of landslide assessments, and how best to present and share this information, before rather than after an earthquake strikes. In this paper, we share the lessons learned from the Gorkha earthquake, with the aim of informing the approach taken by scientists to understand the evolving landslide hazard in future events and the expectations of the humanitarian community involved in disaster response.

  20. Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

    Science.gov (United States)

    Williams, Jack G.; Rosser, Nick J.; Kincey, Mark E.; Benjamin, Jessica; Oven, Katie J.; Densmore, Alexander L.; Milledge, David G.; Robinson, Tom R.; Jordan, Colm A.; Dijkstra, Tom A.

    2018-01-01

    Landslides triggered by large earthquakes in mountainous regions contribute significantly to overall earthquake losses and pose a major secondary hazard that can persist for months or years. While scientific investigations of coseismic landsliding are increasingly common, there is no protocol for rapid (hours-to-days) humanitarian-facing landslide assessment and no published recognition of what is possible and what is useful to compile immediately after the event. Drawing on the 2015 Mw 7.8 Gorkha earthquake in Nepal, we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM) can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated. We find that, at present, many forms of landslide assessment are too slow to generate relative to the speed of a humanitarian response, despite increasingly rapid access to high-quality imagery. Importantly, the value of information on landslides evolves rapidly as a disaster response develops, so identifying the purpose, timescales, and end users of a post-earthquake landslide assessment is essential to inform the approach taken. It is clear that discussions are needed on the form and timing of landslide assessments, and how best to present and share this information, before rather than after an earthquake strikes. In this paper, we share the lessons learned from the Gorkha earthquake, with the aim of informing the approach taken by scientists to understand the evolving landslide hazard in future events and the expectations of the humanitarian community involved in disaster response.

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

    Directory of Open Access Journals (Sweden)

    J. M. Maurer

    2016-09-01

    Full Text Available 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.

  2. 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

  3. Evaluation of ikonos satellite imagery for detecting ice storm damage to oak forests in Eastern Kentucky

    Science.gov (United States)

    W. Henry McNab; Tracy Roof

    2006-01-01

    Ice storms are a recurring landscape-scale disturbance in the eastern U.S. where they may cause varying levels of damage to upland hardwood forests. High-resolution Ikonos imagery and semiautomated detection of ice storm damage may be an alternative to manually interpreted aerial photography. We evaluated Ikonos multispectral, winter and summer imagery as a tool for...

  4. High-resolution IKONOS satellite imagery for normalized difference vegetative index-related assessment applied to land clearance studies

    Science.gov (United States)

    Lavers, Chris R.; Mason, Travis

    2017-07-01

    High-resolution satellite imagery permits verification of human rights land clearance violations across international borders as a result of unstable regimes or socio-economic upheaval. Without direct access to these areas to validate allegations of human rights abuse, the use of remote sensing tools, techniques, and data is extremely important. Humanitarian assessment can benefit from software-based solutions, involving radiometrically calibrated normalized difference vegetation index and temporal change imagery. We discuss the introduction of a matrix filter approach for change detection studies to help assist rapid building detection over large search areas against a bright background to evaluate internally displaced people in the 2005 Porta Farm Zimbabwe clearances. Future wide-scale near real-time space-based monitoring with a range of digital filters would be of great benefit to international human rights observers and human rights networks.

  5. Decision Analysis Model for Refreshment of Geobase Imagery: Basis for Investment Strategy

    National Research Council Canada - National Science Library

    Craig, Matthew

    2003-01-01

    .... The accuracy of the imagery directly impacts the effectiveness of GeoBase. The purpose of this thesis was to develop a decision model to be used in determining imagery refreshment in an installation's...

  6. 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...... 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....

  7. 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.

  8. 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.

  9. SIMPLIFIED BUILDING MODELS EXTRACTION FROM ULTRA-LIGHT UAV IMAGERY

    Directory of Open Access Journals (Sweden)

    O. Küng

    2012-09-01

    Full Text Available Generating detailed simplified building models such as the ones present on Google Earth is often a difficult and lengthy manual task, requiring advanced CAD software and a combination of ground imagery, LIDAR data and blueprints. Nowadays, UAVs such as the AscTec Falcon 8 have reached the maturity to offer an affordable, fast and easy way to capture large amounts of oblique images covering all parts of a building. In this paper we present a state-of-the-art photogrammetry and visual reconstruction pipeline provided by Pix4D applied to medium resolution imagery acquired by such UAVs. The key element of simplified building models extraction is the seamless integration of the outputs of such a pipeline for a final manual refinement step in order to minimize the amount of manual work.

  10. 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...

  11. Chlorophyll concentration forecasts during tropical cyclones using satellite remote sensing imagery

    Science.gov (United States)

    Wei, C. C.

    2016-02-01

    Phytoplankton pigment concentrations such as chlorophyll-a (Chl-a) provide a measure of the biological state of the surface ocean. The Chl-a concentration, a proxy for phytoplankton abundance, is a valuable indicator of the marine ecosystem, and satellite remote sensing is the only way at present to take frequent measurements of Chl-a at regional and ocean-basin scales. Tropical cyclones when passing over land may have devastating effects on human lives, but over the ocean they can strongly enhance another form of life-ocean primary (phytoplankton) production. Researchers indicated that the passing of typhoon in the open ocean can induce the decreasing of sea surface temperature and Chl-a concentration increasing. Meanwhile, the typhoon-induced SST and Chl-a changes is related to the typhoon intensity, moving speed, and days of influence on the ocean. This study adopted the machine learning algorithms in forecasting the Chl-a concentrations from 1- to 5-day ahead by using datasets from the climatologic characteristics of typhoons from Central Weather Bureau (CWB), the typhoon path from Joint Typhoon Warning Center (JTWC), and the satellite observations from Moderate Resolution Imaging Spectroradiometer (MODIS) during typhoon attacks. The study collected the typhoon tracks from JTWC, the typhoon climatologic data issued by CWB, and the atmosphere and ocean color products from MODIS/Aqua satellites. The Chl-a concentration forecast models are constructed by machine learning, namely, multilayer perceptron neural networks and classification and regression tree. The study area was the Taiwan Strait which is between Taiwan and China. This study collected a total of 36 typhoon events affecting the Taiwan Strait over years 2002-2014. The results showed that the proposed methodology was promising to improve the typhoon Chl-a forecast efficiency by prediction models using the typhoon path, climatological, and MODIS/Aqua remote sensing data.

  12. Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

    Science.gov (United States)

    Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

    2018-03-01

    Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

  13. 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

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

    Science.gov (United States)

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

    2017-12-01

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

  15. Land cover classification in multispectral satellite imagery using sparse approximations on learned dictionaries

    Science.gov (United States)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-05-01

    Techniques for automated feature extraction, including neuroscience-inspired machine vision, are of great interest for landscape characterization and change detection in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methodologies to the environmental sciences, using state-of-theart adaptive signal processing, combined with compressive sensing and machine learning techniques. We use a modified Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using CoSA: unsupervised Clustering of Sparse Approximations. We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska (USA). Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties (e.g., soil moisture and inundation), and topographic/geomorphic characteristics. In this paper, we explore learning from both raw multispectral imagery, as well as normalized band difference indexes. We explore a quantitative metric to evaluate the spectral properties of the clusters, in order to potentially aid in assigning land cover categories to the cluster labels.

  16. A dynamic threshold method for obtaining cloud cover from satellite imagery data

    Science.gov (United States)

    Coakley, James A., Jr.

    1987-01-01

    Errors in cloud cover derived by using a fixed threshold applied to imagery data depend not only on the fractional cover but also on cloud size. As a result, a fixed threshold applied to two scenes having the same cloud cover will produce different estimates of the cover when the clouds in the two scenes have different sizes. To allow for this influence due to cloud size, a dynamic threshold method is presented. In this method an infrared threshold is adjusted to achieve the highest correlation between the threshold-derived cloud cover and the mean emitted radiance for mesoscale-sized subregions within the scene. For single-layered cloud systems this threshold achieves a cancellation of errors in the cloud cover for the subregions so that the resulting cloud cover for the region and the associated estimates of cloud properties are in fair agreement with estimates obtained using the spatial coherence method. The agreement illustrates the validity of the layered cloud model used in different ways by the two methods. The performance of the dynamic threshold method is contrasted with that of a fixed threshold applied to the same data in order to illustrate the merits of applying a scene-dependent threshold.

  17. 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.

  18. 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.

  19. SkySat-1: very high-resolution imagery from a small satellite

    Science.gov (United States)

    Murthy, Kiran; Shearn, Michael; Smiley, Byron D.; Chau, Alexandra H.; Levine, Josh; Robinson, M. Dirk

    2014-10-01

    This paper presents details of the SkySat-1 mission, which is the first microsatellite-class commercial earth- observation system to generate sub-meter resolution panchromatic imagery, in addition to sub-meter resolution 4-band pan-sharpened imagery. SkySat-1 was built and launched for an order of magnitude lower cost than similarly performing missions. The low-cost design enables the deployment of a large imaging constellation that can provide imagery with both high temporal resolution and high spatial resolution. One key enabler of the SkySat-1 mission was simplifying the spacecraft design and instead relying on ground- based image processing to achieve high-performance at the system level. The imaging instrument consists of a custom-designed high-quality optical telescope and commercially-available high frame rate CMOS image sen- sors. While each individually captured raw image frame shows moderate quality, ground-based image processing algorithms improve the raw data by combining data from multiple frames to boost image signal-to-noise ratio (SNR) and decrease the ground sample distance (GSD) in a process Skybox calls "digital TDI". Careful qual-ity assessment and tuning of the spacecraft, payload, and algorithms was necessary to generate high-quality panchromatic, multispectral, and pan-sharpened imagery. Furthermore, the framing sensor configuration en- abled the first commercial High-Definition full-frame rate panchromatic video to be captured from space, with approximately 1 meter ground sample distance. Details of the SkySat-1 imaging instrument and ground-based image processing system are presented, as well as an overview of the work involved with calibrating and validating the system. Examples of raw and processed imagery are shown, and the raw imagery is compared to pre-launch simulated imagery used to tune the image processing algorithms.

  20. Continuous Field Vegetation Classification of a Sagebrush (Artemesia spp.) Dominated Ecosystem Using High Spatial-Resolution Multi-spectral Satellite Imagery

    Science.gov (United States)

    Buchert, M. P.; White, M.

    2006-12-01

    Global change scientists have grown increasingly interested over the past decade in continuous field vegetation mapping, whereby remotely sensed imagery is processed to yield a data product whose pixel values represent the percent of ground element land area covered by vegetative canopy. The continuous field approach offers distinct benefits over older discrete classification approaches, but current methods developed for production of global tree cover data sets are biased in favor of taller, denser vegetation and misrepresent percent cover of woody shrubs, the dominant vegetation throughout large reaches of North America's Intermountain West. The underperformance of current methods in accurately representing shrub cover is of significant interest to conservation biologists, as shrub-steppe ecosystems dominated by sagebrush (Artemesia spp.) are among the most threatened habitats in North America. We report on our efforts to generate percent-cover vegetation classifications for shrub, herbaceous, and bare land cover classes for study sites in northeastern Nevada and northeastern Utah, using 4m multi-spectral satellite imagery, a regression-tree classification method, and ground-collected reference data. Continuous field vegetation cover data are typically used as inputs to carbon cycling models, but we anticipate that at the fine grain of our dataset, such data will also be useful in ecological and conservation biological applications. In this vein, we demonstrate the applicability of high resolution shrub percent-cover data to habitat modeling efforts for threatened sage-obligate species.

  1. Mapping and Visualization of The Deepwater Horizon Oil Spill Using Satellite Imagery

    Science.gov (United States)

    Ferreira Pichardo, E.

    2017-12-01

    Satellites are man-made objects hovering around the Earth's orbit and are essential for Earth observation, i.e. the monitoring and gathering of data about the Earth's vital systems. Environmental Satellites are used for atmospheric research, weather forecasting, and warning as well as monitoring extreme weather events. These satellites are categorized into Geosynchronous and Low Earth (Polar) orbiting satellites. Visualizing satellite data is critical to understand the Earth's systems and changes to our environment. The objective of this research is to examine satellite-based remotely sensed data that needs to be processed and rendered in the form of maps or other forms of visualization to understand and interpret the satellites' observations to monitor the status, changes and evolution of the mega-disaster Deepwater Horizon Spill that occurred on April 20, 2010 in the Gulf of Mexico. In this project, we will use an array of tools and programs such as Python, CSPP and Linux. Also, we will use data from the National Oceanic and Atmospheric Administration (NOAA): Polar-Orbiting Satellites Terra Earth Observing System AM-1 (EOS AM-1), and Aqua EOS PM-1 to investigate the mega-disaster. Each of these satellites carry a variety of instruments, and we will use the data obtained from the remote sensor Moderate-Resolution Imaging Spectroradiometer (MODIS). Ultimately, this study shows the importance of mapping and visualizing data such as satellite data (MODIS) to understand the extents of environmental impacts disasters such as the Deepwater Horizon Oil spill.

  2. Variation in the Mississippi River Plume from Data Synthesis of Model Outputs and MODIS Imagery

    Science.gov (United States)

    Fitzpatrick, C.; Kolker, A.; Chu, P. Y.

    2017-12-01

    Understanding the Mississippi River (MR) plume's interaction with the open ocean is crucial for understanding many processes in the Gulf of Mexico. Though the Mississippi River and its delta and plume have been studied extensively, recent archives of model products and satellite imagery have allowed us to highlight patterns in plume behavior over the last two decades through large scale data synthesis. Using 8 years of USGS discharge data and Landsat imagery, we identified the spatial extent, geographic patterns, depth, and freshwater concentration of the MR plume across seasons and years. Using 20 years of HYCOM (HYbrid Coordinate Ocean Model) analysis and reanalysis model output, and several years of NGOFS FVCOM model outputs, we mapped the minimum and maximum spatial area of the MR plume, and its varied extent east and west. From the synthesis and analysis of these data, the statistical probability of the MR plume's spatial area and geographical extent were computed. Measurements of the MR plume and its response to river discharge may predict future behavior and provide a path forward to understanding MR plume influence on nearby ecosystems.

  3. Medium Spatial Resolution Satellite Imagery to Estimate Gross Primary Production in an Urban Area

    Directory of Open Access Journals (Sweden)

    A. Rahman As-syakur

    2010-06-01

    Full Text Available Remote sensing data with medium spatial resolution can provide useful information about Gross Primary Production (GPP, especially on the scale of urban areas. Most models of ecosystem carbon exchange that are based on remote sensing use some form of the light use efficiency (LUE model. The aim of this work is to analyze the distribution of annual GPP in the urban area of Denpasar, Bali. Additional analysis using two types of satellite data (ALOS/AVNIR-2 and Aster addresses the impact of spatial resolution on the detection of various ecosystem processes in Denpasar. Annual GPP estimated using ALOS/AVNIR-2 varied from 0.13 gC m−2 yr−1 to 2,586.18 gC m−2 yr−1. Meanwhile, the Aster estimate varied from 0.14 gC m−2 yr−1 to 2,595.26 gC m−2 yr−1. GPP as measured by ALOS/AVNIR-2 was lower than that from Aster because ALOS/AVNIR-2 has medium spatial resolution and a smaller spectral range than Aster. Variations in land use may influence the measured value of GPP via differences in vegetation type, distribution, and photosynthetic pathway type. The medium spatial resolution of the remote sensing data is crucial for discriminating different land cover types in heterogeneous urban areas. Given the heterogeneity of land cover over Denpasar, ALOS/AVNIR-2 detects a smaller maximum value of GPP than Aster, but the annual mean GPP from ALOS/AVNIR-2 is higher than that from Aster. Based on comparisons with previous work, we find that ALOS/AVNIR-2 and Aster satellite data provided more accurate estimates of maximum GPP in Denpasar and in the tropical Kalimantan-Indonesia and Amazon forest than estimates derived from the MODIS GPP product (MOD17.

  4. University Satellite Campus Management Models

    Science.gov (United States)

    Fraser, Doug; Stott, Ken

    2015-01-01

    Among the 60 or so university satellite campuses in Australia are many that are probably failing to meet the high expectations of their universities and the communities they were designed to serve. While in some cases this may be due to the demand driven system, it may also be attributable in part to the ways in which they are managed. The…

  5. 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...

  6. Using the spatial and spectral precision of satellite imagery to predict wildlife occurrence patterns.

    Science.gov (United States)

    Edward J. Laurent; Haijin Shi; Demetrios Gatziolis; Joseph P. LeBouton; Michael B. Walters; Jianguo. Liu

    2005-01-01

    We investigated the potential of using unclassified spectral data for predicting the distribution of three bird species over a -400,000 ha region of Michigan's Upper Peninsula using Landsat ETM+ imagery and 433 locations sampled for birds through point count surveys. These species, Black-throated Green Warbler, Nashville Warbler, and Ovenbird. were known to be...

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

    Indian Academy of Sciences (India)

    ical objects for extraction from aerial and satel- lite imagery for use in data acquisition and update ... huge objects that might cause occlusions like shad- ows on the roads, the presence of vehicles, and road markings ..... Theoretically, every pixel can be connected to every other pixel in the graph. But, in practice only pixels ...

  8. A cloud pattern recognition algorithm to automate the estimation of mass eruption rates from an umbrella cloud or downwind plume observed via satellite imagery

    Science.gov (United States)

    Jansons, E.; Pouget, S.; Bursik, M. I.; Patra, A. K.; Pitman, E. B.; Tupper, A.

    2013-12-01

    The eruption of Eyjafjallajökull, Iceland in April and May, 2010, brought to light the importance of Volcanic Ash Transport and Dispersion models (VATD) to the estimation of the position and concentration of ash with time, and how vital it is for Volcanic Ash Advisory Centers (VAACs) to be able to detect and track ash clouds with both observations and models. The VATD needs to get Eruption Source Parameters (ESP), including mass eruption rate through time, as input, which ultimately relies on the detection of the eruption regardless of the meteorological conditions. Volcanic cloud recognition is especially difficult when meteorological clouds are also present, which is typically the case in the tropics. Given the fact that meteorological clouds and volcanic clouds behave differently, we developed an agent-based pattern definition algorithm to detect and define volcanic clouds on satellite imagery. We have combined this with a plume growth rate methodology to automate the estimation of volumetric and mass growth with time using plume geometry provided by satellite imagery. This allows an estimation of the mass eruption rate (MER) with time. To test our approach, we used the examples of two eruptions of different source strength, in two different climatic regimes and for which therefore the weather during eruption was quite different: Grímsvötn (Iceland) May 21, 2011, which produced an umbrella cloud readily seen above the cloud deck, and Manam (Papua New Guinea) October 24, 2004, which produced a stratospheric umbrella cloud that rapidly turned into a downwind plume, and was difficult to distinguish from meteorological clouds. The new methods may in the future allow for fast, easy and automated detection of volcanic clouds as well as a remote assessment of the mass eruption rate with time, even for inaccessible volcanoes. The methods may thus provide an additional path to estimation of the ESP and the forecasting of ash cloud propagation.

  9. 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

  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. Using Worldview Satellite Imagery to Map Yield in Avocado (Persea americana: A Case Study in Bundaberg, Australia

    Directory of Open Access Journals (Sweden)

    Andrew Robson

    2017-11-01

    Full Text Available Accurate pre-harvest estimation of avocado (Persea americana cv. Haas yield offers a range of benefits to industry and growers. Currently there is no commercial yield monitor available for avocado tree crops and the manual count method used for yield forecasting can be highly inaccurate. Remote sensing using satellite imagery offers a potential means to achieve accurate pre-harvest yield forecasting. This study evaluated the accuracies of high resolution WorldView (WV 2 and 3 satellite imagery and targeted field sampling for the pre-harvest prediction of total fruit weight (kg·tree−1 and average fruit size (g and for mapping the spatial distribution of these yield parameters across the orchard block. WV 2 satellite imagery was acquired over two avocado orchards during 2014, and WV3 imagery was acquired in 2016 and 2017 over these same two orchards plus an additional three orchards. Sample trees representing high, medium and low vigour zones were selected from normalised difference vegetation index (NDVI derived from the WV images and sampled for total fruit weight (kg·tree−1 and average fruit size (g per tree. For each sample tree, spectral reflectance data was extracted from the eight band multispectral WV imagery and 18 vegetation indices (VIs derived. Principal component analysis (PCA and non-linear regression analysis was applied to each of the derived VIs to determine the index with the strongest relationship to the measured total fruit weight and average fruit size. For all trees measured over the three year period (2014, 2016, and 2017 a consistent positive relationship was identified between the VI using near infrared band one and the red edge band (RENDVI1 to both total fruit weight (kg·tree−1 (R2 = 0.45, 0.28, and 0.29 respectively and average fruit size (g (R2 = 0.56, 0.37, and 0.29 respectively across all orchard blocks. Separate analysis of each orchard block produced higher R2 values as well as identifying different

  12. 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

  13. 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...

  14. On Fire regime modelling using satellite TM time series

    Science.gov (United States)

    Oddi, F.; . Ghermandi, L.; Lanorte, A.; Lasaponara, R.

    2009-04-01

    Wildfires can cause an environment deterioration modifying vegetation dynamics because they have the capacity of changing vegetation diversity and physiognomy. In semiarid regions, like the northwestern Patagonia, fire disturbance is also important because it could impact on the potential productivity of the ecosystem. There is reduction plant biomass and with that reducing the animal carrying capacity and/or the forest site quality with negative economics implications. Therefore knowledge of the fires regime in a region is of great importance to understand and predict the responses of vegetation and its possible effect on the regional economy. Studies of this type at a landscape level can be addressed using GIS tools. Satellite imagery allows detect burned areas and through a temporary analysis can be determined to fire regime and detecting changes at landscape scale. The study area of work is located on the east of the city of Bariloche including the San Ramon Ranch (22,000 ha) and its environs in the ecotone formed by the sub Antarctic forest and the patagonian steppe. We worked with multiespectral Landsat TM images and Landsat ETM + 30m spatial resolution obtained at different times. For the spatial analysis we used the software Erdas Imagine 9.0 and ArcView 3.3. A discrimination of vegetation types has made and was determined areas affected by fires in different years. We determined the level of change on vegetation induced by fire. In the future the use of high spatial resolution images combined with higher spectral resolution will allows distinguish burned areas with greater precision on study area. Also the use of digital terrain models derived from satellite imagery associated with climatic variables will allows model the relationship between them and the dynamics of vegetation.

  15. User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

    Science.gov (United States)

    Huh, Oscar Karl; Leibowitz, Scott G.; Dirosa, Donald; Hill, John M.

    1986-01-01

    The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data.

  16. Content-Aware Adaptive Compression of Satellite Imagery Using Artificial Vision

    Science.gov (United States)

    2013-09-01

    late 1950s era Corona program developed by the United States, which used analog film cameras and airdropped canisters to return imagery to Earth. 1 The...Wavelet Transform (DWT), as according to Meyer [1], it takes ad- vantage of the relatively low energy of ocean texture compared to ship texture in the...ashore. To address this issue, all land terrain is replaced with black, and the bordering ocean texture is faded into the newly erased areas. In this

  17. 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; Fuell, Kevin; Knaff, John; Lee, Thomas

    2012-01-01

    What is an RGB Composite Image? (1) Current and future satellite instruments provide remote sensing at a variety of wavelengths. (2) RGB composite imagery assign individual wavelengths or channel differences to the intensities of the red, green, and blue components of a pixel color. (3) Each red, green, and blue color intensity is related to physical properties within the final composite image. (4) Final color assignments are therefore related to the characteristics of image pixels. (5) Products may simplify the interpretation of data from multiple bands by displaying information in a single image. Current Products and Usage: Collaborations between SPoRT, CIRA, and NRL have facilitated the use and evaluation of RGB products at a variety of NWS forecast offices and National Centers. These products are listed in table.

  18. Turbulence characteristics inferred from time-lagged satellite imagery of surface algae in a shallow tidal sea

    Science.gov (United States)

    Marmorino, George O.; Smith, Geoffrey B.; Miller, W. D.

    2017-09-01

    A pair of time-lagged satellite images of surface algae in the Great Barrier Reef lagoon is used to investigate characteristics of the horizontal velocity field at a spatial resolution as small as 4 m. A distinctive feature is the occurrence of surface patches that are relatively clear of algae and which grow in size. These patches are interpreted as resulting from the horizontally diverging motion associated with boils. The surface divergence in such boils can be as large as 0.01 s-1, as deduced directly from the imagery. Overall, root-mean-squared values of divergence, vorticity, and strain rate are 45, 58, and 170, respectively, when normalized by the Coriolis parameter. By observing the algae and its fluid environment simultaneously, the analysis thus provides a glimpse of how underlying hydrodynamic processes help shape the distribution of surface algae - under the calm winds that favor the formation of dense surface aggregations.

  19. 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.

  20. Application of the Coastal and Marine Ecological Classification Standard (CMECS) Water Column Component (WC) to data derived by the Naval Research Lab (NRL) Automated Processing System (APS) modeling of Moderate Resolution Imaging Spectroradiometer (MODIS) Imagery from the Aqua Earth Orbiting Satellite (EOS) PM in the Northern Gulf of Mexico from 2005-01 to 2009-12 (NODC Accession 0094007)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Satellite-derived data for sea surface temperature, salinity, chlorophyll; euphotic depth; and modeled bottom to surface temperature differences were evaluated to...

  1. DEVELOPMENT OF CAMERA MODEL AND GEOMETRIC CALIBRATION/VALIDATION OF XSAT IRIS IMAGERY

    Directory of Open Access Journals (Sweden)

    L. K. Kwoh

    2012-07-01

    Full Text Available XSAT, launched on 20 April 2011, is the first micro-satellite designed and built in Singapore. It orbits the Earth at altitude of 822 km in a sun synchronous orbit. The satellite carries a multispectral camera IRIS with three spectral bands – 0.52~0.60 mm for Green, 0.63~0.69 mm for Red and 0.76~0.89 mm for NIR at 12 m resolution. In the design of IRIS camera, the three bands were acquired by three lines of CCDs (NIR, Red and Green. These CCDs were physically separated in the focal plane and their first pixels not absolutely aligned. The micro-satellite platform was also not stable enough to allow for co-registration of the 3 bands with simple linear transformation. In the camera model developed, this platform stability was compensated with 3rd to 4th order polynomials for the satellite's roll, pitch and yaw attitude angles. With the camera model, the camera parameters such as the band to band separations, the alignment of the CCDs relative to each other, as well as the focal length of the camera can be validated or calibrated. The results of calibration with more than 20 images showed that the band to band along-track separation agreed well with the pre-flight values provided by the vendor (0.093° and 0.046° for the NIR vs red and for green vs red CCDs respectively. The cross-track alignments were 0.05 pixel and 5.9 pixel for the NIR vs red and green vs red CCDs respectively. The focal length was found to be shorter by about 0.8%. This was attributed to the lower operating temperature which XSAT is currently operating. With the calibrated parameters and the camera model, a geometric level 1 multispectral image with RPCs can be generated and if required, orthorectified imagery can also be produced.

  2. Image Fusion Applied to Satellite Imagery for the Improved Mapping and Monitoring of Coral Reefs: a Proposal

    Science.gov (United States)

    Gholoum, M.; Bruce, D.; Hazeam, S. Al

    2012-07-01

    A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine the quality of the

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

    Directory of Open Access Journals (Sweden)

    Aurelio Di Pasquale

    Full Text Available 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

  4. 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

  5. 3D building reconstruction based on given ground plan information and surface models extracted from spaceborne imagery

    Science.gov (United States)

    Tack, Frederik; Buyuksalih, Gurcan; Goossens, Rudi

    2012-01-01

    3D surface models have gained field as an important tool for urban planning and mapping. However, urban environments have a complex nature to model and they provide a challenge to investigate the current limits of automatic digital surface modeling from high resolution satellite imagery. An approach is introduced to improve a 3D surface model, extracted photogrammetrically from satellite imagery, based on the geometric building information embodied in existing 2D ground plans. First buildings are clipped from the extracted DSM based on the 2D polygonal building ground plans. To generate prismatic shaped structures with vertical walls and flat roofs, building shape is retrieved from the cadastre database while elevation information is extracted from the DSM. Within each 2D building boundary, a constant roof height is extracted based on statistical calculations of the height values. After buildings are extracted from the initial surface model, the remaining DSM is further processed to simplify to a smooth DTM that reflects bare ground, without artifacts, local relief, vegetation, cars and city furniture. In a next phase, both models are merged to yield an integrated city model or generalized DSM. The accuracy of the generalized surface model is assessed according to a quantitative-statistical analysis by comparison with two different types of reference data.

  6. Can Satellite-derived Chlorophyll Imagery Be Used to Trace Surface Dynamics in Coastal Zone? A Case Study in the Northwestern Mediterranean Sea

    Directory of Open Access Journals (Sweden)

    Gael André

    2007-06-01

    Full Text Available A comparison of chlorophyll data from SeaWiFS imagery and modeling results from a 3D hydrodynamical model was performed over the northwestern Mediterranean for the entire year of 2001. The study aims at investigating the information content brought by satellite-derived chlorophyll concentration ([Chl] maps concerning surface dynamics in coastal zone. The study is mainly focused on the Gulf of Lions (GoL and its outer region, which are mainly influenced by the Rhône River, local winds and the Northern Current (NC flowing from the East along the continental slope. The physical hydrodynamical model was continuously run and 40 SeaWiFS images, presenting a significant coverage of the studied area, were selected. The comparison between [Chl] and sea surface salinity (SSS fields on a pixel basis showed no definite correlation trends. Three reasons are given in discussion for that result. However, the comparison emphasized areas close to the coasts which were under the influence of different inputs not considered in the model and also of upwellings. A qualitative analysis of the data performed out of these regions exhibited significant similarities between [Chl] and SSS features. The signature of the Rhône ROFI (Region of Fresh Water Influence and, in some cases, of the NC, was evidenced on [Chl] maps. We found that the intensity of this signature is seasonally modulated, e.g., it is low in open sea during the summer, oligotrophic, season. In addition, the signature of the Rhône ROFI in the western part of the GoL can be only partial due to local chlorophyll deficits. We conclude that, for the regional case studied, chlorophyll imagery can be used as a tracer of surface dynamics through surface salinity but with limitations, especially near the coasts.

  7. Digital processing of satellite imagery application to jungle areas of Peru

    Science.gov (United States)

    Pomalaza, J. C. (Principal Investigator); Pomalaza, C. A.; Espinoza, J.

    1976-01-01

    The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.

  8. 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

  9. SPATIAL AND TEMPORAL ANALYSIS OF SEA SURFACE SALINITY USING SATELLITE IMAGERY IN GULF OF MEXICO

    Directory of Open Access Journals (Sweden)

    S. Rajabi

    2017-09-01

    Full Text Available The recent development of satellite sea surface salinity (SSS observations has enabled us to analyse SSS variations with high spatiotemporal resolution. In this regards, The Level3-version4 data observed by Aquarius are used to examine the variability of SSS in Gulf of Mexico for the 2012-2014 time periods. The highest SSS value occurred in April 2013 with the value of 36.72 psu while the lowest value (35.91 psu was observed in July 2014. Based on the monthly distribution maps which will be demonstrated in the literature, it was observed that east part of the region has lower salinity values than the west part for all months mainly because of the currents which originate from low saline waters of the Caribbean Sea and furthermore the eastward currents like loop current. Also the minimum amounts of salinity occur in coastal waters where the river runoffs make fresh the high saline waters. Our next goal here is to study the patterns of sea surface temperature (SST, chlorophyll-a (CHLa and fresh water flux (FWF and examine the contributions of them to SSS variations. So by computing correlation coefficients, the values obtained for SST, FWF and CHLa are 0.7, 0.22 and 0.01 respectively which indicated high correlation of SST on SSS variations. Also by considering the spatial distribution based on the annual means, it found that there is a relationship between the SSS, SST, CHLa and the latitude in the study region which can be interpreted by developing a mathematical model.

  10. Land surface temperature distribution and development for green open space in Medan city using imagery-based satellite Landsat 8

    Science.gov (United States)

    Sulistiyono, N.; Basyuni, M.; Slamet, B.

    2018-03-01

    Green open space (GOS) is one of the requirements where a city is comfortable to stay. GOS might reduce land surface temperature (LST) and air pollution. Medan is one of the biggest towns in Indonesia that experienced rapid development. However, the early development tends to neglect the GOS existence for the city. The objective of the study is to determine the distribution of land surface temperature and the relationship between the normalized difference vegetation index (NDVI) and the priority of GOS development in Medan City using imagery-based satellite Landsat 8. The method approached to correlate the distribution of land surface temperature derived from the value of digital number band 10 with the NDVI which was from the ratio of groups five and four on satellite images of Landsat 8. The results showed that the distribution of land surface temperature in the Medan City in 2016 ranged 20.57 - 33.83 °C. The relationship between the distribution of LST distribution with NDVI was reversed with a negative correlation of -0.543 (sig 0,000). The direction of GOS in Medan City is therefore developed on the allocation of LST and divided into three priority classes namely first priority class had 5,119.71 ha, the second priority consisted of 16,935.76 ha, and third priority of 6,118.50 ha.

  11. The application of optical satellite imagery and census data for urban population estimation: A case study for Ahmedabad, India

    OpenAIRE

    Nolte, Eike-Marie

    2010-01-01

    The rapid growth of India's urban population leads to the need to employ new technologies for population modelling. In this study, optical satellite images and census data are used to model the population distribution for the city of Ahmedabad (northwest India. The selected spatial scales for which the population data are generated correspond to those often used for earthquake risk modelling and loss estimation.

  12. 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 ...

  13. 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.

  14. Using high-resolution satellite imagery and double sampling as a ...

    African Journals Online (AJOL)

    QuickBird satellite images were used to extract auxiliary variables (image data), such as photogrammetric crown diameter and number of stems, using visual interpretation and measuring tools offered by Erdas 8.7 geographic imaging software. Field inventory data (terrestric data) collected in 2002 were used to obtain the ...

  15. A comparison of low cost satellite imagery for pastoral planning projects in Central Asia

    Science.gov (United States)

    Matthew Reeves; Donald J. Bedunah

    2006-01-01

    We discuss some of the advantages and disadvantages of satellite data for rangeland planning in Central Asia, with our emphasis being on sources of low cost or free data. The availability and use the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) as a base map and tool for coordinated natural resource planning in Central Asia is discussed in...

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Fajar Rizki

    2017-12-01

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

  18. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  19. Predicting water quality by relating secchi-disk transparency and chlorophyll a measurements to Landsat satellite imagery for Michigan inland lakes, 2001-2006

    Science.gov (United States)

    Fuller, L.M.; Minnerick, R.J.

    2007-01-01

    The State of Michigan has more than 11,000 inland lakes; approximately 3,500 of these lakes are greater than 25 acres. The USGS, in cooperation with the Michigan Department of Environmental Quality (MDEQ), has been monitoring the quality of inland lakes in Michigan through the Lake Water Quality Assessment monitoring program. Approximately 100 inland lakes will be sampled per year from 2001 to 2015. Volunteers coordinated by MDEQ started sampling lakes in 1974, and continue to sample to date approximately 250 inland lakes each year through the Cooperative Lakes Monitoring Program (CLMP), Michigan’s volunteer lakes monitoring program. Despite this sampling effort, it is still impossible to physically collect the necessary water-quality measurements for all 3,500 Michigan inland lakes. Therefore, a technique was used by USGS, modeled after Olmanson and others (2001), in cooperation with MDEQ that uses satellite remote sensing to predict water quality in unsampled inland lakes greater than 25 acres. Water-quality characteristics that are associated with water clarity can be predicted for Michigan inland lakes by relating sampled measurements of secchi-disk transparency (SDT) and chlorophyll a concentrations (Chl-a), to satellite imagery. The trophic state index (TSI) which is an indicator of the biological productivity can be calculated based on SDT measurements, Chl-a concentrations, and total phosphorus (TP) concentrations measured near the lake’s surface. Through this process, unsampled inland lakes within the fourteen Landsat satellite scenes encompassing Michigan can be translated into estimated TSI from either predicted SDT or Chl-a (fig. 1).

  20. 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

  1. Model-based satellite image fusion

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  2. 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.

  3. UNOSAT at CERN – 15 years of satellite imagery support to the humanitarian and development community

    CERN Multimedia

    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...

  4. 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.

  5. 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.

  6. 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

  7. Satellite-based terrestrial production efficiency modeling

    Directory of Open Access Journals (Sweden)

    Obersteiner Michael

    2009-09-01

    Full Text Available Abstract Production efficiency models (PEMs are based on the theory of light use efficiency (LUE which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP monitoring. The objectives of this review are as follows: 1 to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS identified in the literature; 2 to review each model to determine potential improvements to the general PEM methodology; 3 to review the related literature on satellite-based gross primary productivity (GPP and NPP modeling for additional possibilities for improvement; and 4 based on this review, propose items for coordinated research. This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling. Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra; there is an urgent need for

  8. Satellite-based terrestrial production efficiency modeling.

    Science.gov (United States)

    McCallum, Ian; Wagner, Wolfgang; Schmullius, Christiane; Shvidenko, Anatoly; Obersteiner, Michael; Fritz, Steffen; Nilsson, Sten

    2009-09-18

    Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research.This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling.Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT) or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra); there is an urgent need for satellite-based biomass

  9. Satellite infrared imagery for thermal plume contamination monitoring in coastal ecosystem of Cernavoda NPP

    Science.gov (United States)

    Zoran, M. A.; Zoran, Liviu Florin V.; Dida, Adrian I.

    2017-10-01

    Satellite remote sensing is an important tool for spatio-temporal analysis and surveillance of NPP environment, thermal heat waste of waters being a major concern in many coastal ecosystems involving nuclear power plants. As a test case the adopted methodology was applied for 700x2 MW Cernavoda nuclear power plant (NPP) located in the South-Eastern part of Romania, which discharges warm water affecting coastal ecology. The thermal plume signatures in the NPP hydrological system have been investigated based on TIR (Thermal Infrared) spectral bands of NOAA AVHRR, Landsat TM/ETM+/OLI, and MODIS Terra/Aqua time series satellite data during 1990-2016 period. If NOAA AVHRR data proved the general pattern and extension of the thermal plume signature in Danube river and Black Sea coastal areas, Landsat TM/ETM and MODIS data used for WST (Water Surface Temperature) change detection, mapping and monitoring provided enhanced information about the plume shape, dimension and direction of dispersion in these waters. Thermal discharge from two nuclear reactors cooling is dissipated as waste heat in Danube-Black -Sea Channel and Danube River. From time-series analysis of satellite data during period 1990-2016 was found that during the winter season thermal plume was localized to an area of a few km of NPP, and the mean temperature difference between the plume and non-plume areas was about 1.7 oC. During summer and fall, derived mean temperature difference between the plume and non-plume areas was of about 1.3°C and thermal plume area was extended up to 5- 10 km far along Danube Black Sea Channel.

  10. A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

    Science.gov (United States)

    Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

    2017-12-01

    The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

  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. Effects of instrument characteristics on cloud properties retrieved from satellite imagery data

    Science.gov (United States)

    Baldwin, D. G.; Coakley, J. A., Jr.; Zhang, M. S.

    1986-01-01

    The relationships between sensor resolution and derived cloud properties in satellite remote sensing were studied by comparisons of cloud characteristics determined by spatial coherence analysis of AVHRR and GOES data. The latter data were simulated from 11 microns AVHRR data and were assigned a resolution (8 sq km) half that of the AVHRR. Day and nighttime passes were considered for single-layer maritime cloud systems. Sample radiance vs local standard deviation plots of 1024 points are provided for the same area from AVHRR and GOES-East sensors, demonstrating a qualitative agreement.

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

    OpenAIRE

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

    2015-01-01

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

  14. Bi-Directional Reflectance Distribution Function: BRDF Effect on Un-mixing, Category Decomposition of the Mixed Pixel (MIXEL) of Remote Sensing Satellite Imagery Data

    OpenAIRE

    Kohei Arai

    2013-01-01

    Method for unmixing, category decomposition of the mixed pixel (MIXEL) of remote sensing satellite imagery data taking into account the effect due to Bi-Directional Reflectance Distribution Function: BRDF is proposed. Although there is not so small BRDF effect on estimation mixing ratios, conventional unmixing methods do not take into account the effect. Through experiments, the effect is clarified. Also the proposed unmixing method with consideration of BRDF effect is validated.

  15. SATELLITE-DERIVED BATHYMETRY USING RANDOM FOREST ALGORITHM AND WORLDVIEW-2 IMAGERY

    Directory of Open Access Journals (Sweden)

    Masita Dwi Mandini Manessa

    2016-10-01

    Full Text Available In empirical approach, the satellite-derived bathymetry (SDB is usually derived from a linear regression. However, the depth variable in surface reflectance has a more complex relation. In this paper, a methodology was introduced using a nonlinear regression of Random Forest (RF algorithm for SDB in shallow coral reef water. Worldview-2 satellite images and water depth measurement samples using single beam echo sounder were utilized. Furthermore, the surface reflectance of six visible bands and their logarithms were used as an input in RF and then compared with conventional methods of Multiple Linear Regression (MLR at ten times cross validation. Moreover, the performance of each possible pair from six visible bands was also tested. Then, the estimated depth from two methods and each possible pairs were evaluated in two sites in Indonesia: Gili Mantra Island and Panggang Island, using the measured bathymetry data. As a result, for the case of all bands used the RF in compared with MLR showed better fitting ensemble, -0.14 and -1.27m of RMSE and 0.16 and 0.47 of R2 improvement for Gili Mantra Islands and Panggang Island, respectively. Therefore, the RF algorithm demonstrated better performance and accuracy compared with the conventional method. While for best pair identification, all bands pair wound did not give the best result. Surprisingly, the usage of green, yellow, and red bands showed good water depth estimation accuracy.

  16. Thermospheric density and satellite drag modeling

    Science.gov (United States)

    Mehta, Piyush Mukesh

    The United States depends heavily on its space infrastructure for a vast number of commercial and military applications. Space Situational Awareness (SSA) and Threat Assessment require maintaining accurate knowledge of the orbits of resident space objects (RSOs) and the associated uncertainties. Atmospheric drag is the largest source of uncertainty for low-perigee RSOs. The uncertainty stems from inaccurate modeling of neutral atmospheric mass density and inaccurate modeling of the interaction between the atmosphere and the RSO. In order to reduce the uncertainty in drag modeling, both atmospheric density and drag coefficient (CD) models need to be improved. Early atmospheric density models were developed from orbital drag data or observations of a few early compact satellites. To simplify calculations, densities derived from orbit data used a fixed CD value of 2.2 measured in a laboratory using clean surfaces. Measurements from pressure gauges obtained in the early 1990s have confirmed the adsorption of atomic oxygen on satellite surfaces. The varying levels of adsorbed oxygen along with the constantly changing atmospheric conditions cause large variations in CD with altitude and along the orbit of the satellite. Therefore, the use of a fixed CD in early development has resulted in large biases in atmospheric density models. A technique for generating corrections to empirical density models using precision orbit ephemerides (POE) as measurements in an optimal orbit determination process was recently developed. The process generates simultaneous corrections to the atmospheric density and ballistic coefficient (BC) by modeling the corrections as statistical exponentially decaying Gauss-Markov processes. The technique has been successfully implemented in generating density corrections using the CHAMP and GRACE satellites. This work examines the effectiveness, specifically the transfer of density models errors into BC estimates, of the technique using the CHAMP and

  17. Accuracy assessment of biomass and forested area classification from modis, landstat-tm satellite imagery and forest inventory plot data

    Science.gov (United States)

    Dumitru Salajanu; Dennis M. Jacobs

    2007-01-01

    The objective of this study was to determine how well forestfnon-forest and biomass classifications obtained from Landsat-TM and MODIS satellite data modeled with FIA plots, compare to each other and with forested area and biomass estimates from the national inventory data, as well as whether there is an increase in overall accuracy when pixel size (spatial resolution...

  18. Identification of the potential gap areas for the developing green infrastructure in the Urban area using High resolution satellite Imagery

    Science.gov (United States)

    Kanaparthi, M. B.

    2017-12-01

    In India urban population is growing day by day which is causing air pollution less air quality finally leading to climate change and global warming. To mitigate the effect of the climate change we need to plant more trees in the urban area. The objective of this study is develop a plan to improve the urban Green Infrastructure (GI) to fight against the climate change and global warming. Improving GI is a challenging and difficult task in the urban areas because land unavailability of land, to overcome the problem greenways is a good the solution. Greenway is a linear open space developed along the rivers, canals, roads in the urban areas to form a network of green spaces. Roads are the most common structures in the urban area. The idea is to develop the greenways alongside the road to connecting the different green spaces. Tree crowns will act as culverts to connect the green spaces. This will require the spatial structure of the green space, distribution of trees along the roads and the gap areas along the road where more trees can be planted. This can be achieved with help of high resolution Satellite Imagery and the object extraction techniques. This study was carried in the city Bhimavaram which is located in state Andhra Pradesh. The final outcome of this study is potential gap areas for planting trees in the city.

  19. Land-Use Planning and Satellite Imagery Used for Green Areas Protection – Case Study of the City of Łódź, Poland

    Directory of Open Access Journals (Sweden)

    Feltynowski Marcin

    2015-12-01

    Full Text Available The article presents the issues of spatial planning on the case study of Łódź. Of significance in Łódź are its outer peripheries, which due to their natural value have become areas that must be protected and monitored in order to limit the anthropogenic impact. Protection of these areas may be carried out through the usage of instruments such as local land-use plans which help to limit the green field development phenomenon and to look after the biologically active surfaces within the borders of the city. The second step which may concern the areas with local land-use plans, as well as those without current local land-use plans, is monitoring. Such monitoring may be carried out through the analyses of satellite imagery of the city area. Such activities are a kind of low-budget enterprises which bring many benefits at a very small cost resulting from the purchase of satellite imagery. From the perspective of the authorities, a crucial fact is that the material collected during the analyses of the satellite imagery may be used in the initial phase of the planning process as an element of the inventory of areas designated for the development of land-use plans.

  20. Winter Crop Mapping for Improving Crop Production Estimates in Argentina Using Moderation Resolution Satellite Imagery

    Science.gov (United States)

    Humber, M. L.; Copati, E.; Sanchez, A.; Sahajpal, R.; Puricelli, E.; Becker-Reshef, I.

    2017-12-01

    Accurate crop production data is fundamental for reducing uncertainly and volatility in the domestic and international agricultural markets. The Agricultural Estimates Department of the Buenos Aires Grain Exchange has worked since 2000 on the estimation of different crop production data. With this information, the Grain Exchange helps different actors of the agricultural chain, such as producers, traders, seed companies, market analyst, policy makers, into their day to day decision making. Since 2015/16 season, the Grain Exchange has worked on the development of a new earth observations-based method to identify winter crop planted area at a regional scale with the aim of improving crop production estimates. The objective of this new methodology is to create a reliable winter crop mask at moderate spatial resolution using Landsat-8 imagery by exploiting bi-temporal differences in the phenological stages of winter crops as compared to other landcover types. In collaboration with the University of Maryland, the map has been validated by photointerpretation of a stratified statistically random sample of independent ground truth data in the four largest producing provinces of Argentina: Buenos Aires, Cordoba, La Pampa, and Santa Fe. In situ measurements were also used to further investigate conditions in the Buenos Aires province. Preliminary results indicate that while there are some avenues for improvement, overall the classification accuracy of the cropland and non-cropland classes are sufficient to improve downstream production estimates. Continuing research will focus on improving the methodology for winter crop mapping exercises on a yearly basis as well as improving the sampling methodology to optimize collection of validation data in the future.

  1. 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.

  2. Phenology-based Spartina alterniflora mapping in coastal wetland of the Yangtze Estuary using time series of GaoFen satellite no. 1 wide field of view imagery

    Science.gov (United States)

    Ai, Jinquan; Gao, Wei; Gao, Zhiqiang; Shi, Runhe; Zhang, Chao

    2017-04-01

    Spartina alterniflora is an aggressive invasive plant species that replaces native species, changes the structure and function of the ecosystem across coastal wetlands in China, and is thus a major conservation concern. Mapping the spread of its invasion is a necessary first step for the implementation of effective ecological management strategies. The performance of a phenology-based approach for S. alterniflora mapping is explored in the coastal wetland of the Yangtze Estuary using a time series of GaoFen satellite no. 1 wide field of view camera (GF-1 WFV) imagery. First, a time series of the normalized difference vegetation index (NDVI) was constructed to evaluate the phenology of S. alterniflora. Two phenological stages (the senescence stage from November to mid-December and the green-up stage from late April to May) were determined as important for S. alterniflora detection in the study area based on NDVI temporal profiles, spectral reflectance curves of S. alterniflora and its coexistent species, and field surveys. Three phenology feature sets representing three major phenology-based detection strategies were then compared to map S. alterniflora: (1) the single-date imagery acquired within the optimal phenological window, (2) the multitemporal imagery, including four images from the two important phenological windows, and (3) the monthly NDVI time series imagery. Support vector machines and maximum likelihood classifiers were applied on each phenology feature set at different training sample sizes. For all phenology feature sets, the overall results were produced consistently with high mapping accuracies under sufficient training samples sizes, although significantly improved classification accuracies (10%) were obtained when the monthly NDVI time series imagery was employed. The optimal single-date imagery had the lowest accuracies of all detection strategies. The multitemporal analysis demonstrated little reduction in the overall accuracy compared with the

  3. A Federated Geospatial and Imagery Exploitation Service (GIXS) Model

    National Research Council Canada - National Science Library

    Weber, Derek

    2000-01-01

    In order for the Geospatial and Imagery Exploitation Service (GIXS) architecture to take advantage of distributed processing of image exploitation tasks, it needs to be adapted to suit a federated environment...

  4. Time series analysis of satellite multi-sensors imagery to study the recursive abnormal grow of floating macrophyte in the lake victoria (central Africa)

    Science.gov (United States)

    Fusilli, Lorenzo; Cavalli, Rosa Maria; Laneve, Giovanni; Pignatti, Stefano; Santilli, Giancarlo; Santini, Federico

    2010-05-01

    integrated use of satellite resources allowed the estimate of the temporal variability of physical parameters that were used to i) sample the spatio-temporal distribution of the whole floating vegetation (i.e. native vegetation and weed) and ii) assess the seasonal recurrence of the abnormal weeds grow, as well as, their possible relation with the hydrological regimes of the rivers. The paper describes how the 2000 - 2009 MODIS images time series, were analysed (navigated and processed) to derive i) the map the floating vegetation on the test area and ii) identify the areas more interested by the growing iii) to discriminate, whenever possible, according to the spectral and spatial resolution of the sensor applied (i.e. LANDSAT, ASTER, CHRIS), the different vegetation species in order to discriminate the weeds from the floating vegetation. The spectral identification of the different species was performed by exploiting the results of a field campaign performed in the past along the Kenyan coastal areas devoted to define a data base of spectral signatures of the main species. Spectral information was treated to define indexes and spectral analysis procedure customized to multispectral high resolution satellite data. Moreover, the results of the images time series has been analysed to identify a possible definition of the temporal occurrence of the floating vegetation growing considering both the natural phenomenological cycles and the conditions related to the abnormal growing. These results, whenever related to ancillary hydrological information (e.g. the amount of rain), they have shown that the synergy of MODIS images time series with lower temporal frequency time series imagery is a powerful tool to monitor the lake Victoria ecosystem and to follow the floating vegetation extension and even to foresee the possibility to set up a model for the abnormal vegetation growing.

  5. 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.

  6. Investigations into Ebb Tidal Fronts Using in Situ Acoustic Backscatter and Optical Satellite Imagery

    Science.gov (United States)

    Sun, D.; Ortiz-Suslow, D. G.; Haus, B. K.; Laxague, N.; Graber, H. C.; Hargrove, J.; Williams, N. J.

    2014-12-01

    The Office of Naval Research sponsored the Riverine and Estuarine Transport (RIVET) experiment during May 2012 at New River Inlet, North Carolina, in an effort to better understand the complex wave-current-wind interactions typical of tidal inlets. Over the course of a month, this highly sheared zone was intensely sampled with an array of Eulerian and Lagrangian instruments, in part, as a means of creating a synoptic, three-dimensional data set for validating various satellite remote sensing platforms. A component of this project was to deploy the Surface Physics Experimental Catamaran (SPEC), which is a mobile vessel designed specifically for collecting detailed meteorological and oceanographic data in coastal waters. Among its suite of instruments, SPEC was outfitted with a pair of acoustic doppler velocimeters (ADV), an acoustic doppler current profiler (ADCP), and an optical backscatter sensor (OBS). This instrument package allowed for high resolution mapping of the acoustic signature of the ebb tidal plume and the sub-surface, two-dimensional flow field. On May 8th, at 18:40 UTC, a panchromatic satellite image with a 0.6 m resolution, covering 122 km2, was taken of the New River Inlet Estuary and the inner shelf waters just off-shore. Numerous interesting features are visible in the image, such as the river outflow plume, surface streaks and slicks, a complex wave-field, and a remnant frontal edge from the past ebb tide. Interpretation of the surface features in these types of optical images remains a significant challenge and we have used data collected by SPEC immediately after the image acquisition to help illuminate the processes underlying these signatures.

  7. Mapping Wetlands of Alaska and Western Canada from Satellite Radar Imagery

    Science.gov (United States)

    Moghaddam, M.; McDonald, K. C.; Cihlar, J.; Chen, W.

    2002-12-01

    Boreal wetlands have an important function in processing methane, carbon dioxide, nitrogen, and sulfur as well as in sequestering carbon. The type and extent of high latitude wetlands are important indicators of methane source areas, while upland forests in the taiga are important methane-consuming sinks. Wetlands regulate biogeochemical processes such as methane production, and fix and store organic matter in the long run. The extent and complexity of wetland ecosystems are still quite uncertain partly because it is difficult to discriminate wetlands on a global scale using widely available optical remote sensing data and techniques, which are not able to detect standing water conditions under most vegetation. The accurate assessment of areal and temporal distributions of wetlands can have a large impact in improving the estimates of the global net carbon exchange. Synthetic Aperture Radar (SAR) sensors are well suited to monitoring wetlands because of their ability to detect various combinations of standing water and vegetation structure and moisture conditions. SARs also penetrate cloud cover and do not require solar illumination, allowing the collection of frequent seasonal data. Multifrequency, multipolarization SAR data needed to classify various wetlands types have been available for several years from airborne systems. Although existing spaceborne SAR data are limited to single frequency and single polarization configurations, combining data from different SAR satellites can emulate a space-based multifrequency multipolarization capability. No large-scale wetlands mapping efforts have been carried out thus far due unavailability of appropriate SAR data sets. However, with the recent availability of the JERS-1 north American boreal mosaic augmented by the partial ERS-2 overlapping data, it is now possible to generate maps of wetland extent, as well as set the stage for performing time-series analysis with future planned SAR satellite systems. We present a

  8. Revisiting Past Earthquakes and Seismo-Volcanic Crises Using Declassified Optical Satellite Imagery (Invited)

    Science.gov (United States)

    Hollingsworth, J.; Leprince, S.; Ayoub, F.; Avouac, J.

    2009-12-01

    In this study we demonstrate that the recently declassified Corona KH-9 images can be used to measure ground deformation due to seismotectonic and volcanic events from optical sub-pixel correlation. We use high resolution (6-9 m) satellite images, available from the USGS for a relatively small cost ($30 per image, swath measuring 250 x 125 km). The images are processed with the user-friendly software package COSI-Corr, which allows for automatic and precise ortho-rectification, co-registration, and sub-pixel correlation of pushbroom satellite and aerial images. Knowledge of the camera calibration information is required to determine the interior and exterior orientation parameters of the camera, which are in turn needed to successfully orthorectify and co-register the images using COSI-Corr. Because the camera information still remains classified, we follow the approach of Surazakov, et al., (2009), who conclude the Hexagon KH9 camera system is similar to the NASA Large Format Camera (LFC) system. We successfully tested the approach on the 1999 Hector Mine, USA (Ms 7.4) and 1992 Landers, USA (Ms 7.5) earthquakes and then moved on to analyze a number of other large events. We have in particular been able to measure the surface deformation induced by the 1975-1984 Krafla rifting crisis in NE Iceland, by correlating a Hexagon image from 15th September 1977 with a SPOT5 image from 2002. During the period 1977-2002 we find an average E-W extension of 3±0.5 m across the rift, which extends NNE from Lake Myvatn in the south to Ásbyrgi canyon near the coast to the north (a distance of over 40 km) and were able to determine which faults were activated. We have also co-registered a number of Hexagon images to both SPOT and ASTER images (orthorectified using either SRTMv2 or ASTER GDEM topographic data) to determine the co-seismic rupture location and amount of displacement in various significant intraplate earthquakes for which InSAR or GPS data is unavailable: 1976

  9. Discriminação de variedades de citros em imagens CCD/CBERS-2 Discrimination of citrus varieties using CCD/CBERS-2 satellite imagery

    Directory of Open Access Journals (Sweden)

    Ieda Del'Arco Sanches

    2008-02-01

    Full Text Available O presente trabalho teve o objetivo de avaliar as imagens CCD/CBERS-2 quanto à possibilidade de discriminarem variedades de citros. A área de estudo localiza-se em Itirapina (SP e, para este estudo, foram utilizadas imagens CCD de três datas (30/05/2004, 16/08/2004 e 11/09/2004. Um modelo que integra os elementos componentes da cena citrícola sensoriada é proposto com o objetivo de explicar a variabilidade das respostas das parcelas de citros em imagens orbitais do tipo CCD/CBERS-2. Foram feitas classificações pelos algoritmos Isoseg e Maxver e, de acordo com o índice kappa, concluiu-se que é possível obterem-se exatidões qualificadas como muito boas, sendo que as melhores classificações foram conseguidas com imagens da estação seca.This paper was aimed at evaluating the possibility of discriminating citrus varieties in CCD imageries from CBERS-2 satellite ("China-Brazil Earth Resouces Satellite". The study area is located in Itirapina, São Paulo State. For this study, three CCD images from 2004 were acquired (May 30, August 16, and September 11. In order to acquire a better understanding and for explaining the variability of the spectral behavior of the citrus areas in orbital images (like as the CCD/CBERS-2 images a model that integrates the elements of the citrus scene is proposed and discussed. The images were classified by Isoseg and MaxVer classifiers. According to kappa index, it was possible to obtain classifications qualified as 'very good'. The best results were obtained with the images from the dry season.

  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. Monitoring bifurcation of Monsoon system through satellite imagery and synoptic data

    International Nuclear Information System (INIS)

    Qureshi, J.; Mahmood, S.A.; Awan, S.A.

    2005-01-01

    The Monsoon phenomenon in Pakistan has quite a unique impact on the weather of our country. In this context summer monsoon are of prime importance considering the water availability in Pakistan. The monsoon conditions are best developed in sub-tropics, as in East and South-East Asia. This Study is an attempt to monitor the summer Monsoon systems affecting most of the Pakistan territory during the primary seasons and causing Large scale heavy rainfall. Monsoon low pressure areas which produce heavy rainfall spells and flooding activity over south Asia are reflective of a specific characteristic from inception to recurvature and dissipation. A study carried out in the monsoon season is indicative of a north westerly track of all the monsoon lows and then after two or three days a point of inflexion has reached before recurvature in easterly and north easterly direction and resulting in quick dissipation. The life of the monsoon low is particularly very short one after the recurvature and it has almost double the speed after recurvature visa vie prior to recurvature. The interesting feature is detected with comparison of surface low pressure center from synoptic charts, satellite image for associated cloud center and upper air convergence center confirming their by north westerly till of the storm structure. (author)

  12. Mid-term fire danger index based on satellite imagery and ancillary geographic data

    Science.gov (United States)

    Stefanidou, A.; Dragozi, E.; Tompoulidou, M.; Stepanidou, L.; Grigoriadis, D.; Katagis, T.; Stavrakoudis, D.; Gitas, I.

    2017-09-01

    Fire danger forecast constitutes one of the most important components of integrated fire management since it provides crucial information for efficient pre-fire planning, alertness and timely response to a possible fire event. The aim of this work is to develop an index that has the capability of predicting accurately fire danger on a mid-term basis. The methodology that is currently under development is based on an innovative approach that employs dry fuel spatial connectivity as well as biophysical and topological variables for the reliable prediction of fire danger. More specifically, the estimation of the dry fuel connectivity is based on a previously proposed automated procedure implemented in R software that uses Moderate Resolution Imaging Spectrometer (MODIS) time series data. Dry fuel connectivity estimates are then combined with other ancillary data such as fuel type and proximity to roads in order to result in the generation of the proposed mid-term fire danger index. The innovation of the proposed index—which will be evaluated by comparison to historical fire data—lies in the fact that its calculation is almost solely affected by the availability of satellite data. Finally, it should be noted that the index is developed within the framework of the National Observatory of Forest Fires (NOFFi) project.

  13. Investigating Gravity Waves in Polar Mesospheric Clouds Using Tomographic Reconstructions of AIM Satellite Imagery

    Science.gov (United States)

    Hart, V. P.; Taylor, M. J.; Doyle, T. E.; Zhao, Y.; Pautet, P.-D.; Carruth, B. L.; Rusch, D. W.; Russell, J. M.

    2018-01-01

    This research presents the first application of tomographic techniques for investigating gravity wave structures in polar mesospheric clouds (PMCs) imaged by the Cloud Imaging and Particle Size instrument on the NASA AIM satellite. Albedo data comprising consecutive PMC scenes were used to tomographically reconstruct a 3-D layer using the Partially Constrained Algebraic Reconstruction Technique algorithm and a previously developed "fanning" technique. For this pilot study, a large region (760 × 148 km) of the PMC layer (altitude 83 km) was sampled with a 2 km horizontal resolution, and an intensity weighted centroid technique was developed to create novel 2-D surface maps, characterizing the individual gravity waves as well as their altitude variability. Spectral analysis of seven selected wave events observed during the Northern Hemisphere 2007 PMC season exhibited dominant horizontal wavelengths of 60-90 km, consistent with previous studies. These tomographic analyses have enabled a broad range of new investigations. For example, a clear spatial anticorrelation was observed between the PMC albedo and wave-induced altitude changes, with higher-albedo structures aligning well with wave troughs, while low-intensity regions aligned with wave crests. This result appears to be consistent with current theories of PMC development in the mesopause region. This new tomographic imaging technique also provides valuable wave amplitude information enabling further mesospheric gravity wave investigations, including quantitative analysis of their hemispheric and interannual characteristics and variations.

  14. Stochastic Capability Models for Degrading Satellite Constellations

    National Research Council Canada - National Science Library

    Gulyas, Cole W

    2005-01-01

    This thesis proposes and analyzes a new measure of functional capability for satellite constellations that incorporates the instantaneous availability and mission effectiveness of individual satellites...

  15. Forest mapping and change analysis, using satellite imagery in Zagros mountain Iran, Islamic Republic o

    International Nuclear Information System (INIS)

    Torahi, A.A.

    2013-01-01

    A methodology to map and monitor land cover change using multi temporal Landsat Thematic Mapper (TM) and ASTER data in Zagros mountains of Iran for 1990, 1998, and 2006 was developed. Land- use/cover mapping is achieved through interpretation of Landsat TM satellite images of 1990, 1998 and TERRA-ASTER image of 2006 using ENVI 4.3. Basedon the Anderson land-use/cover classification system, land-use and land-covers are classified as forest land, range land, water bodies, agricultural land and residential land.The unsupervised image classification method was carried out prior to field visit, in order to determine strata for ground truth. Fieldwork was carried out to collect data for training and validating land use/cover interpretation from satellite image of 2006, and for qualitative description of the characteristics of each land use/cover class. The land - use/cover maps of 1990,1998 and 2006 were produced by using supervised image classification technique based on the Maximum Likelihood Classifier (MLC) and 132 training samples. Error matrices as cross-tabulations of the mapped class vs. the reference class were used to assess classification accuracy. Overall accuracy, users and produce accuracies, and the Kappa statistic were then derived from the error matrices. A multi-date post-classification comparison change detection algorithm was used to determine changes in land cover in three intervals, 1990,1998, 1998, 2006 and 1990, 2006.To evaluate the maps change for the 1990 to 2006 interval, areas classified as change and no-change were randomly sampled and checked whether they were correctly classified. The maps showed that between 1990 and 2006 the amount of forest land decreased from 67% to 38.5% of the total area, while rangelands, agriculture, settlement and surface water increased from 30.8% to 45%, 1.2% to.0%, 0.3% to 7.5% and 0.6% to 1.8%, respectively.In 1990,1998 and 2006, the area was dominated by dense forest (35.9%, 28.9%, 29.3%), open forest and

  16. 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.

  17. 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.

  18. 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.

  19. Mapping Wetlands of the North American Boreal Zone from Satellite Radar Imagery

    Science.gov (United States)

    Moghaddam, M.; McDonald, K.; Podest, E.

    2003-12-01

    The accurate assessment of spatial and temporal distributions of wetlands can have a large impact in improving the estimates of the global net carbon exchange. Synthetic aperture radar (SAR) sensors are well suited to monitoring wetlands because of their ability to detect various combinations of standing water and vegetation conditions. They also penetrate cloud cover and do not require solar illumination, allowing the collection of frequent seasonal data. The recent availability of large-scale satellite SAR mosaics is making it possible to generate baseline wetlands map of the north American boreal zone, where it is hypothesized to exist a substantial carbon sink, and 15-20 percent of the land surface is comprised of wetlands. The present work utilizes the summer and winter JERS-1 mosaics of the region as well as several large-scale coverages of ERS-2 for mapping the north America boreal wetlands. As an intermediate product, an open water map of the area is also being generated, derived from 100-meter resolution JERS-1 SAR mosaic products. We present a large-scale wetlands map covering large parts of Alaska and Canada, generated using a classification algorithm applied to coregistered JERS-1 (L-band HH polarizations) and ERS-2 (C-band VV polarization) SAR mosaics. The former exists for almost the entire area of Alaska and Canada, whereas currently we have access to the latter only for Alaska and Western Canada. The classification method is based on a rule-based decision-tree algorithm, and divides the landscape into the following classes: open water (possibly with sparse emergent vegetation), flooded woody vegetation (e.g., forests), flooded herbaceous vegetation, nonflooded woody vegetation, nonflooded herbaceous vegetation, and nonflooded-nonvegetated. The five standard Canadian wetlands classes of fens, bogs, swamps, marshes, and open water can be mapped into one or more of our vegetation-based wetlands classes. Several local-scale products have been validated

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

    Science.gov (United States)

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

    2017-05-01

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

  1. ROOF TYPE SELECTION BASED ON PATCH-BASED CLASSIFICATION USING DEEP LEARNING FOR HIGH RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    T. Partovi

    2017-05-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

  4. Satellites

    International Nuclear Information System (INIS)

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

    1986-01-01

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

  5. 75 FR 39701 - Revision of a Currently Approved Collection: Users, Uses, and Benefits of Landsat Satellite Imagery

    Science.gov (United States)

    2010-07-12

    ... information from this collection to understand if they are currently meeting the needs of their user community... (1028-0091) provided up-to-date information about the current users and uses of Landsat imagery, as well... provided general information from a broader population of moderate resolution imagery users. This revised...

  6. Surface vegetative biomass modelling from combined AVHRR and Landsat satellite data

    Science.gov (United States)

    Logan, T. L.; Strahler, A. H.

    1984-01-01

    A methodology for the estimation of regional biomass on the basis of Landsat and Polar Orbiter Satellite Advanced Very High Resolution Radiometer (AVHRR) imagery has been developed by the present study, which concentrated on the Sierra Nevada-Cascade Mountains ecological province of California. The Landsat data are only used initially, to calibrate the AVHRR-based biomass data. The essential element of the present approach is a 'pixel proportions' model. An integer block of Landsat pixels corresponds to each AVHRR pixel. The Landsat pixels are converted into biomass pixels using species biomass expression equations available in the literature.

  7. Remote Sensing of Epibenthic Shellfish Using Synthetic Aperture Radar Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Sil Nieuwhof

    2015-03-01

    Full Text Available On intertidal mudflats, reef-building shellfish, like the Pacific oyster and the blue mussel, provide a myriad of ecosystem services. Monitoring intertidal shellfish with high spatiotemporal resolution is important for fisheries, coastal management and ecosystem studies. Here, we explore the potential of X- (TerraSAR-X and C-band (Radarsat-2 dual-polarized SAR data to map shellfish densities, species and coverage. We investigated two backscatter models (the integral equation model (IEM and Oh’s model for inversion possibilities. Surface roughness (vertical roughness RMSz and correlation length L was measured of bare sediments and shellfish beds, which was then linked to shellfish density, presence and species. Oysters, mussels and bare sediments differed in RMSz, but because the backscatter saturates at relatively low RMSz values, it was not possible to retrieve shellfish density or species composition from X- and C-band SAR. Using a classification based on univariate and multivariate logistic regression of the field and SAR image data, we constructed maps of shellfish presence (Kappa statistics for calibration 0.56–0.74 for dual-polarized SAR, which were compared with independent field surveys of the contours of the beds (Kappa statistics of agreement 0.29–0.53 when using dual-polarized SAR. We conclude that spaceborne SAR allows one to monitor the contours of shellfish-beds (thus, distinguishing shellfish substrates from bare sediment and dispersed single shellfish, but not densities and species. Although spaceborne SAR cannot replace ground surveys entirely, it could very well offer a significant improvement in efficiency.

  8. 3-Dimentional Mapping Coastal Zone using High Resolution Satellite Stereo Imageries

    Science.gov (United States)

    Hong, Zhonghua; Liu, Fengling; Zhang, Yun

    2014-03-01

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

  9. DMSP-SSM/1 NASA algorithm validation using primarily LANDSAT and secondarily DMSP and/or AVHRR visible and thermal infrared satellite imagery

    Science.gov (United States)

    Steffen, K.; Barry, R.; Schweiger, A.

    1988-01-01

    The approach to the DMSP SSMI (Defense Meteorological Satellite Program; Special Sensor Microwave Imager) sea-ice validation effort is to demonstrate a quantitative relationship between the SSMI-derived sea ice parameters and those same parameters derived from other data sets including visible and infrared satellite imagery, aerial photographic and high-resolution microwave aircraft imagery. The question to be addressed is to what accuracy (relative to these other observations) can the following ice parameters be determined: (1) position of the ice boundary; (2) total sea ice concentration; and (3) multiyear sea ice concentration. Specific tasks include: (1) a study of the interrelationship of surface information content and sensor spatial and spectral resolution in order to establish relationships between ice surface features and the manner in which they are expressed in the satellite observations; and (2) apply these relationships to map the sea ice features which can be used to evaluate NASA's proposed SSM/1 sea ice algorithms. Other key points to be addressed include the accuracy to which these parameters can be determined in different regions (marginal ice zone such as Bering Sea, Arctic ocean, such as Beaufort Sea); the accuracy of these parameters for different seasons; the accuracy of the algorithms weather filter under different weather conditions; and the effectiveness of the 85.5 GHz channels to locate the ice edge.

  10. Mass and power modeling of communication satellites

    Science.gov (United States)

    Price, Kent M.; Pidgeon, David; Tsao, Alex

    1991-01-01

    Analytic estimating relationships for the mass and power requirements for major satellite subsystems are described. The model for each subsystem is keyed to the performance drivers and system requirements that influence their selection and use. Guidelines are also given for choosing among alternative technologies which accounts for other significant variables such as cost, risk, schedule, operations, heritage, and life requirements. These models are intended for application to first order systems analyses, where resources do not warrant detailed development of a communications system scenario. Given this ground rule, the models are simplified to 'smoothed' representation of reality. Therefore, the user is cautioned that cost, schedule, and risk may be significantly impacted where interpolations are sufficiently different from existing hardware as to warrant development of new devices.

  11. Use of Seasat satellite radar imagery for the detection of standing water beneath forest vegetation

    Science.gov (United States)

    Macdonald, H. C.; Waite, W. P.; Demarcke, J. S.

    1981-01-01

    The Seasat synthetic aperture radar, operating at a 23-cm, L-band wavelength, detected anomalous tonal patterns in areas having relatively uniform vegetable canopy. These anomalously high radar returns were shown to be related more to the underlying terrain (areas of standing water) than to the vegetation canopy. These results show that L-band radars, imaging forested terrain in a Seasat configuration, are sensitive to gross changes in vegetation, and may even penetrate the vegetation canopy, providing an unmistakable radar signature. Properly designed space imaging radar shuttle experiments, using multiple frequency and polarization radars of various depression angles, may provide documentation for a flood-monitoring capability. Height, configuration, and density of the biomass in conjunction with frequency and incidence angle of the imaging system are shown to be important factors in formulating a backscatter model, but the relative significance of each is yet to be determined.

  12. Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

    Science.gov (United States)

    Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, Nicolas; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

    A global systematic sampling scheme has been developed by the UN FAO and the EC TREES project to estimate rates of deforestation at global or continental levels at intervals of 5 to 10 years. This global scheme can be intensified to produce results at the national level. In this paper, using surrogate observations, we compare the deforestation estimates derived from these two levels of sampling intensities (one, the global, for the Brazilian Amazon the other, national, for French Guiana) to estimates derived from the official inventories. We also report the precisions that are achieved due to sampling errors and, in the case of French Guiana, compare such precision with the official inventory precision. We extract nine sample data sets from the official wall-to-wall deforestation map derived from satellite interpretations produced for the Brazilian Amazon for the year 2002 to 2003. This global sampling scheme estimate gives 2.81 million ha of deforestation (mean from nine simulated replicates) with a standard error of 0.10 million ha. This compares with the full population estimate from the wall-to-wall interpretations of 2.73 million ha deforested, which is within one standard error of our sampling test estimate. The relative difference between the mean estimate from sampling approach and the full population estimate is 3.1%, and the standard error represents 4.0% of the full population estimate. This global sampling is then intensified to a territorial level with a case study over French Guiana to estimate deforestation between the years 1990 and 2006. For the historical reference period, 1990, Landsat-5 Thematic Mapper data were used. A coverage of SPOT-HRV imagery at 20 m × 20 m resolution acquired at the Cayenne receiving station in French Guiana was used for year 2006. Our estimates from the intensified global sampling scheme over French Guiana are compared with those produced by the national authority to report on deforestation rates under the Kyoto

  13. 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

  14. Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

    Science.gov (United States)

    Gasiewski, A. J.; Heymsfield, A.; Newman Frey, K.; Davis, R.; Rapp, J.; Bansemer, A.; Coon, T.; Folsom, R.; Pfeufer, N.; Kalloor, J.

    2017-12-01

    Cloud radiative feedback mechanisms are one of the largest sources of uncertainty in global climate models. Variations in local 3D cloud structure impact the interpretation of NASA CERES and MODIS data for top-of-atmosphere radiation studies over clouds. Much of this uncertainty results from lack of knowledge of cloud vertical and horizontal structure. Surface-based data on 3-D cloud structure from a multi-sensor array of low-latency ground-based cameras can be used to intercompare radiative transfer models based on MODIS and other satellite data with CERES data to improve the 3-D cloud parameterizations. Closely related, forecasting of solar insolation and associated cloud cover on time scales out to 1 hour and with spatial resolution of 100 meters is valuable for stabilizing power grids with high solar photovoltaic penetrations. Data for cloud-advection based solar insolation forecasting with requisite spatial resolution and latency needed to predict high ramp rate events obtained from a bottom-up perspective is strongly correlated with cloud-induced fluctuations. The development of grid management practices for improved integration of renewable solar energy thus also benefits from a multi-sensor camera array. The data needs for both 3D cloud radiation modelling and solar forecasting are being addressed using a network of low-cost upward-looking visible light CCD sky cameras positioned at 2 km spacing over an area of 30-60 km in size acquiring imagery on 30 second intervals. Such cameras can be manufactured in quantity and deployed by citizen volunteers at a marginal cost of 200-400 and operated unattended using existing communications infrastructure. A trial phase to understand the potential utility of up-looking multi-sensor visible imagery is underway within this NASA Citizen Science project. To develop the initial data sets necessary to optimally design a multi-sensor cloud camera array a team of 100 citizen scientists using self-owned PDA cameras is being

  15. Integrated Geohazard Screening Using Remote Sensing, Including Satellite and Helicopter Based Imagery, LiDAR, and Geophysics, in Tajikistan and Kyrgyzstan, Central Asia

    Science.gov (United States)

    Wade, A. M.; Kozaci, O.; Hitchcock, C. S.; Konieczny, G.; Garrie, D.

    2015-12-01

    We performed a detailed geohazard investigation of a 5 km-wide, 650km-long corridor through Tajikistan and Kyrgyzstan, Central Asia. The study area includes the Rasht and Alai valleys at the boundary between the Pamir Mountains and the Alai Range of the southern Tien Shan. Ongoing collision between the India and Eurasia plates has resulted in the Tien Shan orogenic belt and the Pamir Mountains. Thus the study area is one of the most seismically active regions in the world. Rapid uplift, erosion, and steep slopes give rise to widespread landsliding and massive rock slope failures in both the Pamir and Tien Shan Mountains. Our integrated data acquisition and interpretation plan used airborne and remote sensing methods including satellite based DEMs and high resolution imagery, LiDAR, aerial photography, and helicopter based electromagnetic resistivity (HEM). Analysis of these data sets allowed us to delineate potential geohazards through surficial geologic mapping. Initial desktop geohazard screening included 1:50,000-scale mapping for potential faults, landslides, and liquefiable deposits, which included traffic light-style susceptibility maps for route refinement and hazard mitigation. As part of detailed investigations, continuous HEM data was collected and processed at a spatial sampling interval of approximately 3m. Apparent resistivity was calculated for each of the five operating frequencies over the entire survey area. For the purposes of this study, resistivity values at 10 m and 20 m depths were sliced from the interpolated 3D Differential Resistivity model for use in the analysis. Using GIS, we compared these results with mapped Quaternary units and found good correlation between resistivity contrasts and the boundaries of mapped surficial units. With this confidence, the HEM measurements were further analyzed to identify subsurface features and to develop a 3D geologic model. Based on this analysis we provided a framework for an optimized geotechnical

  16. Object-based random forest classification of Landsat ETM+ and WorldView-2 satellite imagery for mapping lowland native grassland communities in Tasmania, Australia

    Science.gov (United States)

    Melville, Bethany; Lucieer, Arko; Aryal, Jagannath

    2018-04-01

    This paper presents a random forest classification approach for identifying and mapping three types of lowland native grassland communities found in the Tasmanian Midlands region. Due to the high conservation priority assigned to these communities, there has been an increasing need to identify appropriate datasets that can be used to derive accurate and frequently updateable maps of community extent. Therefore, this paper proposes a method employing repeat classification and statistical significance testing as a means of identifying the most appropriate dataset for mapping these communities. Two datasets were acquired and analysed; a Landsat ETM+ scene, and a WorldView-2 scene, both from 2010. Training and validation data were randomly subset using a k-fold (k = 50) approach from a pre-existing field dataset. Poa labillardierei, Themeda triandra and lowland native grassland complex communities were identified in addition to dry woodland and agriculture. For each subset of randomly allocated points, a random forest model was trained based on each dataset, and then used to classify the corresponding imagery. Validation was performed using the reciprocal points from the independent subset that had not been used to train the model. Final training and classification accuracies were reported as per class means for each satellite dataset. Analysis of Variance (ANOVA) was undertaken to determine whether classification accuracy differed between the two datasets, as well as between classifications. Results showed mean class accuracies between 54% and 87%. Class accuracy only differed significantly between datasets for the dry woodland and Themeda grassland classes, with the WorldView-2 dataset showing higher mean classification accuracies. The results of this study indicate that remote sensing is a viable method for the identification of lowland native grassland communities in the Tasmanian Midlands, and that repeat classification and statistical significant testing can be

  17. A Neutral-Network-Fusion Architecture for Automatic Extraction of Oceanographic Features from Satellite Remote Sensing Imagery

    National Research Council Canada - National Science Library

    Askari, Farid

    1999-01-01

    This report describes an approach for automatic feature detection from fusion of remote sensing imagery using a combination of neural network architecture and the Dempster-Shafer (DS) theory of evidence...

  18. Semi-automatic road extraction from very high resolution remote sensing imagery by RoadModeler

    Science.gov (United States)

    Lu, Yao

    Accurate and up-to-date road information is essential for both effective urban planning and disaster management. Today, very high resolution (VHR) imagery acquired by airborne and spaceborne imaging sensors is the primary source for the acquisition of spatial information of increasingly growing road networks. Given the increased availability of the aerial and satellite images, it is necessary to develop computer-aided techniques to improve the efficiency and reduce the cost of road extraction tasks. Therefore, automation of image-based road extraction is a very active research topic. This thesis deals with the development and implementation aspects of a semi-automatic road extraction strategy, which includes two key approaches: multidirectional and single-direction road extraction. It requires a human operator to initialize a seed circle on a road and specify a extraction approach before the road is extracted by automatic algorithms using multiple vision cues. The multidirectional approach is used to detect roads with different materials, widths, intersection shapes, and degrees of noise, but sometimes it also interprets parking lots as road areas. Different from the multidirectional approach, the single-direction approach can detect roads with few mistakes, but each seed circle can only be used to detect one road. In accordance with this strategy, a RoadModeler prototype was developed. Both aerial and GeoEye-1 satellite images of seven different types of scenes with various road shapes in rural, downtown, and residential areas were used to evaluate the performance of the RoadModeler. The experimental results demonstrated that the RoadModeler is reliable and easy-to-use by a non-expert operator. Therefore, the RoadModeler is much better than the object-oriented classification. Its average road completeness, correctness, and quality achieved 94%, 97%, and 94%, respectively. These results are higher than those of Hu et al. (2007), which are 91%, 90%, and 85

  19. MODELING AND SIMULATION OF HIGH RESOLUTION OPTICAL REMOTE SENSING SATELLITE GEOMETRIC CHAIN

    Directory of Open Access Journals (Sweden)

    Z. Xia

    2018-04-01

    Full Text Available The high resolution satellite with the longer focal length and the larger aperture has been widely used in georeferencing of the observed scene in recent years. The consistent end to end model of high resolution remote sensing satellite geometric chain is presented, which consists of the scene, the three line array camera, the platform including attitude and position information, the time system and the processing algorithm. The integrated design of the camera and the star tracker is considered and the simulation method of the geolocation accuracy is put forward by introduce the new index of the angle between the camera and the star tracker. The model is validated by the geolocation accuracy simulation according to the test method of the ZY-3 satellite imagery rigorously. The simulation results show that the geolocation accuracy is within 25m, which is highly consistent with the test results. The geolocation accuracy can be improved about 7 m by the integrated design. The model combined with the simulation method is applicable to the geolocation accuracy estimate before the satellite launching.

  20. The Effect of Satellite Track Masking on Simulated Cloud Satellite Data in a Global Atmospheric Model

    Science.gov (United States)

    Eichmann, A.; da Silva, A.; Norris, P. M.; Molod, A.; Auer, B.

    2013-12-01

    The CFMIP Observation Simulator Package (COSP) simulates data provided by cloud-observing satellites and products based on the hydrometeor properties in an atmospheric model in order to provide an objective means to compare cloud properties between models. COSP also facilitates comparisons between models and satellite products, but as provided it examines the entire model domain whereas satellites cover only the swath of their respective orbital tracks. This temporal and spatial mismatch in data coverage may introduce biases in time-averaged model cloud fields. Here the data generated by COSP from a year-long integration of the GEOS-5 Earth System Model are masked with the respective orbital tracks of the satellites and compared to the unmasked fields to determine what biases domain-wide coverage may induce.

  1. Evaluating the versatility of EEG models generated from motor imagery tasks: An exploratory investigation on upper-limb elbow-centered motor imagery tasks.

    Science.gov (United States)

    Zhang, Xin; Yong, Xinyi; Menon, Carlo

    2017-01-01

    Electroencephalography (EEG) has recently been considered for use in rehabilitation of people with motor deficits. EEG data from the motor imagery of different body movements have been used, for instance, as an EEG-based control method to send commands to rehabilitation devices that assist people to perform a variety of different motor tasks. However, it is both time and effort consuming to go through data collection and model training for every rehabilitation task. In this paper, we investigate the possibility of using an EEG model from one type of motor imagery (e.g.: elbow extension and flexion) to classify EEG from other types of motor imagery activities (e.g.: open a drawer). In order to study the problem, we focused on the elbow joint. Specifically, nine kinesthetic motor imagery tasks involving the elbow were investigated in twelve healthy individuals who participated in the study. While results reported that models from goal-oriented motor imagery tasks had higher accuracy than models from the simple joint tasks in intra-task testing (e.g., model from elbow extension and flexion task was tested on EEG data collected from elbow extension and flexion task), models from simple joint tasks had higher accuracies than the others in inter-task testing (e.g., model from elbow extension and flexion task tested on EEG data collected from drawer opening task). Simple single joint motor imagery tasks could, therefore, be considered for training models to potentially reduce the number of repetitive data acquisitions and model training in rehabilitation applications.

  2. Stratospheric dryness: model simulations and satellite observations

    Directory of Open Access Journals (Sweden)

    J. Lelieveld

    2007-01-01

    Full Text Available The mechanisms responsible for the extreme dryness of the stratosphere have been debated for decades. A key difficulty has been the lack of comprehensive models which are able to reproduce the observations. Here we examine results from the coupled lower-middle atmosphere chemistry general circulation model ECHAM5/MESSy1 together with satellite observations. Our model results match observed temperatures in the tropical lower stratosphere and realistically represent the seasonal and inter-annual variability of water vapor. The model reproduces the very low water vapor mixing ratios (below 2 ppmv periodically observed at the tropical tropopause near 100 hPa, as well as the characteristic tape recorder signal up to about 10 hPa, providing evidence that the dehydration mechanism is well-captured. Our results confirm that the entry of tropospheric air into the tropical stratosphere is forced by large-scale wave dynamics, whereas radiative cooling regionally decelerates upwelling and can even cause downwelling. Thin cirrus forms in the cold air above cumulonimbus clouds, and the associated sedimentation of ice particles between 100 and 200 hPa reduces water mass fluxes by nearly two orders of magnitude compared to air mass fluxes. Transport into the stratosphere is supported by regional net radiative heating, to a large extent in the outer tropics. During summer very deep monsoon convection over Southeast Asia, centered over Tibet, moistens the stratosphere.

  3. 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.

  4. Built-Up Area and Land Cover Extraction Using High Resolution Pleiades Satellite Imagery for Midrand, in Gauteng Province, South Africa

    Science.gov (United States)

    Fundisi, E.; Musakwa, W.

    2017-09-01

    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.

  5. Comparison of Satellite Reflectance Algorithms for Estimating Phycocyanin Values and Cyanobacterial Total Biovolume in a Temperate Reservoir Using Coincident Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations

    Directory of Open Access Journals (Sweden)

    Richard Beck

    2017-05-01

    Full Text Available We analyzed 27 established and new simple and therefore perhaps portable satellite phycocyanin pigment reflectance algorithms for estimating cyanobacterial values in a temperate 8.9 km2 reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense coincident water surface observations collected from 44 sites within 1 h of image acquisition. The algorithms were adapted to real Compact Airborne Spectrographic Imager (CASI, synthetic WorldView-2, Sentinel-2, Landsat-8, MODIS and Sentinel-3/MERIS/OLCI imagery resulting in 184 variants and corresponding image products. Image products were compared to the cyanobacterial coincident surface observation measurements to identify groups of promising algorithms for operational algal bloom monitoring. Several of the algorithms were found useful for estimating phycocyanin values with each sensor type except MODIS in this small lake. In situ phycocyanin measurements correlated strongly (r2 = 0.757 with cyanobacterial sum of total biovolume (CSTB allowing us to estimate both phycocyanin values and CSTB for all of the satellites considered except MODIS in this situation.

  6. Quantifying the Spatio-temporal Impacts of Sea Level Rise on Carbon Storage Using Repeat Lidar Surveys and Multispectral Satellite Imagery

    Science.gov (United States)

    Smart, L.; Taillie, P. J.; Smith, J. W.; Meentemeyer, R. K.

    2017-12-01

    Sound coastal land-use policy and management decisions to mitigate or adapt to sea level rise impacts depend on understanding vegetation responses to sea level rise over large extents. Accurate methodologies to quantify these changes are necessary to understand the continued production of the ecosystem services upon which human health and well-being depend. This research quantifies spatio-temporal changes in aboveground biomass altered by sea level rise across North Carolina's coastal plain using a combination of repeat-acquisition lidar data and multi-temporal satellite imagery. Using field data from across the study area, we evaluated the reliability of multi-temporal lidar data with disparate densities and accuracies to detect changes along a coastal vegetation gradient from marsh to forested wetland. Despite an 18 fold increase in lidar point density between survey years (2001, 2014), the relationships between lidar-derived heights and field-measured heights were similar (adjusted r2; 0.6 -0.7). Random Forest, a machine learning algorithm, was used to separately predict above-ground biomass pools at the landscape-scale for the two time periods using the 98 field plots as reference data. Models performed well for both years (adjusted r2; 0.67-0.85). The 2001 model required the addition of Landsat spectral indices to meet the same adjusted r2 values as the 2014 model, which utilized lidar-derived metrics alone. Of the many potential lidar-derived predictor metrics, median and mean vegetation height were the best predictors in both time periods. To measure the spatial patterns of biomass change across the landscape, we subtracted the 2001 biomass model from the 2014 model and found significant spatial heterogeneity in biomass change across both the vegetation gradient and across the peninsula over the 12-year time period. In forested areas, we found a mean increase in aboveground biomass whereas in transition zones, marshes and freshwater emergent wetlands we

  7. 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

  8. Mental imagery of speech and movement implicates the dynamics of internal forward models

    Directory of Open Access Journals (Sweden)

    Xing eTian

    2010-10-01

    Full Text Available The classical concept of efference copies in the context of internal forward models has stimulated productive research in cognitive science and neuroscience. There are compelling reasons to argue for such a mechanism, but finding direct evidence in the human brain remains difficult. Here we investigate the dynamics of internal forward models from an unconventional angle: mental imagery, assessed while recording high temporal resolution neuronal activity using magnetoencephalography (MEG. We compare two overt and covert tasks; our covert, mental imagery tasks are unconfounded by overt input/output demands – but in turn necessitate the development of appropriate multi-dimensional topographic analyses. Finger tapping (studies 1-2 and speech experiments (studies 3-5 provide temporally constrained results that implicate the estimation of an efference copy. We suggest that one internal forward model over parietal cortex subserves the kinesthetic feeling in motor imagery. Secondly, observed auditory neural activity ~170 ms after motor estimation in speech experiments (studies 3-5 demonstrates the anticipated auditory consequences of planned motor commands in a second internal forward model in imagery of speech production. Our results provide neurophysiological evidence from the human brain in favor of internal forward models deploying efference copies in somatosensory and auditory cortex, in finger tapping and speech production tasks, respectively, and also suggest the dynamics and sequential updating structure of internal forward models.

  9. Efficient Photometry In-Frame Calibration (EPIC) Gaussian Corrections for Automated Background Normalization of Rate-Tracked Satellite Imagery

    Science.gov (United States)

    Griesbach, J.; Wetterer, C.; Sydney, P.; Gerber, J.

    Photometric processing of non-resolved Electro-Optical (EO) images has commonly required the use of dark and flat calibration frames that are obtained to correct for charge coupled device (CCD) dark (thermal) noise and CCD quantum efficiency/optical path vignetting effects respectively. It is necessary to account/calibrate for these effects so that the brightness of objects of interest (e.g. stars or resident space objects (RSOs)) may be measured in a consistent manner across the CCD field of view. Detected objects typically require further calibration using aperture photometry to compensate for sky background (shot noise). For this, annuluses are measured around each detected object whose contained pixels are used to estimate an average background level that is subtracted from the detected pixel measurements. In a new photometric calibration software tool developed for AFRL/RD, called Efficient Photometry In-Frame Calibration (EPIC), an automated background normalization technique is proposed that eliminates the requirement to capture dark and flat calibration images. The proposed technique simultaneously corrects for dark noise, shot noise, and CCD quantum efficiency/optical path vignetting effects. With this, a constant detection threshold may be applied for constant false alarm rate (CFAR) object detection without the need for aperture photometry corrections. The detected pixels may be simply summed (without further correction) for an accurate instrumental magnitude estimate. The noise distribution associated with each pixel is assumed to be sampled from a Poisson distribution. Since Poisson distributed data closely resembles Gaussian data for parameterized means greater than 10, the data may be corrected by applying bias subtraction and standard-deviation division. EPIC performs automated background normalization on rate-tracked satellite images using the following technique. A deck of approximately 50-100 images is combined by performing an independent median

  10. 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...

  11. Modeling GPS satellite attitude variation for precise orbit determination

    Science.gov (United States)

    Kuang, D.; Rim, H. J.; Schutz, B. E.; Abusali, P. A. M.

    1996-09-01

    High precision geodetic applications of the Global Positioning System (GPS) require highly precise ephemerides of the GPS satellites. An accurate model for the non-gravitational forces on the GPS satellites is a key to high quality GPS orbit determination, especially in long arcs. In this paper the effect of the satellite solar panel orientation error is investigated. These effects are approximated by empirical functions to model the satellite attitude variation in long arc orbit fit. Experiments show that major part of the long arc GPS orbit errors can be accommodated by introducing a periodic variation of the satellite solar panel orientation with respect to the satellite-Sun direction, the desired direction for solar panel normal vector, with an amplitude of about 1 degree and with a frequency of once per orbit revolution.

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

    Science.gov (United States)

    Duxbury, T. C.

    1979-01-01

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

  13. 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...

  14. Satellites and Steep Slopes - the challenge of topography in the Himalaya - Karakorum for cryosphere models

    Science.gov (United States)

    Steiner, J. F.; Buri, P.; Miles, E. S.; Immerzeel, W.

    2016-12-01

    The topography in glaciated catchments in the Himalaya - Karakoram range are extreme in a number of aspects that proof to be a challenge for distributed modelling. High altitude regions, where accumulation areas of glaciers are generally located, can at times be very steep, covered in hanging ice and seasonal snow. On the other hand, lower areas, where ablation zones on glacier tongues are located, tend to be very shallow. This has consequences for obtaining glacier areas from satellite derived glacier inventories (e.g. RGI, ICIMOD). As they are taken perpendicular to the center of the earth, these inventories will underestimate the area of steep regions, sometimes quite considerably (Figure 1). This can have consequences for a number of statistics in glaciological modeling, especially when it comes to the relative comparison of accumulation and ablation and hence overall melt from a glacier. Additionally, these steep head walls cause topographic shading. Depending on the exposition of the valley this can result in very divergent amounts of direct solar radiation reaching the glacier surface from valley to valley. Comparisons of melt between different regions and even glaciers have to be taken with considerable caution. Finally, these shallow glacier tongues are increasingly covered in debris. Such glacier surfaces with a debris cover ranging in grain size from sand to boulders several meters in diameter are very hummocky rather than flat bare ice glacier surfaces. This in turn increases local shading but also increases the overall glacier surface. Using high resolution satellite imagery and DEMs ( 5m) from our field site we investigate the effects of areal misrepresentations on the local scale. Decreasing resolution we then take this analysis to the mountain range scale and can identify to what degree these factors are significant and considering literature values determine the quantitative impact for energy and mass balance studies. Figure 1: A schematic

  15. RADARGRAMMETRIC DIGITAL SURFACE MODELS GENERATION FROM TERRASAR-X IMAGERY: CASE STUDIES, PROBLEMS AND POTENTIALITIES

    Directory of Open Access Journals (Sweden)

    P. Capaldo

    2012-07-01

    Full Text Available The interest for the radargrammetric approach to Digital Surface Models (DSMs generation has been growing in last years thanks to the availability of very high resolution imagery acquired by new SAR (Synthetic Aperture Radar sensors, as COSMO-SkyMed, Radarsat-2 and TerraSAR-X, which are able to supply imagery up to 1 m ground resolution. DSMs radargrammetric generation approach consists of two basic steps, as for the standard photogrammetry applied to optical imagery: the imagery (at least a stereo pair orientation and the image matching for the generation of the points cloud. The steps of the radargrammetric DSMs generation have been implemented into SISAR (Software per Immagini Satellitari ad Alta Risoluzione, a scientific software developed at Geodesy and Geomatics Institute of the University of Rome “La Sapienza”. Moreover, starting from the radargrammetric orientation model, a tool for the Rational Polynomial Coefficients (RPCs for SAR images have been implemented. The possibility to generate RPCs, re-parametrizing a rigorous orientation model through a standardized set of coefficients which can be managed by a Rational Polynomial Coefficients (RPFs model (similarly to optical high resolution imagery sounds of particular interest since, at present, the most part of SAR imagery (except from Radarsat-2 is not supplied with RPCs, although the corresponding RPFs model is available in several commercial software. In particular the RPCs model has been used in the matching process and in the stereo restitution for the DSMs generation, with the advantage of shorter computational time. This paper discusses the application and the results of the implemented algorithm for radargrammetric DSMs generation from TerraSAR-X SpotLight imagery, acquired in Spotlight mode over Trento (Northern Italy. Urban and extra-urban (forested, cultivated areas were considered in two different tiles, and a final overall accuracy ranging from 4.5 to 6 meters was

  16. Predictive models to determine imagery strategies employed by children to judge hand laterality.

    Science.gov (United States)

    Spruijt, Steffie; Jongsma, Marijtje L A; van der Kamp, John; Steenbergen, Bert

    2015-01-01

    A commonly used paradigm to study motor imagery is the hand laterality judgment task. The present study aimed to determine which strategies young children employ to successfully perform this task. Children of 5 to 8 years old (N = 92) judged laterality of back and palm view hand pictures in different rotation angles. Response accuracy and response duration were registered. Response durations of the trials with a correct judgment were fitted to a-priori defined predictive sinusoid models, representing different strategies to successfully perform the hand laterality judgment task. The first model predicted systematic changes in response duration as a function of rotation angle of the displayed hand. The second model predicted that response durations are affected by biomechanical constraints of hand rotation. If observed data could be best described by the first model, this would argue for a mental imagery strategy that does not involve motor processes to solve the task. The second model reflects a motor imagery strategy to solve the task. In line with previous research, we showed an age-related increase in response accuracy and decrease in response duration in children. Observed data for both back and palm view showed that motor imagery strategies were used to perform hand laterality judgments, but that not all the children use these strategies (appropriately) at all times. A direct comparison of response duration patterns across age sheds new light on age-related differences in the strategies employed to solve the task. Importantly, the employment of the motor imagery strategy for successful task performance did not change with age.

  17. Runoff modeling of the Mara River using satellite observed soil ...

    African Journals Online (AJOL)

    The model is developed based on the relationships found between satellite observed soil moisture and rainfall and the measured runoff. It uses the satellite observed rainfall as the prime forcing, and the soil moisture to separate the fast surface runoff and slow base flow contributions. The soil moisture and rainfall products ...

  18. Volcanic and Tectonic Activity in the Red Sea Region (2004-2013): Insights from Satellite Radar Interferometry and Optical Imagery

    KAUST Repository

    Xu, Wenbin

    2015-04-01

    Studying recent volcanic and tectonic events in the Red Sea region is important for improving our knowledge of the Red Sea plate boundary and for regional geohazard assessments. However, limited information has been available about the past activity due to insufficient in-situ data and remoteness of some of the activity. In this dissertation, I have used satellite remote sensing to derive new information about several recent volcanic and tectonic events in the Red Sea region. I first report on three volcanic eruptions in the southern Red Sea, the 2007-8 Jebel at Tair eruption and the 2011-12 & 2013 Zubair eruptions, which resulted in formation of two new islands. Series of high- resolution optical images were used to map the extent of lava flows and to observe and analyze the growth and destructive processes of the new islands. I used Interferometric Synthetic Aperture Radar (InSAR) data to study the evolution of lava flows, to estimate their volumes, as well as to generate ground displacements maps, which were used to model the dikes that fed the eruptions. I then report on my work of the 2009 Harrat Lunayyir dike intrusion and the 2004 Tabuk earthquake sequence in western Saudi Arabia. I used InSAR observations and stress calculations to study the intruding dike at Harrat Lunayyir, while I combined InSAR data and Bayesian estimation to study the Tabuk earthquake activity. The key findings of the thesis are: 1) The recent volcanic eruptions in the southern Red Sea indicate that the area is magmatically more active than previously acknowledged and that a rifting episode has been taken place in the southern Red Sea; 2) Stress interactions between an ascending dike intrusion and normal faulting on graben-bounding faults above the dike can inhibit vertical propagation of magma towards the surface; 3) InSAR observations can improve locations of shallow earthquakes and fault model uncertainties are useful to associate earthquake activity with mapped faults; 4). The

  19. Application of a Topological Metric for Assessing Numerical Ocean Models with Satellite Observations

    Science.gov (United States)

    Morey, S. L.; Dukhovskoy, D. S.; Hiester, H. R.; Garcia-Pineda, O. G.; MacDonald, I. R.

    2015-12-01

    Satellite-based sensors provide a vast amount of observational data over the world ocean. Active microwave radars measure changes in sea surface height and backscattering from surface waves. Data from passive radiometers sensing emissions in multiple spectral bands can directly measure surface temperature, be combined with other data sources to estimate salinity, or processed to derive estimates of optically significant quantities, such as concentrations of biochemical properties. Estimates of the hydrographic variables can be readily used for assimilation or assessment of hydrodynamic ocean models. Optical data, however, have been underutilized in ocean circulation modeling. Qualitative assessments of oceanic fronts and other features commonly associated with changes in optically significant quantities are often made through visual comparison. This project applies a topological approach, borrowed from the field of computer image recognition, to quantitatively evaluate ocean model simulations of features that are related to quantities inferred from satellite imagery. The Modified Hausdorff Distance (MHD) provides a measure of the similarity of two shapes. Examples of applications of the MHD to assess ocean circulation models are presented. The first application assesses several models' representation of the freshwater plume structure from the Mississippi River, which is associated with a significant expression of color, using a satellite-derived ocean color index. Even though the variables being compared (salinity and ocean color index) differ, the MHD allows contours of the fields to be compared topologically. The second application assesses simulations of surface oil transport driven by winds and ocean model currents using surface oil maps derived from synthetic aperture radar backscatter data. In this case, maps of time composited oil coverage are compared between the simulations and satellite observations.

  20. Yield and quality prediction using satellite passive imagery and ground-based active optical sensors in sugar beet, spring wheat, corn, and sunflower

    Science.gov (United States)

    Bu, Honggang

    Remote sensing is one possible approach for improving crop nitrogen use efficiency to save fertilizer cost, reduce environmental pollution, and improve crop yield and quality. Feasibility and potential of using remote sensing tools to predict crops yield and quality as well as detect nitrogen requirements, application timing, rate, and places in season were investigated based on 2012-2013 two-year and four-crop (corn, spring wheat, sugar beet, and sunflower) study. Two ground-based active optical sensors, GreenSeeker and Holland Scientific Crop Circle, and the RapidEye satellite imagery were used to collect sensing data. Highly significant statistical relationships between INSEY (NDVI normalized by growing degree days) and crop yield and quality indices were found for all crops, indicating that remote sensing tools may be useful for managing in-season crop yield and quality prediction.

  1. Potential of High-Resolution Satellite Imagery for Mapping Distribution and Evaluating Ecological Characteristics of Tree Species at the Angkor Monument, Cambodia

    Directory of Open Access Journals (Sweden)

    Tomita Mizuki

    2015-01-01

    Full Text Available Large trees play several vital roles in the Angkor monuments landscape. They protect biodiversity, enhance the tourism experience, and provide various ecosystem services to local residents. A clear understanding of forest composition and distribution of individual species, as well as timely monitoring of changes, is necessary for conservation of these trees. using traditional field work, obtaining this sort of data is time-consuming and labour-intensive. This research investigates classification of very high resolution remote sensing data as a tool for efficient analyses. QuickBird satellite imagery was used to clarify the tree species community in and around Preah Khan temple, to elucidate differences in ecological traits among the three dominant species (Dipterocarpus alatus, Lagerstroemia calyculata and Tetrameles nudiflora, and to identify crowns of the dominant species.

  2. Ocean Wave Energy Estimation Using Active Satellite Imagery as a Solution of Energy Scarce in Indonesia Case Study: Poteran Island's Water, Madura

    Science.gov (United States)

    Nadzir, Z. A.; Karondia, L. A.; Jaelani, L. M.; Sulaiman, A.; Pamungkas, A.; Koenhardono, E. S.; Sulisetyono, A.

    2015-10-01

    Ocean wave energy is one of the ORE (Ocean Renewable Energies) sources, which potential, in which this energy has several advantages over fossil energy and being one of the most researched energy in developed countries nowadays. One of the efforts for mapping ORE potential is by computing energy potential generated from ocean wave, symbolized by Watt per area unit using various methods of observation. SAR (Synthetic Aperture Radar) is one of the hyped and most developed Remote Sensing method used to monitor and map the ocean wave energy potential effectively and fast. SAR imagery processing can be accomplished not only in remote sensing data applications, but using Matrices processing application as well such as MATLAB that utilizing Fast Fourier Transform and Band-Pass Filtering methods undergoing Pre-Processing stage. In this research, the processing and energy estimation from ALOSPALSAR satellite imagery acquired on the 5/12/2009 was accomplished using 2 methods (i.e Magnitude and Wavelength). This resulted in 9 potential locations of ocean wave energy between 0-228 W/m2, and 7 potential locations with ranged value between 182-1317 W/m2. After getting through buffering process with value of 2 km (to facilitate the construction of power plant installation), 9 sites of location were estimated to be the most potential location of ocean wave energy generation in the ocean with average depth of 8.058 m and annual wind speed of 6.553 knot.

  3. Structural And Lithological Reconnaissance Studies Of Part Of North Central Nigeria Using Landsat Enhanced Thematic Mapper Plus Etm And Shuttle Radar Topography Mission Srtm Satellite Imageries

    Directory of Open Access Journals (Sweden)

    Apata Dolapo Moses

    2015-08-01

    Full Text Available The Structural and Lithological studies of a part of North Central Nigeria which lies between latitudes 9o11l21.87N and 11o 3l37.29N and longitudes 7o 43l 53.01E and 6o 25l50.65 E covering an area of 170 km by 183 km was carried out using Landsat enhanced thematic mapper plusETM and shuttle radar topography mission satellite imageries SRTM. These imageries were visually and digitally interpreted using softwares such as ArcGis 9.2 Global mapper Multispec Ilwis 3.4 and Microsoft Paint. The zone is comprised of cellar basement rocks such as Granite Migmatite Gneiss Schist and Quartzite which show megascopic structures such as joints faults and folds. The drainage pattern within the area which include dendritic rectangular braided and annular were identified and their geologic implication was inferred. A Rock Outcrop map and a Lineament map of the study area was constructed. Rossete diagram made from the lineaments shows that the principal Strike direction in the study area is NNE-SSW which conforms to the general structural trend direction in the Nigerian Basement.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sylvia Hofmann

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

  7. Analysis of Satellite and Airborne Imagery for Detection of Water Hyacinth and Other Invasive Floating Macrophytes and Tracking of Aquatic Weed Control Efficacy

    Science.gov (United States)

    Potter, Christopher

    2016-01-01

    Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed an 80 percent overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

  8. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

  9. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  10. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  11. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multispectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  12. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  13. Benchmark validation of statistical models: Application to mediation analysis of imagery and memory.

    Science.gov (United States)

    MacKinnon, David P; Valente, Matthew J; Wurpts, Ingrid C

    2018-03-29

    This article describes benchmark validation, an approach to validating a statistical model. According to benchmark validation, a valid model generates estimates and research conclusions consistent with a known substantive effect. Three types of benchmark validation-(a) benchmark value, (b) benchmark estimate, and (c) benchmark effect-are described and illustrated with examples. Benchmark validation methods are especially useful for statistical models with assumptions that are untestable or very difficult to test. Benchmark effect validation methods were applied to evaluate statistical mediation analysis in eight studies using the established effect that increasing mental imagery improves recall of words. Statistical mediation analysis led to conclusions about mediation that were consistent with established theory that increased imagery leads to increased word recall. Benchmark validation based on established substantive theory is discussed as a general way to investigate characteristics of statistical models and a complement to mathematical proof and statistical simulation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  14. Modeling Forest Structural Parameters in the Mediterranean Pines of Central Spain using QuickBird-2 Imagery and Classification and Regression Tree Analysis (CART

    Directory of Open Access Journals (Sweden)

    José A. Delgado

    2012-01-01

    Full Text Available Forest structural parameters such as quadratic mean diameter, basal area, and number of trees per unit area are important for the assessment of wood volume and biomass and represent key forest inventory attributes. Forest inventory information is required to support sustainable management, carbon accounting, and policy development activities. Digital image processing of remotely sensed imagery is increasingly utilized to assist traditional, more manual, methods in the estimation of forest structural attributes over extensive areas, also enabling evaluation of change over time. Empirical attribute estimation with remotely sensed data is frequently employed, yet with known limitations, especially over complex environments such as Mediterranean forests. In this study, the capacity of high spatial resolution (HSR imagery and related techniques to model structural parameters at the stand level (n = 490 in Mediterranean pines in Central Spain is tested using data from the commercial satellite QuickBird-2. Spectral and spatial information derived from multispectral and panchromatic imagery (2.4 m and 0.68 m sided pixels, respectively served to model structural parameters. Classification and Regression Tree Analysis (CART was selected for the modeling of attributes. Accurate models were produced of quadratic mean diameter (QMD (R2 = 0.8; RMSE = 0.13 m with an average error of 17% while basal area (BA models produced an average error of 22% (RMSE = 5.79 m2/ha. When the measured number of trees per unit area (N was categorized, as per frequent forest management practices, CART models correctly classified 70% of the stands, with all other stands classified in an adjacent class. The accuracy of the attributes estimated here is expected to be better when canopy cover is more open and attribute values are at the lower end of the range present, as related in the pattern of the residuals found in this study. Our findings indicate that attributes derived from

  15. HIGH RESOLUTION LANDCOVER MODELLING WITH PLÉIADES IMAGERY AND DEM DATA IN SUPPORT OF FINE SCALE LANDSCAPE THERMAL MODELLING

    Directory of Open Access Journals (Sweden)

    M. Thompson

    2017-11-01

    Full Text Available In the evaluation of air-borne thermal infrared imaging sensors, the use of simulated spectral infrared scenery is a cost-effective way to provide input to the sensor. The benefit of simulated scenes includes control over parameters governing the spectral and related thermal behaviour of the terrain as well as atmospheric conditions. Such scenes need to have a high degree of radiometric and geometric accuracy, as well as high resolution to account for small objects having different spectral and associated thermal properties. In support of this, innovative use of tri-stereo, ultra-high resolution Pléiades satellite imagery is being used to generated high detail, small scale quantitative terrain surface data to compliment comparable optical data in order to produce detailed urban and rural landscape datasets representative of different landscape features, within which spectrally defined characteristics can be subsequently matched to thermal signatures. Pléiades tri-stereo mode, acquired from the same orbit during the same pass, is particularly favourable for reaching the required metric accuracy because images are radiometrically and geometrically very homogeneous, which allows a very good radiometric matching for relief computation. The tri-stereo approach reduces noise and allows significantly enhanced relief description in landscapes where simple stereo imaging cannot see features, such as in dense urban areas or valley bottoms in steep, mountainous areas. This paper describes the datasets that have been generated for DENEL over the Hartebeespoort Dam region, west of Pretoria, South Africa. The final terrain datasets are generated by integrated modelling of both height and spectral surface characteristics within an object-based modelling environment. This approach provides an operational framework for rapid and highly accurate mapping of building and vegetation structure of wide areas, as is required in support of the evaluation of thermal

  16. Influence of Satellite-Based Heterogeneous Vegetation Momentum Roughness on Mesoscale Model Dynamics During IHOP 2002

    Science.gov (United States)

    Jasinski, Michael; Eastman, Joseph; Borak, Jordan

    2010-01-01

    The sensitivity of mesoscale weather prediction model to a vegetation roughness initialization is investigated for the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database previously derived using a physically based procedure and MODIS imagery, and iii) a MODIS climatologic roughness database that possesses the same spatial heterogeneity as (i) but with mean land class values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations from meteorological stations within the Oklahoma mesonet and surrounding region during IHOP20O2. A sensitivity analysis on the impact the MODIS-based roughness fields is also made through a time-series intercomparison of temperature bias, probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE) the results that, for the current replacement of the standard land-cover type based roughness values with the satellite-derived fields statistically improves model performance for most of the observed variables. Further, the satellite-based roughness enhances the surface wind speed, PBL height and TKE production on the order of 3 to l0 percent, with a lesser effect over grassland and cropland domains, and the greater effect over mixed land cover domains

  17. Archaeological Evidence for Abrupt Cimate Change: Results from Satellite Imagery Analysis and Subsequent Ground-Truthing in the El-Manzalah Region, Northeast Egyptian Delta

    Science.gov (United States)

    Parcak, S. H.

    2003-12-01

    The abrupt global climate changes recorded at 8.2, 5.2 and 4.2 ka BP caused a wide range of transformations within ancient societies, including the focus of this study: ancient Egypt . In the case of the climatic changes that occurred at 4.2 ka BP, scholars have debated hotly the events surrounding the "collapse" of the Old Kingdom. Despite such studies into the Old Kingdom's "collapse", there have been insufficient regional settlement pattern studies in Egypt to augment hypotheses concerning the mechanisms behind the cultural transformations that occurred at the end of the Old Kingdom. Utilizing a combination of satellite imagery analysis and subsequent ground-truthing techniques over a broad region in the East Delta, this study aims to reconstruct pharaonic settlement distributions in relation to the changing northeast delta topography, river courses, marshlands, and coastline. Although geo-political and religious factors played varying roles in settlement patterns, this study overlies the economic and environmental components behind the settlement of individual sites and areas. For instance, prior to the formation of the Manzala lagoon, beginning in the 4th century AD, the Mendesian branch of the Nile flowed past Mendes and its satellite, maritime port at Tell Tebilla: As early as the Old Kingdom, Tell Tebilla provided an ideal location for the formation of a town, being well-located to exploit both riverine and maritime transportation routes through trade, and regional floral and faunal resources from hunting, fishing, cultivation and animal husbandry. Key factors such as long-term fluctuations in precipitation, flood levels, and river courses, can affect dramatically the fortunes of individual settlements, areas, and regions, resulting in the decline and abandonment of some sites and the foundation and flourishing of other sites, especially within marginal regions. The Egyptian delta represents an ideal region for studying the impacts of climatic changes

  18. Analytic Models for Sunlight Charging of a Rapidly Spinning Satellite

    National Research Council Canada - National Science Library

    Tautz, Maurice

    2003-01-01

    ... photoelectrons can be blocked by local potential barriers. In this report, we discuss two analytic models for sunlight charging of a rapidly spinning spherical satellite, both of which are based on blocked photoelectron currents...

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

    Science.gov (United States)

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

    2012-08-01

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

  20. The Potential of Satellite Imagery to Estimate Chlorophyll-a and Water Clarity Data For the Assessment of Lake Water Quality

    Science.gov (United States)

    Shrift, M.; Weathers, K. C.; Norouzi, H.; Ewing, H. A.

    2017-12-01

    Lake water quality is declining nationwide and has become a tremendous point of interest. Remote sensing (RS) data have provided the ability to efficiently study oceans and terrestrial systems over space and time. However, fresh water systems, especially small, nutrient poor lakes have only recently been assessed using remote sensing technology. Prior research suggests that there is poor satellite sensitivity to lakes with low chlorophyll a (chl a) values. This study focuses on the potential to utilize Landsat 8 satellite imagery to predict chl a and Secchi disk transparency values from Lake Auburn, Maine, an oligo-mesotrophic lake that is the primary source of drinking water for the cities of Lewiston and Auburn and has had an increasing number of algal blooms. A total of 28 Landsat scenes from 2013-2017 within 4 days of in-lake measurements were collected for band value extraction and radiometric correction. Band combinations were explored and analyzed to obtain the most reliable prediction of in-lake chl a and Secchi disk values. A nonlinear combination of bands 5 and 4 for chl a, and bands 3 and 2 for Secchi disk transparency show the most promising algorithms, with correlations coefficients of 0.57 and 0.74, respectively. The resultant algorithms show promise for utilizing RS data to estimate water quality for a large array of low-nutrient lakes in northern North America, and thereby to gain a better understanding of water quality of our vital fresh water resources.

  1. Spatial estimation of air PM2.5 emissions using activity data, local emission factors and land cover derived from satellite imagery

    Science.gov (United States)

    Gibe, Hezron P.; Cayetano, Mylene G.

    2017-09-01

    Exposure to particulate matter (PM) is a serious environmental problem in many urban areas on Earth. In the Philippines, most existing studies and emission inventories have mainly focused on point and mobile sources, while research involving human exposures to particulate pollutants is rare. This paper presents a method for estimating the amount of fine particulate (PM2.5) emissions in a test study site in the city of Cabanatuan, Nueva Ecija, in the Philippines, by utilizing local emission factors, regionally procured data, and land cover/land use (activity data) interpreted from satellite imagery. Geographic information system (GIS) software was used to map the estimated emissions in the study area. The present results suggest that vehicular emissions from motorcycles and tricycles, as well as fuels used by households (charcoal) and burning of agricultural waste, largely contribute to PM2.5 emissions in Cabanatuan. Overall, the method used in this study can be applied in other small urbanizing cities, as long as on-site specific activity, emission factor, and satellite-imaged land cover data are available.

  2. Characterization of Karenia brevis blooms on the West Florida Shelf using ocean color satellite imagery: implications for bloom maintenance and evolution

    Science.gov (United States)

    Soto, Inia M.; Muller-Karger, Frank E.; Hu, Chuanmin; Wolny, Jennifer

    2017-01-01

    Satellite ocean color remote sensing techniques, coupled with in situ data, were used to examine the spatial extent and evolution of four Karenia brevis blooms on the West Florida Shelf (WFS) in 2004, 2005, 2006, and 2011. Observations were obtained with the moderate resolution imaging spectroradiometer (MODIS-Aqua). These four blooms were delineated by combining remote-sensing reflectance at 555 nm and normalized fluorescence line height. In 2004 and 2005, the WFS was affected by several hurricanes, including the category 5 storm Hurricane Katrina. These hurricanes led to increased river discharge and vertical mixing which favored bloom intensification and dispersion. No hurricanes passed over the WSF in 2006; however, storms in south Florida may have aided bloom intensification via increased river discharge. In 2011, a bloom appeared off Venice, Florida, where several small creeks discharge. The bloom moved south toward Charlotte Harbor where it intensified and lingered for several months as it received nutrients from riverine discharge and upwelling events. While it is difficult to identify initiation stages of a K. brevis bloom (satellite imagery, the techniques used here provide information about bloom evolution (size, duration, and advection) and insight into factors affecting bloom dynamics.

  3. Spatial estimation of air PM2.5 emissions using activity data, local emission factors and land cover derived from satellite imagery

    Directory of Open Access Journals (Sweden)

    H. P. Gibe

    2017-09-01

    Full Text Available Exposure to particulate matter (PM is a serious environmental problem in many urban areas on Earth. In the Philippines, most existing studies and emission inventories have mainly focused on point and mobile sources, while research involving human exposures to particulate pollutants is rare. This paper presents a method for estimating the amount of fine particulate (PM2.5 emissions in a test study site in the city of Cabanatuan, Nueva Ecija, in the Philippines, by utilizing local emission factors, regionally procured data, and land cover/land use (activity data interpreted from satellite imagery. Geographic information system (GIS software was used to map the estimated emissions in the study area. The present results suggest that vehicular emissions from motorcycles and tricycles, as well as fuels used by households (charcoal and burning of agricultural waste, largely contribute to PM2.5 emissions in Cabanatuan. Overall, the method used in this study can be applied in other small urbanizing cities, as long as on-site specific activity, emission factor, and satellite-imaged land cover data are available.

  4. Determination by Landsat Satellite Imagery to Local Scales in Land and Pollution Monitoring: a Case of Buyuk Melen Watershed (Turkey

    Directory of Open Access Journals (Sweden)

    Ipek Barut

    2015-12-01

    Full Text Available Buyuk Melen Watershed; provides drinking water from the Western Black Sea region to Istanbul province, which Large and Small Melen rivers, Asar Suyu, Ugur Suyu and Aksu rivers. Many settlement areas, fertilized agricultural lands, industrial plants and solid/liquid waste dumping areas are present in Melen watershed, causing substantial pollution problems. Melen watershed is at a serious risk of pollution that a lot of settlement areas, agricultural lands, industrial facilities, and solid and liquid waste. In this study, using the LANDSAT satellite data to monitor the status of this area on the potential of the region studied. In the watershed from the past to change of the 1987, 2001, 2006 and 2010 and also supported by satellite data. However, contaminants in the watershed discharges to the inner parts as shown in the satellite data have also been observed that the increase in pollution.

  5. Solar Radiation Received by Slopes Using COMS Imagery, a Physically Based Radiation Model, and GLOBE

    OpenAIRE

    Yeom, Jong-Min; Seo, You-Kyung; Kim, Dong-Su; Han, Kyung-Soo

    2016-01-01

    This study mapped the solar radiation received by slopes for all of Korea, including areas that are not measured by ground station measurements, through using satellites and topographical data. When estimating insolation with satellite, we used a physical model to measure the amount of hourly based solar surface insolation. Furthermore, we also considered the effects of topography using the Global Land One-Kilometer Base Elevation (GLOBE) digital elevation model (DEM) for the actual amount of...

  6. A two-step nearest neighbors algorithm using satellite imagery for predicting forest structure within species composition classes

    Science.gov (United States)

    Ronald E. McRoberts

    2009-01-01

    Nearest neighbors techniques have been shown to be useful for predicting multiple forest attributes from forest inventory and Landsat satellite image data. However, in regions lacking good digital land cover information, nearest neighbors selected to predict continuous variables such as tree volume must be selected without regard to relevant categorical variables such...

  7. Novel method of drizzle formation observation at large horizontal scales using multi-wavelength satellite imagery simulation

    NARCIS (Netherlands)

    Stepanov, I.; Russchenberg, H.W.J.

    2014-01-01

    The observations of on-board satellite imaging radiometers are representative of a far-reaching two-dimensional cloud top properties, however with a cutback in the capacity of profiling the cloud vertically. A combination of simulated radiances calculated at the top of the cloud in the near-infrared

  8. The use of satellite imagery in sardinella and sardine fisheries in the Mauritanian EEZ - Annual Report 2003

    NARCIS (Netherlands)

    Zeeberg, J.J.

    2004-01-01

    Remote sensing research missions on board Dutch freezer trawlers in the Mauritanian EEZ in 2003 have focused on the relationship between water temperature, trawling tactics, and by-catch. During the research missions, which last 8-12 days each, satellite images of sea surface temperature (SST) are

  9. Combining satellite imagery with forest inventory data to assess damage severity following a major blowdown event in northern Minnesota, USA

    Science.gov (United States)

    Mark D. Nelson; Sean P. Healey; W. Keith Moser; Mark H. Hansen

    2009-01-01

    Effects of a catastrophic blowdown event in northern Minnesota, USA were assessed using field inventory data, aerial sketch maps and satellite image data processed through the North American Forest Dynamics programme. Estimates were produced for forest area and net volume per unit area of live trees pre- and post-disturbance, and for changes in volume per unit area and...

  10. Modeling Earth Albedo for Satellites in Earth Orbit

    DEFF Research Database (Denmark)

    Bhanderi, Dan; Bak, Thomas

    2005-01-01

    Many satellite are influences by the Earthøs albedo, though very few model schemes exist.in order to predict this phenomenon. Earth albedo is often treated as noise, or ignored completely. When applying solar cells in the attitude hardware, Earth albedo can cause the attitude estimate to deviate...... with as much as 20 deg. Digital Sun sensors with Earth albedo correction in hardware exist, but are expensive. In addition, albedo estimates are necessary in thermal calculations and power budgets. We present a modeling scheme base4d on Eartht reflectance, measured by NASA's Total Ozone Mapping Spectrometer......, in which the Earth Probe Satellite has recorded reflectivity data daily since mid 1996. The mean of these data can be used to calculate the Earth albedo given the positions of the satellite and the Sun. Our results show that the albedo varies highly with the solar angle to the satellite's field of view...

  11. Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

    Science.gov (United States)

    Huang, Xin; Chen, Huijun; Gong, Jianya

    2018-01-01

    Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed

  12. A sun-crown-sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery

    Science.gov (United States)

    Fan, Yuanchao; Koukal, Tatjana; Weisberg, Peter J.

    2014-10-01

    Canopy shadowing mediated by topography is an important source of radiometric distortion on remote sensing images of rugged terrain. Topographic correction based on the sun-canopy-sensor (SCS) model significantly improved over those based on the sun-terrain-sensor (STS) model for surfaces with high forest canopy cover, because the SCS model considers and preserves the geotropic nature of trees. The SCS model accounts for sub-pixel canopy shadowing effects and normalizes the sunlit canopy area within a pixel. However, it does not account for mutual shadowing between neighboring pixels. Pixel-to-pixel shadowing is especially apparent for fine resolution satellite images in which individual tree crowns are resolved. This paper proposes a new topographic correction model: the sun-crown-sensor (SCnS) model based on high-resolution satellite imagery (IKONOS) and high-precision LiDAR digital elevation model. An improvement on the C-correction logic with a radiance partitioning method to address the effects of diffuse irradiance is also introduced (SCnS + C). In addition, we incorporate a weighting variable, based on pixel shadow fraction, on the direct and diffuse radiance portions to enhance the retrieval of at-sensor radiance and reflectance of highly shadowed tree pixels and form another variety of SCnS model (SCnS + W). Model evaluation with IKONOS test data showed that the new SCnS model outperformed the STS and SCS models in quantifying the correlation between terrain-regulated illumination factor and at-sensor radiance. Our adapted C-correction logic based on the sun-crown-sensor geometry and radiance partitioning better represented the general additive effects of diffuse radiation than C parameters derived from the STS or SCS models. The weighting factor Wt also significantly enhanced correction results by reducing within-class standard deviation and balancing the mean pixel radiance between sunlit and shaded slopes. We analyzed these improvements with model

  13. Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery

    Science.gov (United States)

    Helmer, E.H.; Kennaway, T.A.; Pedreros, D.H.; Clark, M.L.; Marcano-Vega, H.; Tieszen, L.L.; Ruzycki, T.R.; Schill, S.R.; Carrington, C.M.S.

    2008-01-01

    Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius, testing a more detailed classification than earlier work in the latter three islands. Secondly, we estimate the extents of land cover and protected forest by formation for five islands and ask how land cover has changed over the second half of the 20th century. The image interpretation approach combines image mosaics and ancillary geographic data, classifying the resulting set of raster data with decision tree software. Cloud-free image mosaics for one or two seasons were created by applying regression tree normalization to scene dates that could fill cloudy areas in a base scene. Such mosaics are also known as cloud-filled, cloud-minimized or cloud-cleared imagery, mosaics, or composites. The approach accurately distinguished several classes that more standard methods would confuse; the seamless mosaics aided reference data collection; and the multiseason imagery allowed us to separate drought deciduous forests and woodlands from semi-deciduous ones. Cultivated land areas declined 60 to 100 percent from about 1945 to 2000 on several islands. Meanwhile, forest cover has increased 50 to 950%. This trend will likely continue where sugar cane cultivation has dominated. Like the island of Puerto Rico, most higher-elevation forest formations are protected in formal or informal reserves. Also similarly, lowland forests, which are drier forest types on these islands, are not well represented in reserves. Former cultivated lands in lowland areas could provide lands for new reserves of drier forest types. The land-use history of these islands may provide insight for planners in countries currently considering

  14. Identification and Quantification of Tree Species in Open Mixed Forests using High Resolution QuickBird Satellite Imagery

    Directory of Open Access Journals (Sweden)

    S Arockiaraj

    2015-12-01

    Full Text Available Present study deals with identification and quantification of tree species within an open mixed forest in parts of Ranchi district Jharkhand, India using high resolution QuickBird satellite data using image processing and GIS techniques. A high resolution QuickBird satellite image was used for shadow enhancement and tree crown area extraction. The First Principal Component of QuickBird satellite images was employed to enhance the shadowed area and subsequently shadow and non-shadow area were classified using ISODATA. The satellite image was used for crown area extraction with standard deviation of NDVI value and the crowns were classified into five classes using Maximum Likelihood supervised algorithm. Result shows that barring few limitation, the high resolution QuickBird image provides rapid and accurate results in terms of identification and quantification of tree species in conjugation with field verification and attained 88% of classification accuracy. It reduces the time required for obtaining inventory data in open mixed forest. Results also showed that total 5,522 trees of various species were present in the study area and dominated by Shorea robusta (80.48% followed by Ziziphus mauritiana (16.26%, unknown tree (1.81%, Ficus religiosa (0.98% and Mangifera indica (0.47%. The demography patterns of the locals mainly tribal (89.9% exhibited their direct as well as indirect dependency on mixed forests resources for their subsistence and livelihood. The study necessitate towards the effective implication of policies to raise the standard of living of tribal people in the region.

  15. ISBDD Model for Classification of Hyperspectral Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Na Li

    2018-03-01

    Full Text Available The diverse density (DD algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels. However, the feature vector learned by the DD algorithm cannot always effectively represent one type of ground cover. To handle this problem, an instance space-based diverse density (ISBDD model that employs a novel training strategy is proposed in this paper. In the ISBDD model, DD values of each pixel are computed instead of learning a feature vector, and as a result, the pixel can be classified according to its DD values. Airborne hyperspectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS sensor and the Push-broom Hyperspectral Imager (PHI are applied to evaluate the performance of the proposed model. Results show that the overall classification accuracy of ISBDD model on the AVIRIS and PHI images is up to 97.65% and 89.02%, respectively, while the kappa coefficient is up to 0.97 and 0.88, respectively.

  16. Critical Analysis of Forest Degradation in the Southern Eastern Ghats of India: Comparison of Satellite Imagery and Soil Quality Index.

    Science.gov (United States)

    Ramachandran, Andimuthu; Radhapriya, Parthasarathy; Jayakumar, Shanmuganathan; Dhanya, Praveen; Geetha, Rajadurai

    2016-01-01

    India has one of the largest assemblages of tropical biodiversity, with its unique floristic composition of endemic species. However, current forest cover assessment is performed via satellite-based forest surveys, which have many limitations. The present study, which was performed in the Eastern Ghats, analysed the satellite-based inventory provided by forest surveys and inferred from the results that this process no longer provides adequate information for quantifying forest degradation in an empirical manner. The study analysed 21 soil properties and generated a forest soil quality index of the Eastern Ghats, using principal component analysis. Using matrix modules and geospatial technology, we compared the forest degradation status calculated from satellite-based forest surveys with the degradation status calculated from the forest soil quality index. The Forest Survey of India classified about 1.8% of the Eastern Ghats' total area as degraded forests and the remainder (98.2%) as open, dense, and very dense forests, whereas the soil quality index results found that about 42.4% of the total area is degraded, with the remainder (57.6%) being non-degraded. Our ground truth verification analyses indicate that the forest soil quality index along with the forest cover density data from the Forest Survey of India are ideal tools for evaluating forest degradation.

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

    Science.gov (United States)

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

    2010-01-01

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

  18. Investigations in Satellite MIMO Channel Modeling: Accent on Polarization

    Directory of Open Access Journals (Sweden)

    Karagiannidis George K

    2007-01-01

    Full Text Available Due to the much different environment in satellite and terrestrial links, possibilities in and design of MIMO systems are rather different as well. After pointing out these differences and problems arising from them, two MIMO designs are shown rather well adapted to satellite link characteristics. Cooperative diversity seems to be applicable; its concept is briefly presented without a detailed discussion, leaving solving particular satellite problems to later work. On the other hand, a detailed discussion of polarization time-coded diversity (PTC is given. A physical-statistical model for dual-polarized satellite links is presented together with measuring results validating the model. The concept of 3D polarization is presented as well as briefly describing compact 3D-polarized antennas known from the literature and applicable in satellite links. A synthetic satellite-to-indoor link is constructed and its electromagnetic behavior is simulated via the FDTD (finite-difference time-domain method. Previous result of the authors states that in 3D-PTC situations, MIMO capacity can be about two times higher than SIMO (single-input multiple-output capacity while a diversity gain of nearly is further verified via extensive FDTD computer simulation.

  19. Investigations in Satellite MIMO Channel Modeling: Accent on Polarization

    Directory of Open Access Journals (Sweden)

    Péter Horváth

    2007-05-01

    Full Text Available Due to the much different environment in satellite and terrestrial links, possibilities in and design of MIMO systems are rather different as well. After pointing out these differences and problems arising from them, two MIMO designs are shown rather well adapted to satellite link characteristics. Cooperative diversity seems to be applicable; its concept is briefly presented without a detailed discussion, leaving solving particular satellite problems to later work. On the other hand, a detailed discussion of polarization time-coded diversity (PTC is given. A physical-statistical model for dual-polarized satellite links is presented together with measuring results validating the model. The concept of 3D polarization is presented as well as briefly describing compact 3D-polarized antennas known from the literature and applicable in satellite links. A synthetic satellite-to-indoor link is constructed and its electromagnetic behavior is simulated via the FDTD (finite-difference time-domain method. Previous result of the authors states that in 3D-PTC situations, MIMO capacity can be about two times higher than SIMO (single-input multiple-output capacity while a diversity gain of nearly 2×3 is further verified via extensive FDTD computer simulation.

  20. Resolution Enhancement of Multilook Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Galbraith, Amy E. [Univ. of Arizona, Tucson, AZ (United States)

    2004-07-01

    This dissertation studies the feasibility of enhancing the spatial resolution of multi-look remotely-sensed imagery using an iterative resolution enhancement algorithm known as Projection Onto Convex Sets (POCS). A multi-angle satellite image modeling tool is implemented, and simulated multi-look imagery is formed to test the resolution enhancement algorithm. Experiments are done to determine the optimal con guration and number of multi-angle low-resolution images needed for a quantitative improvement in the spatial resolution of the high-resolution estimate. The important topic of aliasing is examined in the context of the POCS resolution enhancement algorithm performance. In addition, the extension of the method to multispectral sensor images is discussed and an example is shown using multispectral confocal fluorescence imaging microscope data. Finally, the remote sensing issues of atmospheric path radiance and directional reflectance variations are explored to determine their effect on the resolution enhancement performance.

  1. New Methods for Air Quality Model Evaluation with Satellite Data

    Science.gov (United States)

    Holloway, T.; Harkey, M.

    2015-12-01

    Despite major advances in the ability of satellites to detect gases and aerosols in the atmosphere, there remains significant, untapped potential to apply space-based data to air quality regulatory applications. Here, we showcase research findings geared toward increasing the relevance of satellite data to support operational air quality management, focused on model evaluation. Particular emphasis is given to nitrogen dioxide (NO2) and formaldehyde (HCHO) from the Ozone Monitoring Instrument aboard the NASA Aura satellite, and evaluation of simulations from the EPA Community Multiscale Air Quality (CMAQ) model. This work is part of the NASA Air Quality Applied Sciences Team (AQAST), and is motivated by ongoing dialog with state and federal air quality management agencies. We present the response of satellite-derived NO2 to meteorological conditions, satellite-derived HCHO:NO2 ratios as an indicator of ozone production regime, and the ability of models to capture these sensitivities over the continental U.S. In the case of NO2-weather sensitivities, we find boundary layer height, wind speed, temperature, and relative humidity to be the most important variables in determining near-surface NO2 variability. CMAQ agreed with relationships observed in satellite data, as well as in ground-based data, over most regions. However, we find that the southwest U.S. is a problem area for CMAQ, where modeled NO2 responses to insolation, boundary layer height, and other variables are at odds with the observations. Our analyses utilize a software developed by our team, the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS): a free, open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates level 2 satellite retrievals onto a user-defined fixed grid, in effect creating custom-gridded level 3 satellite product. Currently, WHIPS can process the following data products: OMI NO2 (NASA retrieval); OMI NO2 (KNMI retrieval); OMI

  2. Merging Hyperspectural Imagery and Multi Scale Modeling for Laser Lethality

    Science.gov (United States)

    2016-02-24

    the target surface, (3) the distinct characteristics of short pulse laser interactions with a metal target under conditions of spatial confinement by a...phase hydrodynamic simulations of continuous wave (CW) laser interactions with metals is developed and used for investigation of the relative...model is developed and applied for investigation of the distinct characteristics of short pulse laser interactions with a metal target under

  3. Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery

    Science.gov (United States)

    Qin, Rongjun

    2014-10-01

    Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with "change", "non-change" and "uncertain change" status labeled through a voting strategy. The "uncertain changes" are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are

  4. A two year (2008-2009) analysis of severe convective storms in the Mediterranean basin as observed by satellite imagery

    Science.gov (United States)

    Gozzini, B.; Melani, S.; Pasi, F.; Ortolani, A.

    2010-09-01

    The increasing damages caused by natural disasters, a great part of them being direct or indirect effects of severe convective storms (SCS), seem to suggest that extreme events occur with greater frequency, also as a consequence of climate changes. A better comprehension of the genesis and evolution of SCS is then necessary to clarify if and what is changing in these extreme events. The major reason to go through the mechanisms driving such events is given by the growing need to have timely and precise predictions of severe weather events, especially in areas that show to be more and more sensitive to their occurrence. When dealing with severe weather events, either from a researcher or an operational point of view, it is necessary to know precisely the conditions under which these events take place to upgrade conceptual models or theories, and consequently to improve the quality of forecasts as well as to establish effective warning decision procedures. The Mediterranean basin is, in general terms, a sea of small areal extent, characterised by the presence of several islands; thus, a severe convection phenomenon originating over the sea, that lasts several hours, is very likely to make landfall during its lifetime. On the other hand, these storms are quasi-stationary or very slow moving so that, when convection happens close to the shoreline, it is normally very dangerous and in many cases can cause very severe weather, with flash floods or tornadoes. An example of these extreme events is one of the case study analysed in this work, regarding the flash flood occurred in Giampileri (Sicily, Italy) the evening of 1st October 2009, where 18 people died, other 79 injured and the historical centre of the village seriously damaged. Severe weather systems and strong convection occurring in the Mediterranean basin have been investigated for two years (2008-2009) using geostationary (MSG) and polar orbiting (AVHRR) satellite data, supported by ECMWF analyses and severe

  5. Transformation of Landsat imagery into pseudo-hyperspectral imagery by a multiple regression-based model with application to metal deposit-related minerals mapping

    Science.gov (United States)

    Hoang, Nguyen Tien; Koike, Katsuaki

    2017-11-01

    Hyperspectral remote sensing is superior to traditional multispectral remote sensing in detailed spectral information but has limited spatial and temporal coverage. Those limitations require an innovative technique that can simulate hyperspectral imagery from multispectral imagery with global coverage, continuous acquisition, and a small number of bands. For this, a combination of Hyperion and Landsat 7 ETM+ images is a representative target. The present study develops a new method, Pseudo-Hyperspectral Image Transformation Algorithm (PHITA), for transforming Landsat 7 ETM+ imagery into pseudo-Hyperion imagery using correlations between Landsat and Hyperion band reflectance data. Each correlation is defined as a multiple linear regression model selected through Bayesian model averaging, in which Hyperion and Landsat bands are dependent and predictor variables, respectively. The resultant pseudo-image has a number of high-quality Hyperion bands of the same scene size as a Landsat image. Through verification of transformation accuracy by statistical analyses and surface mineral mapping, the pseudo-Hyperion image was proven very similar to the original band reflectances, because of large Pearson's correlation coefficients (generally > 0.94), small RMS error (mostly advantage of the pseudo-image is clarified for the Cuprite hydrothermal alteration area in the western United States. The identification and mapping accuracies of metal deposit-related minerals were high even in areas outside the original Hyperion scene. Featured absorptions were reconstructed in pseudo-reflectance spectra of the typical minerals in the area. The results can enhance the potential of a large Landsat-series dataset over the long term by transformation into pseudo-Hyperion images for global land surfaces.

  6. Constraining the parameters of the EAP sea ice rheology from satellite observations and discrete element model

    Science.gov (United States)

    Tsamados, Michel; Heorton, Harry; Feltham, Daniel; Muir, Alan; Baker, Steven

    2016-04-01

    The new elastic-plastic anisotropic (EAP) rheology that explicitly accounts for the sub-continuum anisotropy of the sea ice cover has been implemented into the latest version of the Los Alamos sea ice model CICE. The EAP rheology is widely used in the climate modeling scientific community (i.e. CPOM stand alone, RASM high resolution regional ice-ocean model, MetOffice fully coupled model). Early results from sensitivity studies (Tsamados et al, 2013) have shown the potential for an improved representation of the observed main sea ice characteristics with a substantial change of the spatial distribution of ice thickness and ice drift relative to model runs with the reference visco-plastic (VP) rheology. The model contains one new prognostic variable, the local structure tensor, which quantifies the degree of anisotropy of the sea ice, and two parameters that set the time scale of the evolution of this tensor. Observations from high resolution satellite SAR imagery as well as numerical simulation results from a discrete element model (DEM, see Wilchinsky, 2010) have shown that these individual floes can organize under external wind and thermal forcing to form an emergent isotropic sea ice state (via thermodynamic healing, thermal cracking) or an anisotropic sea ice state (via Coulombic failure lines due to shear rupture). In this work we use for the first time in the context of sea ice research a mathematical metric, the Tensorial Minkowski functionals (Schroeder-Turk, 2010), to measure quantitatively the degree of anisotropy and alignment of the sea ice at different scales. We apply the methodology on the GlobICE Envisat satellite deformation product (www.globice.info), on a prototype modified version of GlobICE applied on Sentinel-1 Synthetic Aperture Radar (SAR) imagery and on the DEM ice floe aggregates. By comparing these independent measurements of the sea ice anisotropy as well as its temporal evolution against the EAP model we are able to constrain the

  7. AN ENHANCED ALGORITHM FOR AUTOMATIC RADIOMETRIC HARMONIZATION OF HIGH-RESOLUTION OPTICAL SATELLITE IMAGERY USING PSEUDOINVARIANT FEATURES AND LINEAR REGRESSION

    Directory of Open Access Journals (Sweden)

    M. Langheinrich

    2017-05-01

    Full Text Available The growing number of available optical remote sensing data providing large spatial and temporal coverage enables the coherent and gapless observation of the earth’s surface on the scale of whole countries or continents. To produce datasets of that size, individual satellite scenes have to be stitched together forming so-called mosaics. Here the problem arises that the different images feature varying radiometric properties depending on the momentary acquisition conditions. The interpretation of optical remote sensing data is to a great extent based on the analysis of the spectral composition of an observed surface reflection. Therefore the normalization of all images included in a large image mosaic is necessary to ensure consistent results concerning the application of procedures to the whole dataset. In this work an algorithm is described which enables the automated spectral harmonization of satellite images to a reference scene. As the stable and satisfying functionality of the proposed algorithm was already put to operational use to process a high number of SPOT-4/-5, IRS LISS-III and Landsat-5 scenes in the frame of the European Environment Agency's Copernicus/GMES Initial Operations (GIO High-Resolution Layer (HRL mapping of the HRL Forest for 20 Western, Central and (SouthEastern European countries, it is further evaluated on its reliability concerning the application to newer Sentinel-2 multispectral imaging products. The results show that the algorithm is comparably efficient for the processing of satellite image data from sources other than the sensor configurations it was originally designed for.

  8. Geo-Parcel Based Crop Identification by Integrating High Spatial-Temporal Resolution Imagery from Multi-Source Satellite Data

    Directory of Open Access Journals (Sweden)

    Yingpin Yang

    2017-12-01

    Full Text Available Geo-parcel based crop identification plays an important role in precision agriculture. It meets the needs of refined farmland management. This study presents an improved identification procedure for geo-parcel based crop identification by combining fine-resolution images and multi-source medium-resolution images. GF-2 images with fine spatial resolution of 0.8 m provided agricultural farming plot boundaries, and GF-1 (16 m and Landsat 8 OLI data were used to transform the geo-parcel based enhanced vegetation index (EVI time-series. In this study, we propose a piecewise EVI time-series smoothing method to fit irregular time profiles, especially for crop rotation situations. Global EVI time-series were divided into several temporal segments, from which phenological metrics could be derived. This method was applied to Lixian, where crop rotation was the common practice of growing different types of crops, in the same plot, in sequenced seasons. After collection of phenological features and multi-temporal spectral information, Random Forest (RF was performed to classify crop types, and the overall accuracy was 93.27%. Moreover, an analysis of feature significance showed that phenological features were of greater importance for distinguishing agricultural land cover compared to temporal spectral information. The identification results indicated that the integration of high spatial-temporal resolution imagery is promising for geo-parcel based crop identification and that the newly proposed smoothing method is effective.

  9. Assessment of burned areas in Mato Grosso State, Brazil, from a systematic sample of medium resolution satellite imagery

    OpenAIRE

    SHIMABUKURO YOSIO EDEMIR; BEUCHLE Rene'; GRECCHI ROSANA; SIMONETTI DARIO; ACHARD Frederic

    2014-01-01

    This paper presents a method for mapping and assessing burned areas at a regional scale, using a systematic sample of medium spatial resolution satellite images (Landsat). The State of Mato Grosso, located in the Brazilian Amazon region, comprising an area of pproximately 903,366 km², was selected for this study. 77 sample sites (20km × 20km in size) located at each full degree confluence of latitude and longitude were analyzed. The results showed that 52,663 km² or approximately 5.8% of the ...

  10. Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to MODIS satellite imagery

    Science.gov (United States)

    Park, Isaac W.

    2012-11-01

    This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to satellite-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods.

  11. ACCURACY COMPARISON OF DIGITAL SURFACE MODELS CREATED BY UNMANNED AERIAL SYSTEMS IMAGERY AND TERRESTRIAL LASER SCANNER

    Directory of Open Access Journals (Sweden)

    M. Naumann

    2013-08-01

    Full Text Available The main focus of the paper is a comparative study in which we have investigated, whether automatically generated digital surface models (DSM obtained from unmanned aerial systems (UAS imagery are comparable with DSM obtained from terrestrial laser scanning (TLS. The research is conducted at a pilot dike for coastal engineering. The effort and the achievable accuracy of both DSMs are compared. The error budgets of these two methods are investigated and the models obtained in each case compared against each other.

  12. Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling

    Science.gov (United States)

    Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.

    2015-01-01

    Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless

  13. Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Yu Hsin Tsai

    2011-12-01

    Full Text Available The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1 post-classification comparison; and (2 bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst outperformed the true object-based feature delineation approach (ENVI Feature Extraction due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00. The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change.

  14. Estimating rural populations without access to electricity in developing countries through night-time light satellite imagery

    International Nuclear Information System (INIS)

    Doll, Christopher N.H.; Pachauri, Shonali

    2010-01-01

    A lack of access to energy and, in particular, electricity is a less obvious manifestation of poverty but arguably one of the most important. This paper investigates the extent to which electricity access can be investigated using night-time light satellite data and spatially explicit population datasets to compare electricity access between 1990 and 2000. We present here the first satellite derived estimates of rural population without access to electricity in developing countries to draw insights on issues surrounding the delivery of electricity to populations in rural areas. The paper provides additional evidence of the slow progress in expansion of energy access to households in Sub-Saharan Africa and shows how this might be ascribed in part due to the low population densities in rural areas. The fact that this is a continent with some of the lowest per-capita income levels aggravates the intrinsic difficulties associated with making the investments needed to supply electricity in areas with low population density and high dispersion. Clearly, these spatial dimensions of the distributions of the remaining unelectrified populations in the world have an impact on what options are considered the most appropriate in expanding access to these households and the relative attractiveness of decentralized options.

  15. Object-Based Greenhouse Horticultural Crop Identification from Multi-Temporal Satellite Imagery: A Case Study in Almeria, Spain

    Directory of Open Access Journals (Sweden)

    Manuel A. Aguilar

    2015-06-01

    Full Text Available Greenhouse detection and mapping via remote sensing is a complex task, which has already been addressed in numerous studies. In this research, the innovative goal relies on the identification of greenhouse horticultural crops that were growing under plastic coverings on 30 September 2013. To this end, object-based image analysis (OBIA and a decision tree classifier (DT were applied to a set consisting of eight Landsat 8 OLI images collected from May to November 2013. Moreover, a single WorldView-2 satellite image acquired on 30 September 2013, was also used as a data source. In this approach, basic spectral information, textural features and several vegetation indices (VIs derived from Landsat 8 and WorldView-2 multi-temporal satellite data were computed on previously segmented image objects in order to identify four of the most popular autumn crops cultivated under greenhouse in Almería, Spain (i.e., tomato, pepper, cucumber and aubergine. The best classification accuracy (81.3% overall accuracy was achieved by using the full set of Landsat 8 time series. These results were considered good in the case of tomato and pepper crops, being significantly worse for cucumber and aubergine. These results were hardly improved by adding the information of the WorldView-2 image. The most important information for correct classification of different crops under greenhouses was related to the greenhouse management practices and not the spectral properties of the crops themselves.

  16. Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

    Science.gov (United States)

    Shiffman, Smadar

    2004-01-01

    Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

  17. Initialization of a mesoscale model with satellite derived temperature profiles

    Science.gov (United States)

    Kalb, Michael W.

    1986-01-01

    The abilities of rawinsonde data and Tiros-N satellite derived temperature profile data to depict mesoscale precipitation accumulation are evaluated. Four mesoscale simulations using combinations of temperature, low-level wind, and low-level wind initialization were performed with the limited area mesoscale prediction system (LAMPS) model. Comparisons of the simulations with operational LFM forecast accumulations reveal that the LAMPS model simulations provide a better depiction of the observed precipitation accumulation than the LFM forecasts, and the satellite temperature profiles produce better mesoscale precipitation accumulation forecasts than the rawinsonde temperature data.

  18. Comparing satellite SAR and wind farm wake models

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Vincent, P.; Husson, R.

    2015-01-01

    . These extend several tens of kilometres downwind e.g. 70 km. Other SAR wind maps show near-field fine scale details of wake behind rows of turbines. The satellite SAR wind farm wake cases are modelled by different wind farm wake models including the PARK microscale model, the Weather Research and Forecasting...... (WRF) model in high resolution and WRF with coupled microscale parametrization....

  19. Mapping Nearshore Seagrass and Colonized Hard Bottom Spatial Distribution and Percent Biological Cover in Florida, USA Using Object Based Image Analysis of WorldView-2 Satellite Imagery

    Science.gov (United States)

    Baumstark, R. D.; Duffey, R.; Pu, R.

    2016-12-01

    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 depicting the spatial distribution and percent biological cover were created from WorldView-2 satellite imagery using 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 presents an alternative for mapping deeper, offshore habitats capable of producing higher thematic (percent biological cover) and spatial resolution maps compared to those created with the traditional photo-interpretation method.

  20. Morphodynamics of nearshore rhythmic sandbars in a mixed-energy environment (SW France): I. Mapping beach changes using visible satellite imagery

    Science.gov (United States)

    Lafon, V.; De Melo Apoluceno, D.; Dupuis, H.; Michel, D.; Howa, H.; Froidefond, J. M.

    2004-10-01

    This paper presents a new method to analyze the morphology and migration of shallow water sandbanks based on the retrieval of maps from high-resolution Spot satellite imagery. This approach was applied to the study of intertidal ridge and runnel systems and subtidal crescents that border the southwest coast of France. Maps were obtained from 16 Spot images recorded between 1986 and 2000. Ridge and runnel shapes, with regard to a reference level, were delineated using a watercolor reflectance code parameterized and validated with field data. Crescent plan shapes, which appear on the images due to water transparency or breaking-induced foam, were directly extracted. The spatial maps show that, in conformity with field surveys, the mean alongshore spacing of intertidal systems and crescents range from 370 ± 146 m (variability is indicated by standard deviation) to 462 ± 188 m, and from 579 ± 200 to 818 ± 214 m, respectively. Several couples of images also show that ridge and runnel systems and crescents move in the longshore drift direction (southward) by about 2.4-3.1 and 1 m day -1, respectively. Alongshore migration rates of intertidal systems are confirmed by field surveys, whilst crescent dynamics cannot be validated because there is no in situ data available. To complete these measurements, an analysis of the influence of wave climate on both the shape and movements of these rhythmic sedimentary patterns is proposed in a companion paper.

  1. Relative abundance of 'Bacillus' spp., surfactant-associated bacterium present in a natural sea slick observed by satellite SAR imagery over the Gulf of Mexico

    Directory of Open Access Journals (Sweden)

    Kathryn Lynn Howe

    2018-01-01

    Full Text Available The damping of short gravity-capillary waves (Bragg waves due to surfactant accumulation under low wind speed conditions results in the formation of natural sea slicks. These slicks are detectable visually and in synthetic aperture radar satellite imagery. Surfactants are produced by natural life processes of many marine organisms, including bacteria, phytoplankton, seaweed, and zooplankton. In this work, samples were collected in the Gulf of Mexico during a research cruise on the R/V 'F.G. Walton Smith' to evaluate the relative abundance of 'Bacillus' spp., surfactant-associated bacteria, in the sea surface microlayer compared to the subsurface water at 0.2 m depth. A method to reduce potential contamination of microlayer samples during their collection on polycarbonate filters was implemented and advanced, including increasing the number of successive samples per location and changing sample storage procedures. By using DNA analysis (real-time polymerase chain reaction to target 'Bacillus' spp., we found that in the slick areas, these surfactant-associated bacteria tended to reside mostly in subsurface waters, lending support to the concept that the surfactants they may produce move to the surface where they accumulate under calm conditions and enrich the sea surface microlayer.

  2. Ten Years of Post-Fire Vegetation Recovery following the 2007 Zaca Fire using Landsat Satellite Imagery

    Science.gov (United States)

    Hallett, J. K. E.; Miller, D.; Roberts, D. A.

    2017-12-01

    Forest fires play a key role in shaping eco-systems. The risk to vegetation depends on the fire regime, fuel conditions (age and amount), fire temperature, and physiological characteristics such as bark thickness and stem diameter. The 2007 Zaca Fire (24 kilometers NE of Buellton, Santa Barbara County, California) burned 826.4 km2 over the course of 2 months. In this study, we used a time series of Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager imagery, to evaluate plant burn severity and post fire recovery as defined into classes of above average recovery, normal recovery, and below average recovery. We spectrally unmixed the images into green vegetation (GV), non-photosynthetic vegetation (NPV), soil surface (SOIL), and ash with a spectral library developed using Constrained Reference Endmember Selection (CRES). We delineated the fire perimeter using the differenced Normalized Burn Ratio (dNBR) and evaluated changes in this index and the Normalized Difference Vegetation Index through time. The results showed an immediate decline in GV and NPV fractions, with a rise in soil and ash fractions directly following the fire, with a slow recovery in GV fraction and a loss of bare soil cover. The was a sharp increase in the ash fraction following the fire and gradual decrease in the year after. Most areas have recovered as of 2017, with prominent recovery in the center of the burn scar and reduced recovery in areas to the south. These results indicate how post-fire vegetation varies based on initial burn severity and pre-fire GV and NPV fractions.

  3. A Study on Rational Function Model Generation for TerraSAR-X Imagery

    Directory of Open Access Journals (Sweden)

    Mahdi Motagh

    2013-09-01

    Full Text Available The Rational Function Model (RFM has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10−3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.

  4. Radar Satellite Imagery and Automatic Detection of Water Bodies : Radarski satelitski snimci i automatsko otkrivanje vodenih površina

    Directory of Open Access Journals (Sweden)

    Klemen Čotar

    2016-12-01

    Full Text Available System for mapping of water bodies in Slovenia and its immediate neighbourhood with Sentinel-1 radar satellites have implemented. Algorithms automatically detect presence of new data in the archive, download the data, analyse it, write the results, and upload them to a web portal. New acquisitions are currently available every six days, but this time will be halved when the second Sentinel-1 starts delivering the data. : Implementiran je sistem za kartiranje vodenih površina u Sloveniji i u neposrednoj blizini sa Sentinel-1 radarskim satelitima. Algoritmi automatski otkrivaju prisutnost novih podataka u arhivu, preuzimaju podatake, analiziraju, objavljuju rezultate, te ih prenose na web-portal. Nove akvizicije su trenutno dostupne svakih šest dana, ali ovaj puta će vrijeme biti prepolovljeno, kada drugi Sentinel-1 počne sa isporukom podataka.

  5. Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Moody, Daniela Irina

    2018-04-17

    An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

  6. Analysis of the most important river plumes on the Atlantic and Mediterranean Iberian coast by means of satellite imagery

    Directory of Open Access Journals (Sweden)

    Diego Fernandez Novoa

    2014-06-01

    Full Text Available Rivers discharges cause the formation of buoyant plumes in the adjacent coastal area at their mouths, which are characterized by low-salinity water and controlled by outflow inertia, rotation (Coriolis effects, buoyancy, wind, and tide forcing. The turbid plumes influence the adjacent coastal area, since they control the patterns of nutrients, sediments and/or pollutants of fluvial origin on the coastal ocean and can promote strong physical and chemical changes on seawater. These changes affect the biological characteristics of the area, such as primary production, species composition, abundance and distribution of existing microorganism, which demonstrates its high ecological importance. The characterization of the most important river plumes along the Atlantic Iberian coast and the influence of the main forcing drivers (river discharge, wind and tide on them, was carried out through the analysis of plume mean-state images calculated using water leaving radiance data (nLw555 obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer sensor onboard the Aqua satellite during 2003-2013. Satellite data are downloaded from Ocean Color web site (http://oceancolor.gsfc.nasa.gov. Daily high-resolution L1 files from MODIS-Aqua were processed through SeaDAS software. Composite images, interpolated to a regular pixel grid with an approximate resolution of 500m, were built for different synoptic conditions of river discharge, wind regimes and tide, in order to obtain a representative average plume image of each situation and river for the posterior analysis. Results showed that the river discharge is the main forcing factor in the river plume extension. Wind effect is noticeable under high river discharge and tide is important for the estuarine outflow regimes although with some remarkable similarities and differences between the Atlantic rivers due to their intrinsic characteristics.

  7. Empirical Modeling of Solar Radiation Pressure Forces Affecting GPS Satellites

    Science.gov (United States)

    Sibthorpe, A.; Weiss, J. P.; Harvey, N.; Kuang, D.; Bar-Sever, Y.

    2010-12-01

    At an altitude of approximately 20,000km above the Earth, Solar Radiation Pressure (SRP) forces on Global Positioning System (GPS) satellites are second in magnitude only to the gravitational attractive forces exerted by the Earth, Sun and Moon. As GPS orbit processing strategies reach unprecedented levels of precision and accuracy, subtle effects from different GPS SRP models are beginning to emerge above the noise floor. We present an updated approach to the empirical modeling of SRP forces on GPS satellites using 14 years of data. We assess the models via orbit prediction and orbit determination using a suite of internal and external metrics. Our new model results in >10% average improvement of 8th-day orbit prediction differences (3D RMS) for block IIA and IIR satellites against our best final orbit solutions. Internal orbit overlaps from precise orbit determination improve by 7%. We additionally assess the impacts of the updated SRP models on satellite laser range residuals, carrier phase ambiguity resolution, and estimation of earth orientation parameters.

  8. Geomagnetic core field models in the satellite era

    DEFF Research Database (Denmark)

    Lesur, Vincent; Olsen, Nils; Thomson, Alan W. P.

    2011-01-01

    After a brief review of the theoretical basis and difficulties that modelers are facing, we present three recent models of the geomagnetic field originating in the Earth’s core. All three modeling approaches are using recent observatory and near-Earth orbiting survey satellite data. In each case...... between models are generally small. They do not exceed 16 nT which gives an idea of the accuracy of the models. Secular variation models are robustly resolved up to spherical harmonic degree 13, but only on time scale as large as 10 years. On time scale of a year, secular variation models are resolved...

  9. Monitoring Changes in Croplands Due to Water Stress in the Krishna River Basin Using Temporal Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Venkata Ramana Murthy Reddi

    2017-10-01

    Full Text Available Remote sensing-based assessments of large river basins such as the Krishna, which supplies water to many states in India, are useful for operationally monitoring agriculture, especially basins that are affected by abiotic stress. Moderate-Resolution Imaging Spectroradiometer (MODIS time series products can be used to understand cropland changes at the basin level due to abiotic stresses, especially water scarcity. Spectral matching techniques were used to identify land use/land cover (LULC areas for two crop years: 2013–2014, which was a normal year, and 2015–2016, which was a water stress year. Water stress-affected crop areas were categorized into three classes—severe, moderate and mild—based on the normalized difference vegetation index (NDVI and intensity of damage assessed through field sampling. Furthermore, ground survey data were used to assess the accuracy of MODIS-derived classification individual products. Water inflows into and outflows from the Krishna river basin during the study period were used as direct indicators of water scarcity/availability in the Krishna Basin. Furthermore, ground survey data were used to assess the accuracy of MODIS-derived LULC classification of individual year products. Rainfall data from the tropical rainfall monitoring mission (TRMM was used to support the water stress analysis. The nine LULC classes derived using the MODIS temporal imagery provided overall accuracies of 82% for the cropping year 2013–2014 and 85% for the year 2015–2016. Kappa values are 0.78 for 2013–2014 and 0.82 for 2015–2016. MODIS-derived cropland areas were compared with national statistics for the cropping year 2013–2014 with a R2 value of 0.87. Results show that both rainfed and irrigated areas in 2015–2016 saw significant changes that will have significant impacts on food security. It has been also observed that the farmers in the basin tend to use lower inputs and labour per ha during drought years. Among

  10. Shallow-Water Benthic Identification Using Multispectral Satellite Imagery: Investigation on the Effects of Improving Noise Correction Method and Spectral Cover

    Directory of Open Access Journals (Sweden)

    Masita Dwi Mandini Manessa

    2014-05-01

    Full Text Available Lyzenga’s method is used widely for radiative transfer analysis because of its simplicity of application to cases of shallow-water coral reef ecosystems with limited information of water properties. WorldView-2 imagery has been used previously to study bottom-type identification in shallow-water coral reef habitats. However, this is the first time WorldView-2 imagery has been applied to bottom-type identification using Lyzenga’s method. This research applied both of Lyzenga’s methods: the original from 1981 and the one from 2006 with improved noise correction that uses the near-infrared (NIR band. The objectives of this study are to examine whether the utilization of NIR bands in the correction of atmospheric and sea-surface scattering improves the accuracy of bottom classification, and whether increasing the number of visible bands also improves accuracy. Firstly, it has been determined that the improved 2006 correction method, which uses NIR bands, is only more accurate than the original 1981 correction method in the case of three visible bands. When applying six bands, the accuracy of the 1981 correction method is better than that of the 2006 correction method. Secondly, the increased number of visible bands, when applied to Lyzenga’s empirical radiative transfer model, improves the accuracy of bottom classification significantly.

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

    Directory of Open Access Journals (Sweden)

    Giorgos Mallinis

    2016-02-01

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

  12. Numerical modeling of a remote Himalayan glacier constrained by satellite data

    Science.gov (United States)

    Scherler, Dirk; Farinotti, Daniel; Anderson, Robert S.; Strecker, Manfred R.

    2010-05-01

    Himalayan glaciers are amongst the least studied and understood glaciers on Earth, yet their future behavior and water budget is crucial for densely-populated areas in south, central, and eastern Asia. Here, we use remotely-sensed glacier-surface velocities from a glacier in the upper Tons valley of western Uttaranchal in the Indian Himalaya, to evaluate the results from a numerical glacier model. We estimate present-day ice thickness distribution from surface topography with an approach based on mass conservation and principles of ice-flow dynamics. The numerical glacier model is based on the shallow ice approximation, and requires a mass-balance profile and glacier-bedrock topography as input. Optical-satellite imagery is used for mapping glacier extents and deriving glacier-surface velocities from cross correlation of multi-temporal ASTER and SPOT images. Modeling results, employing a mass balance profile from nearby monitored glaciers with a better data base, indicate good agreement between observed and modeled glacier extents and surface velocities. Discrepancies between model and observation in the lower part of the glacier are likely related to (1) poorly constrained effects of debris cover, and (2) the present disequilibrium and down-wasting of the glacier. Our technique will be useful for comparative analyses of glacial behavior worldwide as most data for our study has been obtained from analysis of remote-sensing data, virtually available for any region on Earth.

  13. The use of global ionospheric irregularity models for satellite communications

    Science.gov (United States)

    Pope, J. H.

    1974-01-01

    Scintillation data obtained in the VHF region were used by Fremouw to develop a global scintillation model. An attempt has been made in the present study to improve this model in several respects. One of these is to modify the high latitude term in the model to better represent data obtained in the northern high latitude regions. Another improvement is the extention of the frequency region of validity to the L band and microwave regions. This attempt is based on certain theoretical considerations regarding the effects of distribution in irregularity sizes. Recent satellite in situ measurements indicate that the ionospheric irregularity description is functionally different from that assumed in the past. These satellite measurements are used in connection with the theoretical development to improve the model.

  14. A history of the 2014 Minute 319 environmental pulse flow asdocumented by field measurements and satellite imagery

    Science.gov (United States)

    Nelson, Steven M.; Ramirez-Hernandez, Jorge; Rodriguez-Burgeueno, J. Eliana; Milliken, Jeff; Kennedy, Jeffrey R.; Zamora-Arroyo, Francisco; Schlatter, Karen; Santiago-Serrano, Edith; Carrera-Villa, Edgar

    2017-01-01

    As provided in Minute 319 of the U.S.-Mexico Water Treaty of 1944, a pulse flow of approximately 132 million cubic meters (mcm) was released to the riparian corridor of the Colorado River Delta over an eight-week period that began March 23, 2014 and ended May 18, 2014. Peak flows were released in the early part of the pulse to simulate a spring flood, with approximately 101.7 mcm released at Morelos Dam on the U.S.-Mexico border. The remainder of the pulse flow water was released to the riparian corridor via Mexicali Valley irrigation spillway canals, with 20.9 mcm released at Km 27 Spillway (41 km below Morelos Dam) and 9.3 mcm released at Km 18 Spillway (78 km below Morelos Dam). We used sequential satellite images, overflights, ground observations, water discharge measurements, and automated temperature, river stage and water quality loggers to document and describe the progression of pulse flow water through the study area. The rate of advance of the wetted front was slowed by infiltration and high channel roughness as the pulse flow crossed more than 40 km of dry channel which was disconnected from underlying groundwater and partially overgrown with salt cedar. High lag time and significant attenuation of flow resulted in a changing hydrograph as the pulse flow progressed to the downstream delivery points; two peak flows occurred in some lower reaches. The pulse flow advanced more than 120 km downstream from Morelos Dam to reach the Colorado River estuary at the northern end of the Gulf of California.

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

    Science.gov (United States)

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

    2009-01-01

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

  16. An ocean scatter propagation model for aeronautical satellite communication applications

    Science.gov (United States)

    Moreland, K. W.

    1990-01-01

    In this paper an ocean scattering propagation model, developed for aircraft-to-satellite (aeronautical) applications, is described. The purpose of the propagation model is to characterize the behavior of sea reflected multipath as a function of physical propagation path parameters. An accurate validation against the theoretical far field solution for a perfectly conducting sinusoidal surface is provided. Simulation results for typical L band aeronautical applications with low complexity antennas are presented.

  17. Modeling chlorophyll-a and turbidity concentrations in river Ganga (India) using Landsat-8 OLI imagery

    Science.gov (United States)

    Prasad, Satish; Saluja, Ridhi; Garg, J. K.

    2017-10-01

    Rivers, one of the most complex ecosystems are highly dynamic and vary spatially as well as temporally. Chlorophyll-a (Chl-a) is considered one of the primary indicators of water quality and a measure of river productivity, while turbidity in rivers is a measure of suspended organic matter. Monitoring of river water quality is quite challenging, demand tremendous efforts and resources. Numerous algorithms have been developed in the recent years for estimating environmental parameters such as chlorophyll-a and turbidity from remote sensing imagery. However, most of these algorithms were focused on the lentic ecosystems. There is a paucity of algorithms for rivers from which water quality variables can be estimated using remotely sensed imagery. The primary objective of our study is to develop algorithms based on Landsat 8 OLI imagery and in-situ observations for estimating of Chl-a and turbidity in the Upper Ganga river, India. Band reflectance images from multispectral Landsat-8 OLI pertaining to May and October 2016, and May 2017 were used for model development and validation along with near synchronous ground truth data. Algorithms based on Band 3 (R2= 0.73) proved to be the best applicable algorithm for estimating chlorophyll-a. The best algorithm for estimating turbidity was found to be log (B4/B5) (R2= 0.69) based on band combinations (individual band reflectance, band ratio, logarithmically transformed band reflectance and ratios) tested. The developed algorithms were used to generate maps showing the spatiotemporal variability of chlorophyll-a and turbidity concentration in the Upper Ganga river (Brijghat to Narora) which is also a Ramsar site.

  18. Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

    Science.gov (United States)

    Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John Y.

    2016-01-01

    Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

  19. Improvement of remote monitoring on water quality in a subtropical reservoir by incorporating grammatical evolution with parallel genetic algorithms into satellite imagery.

    Science.gov (United States)

    Chen, Li; Tan, Chih-Hung; Kao, Shuh-Ji; Wang, Tai-Sheng

    2008-01-01

    Parallel GEGA was constructed by incorporating grammatical evolution (GE) into the parallel genetic algorithm (GA) to improve reservoir water quality monitoring based on remote sensing images. A cruise was conducted to ground-truth chlorophyll-a (Chl-a) concentration longitudinally along the Feitsui Reservoir, the primary water supply for Taipei City in Taiwan. Empirical functions with multiple spectral parameters from the Landsat 7 Enhanced Thematic Mapper (ETM+) data were constructed. The GE, an evolutionary automatic programming type system, automatically discovers complex nonlinear mathematical relationships among observed Chl-a concentrations and remote-sensed imageries. A GA was used afterward with GE to optimize the appropriate function type. Various parallel subpopulations were processed to enhance search efficiency during the optimization procedure with GA. Compared with a traditional linear multiple regression (LMR), the performance of parallel GEGA was found to be better than that of the traditional LMR model with lower estimating errors.

  20. Generating the Nighttime Light of the Human Settlements by Identifying Periodic Components from DMSP/OLS Satellite Imagery.

    Science.gov (United States)

    Letu, Husi; Hara, Masanao; Tana, Gegen; Bao, Yuhai; Nishio, Fumihiko

    2015-09-01

    Nighttime lights of the human settlements (hereafter, "stable lights") are seen as a valuable proxy of social economic activity and greenhouse gas emissions at the subnational level. In this study, we propose an improved method to generate the stable lights from Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) daily nighttime light data for 1999. The study area includes Japan, China, India, and other 10 countries in East Asia. A noise reduction filter (NRF) was employed to generate a stable light from DMSP/OLS time-series daily nighttime light data. It was found that noise from amplitude of the 1-year periodic component is included in the stable light. To remove the amplitude of the 1-year periodic component noise included in the stable light, the NRF method was improved to extract the periodic component. Then, new stable light was generated by removing the amplitude of the 1-year periodic component using the improved NRF method. The resulting stable light was evaluated by comparing it with the conventional nighttime stable light provided by the National Oceanic and Atmosphere Administration/National Geophysical Data Center (NOAA/NGDC). It is indicated that DNs of the NOAA stable light image are lower than those of the new stable light image. This might be attributable to the influence of attenuation effects from thin warm water clouds. However, due to overglow effect of the thin cloud, light area in new stable light is larger than NOAA stable light. Furthermore, the cumulative digital numbers (CDNs) and number of light area pixels (NLAP) of the generated stable light and NOAA/NGDC stable light were applied to estimate socioeconomic variables of population, electric power consumption, gross domestic product, and CO2 emissions from fossil fuel consumption. It is shown that the correlations of the population and CO2FF with new stable light data are higher than those in NOAA stable light data; correlations of the EPC and GDP with NOAA

  1. Infralittoral mapping around an oceanic archipelago using MERIS FR satellite imagery and deep kelp observations: A new tool for assessing MPA coverage targets

    Science.gov (United States)

    Amorim, Patrícia; Atchoi, Elizabeth; Berecibar, Estibaliz; Tempera, Fernando

    2015-06-01

    This work presents the first climatologic maps of diffuse attenuation of down-welling solar radiation (KdPAR and Kd490 coefficients) for the Azores derived from full resolution (FR) MERIS satellite imagery. Associating this information with a new mesoscale bathymetry compilation permits estimating the percentage of surface light reaching the seabed. A video annotation dataset derived from a deep kelp survey conducted on the Formigas Bank is subsequently used to estimate the light levels experienced by these bionomically-crucial frondose algae. Empirical light-based thresholds for the lower infralittoral boundary in the Azores are derived from the deepest kelp occurrences. This information is eventually used to map the geographical extent of this major marine biological zone in the archipelago, yielding an area estimate of 894.7 km2. The average depth of the infralittoral limit in the Azores is established at 69 m. It is determined that the present Azores marine protected area (MPA) network already covers 28.9% of the region's infralittoral grounds. However, island-specific values highlight that MPA percentage coverage varies between islands with values ranging from a marginal coverage of 7.3% (on Terceira Island) to 100% coverage around the island of Corvo and the Formigas Bank. These results suggest that conservation managers may make use of the current spatially-based protection framework of the archipelago to, on the whole and for this specific major habitat, surpass the goals suggested by international conventions and conservation fora for MPA coverage. However, an analysis of the statutory MPA regulations further reveals that measures in place are insufficient to provide a no-take and no-disturbance protection of infralittoral biotopes. In order to achieve the recommended strict protection of the currently protected infralittoral zones, conservation measures ought to be enhanced.

  2. Predicting lake trophic state by relating Secchi-disk transparency measurements to Landsat-satellite imagery for Michigan inland lakes, 2003-05 and 2007-08

    Science.gov (United States)

    Fuller, L.M.; Jodoin, R.S.; Minnerick, R.J.

    2011-01-01

    Inland lakes are an important economic and environmental resource for Michigan. The U.S. Geological Survey and the Michigan Department of Natural Resources and Environment have been cooperatively monitoring the quality of selected lakes in Michigan through the Lake Water Quality Assessment program. Sampling for this program began in 2001; by 2010, 730 of Michigan’s 11,000 inland lakes are expected to have been sampled once. Volunteers coordinated by the Michigan Department of Natural Resources and Environment began sampling lakes in 1974 and continue to sample (in 2010) approximately 250 inland lakes each year through the Michigan Cooperative Lakes Monitoring Program. Despite these sampling efforts, it still is impossible to physically collect measurements for all Michigan inland lakes; however, Landsat-satellite imagery has been used successfully in Minnesota, Wisconsin, Michigan, and elsewhere to predict the trophic state of unsampled inland lakes greater than 20 acres by producing regression equations relating in-place Secchi-disk measurements to Landsat bands. This study tested three alternatives to methods previously used in Michigan to improve results for predicted statewide Trophic State Index (TSI) computed from Secchi-disk transparency (TSI (SDT)). The alternative methods were used on 14 Landsat-satellite scenes with statewide TSI (SDT) for two time periods (2003– 05 and 2007–08). Specifically, the methods were (1) satellitedata processing techniques to remove areas affected by clouds, cloud shadows, haze, shoreline, and dense vegetation for inland lakes greater than 20 acres in Michigan; (2) comparison of the previous method for producing a single open-water predicted TSI (SDT) value (which was based on an area of interest (AOI) and lake-average approach) to an alternative Gethist method for identifying open-water areas in inland lakes (which follows the initial satellite-data processing and targets the darkest pixels, representing the deepest water

  3. Interpretation of earthquake-induced landslides triggered by the 12 May 2008, M7.9 Wenchuan earthquake in the Beichuan area, Sichuan Province, China using satellite imagery and Google Earth

    Science.gov (United States)

    Sato, H.P.; Harp, E.L.

    2009-01-01

    The 12 May 2008 M7.9 Wenchuan earthquake in the People's Republic of China represented a unique opportunity for the international community to use commonly available GIS (Geographic Information System) tools, like Google Earth (GE), to rapidly evaluate and assess landslide hazards triggered by the destructive earthquake and its aftershocks. In order to map earthquake-triggered landslides, we provide details on the applicability and limitations of publicly available 3-day-post- and pre-earthquake imagery provided by GE from the FORMOSAT-2 (formerly ROCSAT-2; Republic of China Satellite 2). We interpreted landslides on the 8-m-resolution FORMOSAT-2 image by GE; as a result, 257 large landslides were mapped with the highest concentration along the Beichuan fault. An estimated density of 0.3 landslides/km2 represents a minimum bound on density given the resolution of available imagery; higher resolution data would have identified more landslides. This is a preliminary study, and further study is needed to understand the landslide characteristics in detail. Although it is best to obtain landslide locations and measurements from satellite imagery having high resolution, it was found that GE is an effective and rapid reconnaissance tool. ?? 2009 Springer-Verlag.

  4. Mapping tropical biodiversity using spectroscopic imagery : characterization of structural and chemical diversity with 3-D radiative transfer modeling

    Science.gov (United States)

    Feret, J. B.; Gastellu-Etchegorry, J. P.; Lefèvre-Fonollosa, M. J.; Proisy, C.; Asner, G. P.

    2014-12-01

    The accelerating loss of biodiversity is a major environmental trend. Tropical ecosystems are particularly threatened due to climate change, invasive species, farming and natural resources exploitation. Recent advances in remote sensing of biodiversity confirmed the potential of high spatial resolution spectroscopic imagery for species identification and biodiversity mapping. Such information bridges the scale-gap between small-scale, highly detailed field studies and large-scale, low-resolution satellite observations. In order to produce fine-scale resolution maps of canopy alpha-diversity and beta-diversity of the Peruvian Amazonian forest, we designed, applied and validated a method based on spectral variation hypothesis to CAO AToMS (Carnegie Airborne Observatory Airborne Taxonomic Mapping System) images, acquired from 2011 to 2013. There is a need to understand on a quantitative basis the physical processes leading to this spectral variability. This spectral variability mainly depends on canopy chemistry, structure, and sensor's characteristics. 3D radiative transfer modeling provides a powerful framework for the study of the relative influence of each of these factors in dense and complex canopies. We simulated series of spectroscopic images with the 3D radiative model DART, with variability gradients in terms of leaf chemistry, individual tree structure, spatial and spectral resolution, and applied methods for biodiversity mapping. This sensitivity study allowed us to determine the relative influence of these factors on the radiometric signal acquired by different types of sensors. Such study is particularly important to define the domain of validity of our approach, to refine requirements for the instrumental specifications, and to help preparing hyperspectral spatial missions to be launched at the horizon 2015-2025 (EnMAP, PRISMA, HISUI, SHALOM, HYSPIRI, HYPXIM). Simulations in preparation include topographic variations in order to estimate the robustness

  5. Formation of Ice Giant Satellites During Thommes Model Mirgration

    Science.gov (United States)

    Fuse, Christopher; Spiegelberg, Josephine

    2018-01-01

    Inconsistencies between ice giant planet characteristics and classic planet formation theories have led to a re-evaluation of the formation of the outer Solar system. Thommes model migration delivers proto-Uranus and Neptune from orbits interior to Saturn to their current locations. The Thommes model has also been able to reproduce the large Galilean and Saturnian moons via interactions between the proto-ice giants and the gas giant moon disks.As part of a series of investigations examining the effects of Thommes model migration on the formation of moons, N-body simulations of the formation of the Uranian and Neptunian satellite systems were performed. Previous research has yielded conflicting results as to whether satellite systems are stable during planetary migration. Some studies, such as Beaugé (2002) concluded that the system was not stable over the proposed duration of migration. Conversely, Fuse and Neville (2011) and Yokoyama et al. (2011) found that moons were retained, though the nature of the resulting system was heavily influenced by interactions with planetesimals and other large objects. The results of the current study indicate that in situ simulations of the Uranus and Neptune systems can produce stable moons. Whether with current orbital parameters or located at pre-migration, inner Solar system semi-major axes, the simulations end with 5.8 ± 0.15 or 5.9 ± 0.7 regular satellites around Uranus and Neptune, respectively. Preliminary simulations of a proto-moon disk around a single planet migrating via the Thommes model have failed to retain moons. Furthermore, simulations of ejection of the current Uranian satellite system retained at most one moon. Thus, for the Thommes model to be valid, it is likely that moon formation did not begin until after migration ended. Future work will examine the formation of gas and ice giant moons through other migration theories, such as the Nice model (Tsiganis et al. 2006).

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

    Directory of Open Access Journals (Sweden)

    Quanying Zhao

    2015-02-01

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

  7. Optimal Filtering in Mass Transport Modeling From Satellite Gravimetry Data

    Science.gov (United States)

    Ditmar, P.; Hashemi Farahani, H.; Klees, R.

    2011-12-01

    Monitoring natural mass transport in the Earth's system, which has marked a new era in Earth observation, is largely based on the data collected by the GRACE satellite mission. Unfortunately, this mission is not free from certain limitations, two of which are especially critical. Firstly, its sensitivity is strongly anisotropic: it senses the north-south component of the mass re-distribution gradient much better than the east-west component. Secondly, it suffers from a trade-off between temporal and spatial resolution: a high (e.g., daily) temporal resolution is only possible if the spatial resolution is sacrificed. To make things even worse, the GRACE satellites enter occasionally a phase when their orbit is characterized by a short repeat period, which makes it impossible to reach a high spatial resolution at all. A way to mitigate limitations of GRACE measurements is to design optimal data processing procedures, so that all available information is fully exploited when modeling mass transport. This implies, in particular, that an unconstrained model directly derived from satellite gravimetry data needs to be optimally filtered. In principle, this can be realized with a Wiener filter, which is built on the basis of covariance matrices of noise and signal. In practice, however, a compilation of both matrices (and, therefore, of the filter itself) is not a trivial task. To build the covariance matrix of noise in a mass transport model, it is necessary to start from a realistic model of noise in the level-1B data. Furthermore, a routine satellite gravimetry data processing includes, in particular, the subtraction of nuisance signals (for instance, associated with atmosphere and ocean), for which appropriate background models are used. Such models are not error-free, which has to be taken into account when the noise covariance matrix is constructed. In addition, both signal and noise covariance matrices depend on the type of mass transport processes under

  8. Benchmark Imagery FY11 Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pope, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2011-06-14

    This report details the work performed in FY11 under project LL11-GS-PD06, “Benchmark Imagery for Assessing Geospatial Semantic Extraction Algorithms.” The original LCP for the Benchmark Imagery project called for creating a set of benchmark imagery for verifying and validating algorithms that extract semantic content from imagery. More specifically, the first year was slated to deliver real imagery that had been annotated, the second year to deliver real imagery that had composited features, and the final year was to deliver synthetic imagery modeled after the real imagery.

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

    Science.gov (United States)

    Su, X.

    2017-12-01

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

  10. A Modified FCM Classifier Constrained by Conditional Random Field Model for Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    WANG Shaoyu

    2016-12-01

    Full Text Available Remote sensing imagery has abundant spatial correlation information, but traditional pixel-based clustering algorithms don't take the spatial information into account, therefore the results are often not good. To this issue, a modified FCM classifier constrained by conditional random field model is proposed. Adjacent pixels' priori classified information will have a constraint on the classification of the center pixel, thus extracting spatial correlation information. Spectral information and spatial correlation information are considered at the same time when clustering based on second order conditional random field. What's more, the global optimal inference of pixel's classified posterior probability can be get using loopy belief propagation. The experiment shows that the proposed algorithm can effectively maintain the shape feature of the object, and the classification accuracy is higher than traditional algorithms.

  11. On Fundamental Evaluation Using Uav Imagery and 3d Modeling Software

    Science.gov (United States)

    Nakano, K.; Suzuki, H.; Tamino, T.; Chikatsu, H.

    2016-06-01

    Unmanned aerial vehicles (UAVs), which have been widely used in recent years, can acquire high-resolution images with resolutions in millimeters; such images cannot be acquired with manned aircrafts. Moreover, it has become possible to obtain a surface reconstruction of a realistic 3D model using high-overlap images and 3D modeling software such as Context capture, Pix4Dmapper, Photoscan based on computer vision technology such as structure from motion and multi-view stereo. 3D modeling software has many applications. However, most of them seem to not have obtained appropriate accuracy control in accordance with the knowledge of photogrammetry and/or computer vision. Therefore, we performed flight tests in a test field using an UAV equipped with a gimbal stabilizer and consumer grade digital camera. Our UAV is a hexacopter and can fly according to the waypoints for autonomous flight and can record flight logs. We acquired images from different altitudes such as 10 m, 20 m, and 30 m. We obtained 3D reconstruction results of orthoimages, point clouds, and textured TIN models for accuracy evaluation in some cases with different image scale conditions using 3D modeling software. Moreover, the accuracy aspect was evaluated for different units of input image—course unit and flight unit. This paper describes the fundamental accuracy evaluation for 3D modeling using UAV imagery and 3D modeling software from the viewpoint of close-range photogrammetry.

  12. ON FUNDAMENTAL EVALUATION USING UAV IMAGERY AND 3D MODELING SOFTWARE

    Directory of Open Access Journals (Sweden)

    K. Nakano

    2016-06-01

    Full Text Available Unmanned aerial vehicles (UAVs, which have been widely used in recent years, can acquire high-resolution images with resolutions in millimeters; such images cannot be acquired with manned aircrafts. Moreover, it has become possible to obtain a surface reconstruction of a realistic 3D model using high-overlap images and 3D modeling software such as Context capture, Pix4Dmapper, Photoscan based on computer vision technology such as structure from motion and multi-view stereo. 3D modeling software has many applications. However, most of them seem to not have obtained appropriate accuracy control in accordance with the knowledge of photogrammetry and/or computer vision. Therefore, we performed flight tests in a test field using an UAV equipped with a gimbal stabilizer and consumer grade digital camera. Our UAV is a hexacopter and can fly according to the waypoints for autonomous flight and can record flight logs. We acquired images from different altitudes such as 10 m, 20 m, and 30 m. We obtained 3D reconstruction results of orthoimages, point clouds, and textured TIN models for accuracy evaluation in some cases with different image scale conditions using 3D modeling software. Moreover, the accuracy aspect was evaluated for different units of input image—course unit and flight unit. This paper describes the fundamental accuracy evaluation for 3D modeling using UAV imagery and 3D modeling software from the viewpoint of close-range photogrammetry.

  13. Assessment of soil erodibility indices for conservation reserve program lands in southwestern Kansas using satellite imagery and GIS techniques.

    Science.gov (United States)

    Park, Sunyurp; Egbert, Stephen L

    2005-12-01

    The soil erodibility index (EI) of Conservation Reserve Program (CRP) lands, which was the major criterion for CRP enrollment, was assessed for six counties in southwestern Kansas using USGS seamless digital elevation model data and Geographical Informational System techniques. The proportion of land areas with EI values of 8 or lower was less than 1% of the entire study area and most of the land areas (72.5%) were concentrated on EI values between 8 and 24. Although land acreage with EI values of 24 or higher decreased dramatically, the proportion of CRP lands to the other land-use types did not change much from low to high EI levels. The soil EI and physical soil characteristics of the CRP lands were compared to those of other land-use types. In general, the mean EI values of the land-use types were strongly correlated with physical soil properties, including organic matter content, clay content, available water capacity, permeability, and texture. CRP lands were compared in detail with cropland in terms of their soil characteristics to infer the pivotal cause of the land transformation. Although there was no significant statistical difference in EI between cropland and CRP soils, soil texture, soil family, and permeability were statistically different between the two. Statistical analyses of these three variables showed that CRP soils had coarser texture and higher permeability on average than cropland soils, indicating that CRP lands in the study area are drier than cropland soils. Therefore, soil moisture characteristics, not necessarily soil erosion potential, might have been the key factor for CRP enrollment in the study area.

  14. Solar Radiation Received by Slopes Using COMS Imagery, a Physically Based Radiation Model, and GLOBE

    Directory of Open Access Journals (Sweden)

    Jong-Min Yeom

    2016-01-01

    Full Text Available This study mapped the solar radiation received by slopes for all of Korea, including areas that are not measured by ground station measurements, through using satellites and topographical data. When estimating insolation with satellite, we used a physical model to measure the amount of hourly based solar surface insolation. Furthermore, we also considered the effects of topography using the Global Land One-Kilometer Base Elevation (GLOBE digital elevation model (DEM for the actual amount of incident solar radiation according to solar geometry. The surface insolation mapping, by integrating a physical model with the Communication, Ocean, and Meteorological Satellite (COMS Meteorological Imager (MI image, was performed through a comparative analysis with ground-based observation data (pyranometer. Original and topographically corrected solar radiation maps were created and their characteristics analyzed. Both the original and the topographically corrected solar energy resource maps captured the temporal variations in atmospheric conditions, such as the movement of seasonal rain fronts during summer. In contrast, although the original solar radiation map had a low insolation value over mountain areas with a high rate of cloudiness, the topographically corrected solar radiation map provided a better description of the actual surface geometric characteristics.

  15. A geostationary Earth orbit satellite model using Easy Java Simulation

    Science.gov (United States)

    Wee, Loo Kang; Hwee Goh, Giam

    2013-01-01

    We develop an Easy Java Simulation (EJS) model for students to visualize geostationary orbits near Earth, modelled using a Java 3D implementation of the EJS 3D library. The simplified physics model is described and simulated using a simple constant angular velocity equation. We discuss four computer model design ideas: (1) a simple and realistic 3D view and associated learning in the real world; (2) comparative visualization of permanent geostationary satellites; (3) examples of non-geostationary orbits of different rotation senses, periods and planes; and (4) an incorrect physics model for conceptual discourse. General feedback from the students has been relatively positive, and we hope teachers will find the computer model useful in their own classes.

  16. SpaceWire model development technology for satellite architecture.

    Energy Technology Data Exchange (ETDEWEB)

    Eldridge, John M.; Leemaster, Jacob Edward; Van Leeuwen, Brian P.

    2011-09-01

    Packet switched data communications networks that use distributed processing architectures have the potential to simplify the design and development of new, increasingly more sophisticated satellite payloads. In addition, the use of reconfigurable logic may reduce the amount of redundant hardware required in space-based applications without sacrificing reliability. These concepts were studied using software modeling and simulation, and the results are presented in this report. Models of the commercially available, packet switched data interconnect SpaceWire protocol were developed and used to create network simulations of data networks containing reconfigurable logic with traffic flows for timing system distribution.

  17. Interpretation of aero-magnetic data and satellite imagery to delineate structure - a case study for uranium exploration from Gwalior Basin, India

    International Nuclear Information System (INIS)

    Markandeyulu, A.; Patra, I.; Raju, B.V.S.N.; Chaturvedi, A.K.; Parihar, P.S.

    2012-01-01

    , which corroborate the magnetic data. Merged ETM+ (RGB 751) and PC (PC1-PC2-PC5) images depict litho-logical contrast. Integration of aeromagnetic and satellite imagery data helped in understanding the structural fabric of the Gwalior Basin and to identify favorable loci of uranium mineralization. (author)

  18. Harmonic analysis of dense time series of landsat imagery for modeling change in forest conditions

    Science.gov (United States)

    Barry Tyler. Wilson

    2015-01-01

    This study examined the utility of dense time series of Landsat imagery for small area estimation and mapping of change in forest conditions over time. The study area was a region in north central Wisconsin for which Landsat 7 ETM+ imagery and field measurements from the Forest Inventory and Analysis program are available for the decade of 2003 to 2012. For the periods...

  19. A novel approach for epipolar resampling of cross-track linear pushbroom imagery using orbital parameters model

    Science.gov (United States)

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

    2018-03-01

    This paper presents a novel approach to epipolar resampling of cross-track linear pushbroom imagery using orbital parameters model (OPM). The backbone of the proposed method relies on modification of attitude parameters of linear array stereo imagery in such a way to parallelize the approximate conjugate epipolar lines (ACELs) with the instantaneous base line (IBL) of the conjugate image points (CIPs). Afterward, a complementary rotation is applied in order to parallelize all the ACELs throughout the stereo imagery. The new estimated attitude parameters are evaluated based on the direction of the IBL and the ACELs. Due to the spatial and temporal variability of the IBL (respectively changes in column and row numbers of the CIPs) and nonparallel nature of the epipolar lines in the stereo linear images, some polynomials in the both column and row numbers of the CIPs are used to model new attitude parameters. As the instantaneous position of sensors remains fix, the digital elevation model (DEM) of the area of interest is not required in the resampling process. According to the experimental results obtained from two pairs of SPOT and RapidEye stereo imagery with a high elevation relief, the average absolute values of remained vertical parallaxes of CIPs in the normalized images were obtained 0.19 and 0.28 pixels respectively, which confirm the high accuracy and applicability of the proposed method.

  20. [A Hyperspectral Imagery Anomaly Detection Algorithm Based on Gauss-Markov Model].

    Science.gov (United States)

    Gao, Kun; Liu, Ying; Wang, Li-jing; Zhu, Zhen-yu; Cheng, Hao-bo

    2015-10-01

    With the development of spectral imaging technology, hyperspectral anomaly detection is getting more and more widely used in remote sensing imagery processing. The traditional RX anomaly detection algorithm neglects spatial correlation of images. Besides, it does not validly reduce the data dimension, which costs too much processing time and shows low validity on hyperspectral data. The hyperspectral images follow Gauss-Markov Random Field (GMRF) in space and spectral dimensions. The inverse matrix of covariance matrix is able to be directly calculated by building the Gauss-Markov parameters, which avoids the huge calculation of hyperspectral data. This paper proposes an improved RX anomaly detection algorithm based on three-dimensional GMRF. The hyperspectral imagery data is simulated with GMRF model, and the GMRF parameters are estimated with the Approximated Maximum Likelihood method. The detection operator is constructed with GMRF estimation parameters. The detecting pixel is considered as the centre in a local optimization window, which calls GMRF detecting window. The abnormal degree is calculated with mean vector and covariance inverse matrix, and the mean vector and covariance inverse matrix are calculated within the window. The image is detected pixel by pixel with the moving of GMRF window. The traditional RX detection algorithm, the regional hypothesis detection algorithm based on GMRF and the algorithm proposed in this paper are simulated with AVIRIS hyperspectral data. Simulation results show that the proposed anomaly detection method is able to improve the detection efficiency and reduce false alarm rate. We get the operation time statistics of the three algorithms in the same computer environment. The results show that the proposed algorithm improves the operation time by 45.2%, which shows good computing efficiency.

  1. Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP

    KAUST Repository

    Houborg, Rasmus

    2013-08-01

    This study investigates the utility of in situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (V-max) represents a key control on leaf photosynthesis within the widely employed C-3 and C-4 photosynthesis models proposed by Farquhar et al. (1980) and Collatz et al. (1992), respectively. A semi-mechanistic relationship between V-max(5) (V-max normalized to 25 degrees C) and Chl is derived based on interlinkages between V-max(25), Rubisco enzyme kinetics, leaf nitrogen, and Chl reported in the experimental literature. The resulting linear V-max(25) - Chl relationship is embedded within the photosynthesis scheme of the Community Land Model (CLM), thereby bypassing the use of fixed plant functional type (PFT) specific V-max(25) values. The effect of the updated parameterization on simulated carbon fluxes is tested over a corn field growing season using: (1) a detailed Chl time-series established on the basis of intensive field measurements and (2) Chl estimates derived from Landsat imagery using the REGularized canopy reFLECtance (REGFLEC) tool. Validations against flux tower observations demonstrate benefit of using Chl to parameterize V-max(25) to account for variations in nitrogen availability imposed by severe environmental conditions. The use of V-max(25) that varied seasonally as a function of satellite-based Chl, rather than a fixed PFT-specific value, significantly improved the agreement with observed tower fluxes with Pearson\\'s correlation coefficient (r) increasing from 0.88 to 0.93 and the root-mean-square-deviation decreasing from 4.77 to 3.48 mu mol m(-2) s(-1). The results support the use of Chl as a proxy for photosynthetic capacity using generalized relationships between V-max(25) and Chl, and advocate the potential of satellite retrieved Chl for

  2. Modelling Stresses on Icy Satellites: Upgrading SatStressGUI

    Science.gov (United States)

    Harper, Chad; Pappalardo, Robert T.; Patthoff, Alex; Doan, Nhu

    2017-10-01

    SatStressGUI is a program that calculates surface stresses resulting from candidate stress sources, specifically: diurnal tidal forces, nonsynchronous rotation, ice shell thickening, obliquity, and orbital migration on icy and rocky satellites. SatStressGUI is designed to enable quick calculations and easy to create stress field visuals. Here we report on recent upgrades to SatStressGUI; specifically, enabling it to calculate stresses resulting from obliquity driven stressing in a viscoelastic regime. We define obliquity as the tilt of the satellite’s equatorial plane relative to the orbital plane. Obliquity driven stresses cause asymmetric stress fields about the equator. The resulting asymmetries can affect the orientation of the principal stresses and thereby result in the arcuate (as opposed to boxy) cycloid patterns seen in some icy satellites and allow for fractures to propagate across the equator. In the past, SatStressGUI had the ability to calculate obliquity stresses only for an elastic body; however, icy satellites are better described as viscoelastic bodies. As a result of our recent upgrades; these stress fields, which can result in the formation of surface features such as the lineaments and cycloids found on Europa, can now be more accurately simulated. We used an obliquity model that follows the calculations the calculations of Hermes et al. (Icarus, 215, 417-438, 2011), which takes a closer look at the effects of a non-zero obliquity in a viscoelastic regime. By the calculations of Hermes et al. (Icarus, 215, 417-438, 2011), accounting for viscoelastic behavior of ice could result in a westward shift of the entire stress field. By permitting simulation of surface features from various tidal stresses and comparison them to observations, SatStressGUI can help us gain insight into icy bodies’ deformation history: a history which can better informing our predictions about the interiors and geological histories of satellites such as Europa.

  3. Navy Exploitation of SeaWiFS and MODIS Satellite Imagery for Detection of Desert Dust Storms Over Land and Water

    Science.gov (United States)

    Miller, S. D.

    2002-12-01

    The United States Navy gives serious consideration to the subject of dust detection. In a recent study of Naval aviation mishaps over the period 1990-1998 (Cantu, 2001), it was found that 70% were associated with visibility problems and accounted for annual equipment losses of nearly 50 million dollars. This figure does not include the tax dollars lost in jettisoned or off-target ordnance owing to obscured targets or failure of laser-guided systems in the presence of significant dust. Nor can it account for the loss of life during a subset of these mishaps. As such, a strong research emphasis has been placed on detecting and quantifying dust over data-sparse/denied parts of the world. The prolific and complex dust climatology of Southwest Asia has posed considerable challenges to Navy operations over the course of Operation Enduring Freedom. In an effort to support the ongoing needs of the Meteorology/Oceanography (METOC) officers afloat, the Satellite Applications Section of the Naval Research Laboratory (NRL) Marine Meteorology Division has developed a novel approach to enhancing significant dust events that appeals to high spatial and spectral resolution satellite data currently available from state of the art ocean/atmospheric radiometers. This paper summarizes progress made on daytime enhancements of desert dust storms over both land and ocean using multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS; aboard Earth Observing System Terra and Aqua platforms) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; aboard the NASA/Orbimage SeaStar platform). The approach leverages the multi-spectral visible capability of these sensors to distinguish dust from clouds over water bodies, and the high spatial resolution required to refine the fine-scale structures that often accompany these events. The MODIS algorithm combines this information with that of several near-to-far infrared channels, taking advantage of unique spectral

  4. The Use of LiDAR Elevation Data and Satellite Imagery to Locate Critical Source Areas to Diffuse Pollution in Agricultural Watersheds

    Science.gov (United States)

    Drouin, Ariane; Michaud, Aubert; Thériault, Georges; Beaudin, Isabelle; Rodrigue, Jean-François; Denault, Jean-Thomas; Desjardins, Jacques; Côté, Noémi

    2013-04-01

    In Quebec / Canada, water quality improvement in rural areas greatly depends on the reduction of diffuse pollution. Indeed, point source pollution has been reduced significantly in Canada in recent years by creating circumscribed pits for manure and removing animals from stream. Diffuse pollution differs from point source pollution because it is spread over large areas. In agricultural areas, sediment loss by soil and riverbank erosion along with loss of nutrients (phosphorus, nitrogen, etc.) and pesticides from fields represent the main source of non-point source pollution. The factor mainly responsible for diffuse pollution in agricultural areas is surface runoff occurring in poorly drained areas in fields. The presence of these poorly drained areas is also one of the most limiting factors in crop productivity. Thus, a reconciliation of objectives at the farm (financial concern for farmers) and off-farm concerns (environmental concern) is possible. In short, drainage, runoff, erosion, water quality and crop production are all interconnected issues that need to be tackled together. Two complementary data sources are mainly used in the diagnosis of drainage, surface runoff and erosion : elevation data and multispectral satellite images. In this study of two watersheds located in Québec (Canada), LiDAR elevation data and satellite imagery (QuickBird, Spot and Landsat) were acquired. The studied territories have been partitioned in hydrologic response units (HRUs) according to sub-basins, soils, elevation (topographic index) and land use. These HRUs are afterwards used in a P index software (P-Edit) that calculates the quantities of sediments and phosphorus exported from each HRUs. These exports of sediments and phosphorus are validated with hydrometric and water quality data obtain in two sub-basins and are also compared to soil brightness index derived from multispectral images. This index is sensitive to soil moisture and thus highlights areas where the soil is

  5. Polar-Orbiting Satellite (POES) Images

    Data.gov (United States)

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

  6. Defense Meteorological Satellite Program (DMSP)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Defense Meteorological Satellite Program (DMSP) satellites collect visible and infrared cloud imagery as well as monitoring the atmospheric, oceanographic,...

  7. Crop specific LAI retrieval using optical and radar satellite data for regional crop growth monitoring and modelling

    Science.gov (United States)

    Guissard, Vincent; Lucau-Danila, Cozmin; Defourny, Pierre

    2005-10-01

    After a review of the current state of the art in LAI retrieval with optical and radar remote sensing data, this study investigates the capabilities of satellite remote sensing imagery in operational crop growth monitoring. This study demonstrated that the availability of an extensive crop field delineation database (like existing for the entire Belgian country) is of crucial in interest in order to retrieve crop specific information. LAI remote sensing retrieval was achieved during the year 2003 on a large Belgian agricultural area (4500 km2) for Sugar beet, Winter wheat and Maize crops. In order to increase the monitoring temporal frequency, an integration of SPOT-HRV, ENVISAT-MERIS and ERS2-SAR sensors was carried out, with a good level of accordance. The retrieval results were compatible with the concurrent field measurements as well as with the outputs given by the WOFOST crop growth model.

  8. Building a 2.5D Digital Elevation Model from 2D Imagery

    Science.gov (United States)

    Padgett, Curtis W.; Ansar, Adnan I.; Brennan, Shane; Cheng, Yang; Clouse, Daniel S.; Almeida, Eduardo

    2013-01-01

    When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geogr