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Sample records for resolution satellite imagesgps

  1. Medium Spatial Resolution Satellite Characterization

    NASA Technical Reports Server (NTRS)

    Stensaas, Greg

    2007-01-01

    This project provides characterization and calibration of aerial and satellite systems in support of quality acquisition and understanding of remote sensing data, and verifies and validates the associated data products with respect to ground and and atmospheric truth so that accurate value-added science can be performed. The project also provides assessment of new remote sensing technologies.

  2. Improved reduced-resolution satellite imagery

    NASA Technical Reports Server (NTRS)

    Ellison, James; Milstein, Jaime

    1995-01-01

    The resolution of satellite imagery is often traded-off to satisfy transmission time and bandwidth, memory, and display limitations. Although there are many ways to achieve the same reduction in resolution, algorithms vary in their ability to preserve the visual quality of the original imagery. These issues are investigated in the context of the Landsat browse system, which permits the user to preview a reduced resolution version of a Landsat image. Wavelets-based techniques for resolution reduction are proposed as alternatives to subsampling used in the current system. Experts judged imagery generated by the wavelets-based methods visually superior, confirming initial quantitative results. In particular, compared to subsampling, the wavelets-based techniques were much less likely to obscure roads, transmission lines, and other linear features present in the original image, introduce artifacts and noise, and otherwise reduce the usefulness of the image. The wavelets-based techniques afford multiple levels of resolution reduction and computational speed. This study is applicable to a wide range of reduced resolution applications in satellite imaging systems, including low resolution display, spaceborne browse, emergency image transmission, and real-time video downlinking.

  3. High resolution analysis of satellite gradiometry

    NASA Technical Reports Server (NTRS)

    Colombo, O. L.

    1989-01-01

    Satellite gravity gradiometry is a technique now under development which, by the middle of the next decade, may be used for the high resolution charting from space of the gravity field of the earth and, afterwards, of other planets. Some data analysis schemes are reviewed for getting detailed gravity maps from gradiometry on both a global and a local basis. It also presents estimates of the likely accuracies of such maps, in terms of normalized spherical harmonics expansions, both using gradiometry alone and in combination with data from a Global Positioning System (GPS) receiver carried on the same spacecraft. It compares these accuracies with those of current and future maps obtained from other data (conventional tracking, satellite-satellite tracking, etc.), and also with the spectra of various signals of geophysical interest.

  4. Information extraction from high resolution satellite images

    NASA Astrophysics Data System (ADS)

    Yang, Haiping; Luo, Jiancheng; Shen, Zhanfeng; Xia, Liegang

    2014-11-01

    Information extracted from high resolution satellite images, such as roads, buildings, water and vegetation, has a wide range of applications in disaster assessment and environmental monitoring. At present, object oriented supervised learning is usually used in the objects identification from the high spatial resolution satellite images. In classical ways, we have to label some regions of interests from every image to be classified at first, which is labor intensive. In this paper, we build a feature base for information extraction in order to reduce the labeling efforts. The features stored are regulated and labeled. The labeled samples for a new coming image can be selected from the feature base. And the experiments are taken on GF-1 and ZY-3 images. The results show the feasibility of the feature base for image interpretation.

  5. High Spatial Resolution Thermal Satellite Technologies

    NASA Technical Reports Server (NTRS)

    Ryan, Robert

    2003-01-01

    This document in the form of viewslides, reviews various low-cost alternatives to high spatial resolution thermal satellite technologies. There exists no follow-on to Landsat 7 or ASTER high spatial resolution thermal systems. This document reviews the results of the investigation in to the use of new technologies to create a low-cost useful alternative. Three suggested technologies are examined. 1. Conventional microbolometer pushbroom modes offers potential for low cost Landsat Data Continuity Mission (LDCM) thermal or ASTER capability with at least 60-120 ground sampling distance (GSD). 2. Backscanning could produce MultiSpectral Thermal Imager performance without cooled detectors. 3. Cooled detector could produce hyperspectral thermal class system or extremely high spatial resolution class instrument.

  6. Ambiguity resolution for satellite Doppler positioning systems

    NASA Technical Reports Server (NTRS)

    Argentiero, P.; Marini, J.

    1979-01-01

    The implementation of satellite-based Doppler positioning systems frequently requires the recovery of transmitter position from a single pass of Doppler data. The least-squares approach to the problem yields conjugate solutions on either side of the satellite subtrack. It is important to develop a procedure for choosing the proper solution which is correct in a high percentage of cases. A test for ambiguity resolution which is the most powerful in the sense that it maximizes the probability of a correct decision is derived. When systematic error sources are properly included in the least-squares reduction process to yield an optimal solution the test reduces to choosing the solution which provides the smaller valuation of the least-squares loss function. When systematic error sources are ignored in the least-squares reduction, the most powerful test is a quadratic form comparison with the weighting matrix of the quadratic form obtained by computing the pseudoinverse of a reduced-rank square matrix. A formula for computing the power of the most powerful test is provided. Numerical examples are included in which the power of the test is computed for situations that are relevant to the design of a satellite-aided search and rescue system.

  7. High-resolution satellite imagery for mesoscale meteorological studies

    NASA Technical Reports Server (NTRS)

    Johnson, David B.; Flament, Pierre; Bernstein, Robert L.

    1994-01-01

    In this article high-resolution satellite imagery from a variety of meteorological and environmental satellites is compared. Digital datasets from Geostationary Operational Environmental Satellite (GOES), National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program (DMSP), Landsat, and Satellite Pour l'Observation de la Terre (SPOT) satellites were archived as part of the 1990 Hawaiian Rainband Project (HaRP) and form the basis of the comparisons. During HaRP, GOES geostationary satellite coverage was marginal, so the main emphasis is on the polar-orbiting satellites.

  8. Ambiguity resolution for satellite Doppler positioning systems

    NASA Technical Reports Server (NTRS)

    Argentiero, P. D.; Marini, J. W.

    1977-01-01

    A test for ambiguity resolution was derived which was the most powerful in the sense that it maximized the probability of a correct decision. When systematic error sources were properly included in the least squares reduction process to yield an optimal solution, the test reduced to choosing the solution which provided the smaller valuation of the least squares loss function. When systematic error sources were ignored in the least squares reduction, the most powerful test was a quadratic form comparison with the weighting matrix of the quadratic form obtained by computing the pseudo-inverse of a reduced rank square matrix. A formula is presented for computing the power of the most powerful test. A numerical example is included in which the power of the test is computed for a situation which may occur during an actual satellite aided search and rescue mission.

  9. Road Extraction from High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Özkaya, M.

    2012-07-01

    Roads are significant objects of an infrastructure and the extraction of roads from aerial and satellite images are important for different applications such as automated map generation and change detection. Roads are also important to detect other structures such as buildings and urban areas. In this paper, the road extraction approach is based on Active Contour Models for 1-meter resolution gray level images. Active Contour Models contains Snake Approach. During applications, the road structure was separated as salient-roads, non-salient roads and crossings and extraction of these is provided by using Ribbon Snake and Ziplock Snake methods. These methods are derived from traditional snake model. Finally, various experimental results were presented. Ribbon and Ziplock Snake methods were compared for both salient and non-salient roads. Also these methods were used to extract roads in an image. While Ribbon snake is described for extraction of salient roads in an image, Ziplock snake is applied for extraction of non-salient roads. Beside these, some constant variables in literature were redefined and expressed in a formula as depending on snake approach and a new approach for extraction of crossroads were described and tried.

  10. Vehicle Detection and Classification from High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Abraham, L.; Sasikumar, M.

    2014-11-01

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

  11. A method for generating high resolution satellite image time series

    NASA Astrophysics Data System (ADS)

    Guo, Tao

    2014-10-01

    There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation

  12. Using Progressive Resolution to Visualize large Satellite Image dataset

    NASA Astrophysics Data System (ADS)

    ho, yuan; ramanmurthy, mohan

    2014-05-01

    Unidata's Integrated Data Viewer (IDV) is a Java-based software application that provides new and innovative ways of displaying satellite imagery, gridded data, and surface, upper air, and radar data within a unified interface. Progressive Resolution (PR) is a advanced feature newly developed in the IDV. When loading a large satellite dataset with PR turned on, the IDV calculates the resolution of the view window, sets the magnification factors dynamically, and loads a sufficient amount of the data to generate an image at the correct resolution. A rubber band box (RBB) interface allows the user to zoom in/out or change the projection, forcing the IDV to recalculate the magnification factors and get higher/lower resolution data. This new feature improves the IDV memory usage significantly. In the preliminary test, loading 100 time steps of GOES-East 1 km 0.65 visible image data (100 X 10904 X 6928) with PR, both memory and CPU usage are comparable to generating a single time-step display at full resolution (10904 X 6928), and the quality of the resulting image is not compromised. The PR feature is currently available for both satellite imagery and gridded datasets, and will be expanded to other datasets. In this presentation we will present examples of PR usage with large satellite datasets for academic investigations and scientific discovery.

  13. Mapping riparian and wetland weeds with high resolution satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aquatic and wetland weeds are a serious management problem in many freshwater ecosystems of the world. This paper presents an overview on the application of using high resolution QuickBird multi-spectral satellite imagery for detecting weeds in waterways and wetlands in Texas. Unsupervised image a...

  14. Evaluating high resolution SPOT 5 satellite imagery for crop identification

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High resolution satellite imagery offers new opportunities for crop monitoring and assessment. A SPOT 5 image with four spectral bands (green, red, near-infrared, and mid-infrared) and 10-m pixel size covering intensively cropped areas in south Texas was evaluated for crop identification. Two images...

  15. Unsupervised Feature Learning for High-Resolution Satellite Image Classification

    SciTech Connect

    Cheriyadat, Anil M

    2013-01-01

    The rich data provided by high-resolution satellite imagery allow us to directly model geospatial neighborhoods by understanding their spatial and structural patterns. In this paper we explore an unsupervised feature learning approach to model geospatial neighborhoods for classification purposes. While pixel and object based classification approaches are widely used for satellite image analysis, often these approaches exploit the high-fidelity image data in a limited way. In this paper we extract low-level features to characterize the local neighborhood patterns. We exploit the unlabeled feature measurements in a novel way to learn a set of basis functions to derive new features. The derived sparse feature representation obtained by encoding the measured features in terms of the learned basis function set yields superior classification performance. We applied our technique on two challenging image datasets: ORNL dataset representing one-meter spatial resolution satellite imagery representing five land-use categories and, UCMERCED dataset consisting of 21 different categories representing sub-meter resolution overhead imagery. Our results are highly promising and, in the case of UCMERCED dataset we outperform the best results obtained for this dataset. We show that our feature extraction and learning methods are highly effective in developing a detection system that can be used to automatically scan large-scale high-resolution satellite imagery for detecting large-facility.

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

    NASA Astrophysics Data System (ADS)

    Kandylakis, Z.; Karantzalos, K.

    2016-06-01

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

  17. Updating Maps Using High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  18. Linear mixing model applied to coarse resolution satellite data

    NASA Technical Reports Server (NTRS)

    Holben, Brent N.; Shimabukuro, Yosio E.

    1992-01-01

    A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

  19. Resolution-independent characteristic scale dedicated to satellite images.

    PubMed

    Luo, Bin; Aujol, Jean-François; Gousseau, Yann; Ladjal, Saïd; Maître, Henri

    2007-10-01

    We study the problem of finding the characteristic scale of a given satellite image. This feature is defined so that it does not depend on the spatial resolution of the image. This is a different problem than achieving scale invariance, as often studied in the literature. Our approach is based on the use of a linear scale space and the total variation (TV). The critical scale is defined as the one at which the normalized TV reaches its maximum. It is shown experimentally, both on synthetic and real data, that the computed characteristic scale is resolution independent. PMID:17926932

  20. Mapping Hazardous River Ice from High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Jones, C.; Kielland, K.; Prakash, A.; Hinzman, L. D.

    2014-12-01

    In interior Alaska, frozen river systems are important transportation corridors, due to the very limited road network. Long-time Alaskan residents report that winter travel conditions on Interior rivers have become more dangerous in recent memory. Field experience suggested that visual clues may provide experienced river travelers with clues of ice conditions. We explored the utility of airborne or satellite imagery as useful tools to map dangerous ice conditions on rivers in interior Alaska. Unsupervised classification of high-resolution satellite imagery was used to identify and map open water and degraded ice conditions on the Tanana River. An accuracy assessment indicated that snow, degraded ice, and open water were mapped with an overall accuracy of 73%, producer's accuracies between (82 and 100%), and user's accuracy ranging from (62 to 86%). Over 95% of the errors were caused by shadowing of trees or topographic features in the snow. The classification system performed well for a variety of satellite images and across different satellite platforms. With further development, these types of satellite remote sensing tools could prove to be very useful across a range of disciplines and industry in northern climates.

  1. Exploring NASA Satellite Data with High Resolution Visualization

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  2. Detecting Climate Signatures with High Spectral Resolution Infrared Satellite Measurements

    NASA Astrophysics Data System (ADS)

    Deslover, D. H.; Tobin, D.; Knuteson, R. O.; Revercomb, H. E.

    2013-12-01

    Upwelling atmospheric infrared radiances can be accurately monitored from high spectral resolution satellite observations. The high spectral resolution nature of these measurements affords the ability to track various climate relevant parameters such as window channels sensitive to surface temperature and clouds, channels with higher sensitivity to trace gases including CO2, CH4, SO2, HNO3, as well as channels sensitive only to upper tropospheric or lower stratospheric temperature. NASA's Atmospheric Infrared Sounder (AIRS) provides a data record that extends from its 2002 launch to the present. The Infrared Atmospheric Sounding Interferometer (IASI) onboard Metop- (A launched in 2006, B in 2012), as well as the Joint Polar Satellite System (JPSS) Cross-track Infrared Sounder (CrIS) launched in 2011, complement this data record. Future infrared sounders with similar capabilities will augment these measurements into the distant future. We have created a global data set from the aforementioned satellite observations. Our analysis yields a channel dependent approach that can be further constrained in terms of diurnal, seasonal and geographic limits, with measurement accuracies of better than a few tenths of degree Kelvin. In this study, we have applied this concept to obtain a better understanding of long-term stratospheric temperature trends. We will present a survey of temperature trends for spectral channels that were chosen to be sensitive to stratospheric emission. Results will be shown for tropical, mid-latitude and polar stratospheric observations.

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

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  4. a New Optimized Rfm of High-Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Li, C.; Liu, X. J.; Deng, T.

    2016-06-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Merline, William

    2012-02-01

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

  6. Study of radar pulse compression for high resolution satellite altimetry

    NASA Technical Reports Server (NTRS)

    Dooley, R. P.; Nathanson, F. E.; Brooks, L. W.

    1974-01-01

    Pulse compression techniques are studied which are applicable to a satellite altimeter having a topographic resolution of + 10 cm. A systematic design procedure is used to determine the system parameters. The performance of an optimum, maximum likelihood processor is analysed, which provides the basis for modifying the standard split-gate tracker to achieve improved performance. Bandwidth considerations lead to the recommendation of a full deramp STRETCH pulse compression technique followed by an analog filter bank to separate range returns. The implementation of the recommended technique is examined.

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

    NASA Astrophysics Data System (ADS)

    Ioannou, Maria Teresa; Georgopoulos, Andreas

    2013-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Agrafiotis, P.; Georgopoulos, A.

    2015-03-01

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

  9. Automatic Crowd Analysis from Very High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Sirmacek, B.; Reinartz, P.

    2011-04-01

    Recently automatic detection of people crowds from images became a very important research field, since it can provide crucial information especially for police departments and crisis management teams. Due to the importance of the topic, many researchers tried to solve this problem using street cameras. However, these cameras cannot be used to monitor very large outdoor public events. In order to bring a solution to the problem, herein we propose a novel approach to detect crowds automatically from remotely sensed images, and especially from very high resolution satellite images. To do so, we use a local feature based probabilistic framework. We extract local features from color components of the input image. In order to eliminate redundant local features coming from other objects in given scene, we apply a feature selection method. For feature selection purposes, we benefit from three different type of information; digital elevation model (DEM) of the region which is automatically generated using stereo satellite images, possible street segment which is obtained by segmentation, and shadow information. After eliminating redundant local features, remaining features are used to detect individual persons. Those local feature coordinates are also assumed as observations of the probability density function (pdf) of the crowds to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding pdf which gives us information about dense crowd and people locations. We test our algorithm usingWorldview-2 satellite images over Cairo and Munich cities. Besides, we also provide test results on airborne images for comparison of the detection accuracy. Our experimental results indicate the possible usage of the proposed approach in real-life mass events.

  10. Detection of Barchan Dunes in High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Azzaoui, M. A.; Adnani, M.; El Belrhiti, H.; Chaouki, I. E.; Masmoudi, C.

    2016-06-01

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

  11. High-Resolution Satellite Data Open for Government Research

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  12. Graph - Based High Resolution Satellite Image Segmentation for Object Recognition

    NASA Astrophysics Data System (ADS)

    Ravali, K.; Kumar, M. V. Ravi; Venugopala Rao, K.

    2014-11-01

    Object based image processing and analysis is challenging research in very high resolution satellite utilisation. Commonly ei ther pixel based classification or visual interpretation is used to recognize and delineate land cover categories. The pixel based classification techniques use rich spectral content of satellite images and fail to utilise spatial relations. To overcome th is drawback, traditional time consuming visual interpretation methods are being used operational ly for preparation of thematic maps. This paper addresses computational vision principles to object level image segmentation. In this study, computer vision algorithms are developed to define the boundary between two object regions and segmentation by representing image as graph. Image is represented as a graph G (V, E), where nodes belong to pixels and, edges (E) connect nodes belonging to neighbouring pixels. The transformed Mahalanobis distance has been used to define a weight function for partition of graph into components such that each component represents the region of land category. This implies that edges between two vertices in the same component have relatively low weights and edges between vertices in different components should have higher weights. The derived segments are categorised to different land cover using supervised classification. The paper presents the experimental results on real world multi-spectral remote sensing images of different landscapes such as Urban, agriculture and mixed land cover. Graph construction done in C program and list the run time for both graph construction and segmentation calculation on dual core Intel i7 system with 16 GB RAM, running 64bit window 7.

  13. Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

  14. Sea state variability observed by high resolution satellite radar images

    NASA Astrophysics Data System (ADS)

    Pleskachevsky, A.; Lehner, S.

    2012-04-01

    The spatial variability of the wave parameters is measured and investigated using new TerraSAR-X (TS-X) satellite SAR (Synthetic Aperture Radar) images. Wave groupiness, refraction and breaking of individual wave are studied. Space borne SAR is a unique sensor providing two dimensional information of the ocean surface. Due to its daylight, weather independency and global coverage, the TS-X radar is particularly suitable for many ocean and coastal observations and it acquires images of the sea surface with up to 1m resolution; individual ocean waves with wavelength below 30m are detectable. Two-dimensional information of the ocean surface, retrieved using TS-X data, is validated for different oceanographic applications: derivation of the fine resolved wind field (XMOD algorithm) and integrated sea state parameters (XWAVE algorithm). The algorithms are capable to take into account fine-scale effects in the coastal areas. This two-dimensional information can be successfully applied to validate numerical models. For this, wind field and sea state information retrieved from SAR images are given as input for a spectral numerical wave model (wind forcing and boundary condition). The model runs and sensitivity studies are carried out at a fine spatial horizontal resolution of 100m. The model results are compared to buoy time series at one location and with spatially distributed wave parameters obtained from SAR. The comparison shows the sensitivity of waves to local wind variations and the importance of local effects on wave behavior in coastal areas. Examples for the German Bight, North Sea and Rottenest Island, Australia are shown. The wave refraction, rendered by high resolution SAR images, is also studied. The wave ray tracking technique is applied. The wave rays show the propagation of the peak waves in the SAR-scenes and are estimated using image spectral analysis by deriving peak wavelength and direction. The changing of wavelength and direction in the rays allows

  15. High Resolution Soil Water from Regional Databases and Satellite Images

    NASA Technical Reports Server (NTRS)

    Morris, Robin D.; Smelyanskly, Vadim N.; Coughlin, Joseph; Dungan, Jennifer; Clancy, Daniel (Technical Monitor)

    2002-01-01

    This viewgraph presentation provides information on the ways in which plant growth can be inferred from satellite data and can then be used to infer soil water. There are several steps in this process, the first of which is the acquisition of data from satellite observations and relevant information databases such as the State Soil Geographic Database (STATSGO). Then probabilistic analysis and inversion with the Bayes' theorem reveals sources of uncertainty. The Markov chain Monte Carlo method is also used.

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

    SciTech Connect

    Marois, C

    2007-01-04

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

  17. High Spatial Resolution Commercial Satellite Imaging Product Characterization

    NASA Technical Reports Server (NTRS)

    Ryan, Robert E.; Pagnutti, Mary; Blonski, Slawomir; Ross, Kenton W.; Stnaley, Thomas

    2005-01-01

    NASA Stennis Space Center's Remote Sensing group has been characterizing privately owned high spatial resolution multispectral imaging systems, such as IKONOS, QuickBird, and OrbView-3. Natural and man made targets were used for spatial resolution, radiometric, and geopositional characterizations. Higher spatial resolution also presents significant adjacency effects for accurate reliable radiometry.

  18. Combined adjustment of multi-resolution satellite imagery for improved geo-positioning accuracy

    NASA Astrophysics Data System (ADS)

    Tang, Shengjun; Wu, Bo; Zhu, Qing

    2016-04-01

    Due to the widespread availability of satellite imagery nowadays, it is common for regions to be covered by satellite imagery from multiple sources with multiple resolutions. This paper presents a combined adjustment approach to integrate multi-source multi-resolution satellite imagery for improved geo-positioning accuracy without the use of ground control points (GCPs). Instead of using all the rational polynomial coefficients (RPCs) of images for processing, only those dominating the geo-positioning accuracy are used in the combined adjustment. They, together with tie points identified in the images, are used as observations in the adjustment model. Proper weights are determined for each observation, and ridge parameters are determined for better convergence of the adjustment solution. The outputs from the combined adjustment are the improved dominating RPCs of images, from which improved geo-positioning accuracy can be obtained. Experiments using ZY-3, SPOT-7 and Pleiades-1 imagery in Hong Kong, and Cartosat-1 and Worldview-1 imagery in Catalonia, Spain demonstrate that the proposed method is able to effectively improve the geo-positioning accuracy of satellite images. The combined adjustment approach offers an alternative method to improve geo-positioning accuracy of satellite images. The approach enables the integration of multi-source and multi-resolution satellite imagery for generating more precise and consistent 3D spatial information, which permits the comparative and synergistic use of multi-resolution satellite images from multiple sources.

  19. Visibility conflict resolution for multiple antennae and multi-satellites via genetic algorithm

    NASA Astrophysics Data System (ADS)

    Lee, Junghyun; Hyun, Chung; Ahn, Hyosung; Wang, Semyung; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

    Satellite mission control systems typically are operated by scheduling missions to the visibility between ground stations and satellites. The communication for the mission is achieved by interacting with satellite visibility and ground station support. Specifically, the satellite forms a cone-type visibility passing over a ground station, and the antennas of ground stations support the satellite. When two or more satellites pass by at the same time or consecutively, the satellites may generate a visibility conflict. As the number of satellites increases, solving visibility conflict becomes important issue. In this study, we propose a visibility conflict resolution algorithm of multi-satellites by using a genetic algorithm (GA). The problem is converted to scheduling optimization modeling. The visibility of satellites and the supports of antennas are considered as tasks and resources individually. The visibility of satellites is allocated to the total support time of antennas as much as possible for users to obtain the maximum benefit. We focus on a genetic algorithm approach because the problem is complex and not defined explicitly. The genetic algorithm can be applied to such a complex model since it only needs an objective function and can approach a global optimum. However, the mathematical proof of global optimality for the genetic algorithm is very challenging. Therefore, we apply a greedy algorithm and show that our genetic approach is reasonable by comparing with the performance of greedy algorithm application.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  1. Evaluating high resolution SPOT 5 satellite imagery for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High resolution satellite imagery has the potential for mapping within-field variability in crop growth and yield. This study examined SPOT 5 multispectral imagery for estimating grain sorghum yield. A SPOT 5 image with 10-m spatial resolution and four spectral bands (green, red, near-infrared, and ...

  2. Evaluation of a Moderate Resolution, Satellite-Based Impervious Surface Map Using an Independent, High-Resolution Validation Dataset

    EPA Science Inventory

    Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data ...

  3. An Error Model for High-Time Resolution Satellite Precipitation Products

    NASA Astrophysics Data System (ADS)

    Maggioni, V.; Sapiano, M.; Adler, R. F.; Huffman, G. J.; Tian, Y.

    2013-12-01

    A new error scheme (PUSH: Precipitation Uncertainties for Satellite Hydrology) is presented to provide global estimates of errors for high time resolution, merged precipitation products. Errors are estimated for the widely used Tropical Rainfall Monitoring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 product at daily/0.25° resolution, using the high quality NOAA CPC-UNI gauge analysis as the benchmark. Each of the following four scenarios is explored and explicitly modeled: correct no-precipitation detection (both satellite and gauges detect no precipitation), missed precipitation (satellite records a zero, but it is incorrect), false alarm (satellite detects precipitation, but the reference is zero), and hit (both satellite and gauges detect precipitation). Results over Oklahoma show that the estimated probability distributions are able to reproduce the probability density functions of the benchmark precipitation, in terms of both expected values and quantiles. PUSH adequately captures missed precipitation and false detection uncertainties, reproduces the spatial pattern of the error, and shows a good agreement between observed and estimated errors. The resulting error estimates could be attached to the standard products for the scientific community to use. Investigation is underway to: 1) test the approach in different regions of the world; 2) verify the ability of the model to discern the systematic and random components of the error; 3) and evaluate the model performance when higher time-resolution satellite products (i.e., 3-hourly) are employed.

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

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

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

  5. Evaluation of a moderate resolution, satellite-based impervious surface map using an independent, high-resolution validation data set

    USGS Publications Warehouse

    Jones, J.W.; Jarnagin, T.

    2009-01-01

    Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data products high quality, independently derived validation data are needed. High-resolution data were collected across a gradient of development within the Mid-Atlantic region to assess the accuracy of National Land Cover Data (NLCD) Landsat-based ISA estimates. Absolute error (satellite predicted area - "reference area") and relative error [satellite (predicted area - "reference area")/ "reference area"] were calculated for each of 240 sample regions that are each more than 15 Landsat pixels on a side. The ability to compile and examine ancillary data in a geographic information system environment provided for evaluation of both validation and NLCD data and afforded efficient exploration of observed errors. In a minority of cases, errors could be explained by temporal discontinuities between the date of satellite image capture and validation source data in rapidly changing places. In others, errors were created by vegetation cover over impervious surfaces and by other factors that bias the satellite processing algorithms. On average in the Mid-Atlantic region, the NLCD product underestimates ISA by approximately 5%. While the error range varies between 2 and 8%, this underestimation occurs regardless of development intensity. Through such analyses the errors, strengths, and weaknesses of particular satellite products can be explored to suggest appropriate uses for regional, satellite-based data in rapidly developing areas of environmental significance. ?? 2009 ASCE.

  6. Advanced DTM Generation from Very High Resolution Satellite Stereo Images

    NASA Astrophysics Data System (ADS)

    Perko, R.; Raggam, H.; Gutjahr, K. H.; Schardt, M.

    2015-03-01

    This work proposes a simple filtering approach that can be applied to digital surface models in order to extract digital terrain models. The method focusses on robustness and computational efficiency and is in particular tailored to filter DSMs that are extracted from satellite stereo images. It represents an evolution of an existing DTM generation method and includes distinct advancement through the integration of multi-directional processing as well as slope dependent filtering, thus denoted "MSD filtering". The DTM generation workflow is fully automatic and requires no user interaction. Exemplary results are presented for a DSM generated from a Pléiades tri-stereo image data set. Qualitative and quantitative evaluations with respect to highly accurate reference LiDAR data confirm the effectiveness of the proposed algorithm.

  7. Application of high resolution satellite observations to monitor urban ecosystems

    NASA Astrophysics Data System (ADS)

    Gorokhova, I. N.

    2011-02-01

    Topographic identification and mapping were carried out for different key plots in Moscow according to satellite images using geoinformation technologies; a complex ecological map was constructed for the key plots. The main advantage of this project is using the remote information for obtaining quick-look data on the ecosystem's state. The following ecological parameters were determined during the mapping: the percentage of forest area, the canopy's density, and the sites of forest uprooting in forests-parks; the recreational load on the soil cover in the forests, valleys of small rivers, and public gardens; the areas of disturbances of the herbaceous cover and soil overcompaction in lawns; the vertical and lateral structure of line plantings in community landscapes; and the disturbances in the land use in the territory of water-control areas of small rivers.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  9. Research on Complicated Imaging Condition of GEO Optical High Resolution Earth Observing Satellite

    NASA Astrophysics Data System (ADS)

    Guo, Linghua

    2012-07-01

    The requirement for high time and space resolution of optical remote sensing satellite in disaster, land resources, environment, marine monitoring and meteorology observation, etc is getting urgent and strict. For that reason, a remote sensing satellite system solely located in MEO or LEO cannot operate continuous observation and Surveillance. GEO optical high resolution earth observing satellite in the other hand can keep the mesoscale and microscale target under continuous surveillance by controlling line of sight(LOS), and can provide imaging observation of an extensive region in a short time. The advantages of GEO satellite such as real-time observation of the mesoscale and microscale target, rapid response of key events, have been recognized by lots of countries and become a new trend of remote sensing satellite. As many advantages as the GEO remote sensing satellite has, its imaging condition is more complicated. Many new characteristics of imaging observation and imaging quality need to be discussed. We analyze each factor in the remote sensing link, using theoretical analysis and modeling simulation to get coefficient of each factor to represent its effect on imaging system. Such research achievements can provide reference for satellite mission analysis and system design.

  10. A Modeling Approach to Global Land Surface Monitoring with Low Resolution Satellite Imaging

    NASA Technical Reports Server (NTRS)

    Hlavka, Christine A.; Dungan, Jennifer; Livingston, Gerry P.; Gore, Warren J. (Technical Monitor)

    1998-01-01

    The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.

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

    USGS Publications Warehouse

    Watkins, Allen H.; Thormodsgard, June M.

    1987-01-01

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

  12. Cirrus cloud characteristics derived from volume imaging lidar, high spectral resolution lidar, HIS radiometer, and satellite

    NASA Technical Reports Server (NTRS)

    Grund, Christian J.; Ackerman, Steven A.; Eloranta, Edwin W.; Knutsen, Robert O.; Revercomb, Henry E.; Smith, William L.; Wylie, Donald P.

    1990-01-01

    Preliminary measurement results are presented from the Cirrus Remote Sensing Pilot Experiment which used a unique suite of instruments to simultaneously retrieve cirrus cloud visible and IR optical properties, while addressing the disparities between satellite volume averages and local point measurements. The experiment employed a ground-based high resolution interferometer sounder (HIS) and a second Fourier transform spectrometer to measure the spectral radiance in the 4-20 micron band, a correlated high spectral resolution lidar, a volume imaging lidar, a CLASS radiosonde system, the Scripps Whole Sky Imager, and multispectral VAS, HIRS, and AVHRR satellite data from polar orbiting and geostationary satellites. Data acquired during the month long experiment included continuous daytime monitoring with the Whole Sky Imager.

  13. Object-Based Greenhouse Classification from High Resolution Satellite Imagery: a Case Study Antalya-Turkey

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    Pixel-based classification method is widely used with the purpose of detecting land use and land cover with remote sensing technology. Recently, object-based classification methods have begun to be used as well as pixel-based classification method on high resolution satellite imagery. In the studies conducted, it is indicated that object-based classification method has more successful results than other classification methods. While pixel-based classification method is performed according to the grey value of pixels, object-based classification process is executed by generating imagery segmentation and updatable rule sets. In this study, it was aimed to detect and map the greenhouses from object-based classification method by using high resolution satellite imagery. The study was carried out in the Antalya province which includes greenhouse intensively. The study consists of three main stages including segmentation, classification and accuracy assessment. At the first stage, which was segmentation, the most important part of the object-based imagery analysis; imagery segmentation was generated by using basic spectral bands of high resolution Worldview-2 satellite imagery. At the second stage, applying the nearest neighbour classifier to these generated segments classification process was executed, and a result map of the study area was generated. Finally, accuracy assessments were performed using land studies and digital data of the area. According to the research results, object-based greenhouse classification using high resolution satellite imagery had over 80% accuracy.

  14. Estimating ground cover of field crops using medium-resolution multispectral satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing is useful for estimating plant canopy characteristics, such as leaf area index (LAI) and ground cover (GC). When the source of remote sensing data is medium-resolution satellite imagery, plant canopy characteristics can be estimated for numerous fields within an agricultural region. I...

  15. Estimating ground cover of field crops using medium resolution multispectral satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing is useful for estimating plant canopy characteristics, such as leaf area index (LAI) and ground cover (GC). When the source of remote sensing data is medium-resolution satellite imagery, plant canopy characteristics can be estimated for numerous fields within an agricultural region. I...

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

    EPA Science Inventory

    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...

  17. Role of light satellites in the high-resolution Earth observation domain

    NASA Astrophysics Data System (ADS)

    Fishman, Moshe

    1999-12-01

    Current 'classic' applications using and exploring space based earth imagery are exclusive, narrow niche tailored, expensive and hardly accessible. On the other side new, inexpensive and widely used 'consumable' applications will be only developed concurrently to the availability of appropriate imagery allowing that process. A part of these applications can be imagined today, like WWW based 'virtual tourism' or news media, but the history of technological, cultural and entertainment evolution teaches us that most of future applications are unpredictable -- they emerge together with the platforms enabling their appearance. The only thing, which can be ultimately stated, is that the definitive condition for such applications is the availability of the proper imagery platform providing low cost, high resolution, large area, quick response, simple accessibility and quick dissemination of the raw picture. This platform is a constellation of Earth Observation satellites. Up to 1995 the Space Based High Resolution Earth Observation Domain was dominated by heavy, super-expensive and very inflexible birds. The launch of Israeli OFEQ-3 Satellite by MBT Division of Israel Aircraft Industries (IAI) marked the entrance to new era of light, smart and cheap Low Earth Orbited Imaging satellites. The Earth Resource Observation System (EROS) initiated by West Indian Space, is based on OFEQ class Satellites design and it is capable to gather visual data of Earth Surface both at high resolution and large image capacity. The main attributes, derived from its compact design, low weight and sophisticated logic and which convert the EROS Satellite to valuable and productive system, are discussed. The major advantages of Light Satellites in High Resolution Earth Observation Domain are presented and WIS guidelines featuring the next generation of LEO Imaging Systems are included.

  18. Tree Species Classification By Multiseasonal High Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  19. Space instrument performance traceability for high resolution satellite systems

    NASA Astrophysics Data System (ADS)

    Eckardt, A.; Börner, A.; Jahn, H.; Reulke, R.

    2008-08-01

    Technology changes in detector development and the significant improvement of manufacturing accuracy in combination with the permanent engineering research influences the spaceborne sensor systems, which are focused on Earth observation and remote sensing. Developments in focal plane technology, e.g. the combination of large TDI lines, intelligent synchronisation control, fast readable sensors and new focal plane and telescope concepts are the key developments for new remote sensing instruments. This class of instruments disposes of high spatial and radiometric resolution for the generation of data products for mapping and 3D GIS VR applications. Systemic approaches are essential for the design of complex sensor systems based on dedicated tasks. The system-theoretical description of the instrument inside and a simulated environment is the basic approach for the optimisation process of the optical, mechanical and electrical designs and assembly. Single modules and the entire system have to be calibrated and verified. The traceability of the performance-related parameters from the single sensor up to the flight readiness of the instrument forms the main focus inside such complex systems. In the future it will also be possible to prove the sensor performance on wafer level before assembly. This paper gives an overview about current technologies for performance measurements on sensor, focal plane assembly (FPA) and instrument level without the optical performance of the telescope. The paper proposes also a technology, which can be used for sensor performance measurements on wafer level.

  20. Vehicle extraction from high-resolution satellite image using template matching

    NASA Astrophysics Data System (ADS)

    Natt, Dehchaiwong; Cao, Xiaoguang

    2015-12-01

    The process of vehicle examination by using satellite images is complicated and cumbersome process. At the present, the high definition satellite images are being used, however, the images of the vehicles can be seen as just a small point which is difficult to separate it out from the background that the image details are not sufficient to identify small objects. In this research, the techniques for the process of vehicle examination by using satellite images were applied by using image data from Pléiades which is the satellite image with high resolution of 0.40 m. The objective of this research is to study and develop the device for data extracting from satellite images, and the received data would be organized and created as Geospatial information by the concept of the picture matching with a pattern matching or Template Matching developed with Matlab program and Sum of Absolute Difference method collaborated with Neural Network technique in order to help evaluating pattern matching between template images of cars and cars' images which were used to examine from satellite images. The result obtained from the comparison with template data shows that data extraction accuracy is greater than 90%, and the extracted data can be imported into Geospatial information database. Moreover, the data can be displayed in Geospatial information Software, and it also can be searched by quantity condition and satellite image position.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  3. Building identification from very high-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Lhomme, Stephane

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

  4. Object-Based Forest Change Detection Using High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Chehata, N.; Orny, C.; Boukir, S.; Guyon, D.

    2011-04-01

    An object-based approach for forest disaster change detection using High Resolution (HR) satellite images is proposed. An automatic feature selection process is used to optimize image segmentation via an original calibration-like procedure. A multitemporal classification then enables the separation of wind-fall from intact areas based on a new descriptor that depends on the level of fragmentation of the detected regions. The mean shift algorithm was used in both the segmentation and the classification processes. The method was tested on a high resolution Formosat-2 multispectral satellite image pair acquired before and after the Klaus storm. The obtained results are encouraging and the contribution of high resolution images for forest disaster mapping is discussed.

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  6. Advancing Satellite-Based Flood Prediction in Complex Terrain Using High-Resolution Numerical Weather Prediction

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Anagnostou, E. N.; Nikolopoulos, E. I.; Bartsotas, N. S.

    2015-12-01

    Floods constitute one of the most significant and frequent natural hazard in mountainous regions. Satellite-based precipitation products offer in many cases the only available source of QPE. However, satellite-based QPE over complex terrain suffer from significant bias that limits their applicability for hydrologic modeling. In this work we investigate the potential of a new correction procedure, which involves the use of high-resolution numerical weather prediction (NWP) model simulations to adjust satellite QPE. Adjustment is based on the pdf matching of satellite and NWP (used as reference) precipitation distribution. The impact of correction procedure on simulating the hydrologic response is examined for 15 storm events that generated floods over the mountainous Upper Adige region of Northern Italy. Atmospheric simulations were performed at 1-km resolution from a state-of-the-art atmospheric model (RAMS/ICLAMS). The proposed error correction procedure was then applied on the widely used TRMM 3B42 satellite precipitation product and the evaluation of the correction was based on independent in situ precipitation measurements from a dense rain gauge network (1 gauge / 70 km2) available in the study area. Satellite QPE, before and after correction, are used to simulate flood response using ARFFS (Adige River Flood Forecasting System), a semi-distributed hydrologic model, which is used for operational flood forecasting in the region. Results showed that bias in satellite QPE before correction was significant and had a tremendous impact on the simulation of flood peak, however the correction procedure was able to reduce bias in QPE and therefore improve considerably the simulated flood hydrograph.

  7. [The possibility of using high resolution satellite images for detection of marine mammals].

    PubMed

    Platonov, N G; Mordvintsev, I N; Rozhnov, V V

    2013-01-01

    The possibility of using modern systems of remote sensing in the optical range from high spatial resolution satellites for detection of marine mammals and traces of their activity is investigated. An image obtained by the GeoEye satellite within the FEAC project was used for the analysis. The image covers Herald Island and adjacent waters, which are a part of the Wrangel Island Reserve, during the seasonal thaw (June 2009). It is shown that marine mammals (polar bears, walruses, and whales) can be identified on such images. The absence of synchronous ground truth observations reduces the reliability of the results. PMID:23789427

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

    NASA Astrophysics Data System (ADS)

    Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

    2016-04-01

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

  9. High Resolution Satellite Remote Sensing of the 2013-2014 Eruption of Sinabung Volcano, Sumatra, Indonesia

    NASA Astrophysics Data System (ADS)

    Wessels, R. L.; Griswold, J. P.

    2014-12-01

    Satellite remote sensing provided timely observations of the volcanic unrest and several months-long eruption at Sinabung Volcano, Indonesia. Visible to thermal optical and synthetic aperture radar (SAR) systems provided frequent observations of Sinabung. High resolution image data with spatial resolutions from 0.5 to 1.5m offered detailed measurements of early summit deformation and subsequent lava dome and lava flow extrusion. The high resolution data were captured by commercial satellites such as WorldView-1 and -2 visible to near-infrared (VNIR) sensors and by CosmoSkyMed, Radarsat-2, and TerraSar-X SAR systems. Less frequent 90 to 100m spatial resolution night time thermal infrared (TIR) observations were provided by ASTER and Landsat-8. The combination of data from multiple sensors allowed us to construct a more complete timeline of volcanic activity than was available via only ground-based observations. This satellite observation timeline documents estimates of lava volume and effusion rates and major explosive and lava collapse events. Frequent, repeat volume estimates suggest at least three high effusion rate pulses of up to 20 m3/s occurred during the first three months of lava effusion with an average effusion rate of 6m3/s from January 2014 to August 2014. Many of these rates and events show some correlation to variations in the Real-time Seismic-Amplitude Measurement (RSAM) documented by the Indonesian Center for Volcanology and Geologic Hazard Mitigation (CVGHM).

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  11. Satellites

    SciTech Connect

    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.

  12. Automatic Mrf-Based Registration of High Resolution Satellite Video Data

    NASA Astrophysics Data System (ADS)

    Platias, C.; Vakalopoulou, M.; Karantzalos, K.

    2016-06-01

    In this paper we propose a deformable registration framework for high resolution satellite video data able to automatically and accurately co-register satellite video frames and/or register them to a reference map/image. The proposed approach performs non-rigid registration, formulates a Markov Random Fields (MRF) model, while efficient linear programming is employed for reaching the lowest potential of the cost function. The developed approach has been applied and validated on satellite video sequences from Skybox Imaging and compared with a rigid, descriptor-based registration method. Regarding the computational performance, both the MRF-based and the descriptor-based methods were quite efficient, with the first one converging in some minutes and the second in some seconds. Regarding the registration accuracy the proposed MRF-based method significantly outperformed the descriptor-based one in all the performing experiments.

  13. Application of high-resolution stereo satellite images to detailed landslide hazard assessment

    NASA Astrophysics Data System (ADS)

    Nichol, Janet E.; Shaker, Ahmed; Wong, Man-Sing

    2006-06-01

    This study investigates and demonstrates the state of the art in remote sensing techniques for detailed landslide hazard assessment applicable to large areas. Since the most common methods of landslide hazard assessment using simple inventories and weighted overlays are heavily dependent on three-dimensional terrain visualization and analysis, stereo satellite images from the IKONOS Very High Resolution (VHR) sensor are used for this study. The DEMs created from IKONOS stereo images appear to be much more accurate and sensitive to micro-scale terrain features than a DEM created from digital contour data with a 2 m contour interval. Pan-sharpened stereo IKONOS images permit interpretation of recent landslides as small as 2-3 m in width as well as relict landslides older than 50 years. A cost-benefit analysis comparing stereo air photo interpretation with stereo satellite image interpretation suggests that stereo satellite imagery is usually more cost-effective for detailed landslide hazard assessment over large areas.

  14. Assimilation of high resolution satellite imagery into the 3D-CMCC forest ecosystem model

    NASA Astrophysics Data System (ADS)

    Natali, S.; Collalti, A.; Candini, A.; Della Vecchia, A.; Valentini, R.

    2012-04-01

    The use of satellite observations for the accurate monitoring of the terrestrial biosphere has been carried out since the very early stage of remote sensing applications. The possibility to observe the ground surface with different wavelengths and different observation modes (namely active and passive observations) has given to the scientific community an invaluable tool for the observation of wide areas with a resolution down to the single tree. On the other hand, the continuous development of forest ecosystem models has permitted to perform simulations of complex ("natural") forest scenarios to evaluate forest status, forest growth and future dynamics. Both remote sensing and modelling forest assessment methods have advantages and disadvantages that could be overcome by the adoption of an integrated approach. In the framework of the European Space Agency Project KLAUS, high resolution optical satellite data has been integrated /assimilated into a forest ecosystem model (named 3D-CMCC) specifically developed for multi-specie, multi-age forests. 3D-CMCC permits to simulate forest areas with different forest layers, with different trees at different age on the same point. Moreover, the model permits to simulate management activities on the forest, thus evaluating the carbon stock evolution following a specific management scheme. The model has been modified including satellite data at 10m resolution, permitting the use of directly measured information, adding to the model the real phenological cycle of each simulated point. Satellite images have been collected by the JAXA ALOS-AVNIR-2 sensor. The integration schema has permitted to identify a spatial domain in which each pixel is characterised by a forest structure (species, ages, soil parameters), meteo-climatological parameters and estimated Leaf Area Index from satellite. The resulting software package (3D-CMCC-SAT) is built around 3D-CMCC: 2D / 3D input datasets are processed iterating on each point of the

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

    NASA Astrophysics Data System (ADS)

    Gong, K.; Fritsch, D.

    2016-06-01

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

  16. High-resolution electron momentum spectroscopy of valence satellites of carbon disulfide

    NASA Astrophysics Data System (ADS)

    Huang, Chengwu; Shan, Xu; Zhang, Zhe; Wang, Enliang; Li, Zhongjun; Chen, XiangJun

    2010-09-01

    The binding energy spectrum of carbon disulphide (CS2) in the energy range of 9-23 eV has been measured by a high-resolution (e,2e) spectrometer employing asymmetric noncoplanar kinematics at an impact energy of 2500 eV plus the binding energy. Taking the advantage of the high energy resolution of 0.54 eV, four main peaks and five satellites in the outer-valence region are resolved. The assignments and pole strengths for these satellite states are achieved by comparing the experimental electron momentum profiles with the corresponding theoretical ones calculated using Hartree-Fock and density functional theory methods. The results are also compared in detail with the recent SAC-CI general-R calculations. General agreement is satisfactory, while the present experiment suggests cooperative contributions from Π2u, Σg+2 states to satellite 2 and Σg+2, Π2g states to satellite 3. Besides, relatively low pole strength for X Π2g state is obtained which contradicts all the theoretical calculations [2ph-TDA, ADC(3), SAC-CI general-R, ADC(4)] so far.

  17. The high-resolution Doppler imager on the Upper Atmosphere Research Satellite

    NASA Technical Reports Server (NTRS)

    Hays, Paul B.; Abreu, Vincent J.; Dobbs, Michael E.; Gell, David A.; Grassl, Heinz J.; Skinner, Wilbert R.

    1993-01-01

    The high-resolution Doppler imager (HRDI) on the Upper Atmosphere Research Satellite is a triple-etalon Fabry-Perot interferometer designed to measure winds in the stratosphere, mesosphere, and lower thermosphere. Winds are determined by measuring the Doppler shifts of rotational lines of the O2 atmospheric band, which are observed in emission in the mesosphere and lower thermosphere and in absorption in the stratosphere. The interferometer has high resolution (0.05/cm), good offhand rejection, aud excellent stability. This paper provides details of the design and capabilities of the HRDI instrument.

  18. High Resolution Imager (HRI) for the Roentgen Satellite (ROSAT) definition study

    NASA Technical Reports Server (NTRS)

    1983-01-01

    The design of the high resolution imager (HRI) on HEAO 2 was modified for use in the instrument complement of the Roentgen Satellite (ROSAT). Mechanical models of the front end assembly, central electronics assembly, and detector assembly were used to accurately represent the HRI envelope for both fit checks and focal plane configuration studies. The mechanical and electrical interfaces were defined and the requirements for electrical ground support equipment were established. A summary description of the ROSAT telescope and mission is included.

  19. The Value of Real-time High Resolution Satellite Precipitation in Capturing Extreme Rainfall Event

    NASA Astrophysics Data System (ADS)

    Imam, B.; Kuranjekar, P.; Behrangi, A.; Hsu, K.; Sorooshian, S.

    2008-05-01

    In many parts of the world, operational real-time flood and hydrologic forecasting are hindered by the lack of reliable real-time precipitation observations. The insufficient ground observations have made satellite-based precipitation estimates the only available source for wide coverage data. As the spatial and temporal resolution of satellite-based rainfall estimates continue to improve, assessing the usefulness of these products, particularly in capturing extreme precipitation events becomes an important issue. This presentation demonstrates and discusses a framework for evaluating real-time high resolution precipitation products in terms of their operational utility. As an example of operational high resolution precipitation products, the 3 hourly near real-time, 0.04°x0.04° Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) (Hong et. al., 2004) product is compared against gauge and NEXRAD observations of several heavy precipitation events including tropical storm Erin, which affected Texas and Oklahoma during the period of August 10-20, 2007. For each storm, a swath of precipitation along the storm track is analyzed using both real-time and quality controlled versions of the products. Traditional as well as threshold- based (e.g. verification) performance measures are used to describe differences between NEXRAD and Satellite observations' ability to capture severe storm characteristics within the target area and to assess possible shifts in rainfall amount spectrum. While not fully conclusive, the results indicate that for operational purposes, high resolution satellite-based precipitation estimates can fill in a much needed observational gap during severe storm events.

  20. Super Resolution Reconstruction Based on Adaptive Detail Enhancement for ZY-3 Satellite Images

    NASA Astrophysics Data System (ADS)

    Zhu, Hong; Song, Weidong; Tan, Hai; Wang, Jingxue; Jia, Di

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    This study presents an approach to determine the volume of water in small lakes (<100 ha) by combining satellite altimetry data and high-resolution (HR) images. The lake being studied is located in the south-west of France and is only used for agricultural irrigation purposes. The altimetry satellite data are provided by RA-2 sensor on board Envisat, and the high-resolution images (<10 m) are obtained from optical (Formosat-2) and synthetic aperture radar (SAR) sensors (Terrasar-X and Radarsat-2) satellites. The altimetry data (data are obtained every 35 days) and the HR images (45) have been available since 2003 and 2010, respectively. In situ data (for the water levels and volumes) going back to 2003 have been provided by the manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2altimetry = 0.97, RMSEaltimetry = 5.2%, R2imagery = 0.90, and RMSEimagery = 7.4%). The third method combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2 = 0.99) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.

  2. Underwater monitoring experiment using hyperspectral sensor, LiDAR and high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Yang, Chan-Su; Kim, Sun-Hwa

    2014-10-01

    In general, hyper-spectral sensor, LiDAR and high spatial resolution satellite imagery for underwater monitoring are dependent on water clarity or water transparency that can be measured using a Secchi disk or satellite ocean color data. Optical properties in the sea waters of South Korea are influenced mainly by a strong tide and oceanic currents, diurnal, daily and seasonal variations of water transparency. The satellite-based Secchi depth (ZSD) analysis showed the applicability of hyper-spectral sensor, LiDAR and optical satellite, determined by the location connected with the local distribution of Case 1 and 2 waters. The southeast coastal areas of Jeju Island are selected as test sites for a combined underwater experiment, because those areas represent Case 1 water. Study area is a small port (<15m) in the southeast area of the island and linear underwater target used by sewage pipe is located in this area. Our experiments are as follows: 1. atmospheric and sun-glint correction methods to improve the underwater monitoring ability; 2. intercomparison of water depths obtained from three different sensors. Three sensors used here are the CASI-1500 (Wide-Array Airborne Hyperspectral VNIR Imager (0.38-1.05 microns), the Coastal Zone Mapping and Imaging Lidar (CZMIL) and Korean Multi-purpose Satellite-3 (KOMPSAT-3) with 2.8 meter multi-spectral resolution. The experimental results were affected by water clarity and surface condition, and the bathymetric results of three sensors show some differences caused by sensor-itself, bathymetric algorithm and tide level. It is shown that CASI-1500 was applicable for bathymetry and underwater target detection in this area, but KOMPSAT-3 should be improved for Case 1 water. Although this experiment was designed to compare underwater monitoring ability of LIDAR, CASI-1500, KOMPSAT-3 data, this paper was based on initial results and suggested only results about the bathymetry and underwater target detection.

  3. Ionosphere influence on success rate of GPS ambiguity resolution in a satellite formation flying

    NASA Astrophysics Data System (ADS)

    Baroni, Leandro

    2015-10-01

    Satellite formation flying is one of the most promising technologies for future space missions. The distribution of sensors and payloads among different satellites provides more redundancy, flexibility, improved communication coverage, among other advantages. One of the fundamental issues in spacecraft formation flying is precise position and velocity determination between satellites. For missions in low Earth orbits, GPS system can meet the precision requirement in relative positioning, since the satellite dynamics is modeled properly. The key for high accuracy GPS relative positioning is to resolve the ambiguities to their integer values. Ambiguities resolved successfully can improve the positioning accuracy to decimetre or even millimetre-level. So, integer carrier phase ambiguity resolution is often a prerequisite for high precision GPS positioning. The determination of relative position was made using an extended Kalman filter. The filter must take into account imperfections in dynamic modeling of perturbations affecting the orbital flight, and changes in solar activity that affects the GPS signal propagation, for mitigating these effects on relative positioning accuracy. Thus, this work aims to evaluate the impact of ionosphere variation, caused by changes in solar activity, in success rate of ambiguity resolution. Using the Ambiguity Dilution of Precision (ADOP) concept, the ambiguity success rate is analyzed and the expected precision of the ambiguity-fixed solution is calculated. Evaluations were performed using actual data from GRACE mission and analyzed for their performance in real scenarios. Analyses were conducted in different configurations of relative position and during different levels of solar activity. Results bring the impact of various disturbances and modeling of solar activity level on the success rate of ambiguity resolution.

  4. Old high resolution satellite images for landscape archaeology: case studies from Turkey and Iraq

    NASA Astrophysics Data System (ADS)

    Scardozzi, Giuseppe

    2008-10-01

    The paper concerns the contribution for Landscape Archaeology from satellite images of 1960s and 1970s, very useful when old aerial photographs are scarce. Particularly, the study concerns the panchromatic photos taken by USA reconnaissance satellites from 1963 to 1972, declassified for civil use in 1995 and 2002, that in the last years are very used in the archaeological research; in fact, a lot of these images have an high geometric resolution, about between 2.74 and 1.83 m (Corona KH-4A and KH-4B), and some have a ground resolution about between 1.20 and 0.60 m (Gambit KH-7). These satellite images allow to examine very in detail ancient urban areas and territories that later are changed or partially destroyed; so, it is possible to detect and examine ancient structures, palaeo-environmental elements and archaeological traces of buried features now not visible. The paper presents some exemplificative cases study in Turkey and Iraq, in which the analysis of these images has made a fundamental contribution to the archaeological researches: particularly, for the reconstruction of the urban layout of the ancient city of Hierapolis of Phrygia and for the surveys in its territory, and for the study of the ancient topography of some archaeological sites of Iraq. In this second case, the research is gained in the context of the Iraq Virtual Museum Project; the comparison with recent high resolution satellite images (Ikonos-2, QuickBird-2, WorldView-1) also provide a fundamental tool for monitoring archaeological areas and for an evaluation of the situation after the first and the second Gulf War.

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

    NASA Astrophysics Data System (ADS)

    Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie

    2016-04-01

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

  6. Mapping of Settlements in High Resolution Satellite Imagery using High Performance Computing

    SciTech Connect

    Cheriydat, Anil; Bright, Eddie A; Bhaduri, Budhendra L; Potere, David T

    2007-01-01

    Classifying urban land cover from high-resolution satellite imagery is challenging, and those challenges are compounded when the imagery databases are very large. Accurate land cover data is a crucial component of the population distribution modeling efforts of the Oak Ridge National Laboratory's (ORNL) LandScan Program. Currently, LandScan Program imagery analysts manually interpret high-resolution (1-5 meter) imagery to augment existing satellite-derived medium (30m) and coarse (1km) resolution land cover datasets. At LandScan, the high-resolution image archives that require interpretation are on the order of terabytes. The goal of this research is to automate urban land cover mapping utilizing ORNL's high performance computing capabilities. Our algorithm employs gray-level and local edge-pattern co-occurrence matrices to generate texture and edge patterns. Areas of urban land cover correlate with statistical features derived from these texture and edge patterns. We have parallelized our algorithms for implementation on a 64-node system using a single instruction multiple data programming model (SIMD) with Message Passing Interface (MPI) as the communication mode. Our parallel-configured classifier performs 30-40 times faster than stand-alone alternatives. When compared with manually interpreted IKONOS imagery, the classifier achieves a 91% overall accuracy. These early results are promising, pointing towards future large-scale classification of urban areas.

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

    NASA Astrophysics Data System (ADS)

    Wilson, Robin; Milton, Edward; Nield, Joanna

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  9. OMI NO2 column densities over North American urban cities: the effect of satellite footprint resolution

    NASA Astrophysics Data System (ADS)

    Kim, Hyun Cheol; Lee, Pius; Judd, Laura; Pan, Li; Lefer, Barry

    2016-03-01

    Nitrogen dioxide vertical column density (NO2 VCD) measurements via satellite are compared with a fine-scale regional chemistry transport model, using a new approach that considers varying satellite footprint sizes. Space-borne NO2 VCD measurement has been used as a proxy for surface nitrogen oxide (NOx) emission, especially for anthropogenic urban emission, so accurate comparison of satellite and modeled NO2 VCD is important in determining the future direction of NOx emission policy. The NASA Ozone Monitoring Instrument (OMI) NO2 VCD measurements, retrieved by the Royal Netherlands Meteorological Institute (KNMI), are compared with a 12 km Community Multi-scale Air Quality (CMAQ) simulation from the National Oceanic and Atmospheric Administration. We found that the OMI footprint-pixel sizes are too coarse to resolve urban NO2 plumes, resulting in a possible underestimation in the urban core and overestimation outside. In order to quantify this effect of resolution geometry, we have made two estimates. First, we constructed pseudo-OMI data using fine-scale outputs of the model simulation. Assuming the fine-scale model output is a true measurement, we then collected real OMI footprint coverages and performed conservative spatial regridding to generate a set of fake OMI pixels out of fine-scale model outputs. When compared to the original data, the pseudo-OMI data clearly showed smoothed signals over urban locations, resulting in roughly 20-30 % underestimation over major cities. Second, we further conducted conservative downscaling of OMI NO2 VCDs using spatial information from the fine-scale model to adjust the spatial distribution, and also applied averaging kernel (AK) information to adjust the vertical structure. Four-way comparisons were conducted between OMI with and without downscaling and CMAQ with and without AK information. Results show that OMI and CMAQ NO2 VCDs show the best agreement when both downscaling and AK methods are applied, with the correlation

  10. OMI NO2 column densities over North American urban cities: the effect of satellite footprint resolution

    NASA Astrophysics Data System (ADS)

    Kim, H. C.; Lee, P.; Judd, L.; Pan, L.; Lefer, B.

    2015-10-01

    Nitrogen dioxide vertical column density (NO2 VCD) measurements via satellite are compared with a fine-scale regional chemistry transport model, using a new approach that considers varying satellite footprint sizes. Space-borne NO2 VCD measurement has been used as a proxy for surface nitrogen oxide (NOx) emission, especially for anthropogenic urban emission, so accurate comparison of satellite and modeled NO2 VCD is important in determining the future direction of NOx emission policy. The National Aeronautics and Space Administration Ozone Monitoring Instrument (OMI) NO2 VCD measurements, retrieved by the Royal Netherlands Meteorological Institute (KNMI), are compared with a 12 km Community Multi-scale Air Quality (CMAQ) simulation from the National Oceanic and Atmospheric Administration. We found that OMI footprint pixel sizes are too coarse to resolve urban NO2 plumes, resulting in a possible underestimation in the urban core and overestimation outside. In order to quantify this effect of resolution geometry, we have made two estimates. First, we constructed pseudo-OMI data using fine-scale outputs of the model simulation. Assuming the fine-scale model output is a true measurement, we then collected real OMI footprint coverages and performed conservative spatial regridding to generate a set of fake OMI pixels out of fine-scale model outputs. When compared to the original data, the pseudo-OMI data clearly showed smoothed signals over urban locations, resulting in roughly 20-30 % underestimation over major cities. Second, we further conducted conservative downscaling of OMI NO2 VCD using spatial information from the fine-scale model to adjust the spatial distribution, and also applied Averaging Kernel (AK) information to adjust the vertical structure. Four-way comparisons were conducted between OMI with and without downscaling and CMAQ with and without AK information. Results show that OMI and CMAQ NO2 VCDs show the best agreement when both downscaling and AK

  11. Transfer of Technology for Cadastral Mapping in Tajikistan Using High Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Kaczynski, R.

    2012-07-01

    European Commission funded project entitled: "Support to the mapping and certification capacity of the Agency of Land Management, Geodesy and Cartography" in Tajikistan was run by FINNMAP FM-International and Human Dynamics from Nov. 2006 to June 2011. The Agency of Land Management, Geodesy and Cartography is the state agency responsible for development, implementation, monitoring and evaluation of state policies on land tenure and land management, including the on-going land reform and registration of land use rights. The specific objective was to support and strengthen the professional capacity of the "Fazo" Institute in the field of satellite geodesy, digital photogrammetry, advanced digital satellite image processing of high resolution satellite data and digital cartography. Lectures and on-the-job trainings for the personnel of "Fazo" and Agency in satellite geodesy, digital photogrammetry, cartography and the use of high resolution satellite data for cadastral mapping have been organized. Standards and Quality control system for all data and products have been elaborated and implemented in the production line. Technical expertise and trainings in geodesy, photogrammetry and satellite image processing to the World Bank project "Land Registration and Cadastre System for Sustainable Agriculture" has also been completed in Tajikistan. The new map projection was chosen and the new unclassified geodetic network has been established for all of the country in which all agricultural parcel boundaries are being mapped. IKONOS, QuickBird and WorldView1 panchromatic data have been used for orthophoto generation. Average accuracy of space triangulation of non-standard (long up to 90km) satellite images of QuickBird Pan and IKONOS Pan on ICPs: RMSEx = 0.5m and RMSEy = 0.5m have been achieved. Accuracy of digital orthophoto map is RMSExy = 1.0m. More then two and half thousands of digital orthophoto map sheets in the scale of 1:5000 with pixel size 0.5m have been produced

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  13. Monitoring black-tailed prairie dog colonies with high-resolution satellite imagery

    USGS Publications Warehouse

    Sidle, John G.; Johnson, D.H.; Euliss, B.R.; Tooze, M.

    2002-01-01

    The United States Fish and Wildlife Service has determined that the black-tailed prairie dog (Cynomys ludovicianus) warrants listing as a threatened species under the Endangered Species Act. Central to any conservation planning for the black-tailed prairie dog is an appropriate detection and monitoring technique. Because coarse-resolution satellite imagery is not adequate to detect black-tailed prairie dog colonies, we examined the usefulness of recently available high-resolution (1-m) satellite imagery. In 6 purchased scenes of national grasslands, we were easily able to visually detect small and large colonies without using image-processing algorithms. The Ikonos (Space Imaging(tm)) satellite imagery was as adequate as large-scale aerial photography to delineate colonies. Based on the high quality of imagery, we discuss a possible monitoring program for black-tailed prairie dog colonies throughout the Great Plains, using the species' distribution in North Dakota as an example. Monitoring plots could be established and imagery acquired periodically to track the expansion and contraction of colonies.

  14. Degradation and restoration of high resolution TDICCD imagery due to satellite vibrations

    NASA Astrophysics Data System (ADS)

    Zhi, Xiyang; Hou, Qingyu; Sun, Xuan; Zhang, Wei; Li, Liyuan

    2014-11-01

    A new method is proposed to solve the problem of image restoration of high resolution TDICCD camera due to satellite vibrations, which considers image blur and irregular sampling geometric quality degradation simultaneously. Firstly, the image quality degradation process is analyzed according to imaging characteristics of TDICCD camera, owing to image motions during TDICCD integration time induced by satellite vibrations. In addition, the vibration simulation model is established, and the irregular sampling degradation process of geometric quality is mathematically modeled using bicubic Hermite interpolation. Subsequently, a full image degradation model is developed combined with blurred and noisy degradation process. On this basis, a new method of image restoration is presented, which can implement not only deblurring but also irregular to regular sampling. Finally, the method is verified using real remote sensing images, and compared with the recent restoration methods. Experimental results indicate that the proposed method performs well, and the Structural Similarity between the restored and ideal images are greater than 0.9 in the case of seriously blurred, irregularly sampled and noisy images. The proposed method can be applied to restore high resolution on-orbit satellite images effectively.

  15. Effects of satellite data resolution on measuring the space/time variations of surfaces and clouds

    NASA Technical Reports Server (NTRS)

    Seze, Genevieve; Rossow, William B.

    1991-01-01

    The correlated distributions of satellite-measured visible and infrared radiances, caused by spatial and temporal variations in clouds and surfaces, have been found to be characteristic of the major climate regimes and can be described by the attributes of bidimensional and monodimensional histograms and time-composite images. Most of the variability of both the surfaces and clouds is found to occur at scales larger than the minimum resolved by satellite imagery. Since satellite imaging data sets are difficult to analyze because of their large volumes, many studies reduce the volume by various sampling or averaging schemes. The effects of data resolution and sampling on the radiance histogram statistics and on the time-composite image characteristics are examined. In particular, the sampling strategy used by the International Satellite Cloud Climatology Project is tested. This sampling strategy is found to preserve the statistics of smaller cloud variations for most regions, with the exception of very rare events, if they are accumulated over large enough areas (at least 500 km in dimension) and long enough time periods (at least one month).

  16. Study of satellite retrieved aerosol optical depth spatial resolution effect on particulate matter concentration prediction

    NASA Astrophysics Data System (ADS)

    Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.

    2014-10-01

    The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.

  17. Satellite tobacco mosaic virus refined to 1.4 Å resolution

    PubMed Central

    Larson, Steven B.; Day, John S.; McPherson, Alexander

    2014-01-01

    Satellite tobacco mosaic virus (STMV) is among the smallest viruses, having 60 identical subunits arranged with T = 1 icosahedral symmetry. Its crystal structure was solved at 290 K and was refined using, in part, crystals grown in microgravity. Electron-density maps revealed nearly 57% of the genomic ssRNA. Using six flash-cooled crystals, diffraction data were recorded to 1.4 Å resolution and independent refinements of the STMV model were carried out versus the previous 1.8 Å resolution data representing merged data from 21 crystals (271 689 unique reflections), data consisting of corresponding reflections to 1.8 Å resolution from the cooled crystals and 1.4 Å resolution data from the cooled crystals comprised of 570 721 unique reflections. Models were independently refined with full NCS constraints using the program CNS and in restrained mode using the programs CNS, REFMAC5 and SHELX-97, with the latter two procedures including anisotropic temperature factors. Significant additional structural detail emerged from the analyses, including a unique cation and anion arrangement on fivefold axes and a precise assessment of icosahedral symmetry exactness in the crystal lattice. STMV represents the highest resolution native virus structure currently known by a substantial margin, and it permits the evaluation of a precise atomic model of a spherical virus at near-atomic resolution for the first time. PMID:25195746

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

    NASA Astrophysics Data System (ADS)

    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

  19. Probabilistic Change Detection Framework for Analyzing Settlement Dynamics Using Very High-resolution Satellite Imagery

    SciTech Connect

    Vatsavai, Raju; Graesser, Jordan B

    2012-01-01

    Global human population growth and an increasingly urbanizing world have led to rapid changes in human settlement landscapes and patterns. Timely monitoring and assessment of these changes and dissemination of accurate information is important for policy makers, city planners, and humanitarian relief workers. Satellite imagery provides useful data for the aforementioned applications, and remote sensing can be used to identify and quantify change areas. We explore a probabilistic framework to identify changes in human settlements using very high-resolution satellite imagery. As compared to predominantly pixel-based change detection systems which are highly sensitive to image registration errors, our grid (block) based approach is more robust to registration errors. The presented framework is an automated change detection system applicable to both panchromatic and multi-spectral imagery. The detection system provides comprehensible information about change areas, and minimizes the post-detection thresholding procedure often needed in traditional change detection algorithms.

  20. Remote Sensing Image Classification of Geoeye-1 High-Resolution Satellite

    NASA Astrophysics Data System (ADS)

    Yang, B.; Yu, X.

    2014-04-01

    Networks play the role of a high-level language, as is seen in Artificial Intelligence and statistics, because networks are used to build complex model from simple components. These years, Bayesian Networks, one of probabilistic networks, are a powerful data mining technique for handling uncertainty in complex domains. In this paper, we apply Bayesian Networks Augmented Naive Bayes (BAN) to texture classification of High-resolution satellite images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples. In the experiment, we choose GeoEye-1 satellite images. Experimental results demonstrate BAN outperform than NBC in the overall classification accuracy. Although it is time consuming, it will be an attractive and effective method in the future.

  1. Building Change Detection in Very High Resolution Satellite Stereo Image Time Series

    NASA Astrophysics Data System (ADS)

    Tian, J.; Qin, R.; Cerra, D.; Reinartz, P.

    2016-06-01

    There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.

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

    SciTech Connect

    Ruiz-Arias, Jose A.; Tovar-Pescador, Joaquin; Cebecauer, Tomas; Suri, Marcel

    2010-09-15

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

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    This study presents an approach to determining the volume of water in small lakes (<100 ha) by combining satellite altimetry data and high-resolution (HR) images. In spite of the strong interest in monitoring surface water resources on a small scale using radar altimetry and satellite imagery, no information is available about the limits of the remote-sensing technologies for small lakes mainly used for irrigation purposes. The lake being studied is located in the south-west of France and is only used for agricultural irrigation purposes. The altimetry satellite data are provided by an RA-2 sensor onboard Envisat, and the high-resolution images (<10 m) are obtained from optical (Formosat-2) and synthetic aperture radar (SAR) antenna (Terrasar-X and Radarsat-2) satellites. The altimetry data (data are obtained every 35 days) and the HR images (77) have been available since 2003 and 2010, respectively. In situ data (for the water levels and volumes) going back to 2003 have been provided by the manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches (HRBV and ABV) are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2ABV = 0.98, RMSEABV = 5%, R2HRBV = 0.90, and RMSEABV = 7.4%), assuming a time-varying triangular shape for the shore slope of the lake (this form is well adapted since it implies a difference inferior to 2% between the theoretical volume of the lake and the one estimated from bathymetry). The third method (AHRBVC) combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2AHRBVC = 0.98) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to

  5. A contribution towards simplifying area-wide tsetse surveys using medium resolution meteorological satellite data.

    PubMed

    Hendrickx, G; Napala, A; Slingenbergh, J H; De Deken, R; Rogers, D J

    2001-10-01

    A raster or grid-based Geographic Information System with data on tsetse, trypanosomiasis, animal production, agriculture and land use has recently been developed in Togo. The area-wide sampling of tsetse fly, aided by satellite imagery, is the subject of two separate papers. This paper follows on a first paper, published in this journal, describing the generation of digital tsetse distribution and abundance maps and how these accord with the local climatic and agro-ecological setting. Such maps when combined with data on the disease, the hosts and their owners, should contribute to the knowledge of the spatial epidemiology of trypanosomiasis and assist planning of integrated control operations. Here we address the problem of generating tsetse distribution and abundance maps from remotely sensed data, using a restricted amount of field data. Different discriminant analysis models have been applied using contemporary tsetse data and remotely sensed, low resolution data acquired from the National Oceanographic and Atmospheric Administration (NOAA) and Meteosat platforms. The results confirm the potential of satellite data application and multivariate analysis for the prediction of the tsetse distribution and abundance. This opens up new avenues because satellite predictions and field data may be combined to strengthen and/or substitute one another. The analysis shows how the strategic incorporation of satellite imagery may minimize field collection of data. Field surveys may be modified and conducted in two stages, first concentrating on the expected fly distribution limits and thereafter on fly abundance. The study also shows that when applying satellite data, care should be taken in selecting the optimal number of predictor variables because this number varies with the amount of training data for predicting abundance and on the homogeneity of the distribution limits for predicting fly presence. Finally, it is suggested that in addition to the use of contemporary

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

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.

    2013-10-01

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

  7. Agricultural land-use mapping using very high resolution satellite images in Canary Islands

    NASA Astrophysics Data System (ADS)

    Labrador Garcia, Mauricio; Arbelo, Manuel; Evora Brondo, Juan Antonio; Hernandez-Leal, Pedro A.; Alonso-Benito, Alfonso

    Crop maps are a basic tool for rural planning and a way to asses the impact of politics and infrastructures in the rural environment. Thus, they must be accurate and updated. Because of the small size of the land fields in Canary Islands, until now the crop maps have been made by means of an intense and expensive field work. The tiny crop terraces do not allow the use of traditional medium-size resolution satellite images. The launch of several satellites with sub-meter spatial resolutions in the last years provides an opportunity to update land use maps in these fragmented areas. SATELMAC is a project financed by the PCT-MAC 2007-2013 (FEDER funds). One of the main objectives of this project is to develop a methodology that allows the use of very high resolution satellite images to automate as much as possible the updating of agricultural land use maps. The study was carried out in 3 different areas of the two main islands of the Canarian Archipelago, Tenerife and Gran Canaria. The total area is about 550 km2 , which includes both urban and rural areas. Multitemporal images from Geo-Eye 1 were acquired during a whole agricultural season to extract information about annual and perennial crops. The work includes a detailed geographic correction of the images and dealing with many adverse factors like cloud shadows, variability of atmospheric conditions and the heterogeneity of the land uses within the study area. Different classification methods, including traditional pixel-based methods and object-oriented approach, were compared in order to obtain the best accuracy. An intensive field work was carried out to obtain the ground truth, which is the base for the classification procedures and the validation of the results. The final results will be integrated into a cadastral vector layer.

  8. Annual evapotranspiration retrieved from satellite vegetation indices for the eastern Mediterranean at 250 m spatial resolution

    NASA Astrophysics Data System (ADS)

    Helman, D.; Givati, A.; Lensky, I. M.

    2015-11-01

    We present a model to retrieve actual evapotranspiration (ET) from satellites' vegetation indices (Parameterization of Vegetation Indices for ET estimation model, or PaVI-E) for the eastern Mediterranean (EM) at a spatial resolution of 250 m. The model is based on the empirical relationship between satellites' vegetation indices (normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from MODIS) and total annual ET (ETAnnual) estimated at 16 FLUXNET sites, representing a wide range of plant functional types and ETAnnual. Empirical relationships were first examined separately for (a) annual vegetation systems (i.e. croplands and grasslands) and (b) systems with combined annual and perennial vegetation (i.e. woodlands, forests, savannah and shrublands). Vegetation indices explained most of the variance in ETAnnual in those systems (71 % for annuals, and 88 % for combined annual and perennial systems), while adding land surface temperature data in a multiple-variable regression and a modified version of the Temperature and Greenness model did not result in better correlations (p > 0.1). After establishing empirical relationships, PaVI-E was used to retrieve ETAnnual for the EM from 2000 to 2014. Models' estimates were highly correlated (R = 0.92, p < 0.01) with ETAnnual calculated from water catchment balances along rainfall gradient of the EM. They were also comparable to the coarser-resolution ET products of the Land Surface Analysis Satellite Applications Facility (LSA-SAF MSG ETa, 3.1 km) and MODIS (MOD16, 1 km) at 148 EM basins with R of 0.75 and 0.77 and relative biases of 5.2 and -5.2 %, respectively (p < 0.001 for both). In the absence of high-resolution (< 1 km) ET models for the EM the proposed model is expected to contribute to the hydrological study of this region, assisting in water resource management, which is one of the most valuable resources of this region.

  9. GNSS Carrier Phase Integer Ambiguity Resolution with Camera and Satellite images

    NASA Astrophysics Data System (ADS)

    Henkel, Patrick

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    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

  11. Road Network Extraction from High Resolution Multispectral Satellite Imagery Based on Object Oriented Techniques

    NASA Astrophysics Data System (ADS)

    Kumar, M.; Singh, R. K.; Raju, P. L. N.; Krishnamurthy, Y. V. N.

    2014-11-01

    High Resolution satellite Imagery is an important source for road network extraction for urban road database creation, refinement and updating. However due to complexity of the scene in an urban environment, automated extraction of such features using various line and edge detection algorithms is limited. In this paper we present an integrated approach to extract road network from high resolution space imagery. The proposed approach begins with segmentation of the scene with Multi-resolution Object Oriented segmentation. This step focuses on exploiting both spatial and spectral information for the target feature extraction. The road regions are automatically identified using a soft fuzzy classifier based on a set of predefined membership functions. A number of shape descriptors are computed to reduce the misclassifications between road and other spectrally similar objects. The detected road segments are further refined using morphological operations to form final road network, which is then evaluated for its completeness, correctness and quality. The experiments were carried out of fused IKONOS 2 , Quick bird ,Worldview 2 Products with fused resolution's ranging from 0.5m to 1 m. Results indicate that the proposed methodology is effective in extracting accurate road networks from high resolution imagery.

  12. High resolution satellite observations of mesoscale oceanography in the Tasman Sea, 1978 - 1979

    NASA Technical Reports Server (NTRS)

    Nilsson, C. S.; Andrews, J. C.; Hornibrook, M.; Latham, A. R.; Speechley, G. C.; Scully-Power, P. (Principal Investigator)

    1982-01-01

    Of the Nearly 1000 standard infrared photographic images received, 273 images were on computer compatible tape. It proved necessary to digitally enhance the scene contrast to cover only a select few degrees K over the photographic grey scale appropriate to the scene-specific range of sea surface temperature (SST). Some 178 images were so enhanced. Comparison with sea truth show that SST, as seen by satellite, provides a good guide to the ocean currents and eddies off East Australia, both in summer and winter. This is in contrast, particularly in summer, to SST mapped by surface survey, which usually lacks the necessary spatial resolution.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

  16. IMPROVING THE ACCURACY OF HISTORIC SATELLITE IMAGE CLASSIFICATION BY COMBINING LOW-RESOLUTION MULTISPECTRAL DATA WITH HIGH-RESOLUTION PANCHROMATIC DATA

    SciTech Connect

    Getman, Daniel J

    2008-01-01

    Many attempts to observe changes in terrestrial systems over time would be significantly enhanced if it were possible to improve the accuracy of classifications of low-resolution historic satellite data. In an effort to examine improving the accuracy of historic satellite image classification by combining satellite and air photo data, two experiments were undertaken in which low-resolution multispectral data and high-resolution panchromatic data were combined and then classified using the ECHO spectral-spatial image classification algorithm and the Maximum Likelihood technique. The multispectral data consisted of 6 multispectral channels (30-meter pixel resolution) from Landsat 7. These data were augmented with panchromatic data (15m pixel resolution) from Landsat 7 in the first experiment, and with a mosaic of digital aerial photography (1m pixel resolution) in the second. The addition of the Landsat 7 panchromatic data provided a significant improvement in the accuracy of classifications made using the ECHO algorithm. Although the inclusion of aerial photography provided an improvement in accuracy, this improvement was only statistically significant at a 40-60% level. These results suggest that once error levels associated with combining aerial photography and multispectral satellite data are reduced, this approach has the potential to significantly enhance the precision and accuracy of classifications made using historic remotely sensed data, as a way to extend the time range of efforts to track temporal changes in terrestrial systems.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Singh, Pankaj Pratap; Garg, Rahul Dev

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  20. Resolution of the Scripps/NOAA Marine Gravity Field from satellite altimetry

    NASA Astrophysics Data System (ADS)

    Marks, Karen M.

    The July 1995 declassification of the entire Geosat GM satellite altimeter data set enabled a joint Scripps/NOAA effort to compute a new (version 7.2) marine gravity field on a 2-minute grid. This gravity field covers the world's oceans between 72°N and 72°S, and is derived from a combination of ERS-1 and Geosat GM and ERM data. An earlier NOAA Geosat-only gravity field solution was confined to the southern latitudes because the 1992 declassification was limited to GM data south of 30°S. A simple coherence analysis between accurately-navigated ship gravity profiles and comparable gravity profiles obtained from the gravity grids reveals that the Scripps/NOAA gravity field is coherent with ship gravity down to ˜≥ 23-30 km. This slight increase in resolution over the previous NOAA Geosat-only gravity field (short-wavelength resolution of ˜26-30 km) implies that the increased spatial coverage provided by the ERS-I altimeter, when combined with Geosat, improves the solution. Coherence analyses between satellite gravity and ship topography, and ship gravity and ship topography, show that even shorter wavelength gravity anomalies (˜13 km) are present in sea-surface measurements made by ship. Even so, the Scripps/NOAA marine gravity field does an excellent job of resolving most of the short-wavelength gravity anomalies covering the world’s oceans.

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

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

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

  2. Unsupervised individual tree crown detection in high-resolution satellite imagery

    DOE PAGESBeta

    Skurikhin, Alexei N.; McDowell, Nate G.; Middleton, Richard S.

    2016-01-26

    Rapidly and accurately detecting individual tree crowns in satellite imagery is a critical need for monitoring and characterizing forest resources. We present a two-stage semiautomated approach for detecting individual tree crowns using high spatial resolution (0.6 m) satellite imagery. First, active contours are used to recognize tree canopy areas in a normalized difference vegetation index image. Given the image areas corresponding to tree canopies, we then identify individual tree crowns as local extrema points in the Laplacian of Gaussian scale-space pyramid. The approach simultaneously detects tree crown centers and estimates tree crown sizes, parameters critical to multiple ecosystem models. Asmore » a demonstration, we used a ground validated, 0.6 m resolution QuickBird image of a sparse forest site. The two-stage approach produced a tree count estimate with an accuracy of 78% for a naturally regenerating forest with irregularly spaced trees, a success rate equivalent to or better than existing approaches. In addition, our approach detects tree canopy areas and individual tree crowns in an unsupervised manner and helps identify overlapping crowns. Furthermore, the method also demonstrates significant potential for further improvement.« less

  3. Unsupervised individual tree crown detection in high-resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Skurikhin, Alexei N.; McDowell, Nate G.; Middleton, Richard S.

    2016-01-01

    Rapidly and accurately detecting individual tree crowns in satellite imagery is a critical need for monitoring and characterizing forest resources. We present a two-stage semiautomated approach for detecting individual tree crowns using high spatial resolution (0.6 m) satellite imagery. First, active contours are used to recognize tree canopy areas in a normalized difference vegetation index image. Given the image areas corresponding to tree canopies, we then identify individual tree crowns as local extrema points in the Laplacian of Gaussian scale-space pyramid. The approach simultaneously detects tree crown centers and estimates tree crown sizes, parameters critical to multiple ecosystem models. As a demonstration, we used a ground validated, 0.6 m resolution QuickBird image of a sparse forest site. The two-stage approach produced a tree count estimate with an accuracy of 78% for a naturally regenerating forest with irregularly spaced trees, a success rate equivalent to or better than existing approaches. In addition, our approach detects tree canopy areas and individual tree crowns in an unsupervised manner and helps identify overlapping crowns. The method also demonstrates significant potential for further improvement.

  4. FFT-enhanced IHS transform method for fusing high-resolution satellite images

    USGS Publications Warehouse

    Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

    2007-01-01

    Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

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

    USGS Publications Warehouse

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

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    NASA Technical Reports Server (NTRS)

    Kim, Edward J.; Tedesco, Marco

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  9. Detecting and tracking dust outbreaks by using high temporal resolution satellite data

    NASA Astrophysics Data System (ADS)

    Sannazzaro, Filomena; Marchese, Francesco; Filizzola, Carolina; Tramutoli, Valerio; Pergola, Nicola; Mazzeo, Giuseppe; Paciello, Rossana

    2013-04-01

    A dust storm is a meteorological phenomenon generated by the action of wind, mainly in arid and semi-arid regions of the planet, particularly at subtropical latitudes. Dust outbreaks, of which frequency increases from year to year concurrently with climate change and reduction of moisture in the soil, may strongly impact on human activity as well as on environment and climate. Efficient early warning systems are then required to monitor them and to mitigate their effects. Satellite remote sensing thanks to a global coverage, to a high frequency of observation and low costs of data represents an important tool for studying and monitoring dust outbreaks. Several techniques have been then proposed to detect and monitor these phenomena from space, analyzing signal in different bands of the electromagnetic spectrum. In particular, methods based on the reverse absorption behaviour of silicate particles in comparison with ice crystals and water droplets, at 11 and 12 micron wavelengths, have been largely employed for detecting dust, although some important issues both in terms of reliability and sensitivity still remain. In this work, an optimized configuration of an innovative algorithm for dust detection, based on the largely accepted Robust Satellite Techniques (RST) multi-temporal approach, is then presented. This optimized algorithm configuration is tested here on Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, analyzing some important dust events affecting Mediterranean basin in recent years. Results of this study, assessed on the basis of independent satellite-based aerosol products, generated by using the Total Ozone Mapping Spectrometer (TOMS), the Ozone Monitoring Instrument (OMI), and the Moderate Resolution Imaging Spectroradiometer (MODIS) data, show that when the spectral resolution of SEVIRI is properly exploited dust and meteorological clouds may be better discriminated. These results encourage further experimentations of the proposed

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

    USGS Publications Warehouse

    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 <15%). Satellite imagery may be an effective monitoring tool 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  13. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite

    PubMed Central

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN usingimages of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN. PMID:26447470

  14. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

    PubMed

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN. PMID:26447470

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

    SciTech Connect

    Gillet, N.; Ocvirk, P.; Aubert, D.; Knebe, A.; Yepes, G.; Libeskind, N.; Gottlöber, S.; Hoffman, Y.

    2015-02-10

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

  16. A high-resolution approach to estimating ecosystem respiration at continental scales using operational satellite data.

    PubMed

    Jägermeyr, Jonas; Gerten, Dieter; Lucht, Wolfgang; Hostert, Patrick; Migliavacca, Mirco; Nemani, Ramakrishna

    2014-04-01

    A better understanding of the local variability in land-atmosphere carbon fluxes is crucial to improving the accuracy of global carbon budgets. Operational satellite data backed by ground measurements at Fluxnet sites proved valuable in monitoring local variability of gross primary production at highly resolved spatio-temporal resolutions. Yet, we lack similar operational estimates of ecosystem respiration (Re) to calculate net carbon fluxes. If successful, carbon fluxes from such a remote sensing approach would form an independent and sought after measure to complement widely used dynamic global vegetation models (DGVMs). Here, we establish an operational semi-empirical Re model, based only on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) with a resolution of 1 km and 8 days. Fluxnet measurements between 2000 and 2009 from 100 sites across North America and Europe are used for parameterization and validation. Our analysis shows that Re is closely tied to temperature and plant productivity. By separating temporal and intersite variation, we find that MODIS land surface temperature (LST) and enhanced vegetation index (EVI) are sufficient to explain observed Re across most major biomes with a negligible bias [R² = 0.62, RMSE = 1.32 (g C m(-2) d(-1)), MBE = 0.05 (g C m(-2) d(-1))]. A comparison of such satellite-derived Re with those simulated by the DGVM LPJmL reveals similar spatial patterns. However, LPJmL shows higher temperature sensitivities and consistently simulates higher Re values, in high-latitude and subtropical regions. These differences remain difficult to explain and they are likely associated either with LPJmL parameterization or with systematic errors in the Fluxnet sampling technique. While uncertainties remain with Re estimates, the model formulated in this study provides an operational, cross-validated and unbiased approach to scale Fluxnet Re to the continental scale and advances knowledge of spatio-temporal Re variability

  17. Simple method of deriving a surface information form series of historical, panchromatic, high resolution satellite imagery (CORONA program)

    NASA Astrophysics Data System (ADS)

    Skocki, Krzysztof

    2006-03-01

    From many years, satellite obtaining remote sensing data are used for monitoring and research a surface of Earth. Since 1972 when ERTS-1 satellite (Landsat 1) has started a service on orbit, multispectral satellite data has been available for scientists and general public. With typical spatial resolution of 5 - 25 meters we can use this data to analyze a natural and anthropogenic changes on our planet in small and medium scale. Initial data from early 70's have geometric resolution about 70 meters (MSS scanner) which is insufficient for many analyses. After 1995 we can easily obtain a declassified high-resolution military surveillance satellite imagery from CORONA satellites. Data collected from period 1961-1980 in analog form (photographic film) have typically spatial resolution in range 1 - 10 meters, but in wide, panchromatic channel. This article proposes a simple method for retrieving valuable information from series of panchromatic imagery collected over the same area in different seasons. This method utilizes a different properties of land cover types, specially from different vegetation canopies to retrieve a superficial, synthetic spectral channels that can be then analyzed and interpreted. This paper analyzes a method, verifies a results and proposes an interpretation methodology to use with multitemporal CORONA imagery. Concluding, we can obtain a valuable high resolution historical data in multichannel form covering 1972-1980 period. This method can be used for long-time analyses of land cover and land use changes in big scales (up to 1:10,000).

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

    USGS Publications Warehouse

    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

  19. Semi-auto assessment system on building damage caused by landslide disaster with high-resolution satellite and aerial images

    NASA Astrophysics Data System (ADS)

    Sun, Bo; Xu, Qihua; He, Jun; Ge, Fengxiang; Wang, Ying

    2015-10-01

    In recent years, earthquake and heavy rain have triggered more and more landslides, which have caused serious economic losses. The timely detection of the disaster area and the assessment of the hazard are necessary and primary for disaster mitigation and relief. As high-resolution satellite and aerial images have been widely used in the field of environmental monitoring and disaster management, the damage assessment by processing satellite and aerial images has become a hot spot of research work. The rapid assessment of building damage caused by landslides with high-resolution satellite or aerial images is the focus of this article. In this paper, after analyzing the morphological characteristics of the landslide disaster, we proposed a set of criteria for rating building damage, and designed a semi-automatic evaluation system. The system is applied to the satellite and aerial images processing. The performance of the experiments demonstrated the effectiveness of our system.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    USGS Publications Warehouse

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  3. Monitoring Powdery Mildew of Winter Wheat by Using Moderate Resolution Multi-Temporal Satellite Imagery

    PubMed Central

    Zhang, Jingcheng; Pu, Ruiliang; Yuan, Lin; Wang, Jihua; Huang, Wenjiang; Yang, Guijun

    2014-01-01

    Powdery mildew is one of the most serious diseases that have a significant impact on the production of winter wheat. As an effective alternative to traditional sampling methods, remote sensing can be a useful tool in disease detection. This study attempted to use multi-temporal moderate resolution satellite-based data of surface reflectances in blue (B), green (G), red (R) and near infrared (NIR) bands from HJ-CCD (CCD sensor on Huanjing satellite) to monitor disease at a regional scale. In a suburban area in Beijing, China, an extensive field campaign for disease intensity survey was conducted at key growth stages of winter wheat in 2010. Meanwhile, corresponding time series of HJ-CCD images were acquired over the study area. In this study, a number of single-stage and multi-stage spectral features, which were sensitive to powdery mildew, were selected by using an independent t-test. With the selected spectral features, four advanced methods: mahalanobis distance, maximum likelihood classifier, partial least square regression and mixture tuned matched filtering were tested and evaluated for their performances in disease mapping. The experimental results showed that all four algorithms could generate disease maps with a generally correct distribution pattern of powdery mildew at the grain filling stage (Zadoks 72). However, by comparing these disease maps with ground survey data (validation samples), all of the four algorithms also produced a variable degree of error in estimating the disease occurrence and severity. Further, we found that the integration of MTMF and PLSR algorithms could result in a significant accuracy improvement of identifying and determining the disease intensity (overall accuracy of 72% increased to 78% and kappa coefficient of 0.49 increased to 0.59). The experimental results also demonstrated that the multi-temporal satellite images have a great potential in crop diseases mapping at a regional scale. PMID:24691435

  4. Luobei graphite mines surrounding ecological environment monitoring based on high-resolution satellite data

    NASA Astrophysics Data System (ADS)

    Zhang, Lifeng; Liu, Xiaosha; Wan, Huawei; Liu, Xiaoman

    2014-11-01

    Graphite is one of the important industrial mineral raw materials, but the high content of heavy metals in tailings may cause soil pollution and other regional ecological environmental problems. Luobei has already become the largest production base of graphite. To find out the ecological situation in the region, further ecological risk analysis has been carried out. Luobei graphite mine which is located in Yabdanhe basin has been selected as the study area, SVM classifiers method with the support of GF-1 Satellite remote sensing data has been used, which is the first high-resolution earth observation satellite in China. The surrounding ecological environment was monitored and its potential impact on the ecological environment was analyzed by GIS platform. The results showed that the Luobei graphite mine located Yadanhe basin covers an area of 499.65 km2, the main types of forest ecosystems ( 44.05% of the total basin area ), followed by agricultural area( 35.14% ), grass area( 15.52% ), residential area ( 4.34% ), mining area ( 0.64% ) and water area( 0.30% ). By confirming the classification results, the total accuracy is 91.61%, the Kappa coefficient is 0.8991. Overall, GF-1 Satellite data can obtain regional ecosystems quickly, and provide a better data support for regional ecological resource protection zone. For Luobei graphite mines area, farmland and residential areas within its watershed are most vulnerable to mining, the higher proportion of farmland in duck river basin. The regulatory tailings need to be strengthened in the process of graphite mining processing.

  5. High resolution CASSINI VIMS mosaics of Titan and the icy satellites of Saturn

    NASA Astrophysics Data System (ADS)

    Jaumann, R.; Stephan, K.; Roatsch, T.; Scholten, F.; Matz, K.; Brown, R. H.

    2005-12-01

    The Visual Infrared Mapping Spectrometer VIMS onboard the CASSINI spacecraft obtained new spectral data of the icy satellites of Saturn after its arrival at Saturn in June 2004. VIMS operates in a spectral range of 0.3 and 5.1 microns, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. VIMS consists of two separate optical systems, the visible channel VIMS-V and the infrared channel VIMS-IR. VIMS-V acquires its data in push-broom-mode and views one row of a square scene at a time. VIMS-IR uses a linear array detector in order to acquire its data in whiskbroom mode, where it views only one single spatial pixel per exposure. Each of these channels can operated in different modi which cause differences in size and spatial resolution of the image cubes. Therefore, image cubes which combine the spectral data of both optical systems may result in a different location of the target in the VIS-channels and the IR-channels within the image cubes. To analyse the spectral data in a spatial way it is necessary that all 352 spectral elements of each pixel show the same area of the specific surface. We developed an algorithm to reproject each pixel geometrically and to convert the spectral data into a map projection. The algorithm includes the mosaicking of different VIMS observations. Based on these mosaics spatial maps of the spectral properties for each satellite can be derived and can be attributed to location, geological and geomorphologic features. VIMS mosaics of the available VIMS data of the Saturnian satellites, including Titan will be presented.

  6. Technical development for automatic aerial triangulation of high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Xiong, Zhen

    Because they contain abundant spatial information, high resolution satellite images are widely used in a variety of applications. Aerial triangulation is one of the most important technologies to obtain accurate spatial information from those images. Thus aerial triangulation is always an important research topic in the photogrammetric community and automatic aerial triangulation is a common goal of such PhD research activities. To date, many techniques have been developed to improve the efficiency and accuracy of aerial triangulation. However, for processing high resolution satellite images, automatic aerial triangulation still faces many challenges, including tie point extraction and sensor model refinement. The main purpose of this research is to develop and test new tie point extraction, sensor model refinement and bundle block adjustment methods for improving the automation and accuracy of aerial triangulation. The accuracy of tie points directly determines the success of aerial triangulation. Generally both the corner point and the gravity center point of a rectangular or circular object can be used as tie points, but the resulting outcomes can vary greatly in aerial triangulation. However, this difference has not drawn much attention from researchers yet. Thus, most of the tie point extraction algorithms only extract various corners. In order to quantify the difference between corner and center tie points for image registration, this research analyzed the error introduced by using corner or center tie points in different cases. Through quantitative analysis and experiments, the author reached the conclusion that the 'center' points, when used as tie points, can improve the accuracy of image registration by at least 40 percent over that for the 'corner' points. Extracting a large number of tie points is the prerequisite of automatic aerial triangulation. Interest point matching can extract tie points automatically. To date numerous interest point matching

  7. Monitoring Disease Trends using Hospital Traffic Data from High Resolution Satellite Imagery: A Feasibility Study

    PubMed Central

    Nsoesie, Elaine O.; Butler, Patrick; Ramakrishnan, Naren; Mekaru, Sumiko R.; Brownstein, John S.

    2015-01-01

    Challenges with alternative data sources for disease surveillance include differentiating the signal from the noise, and obtaining information from data constrained settings. For the latter, events such as increases in hospital traffic could serve as early indicators of social disruption resulting from disease. In this study, we evaluate the feasibility of using hospital parking lot traffic data extracted from high-resolution satellite imagery to augment public health disease surveillance in Chile, Argentina and Mexico. We used archived satellite imagery collected from January 2010 to May 2013 and data on the incidence of respiratory virus illnesses from the Pan American Health Organization as a reference. We developed dynamical Elastic Net multivariable linear regression models to estimate the incidence of respiratory virus illnesses using hospital traffic and assessed how to minimize the effects of noise on the models. We noted that predictions based on models fitted using a sample of observations were better. The results were consistent across countries with selected models having reasonably low normalized root-mean-squared errors and high correlations for both the fits and predictions. The observations from this study suggest that if properly procured and combined with other information, this data source could be useful for monitoring disease trends. PMID:25765943

  8. Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

    NASA Astrophysics Data System (ADS)

    Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

    2010-09-01

    ground cover. Thermal-based energy balance models are more suitable than the FAO-Kc model for estimating crop ET, especially under moisture stress conditions, but they require many inputs and detailed theoretical background knowledge; so they can be only used in regions where high quality, hourly agricultural weather data are readily available providing instantaneous values of heat fluxes corresponding to the time of the satellite overpass. Thus, FAO-Kc approach is widely used in research activities and real-time irrigation scheduling for several water applications since it does not require temporal upscaling for obtaining daily values and satellite imagery in the reflective bands used for vegetation index computation are more readily available at higher spatial resolution than thermal band data. There is no simple way to compute crop coefficients because they depend on climate, soil type, crop and its varieties, irrigation method, soil water, nutrient content and plant phenology. Consequently, specific calibrations of crop coefficient are required in various climatic regions. Many authors suggested a linear relationship between Kc and vegetation indices, but non-linear relationships have been proposed too. However, according to the radiative transfer theory, the nature of such relationships depends on the crop architecture and the definition of the adopted vegetation index, but the linear assumption can be adopted as first. Such studies, mainly investigated the possibility to use high resolution satellite data, such as Quickbird, Ikonos, TM, which are not suitable for operational purposes since in spite of the high spatial sampling they have an inadequate revisiting time over a given area. To obtain adequate temporal sampling, some authors proposed the use of a virtual constellation made by all currently available high-resolution satellites (e.g., DEMETER project). However the joint use of data from different satellites requires a carefully inter-satellite cross

  9. High-resolution inversion of methane emissions in North America using satellite observations (SCIAMACHY, TES, GOSAT)

    NASA Astrophysics Data System (ADS)

    Wecht, K.; Jacob, D. J.; Payer, M.; Henze, D. K.; Worden, J.; Payne, V.; Frankenberg, C.; Bowman, K. W.; Boesch, H.

    2012-12-01

    Methane emissions from North America are poorly known and potentially subject to rapid anthropogenic and natural changes. Satellite retrievals of methane columns from SCIAMACHY, TES, and GOSAT offer a unique resource for constraining and monitoring methane emissions using adjoint inverse modeling. We validate these methane retrievals using INTEX-A, HIPPO and NOAA/GMD aircraft observations. We also evaluate the consistency between the different satellite instruments with respect to the GEOS-Chem chemical transport model (CTM) as an intercomparison platform. We derive fine-scale constraints on methane sources through a four-dimensional variational (4D-VAR) inversion using the adjoint of GEOS-Chem with 1/2o × 2/3o (~50 × 50 km2) horizontal resolution over North America. Boundary conditions over the oceans are optimized as part of the inversion, thus preventing any global model bias from impacting the North American GEOS-Chem domain. In situ observations from aircraft campaigns and ground-based networks are used to evaluate the inversion results. We find that current inventories overestimate emissions from natural wetlands and underestimate emissions from natural gas production and enteric fermentation. Our results provide guidance to the US EPA for improving its national emission inventories.

  10. Land cover characterization and mapping of continental southeast Asia using multi-resolution satellite sensor data

    USGS Publications Warehouse

    Giri, Chandra; Defourny, P.; Shrestha, Surendra

    2003-01-01

    Land use/land cover change, particularly that of tropical deforestation and forest degradation, has been occurring at an unprecedented rate and scale in Southeast Asia. The rapid rate of economic development, demographics and poverty are believed to be the underlying forces responsible for the change. Accurate and up-to-date information to support the above statement is, however, not available. The available data, if any, are outdated and are not comparable for various technical reasons. Time series analysis of land cover change and the identification of the driving forces responsible for these changes are needed for the sustainable management of natural resources and also for projecting future land cover trajectories. We analysed the multi-temporal and multi-seasonal NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite data of 1985/86 and 1992 to (1) prepare historical land cover maps and (2) to identify areas undergoing major land cover transformations (called ‘hot spots’). The identified ‘hot spot’ areas were investigated in detail using high-resolution satellite sensor data such as Landsat and SPOT supplemented by intensive field surveys. Shifting cultivation, intensification of agricultural activities and change of cropping patterns, and conversion of forest to agricultural land were found to be the principal reasons for land use/land cover change in the Oudomxay province of Lao PDR, the Mekong Delta of Vietnam and the Loei province of Thailand, respectively. Moreover, typical land use/land cover change patterns of the ‘hot spot’ areas were also examined. In addition, we developed an operational methodology for land use/land cover change analysis at the national level with the help of national remote sensing institutions.

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

    NASA Astrophysics Data System (ADS)

    Yurovskaya, Maria; Dulov, Vladimir; Kozlov, Igor

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  13. High Resolution Satellite Multi-Temporal Interferometry for Landslide and Subsidence Hazard Assessment: An Overview

    NASA Astrophysics Data System (ADS)

    Wasowski, J.; Bovenga, F.; Nitti, D. O.; Nutricato, R.; Chiaradia, M.

    2014-12-01

    The new and planned satellite missions can not only provide global capacity for research-oriented and practical applications such as mapping, characterizing and monitoring of areas affected by slope and subsidence hazards, but also offer a possibility to push the research frontier and prompt innovative detailed-scale studies on ground movement dynamics and processes. Among a number of emerging space-based remote sensing techniques, synthetic aperture radar (SAR), multi-temporal interferometry (MTI) seems the most promising for important innovation in landslide and subsidence hazards assessment and monitoring. MTI is appealing to those concerned with terrain instability hazards because it can provide very precise information on slow displacements of the ground surface over vast areas with limited vegetation cover. Although MTI techniques are considered to have already reached the operational level, it is apparent that in both research and practice we are at present only beginning to benefit from the high-resolution imagery that is currently acquired by the new generation radar satellites (e.g. COSMO-SkyMed, TerraSAR-X). In this overview we illustrate the great potential of high resolution MTI and explain what this technique can deliver in terms of detection and monitoring of slope and subsidence hazards. This is done by considering different areas characterized by a wide range of geomorphic, climatic and vegetation conditions, and presenting selected case study examples of local to regional scale MTI applications from Europe, China and Haiti. We envision that the current approach to assessment of hazard can be transformed by capitalizing more on the presently underexploited advantage of the MTI technique, i.e. the capability to provide regularly spatially-dense quantitative information for large areas currently unaffected by instabilities, but where the terrain geomorphology and geology may indicate potential for future ground failures.

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

    SciTech Connect

    Newsam, S D; Kamath, C

    2004-01-22

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

  15. Comparison of Satellite NO{sub 2} Observations with High Resolution Model Simulations over the Balkan Peninsula

    SciTech Connect

    Zyrichidou, I.; Koukouli, M. E.; Balis, D. S.; Katragkou, E.; Poupkou, A.; Kioutsioukis, I.; Markakis, K.; Melas, D.; van der A., R.; Boersma, F. K.; Roozendael, M. van

    2010-01-21

    High resolution model estimations of tropospheric NO{sub 2} column amounts from the Comprehensive Air Quality Model (CAMx) were simulated for the Balkan Peninsula and were compared with satellite data for a period of one year, in order to study the characteristics of the spatial and temporal variability of pollution in the area. The Balkan area is considered a crossroad of different pollution sources and therefore has been divided in urban, industrial and rural regions, aiming to investigate the consistency of satellite retrievals and model predictions at high spatial resolution. Satellite measurements of tropospheric NO{sub 2} are available daily at 13:30 LT since 2004 from OMI/Aura with a resolution of 13x24 km. The anthropogenic emissions used in CAMx for the domain under study, was compiled employing bottom-up approaches (road transport sector, off-road machinery) as well as other national registries and international databases. High resolution GIS maps (road network, landuses, population) were also used in order to achieve high spatial resolution. In most of the cases the model reveals similar spatial patterns with the satellite data, while over certain areas discrepancies were found and investigated.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  17. Geometric Correction of High Resolution Imagery from Indian Remote Sensing Satellite (IRS-1C/D)

    NASA Astrophysics Data System (ADS)

    Katiyar, S. K.; Dikshit, O.; Kumar, K.

    Precise and up-to-date mapping of earth features is required for various applications. The high-resolution remotely sensed images could prove an alternative data capture tool for quick updating of maps and other applications. A major concern in remote sensing information extraction and data handling is to ensure geometric integrity of the acquired image. For the reliable and precise information extraction from remotely sensed data, the geometric distortions introduced due to various factors must be removed with high degree of precision. In general there are two approaches for the correction of geometric distortions. The parametric approach is model-based while the non-parametric one makes use of ground control points (GCP). The parametric method involves modeling of satellite viewing geometry with the help of ephemeris data. Here, satellite attitude angles (roll, pitch and yaw) should be known with high degree of precision. A small error in attitude measurements is magnified considerably in terms of corresponding ground error. Some GCPs are necessary for the precise attitude angle estimation. The GCP- based method utilizes least square technique for the fitting of low order polynomial functions with the help of GCPs. In this method polynomials are not very appropriate for modeling the physical causes of geometric distortions and require a large number of well-distributed GCPs for avoiding degradation of image in the regions, where no GCPs are available. This paper presents results of geometric correction of LISS III and PAN sensor data of Indian Remote Sensing Satellite (IRS-1C/D), by using combination of above mentioned approaches of geometric correction. The present study makes use of IRS-1C/D satellite ephemeris information (position, velocity and attitude angles) available at one second interval. Position and velocity vector component variations with the time can be modeled with sub-pixel accuracy using 3rd and 4th order polynomial functions and acceptable at

  18. The Optimized Block-Regression Fusion Algorithm for Pansharpening of Very High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Zhang, J. X.; Yang, J. H.; Reinartz, P.

    2016-06-01

    Pan-sharpening of very high resolution remotely sensed imagery need enhancing spatial details while preserving spectral characteristics, and adjusting the sharpened results to realize the different emphases between the two abilities. In order to meet the requirements, this paper is aimed at providing an innovative solution. The block-regression-based algorithm (BR), which was previously presented for fusion of SAR and optical imagery, is firstly applied to sharpen the very high resolution satellite imagery, and the important parameter for adjustment of fusion result, i.e., block size, is optimized according to the two experiments for Worldview-2 and QuickBird datasets in which the optimal block size is selected through the quantitative comparison of the fusion results of different block sizes. Compared to five fusion algorithms (i.e., PC, CN, AWT, Ehlers, BDF) in fusion effects by means of quantitative analysis, BR is reliable for different data sources and can maximize enhancement of spatial details at the expense of a minimum spectral distortion.

  19. Low Frequency Error Analysis and Calibration for High-Resolution Optical Satellite's Uncontrolled Geometric Positioning

    NASA Astrophysics Data System (ADS)

    Wang, Mi; Fang, Chengcheng; Yang, Bo; Cheng, Yufeng

    2016-06-01

    The low frequency error is a key factor which has affected uncontrolled geometry processing accuracy of the high-resolution optical image. To guarantee the geometric quality of imagery, this paper presents an on-orbit calibration method for the low frequency error based on geometric calibration field. Firstly, we introduce the overall flow of low frequency error on-orbit analysis and calibration, which includes optical axis angle variation detection of star sensor, relative calibration among star sensors, multi-star sensor information fusion, low frequency error model construction and verification. Secondly, we use optical axis angle change detection method to analyze the law of low frequency error variation. Thirdly, we respectively use the method of relative calibration and information fusion among star sensors to realize the datum unity and high precision attitude output. Finally, we realize the low frequency error model construction and optimal estimation of model parameters based on DEM/DOM of geometric calibration field. To evaluate the performance of the proposed calibration method, a certain type satellite's real data is used. Test results demonstrate that the calibration model in this paper can well describe the law of the low frequency error variation. The uncontrolled geometric positioning accuracy of the high-resolution optical image in the WGS-84 Coordinate Systems is obviously improved after the step-wise calibration.

  20. Use of high spatial resolution satellite imagery to characterize landscapes at risk for bluetongue.

    PubMed

    Guis, Hélène; Tran, Annelise; de La Rocque, Stéphane; Baldet, Thierry; Gerbier, Guillaume; Barragué, Bruno; Biteau-Coroller, Fabienne; Roger, François; Viel, Jean-François; Mauny, Frédéric

    2007-01-01

    The recent and rapid spread in the Mediterranean Basin of bluetongue, a viral disease of ruminants transmitted by some species of Culicoides (biting midges), highlights the necessity of determining the conditions of its emergence. This study uses high spatial resolution satellite imagery and methods from landscape ecology science to identify environmental parameters related to bluetongue occurrence in Corsica, a French Mediterranean island where the disease occurred for the first time in 2000. A set of environmental variables recorded in the neighborhood of 80 sheep farms were related to case occurrence through a logistic regression model computed within three subsequent buffer distances of 0.5, 1 and 2 km. The results reveal the role of landscape metrics, particularly those characterizing land-use units such as prairies and woodlands, as well as farm type, latitude and sunshine to explain the presence of bluetongue. Internal and external validation both indicate that the best results are obtained with the 1 km buffer size model (area under Receiver Operating Characteristic curve = 0.9 for internal validation and 0.81 for external validation). The results show that high spatial resolution remote sensing (i.e. 10 m pixels) and landscape ecology approaches contribute to improving the understanding of bluetongue epidemiology. PMID:17583664

  1. Spectral Diagnostics for Early-Type Stars in Support of High-Resolution Satellite Observation

    NASA Technical Reports Server (NTRS)

    MacFarlane, Joseph J.

    2001-01-01

    High-resolution X-ray spectra have recently been obtained using the Chandra X-ray Satellite Observatory for the two hot supergiant stars zeta Pup and delta Ori. The spectra show the presence of strong K-shell line emission from O, Ne, Mg, Si, and S, as well as strong L-shell line emission from Fe. Initial examination of the spectra indicates that the lines are significantly broader than what would be expected for a stationary plasma, and appear to be consistent with Doppler-broadened emission from hot plasma forming in shock-heated regions embedded in the wind (see Figure 1). Chandra has sufficient spectral resolution to study the velocity structure of isolated X-ray line profiles. Our analysis for zeta Pup has shown blue-shifted and skewed line profiles, providing the most direct evidence that the X-ray source is embedded in the stellar wind. The sensitivity of the He-like fir (forbidden-intercombination-resonance) lines to a strong UV radiation field is used to estimate the radial distances at which lines of O VII, Ne IX, Mg XI, Si XIII, and S XV originate.

  2. Obtaining Accurate Change Detection Results from High-Resolution Satellite Sensors

    NASA Technical Reports Server (NTRS)

    Bryant, N.; Bunch, W.; Fretz, R.; Kim, P.; Logan, T.; Smyth, M.; Zobrist, A.

    2012-01-01

    Multi-date acquisitions of high-resolution imaging satellites (e.g. GeoEye and WorldView), can display local changes of current economic interest. However, their large data volume precludes effective manual analysis, requiring image co-registration followed by image-to-image change detection, preferably with minimal analyst attention. We have recently developed an automatic change detection procedure that minimizes false-positives. The processing steps include: (a) Conversion of both the pre- and post- images to reflectance values (this step is of critical importance when different sensors are involved); reflectance values can be either top-of-atmosphere units or have full aerosol optical depth calibration applied using bi-directional reflectance knowledge. (b) Panchromatic band image-to-image co-registration, using an orthorectified base reference image (e.g. Digital Orthophoto Quadrangle) and a digital elevation model; this step can be improved if a stereo-pair of images have been acquired on one of the image dates. (c) Pan-sharpening of the multispectral data to assure recognition of change objects at the highest resolution. (d) Characterization of multispectral data in the post-image ( i.e. the background) using unsupervised cluster analysis. (e) Band ratio selection in the post-image to separate surface materials of interest from the background. (f) Preparing a pre-to-post change image. (g) Identifying locations where change has occurred involving materials of interest.

  3. Study on mosaic method for new mode satellite images with high spatial resolution covering urban areas

    NASA Astrophysics Data System (ADS)

    Ran, Qiong; Wang, Zhiyong; Wen, Qiang; Li, Wei; Gao, Lianru

    2014-11-01

    New imaging mode has been brought up for collecting multiple scenes in one pass, as is implemented on World View-II. This greatly helps for acquiring high spatial resolution images that cover urban areas, and is to be adopted in the coming Chinese satellites. This paper is to discuss the mosaic characteristic and propose a mosaic line generation method by integrating correlation and the road information. The mosaic line is formed by linking the unique mosaic point on each line restricted within the road. We position the starting point by connectivity analysis of the road lines, and then locate the adjacent point along the road with connectivity analysis. A weighed vector, combining correlation and distance to centre of the road, is used to pick the best point. The points are located on the road unless it is unavoidable, for example, the road ends or the line touches edge of the image. This method provides instant mosaic line generation for urban areas with road information available in most cases. By resorting to the road, the mosaic line is more applicable since many problems for mosaic of high spatial resolution images are solved, for example, tilting of the buildings, the shadows, motions of the vehicles etc. Experiments have been done with WV-II images and gained favorable results.

  4. Impact of Atmospheric Attenuations Time Resolutions in Solar Radiation Derived from Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Cony, Marco; Liria, Juan; Weisenberg, Ralf; Serrano, Enrique

    2014-05-01

    Accurate knowledge of solar irradiance components at the earth surface is of highly interest in many scientific and technology branches concerning meteorology, climate, agriculture and solar energy applications. In the specific case of solar energy systems the solar resource analysis with accuracy is a first step in every project since it is a required data for design, power output estimations, systems simulations and risk assessments. Solar radiation measurement availability is increasing both in spatial density and in historical archiving. However, it is still quite limited and most of the situations cannot make use of a long term ground database of high quality since solar irradiance is not generally measured where users need data. Satellite-derived solar radiation estimations are a powerful and valuable tool for solar resource assessment studies that have achieved a relatively high maturity due to years of developments and improvements. However, several sources of uncertainty are still present in satellite-derived methods. In particular, the strong influence of atmospheric attenuation information as input to the method is one of the main topics of improvement. Since solar radiation attenuation by atmospheric aerosols, and water vapor in a second place, is, after clouds, the second most important factor determining solar radiation, and particularly direct normal irradiance, the accurate knowledge of aerosol optical depth and water vapor content is relevant in the final output of satellite-derived methods. This present work, two different datasets we are used for extract atmospheric attenuation information. On the one hand the monthly mean values of the Linke turbidity factor from Meteotest database, which are twelve unique values of the Linke turbidity worldwide with a spatial resolution of 1/12º. On the other hand, daily values of AOD (Aerosol Optical Depth) at 550 nm, Angstrom alpha exponent and water vapor column were taken from a gridded database that

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  6. Estimating percent surface-water area using intermediate resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Ji, L.; Wylie, B.; Rover, J.

    2008-12-01

    Intermediate spatial resolution satellite data, such as Landsat TM/ETM+, have been used widely for mapping surface-water bodies at regional and national scales. Accurate estimation of surface-water area, however, still remains a challenge because the intermediate resolution images are not capable of detecting very small lakes, ponds, and streams that are usually predominant in wetland regions. To compensate for the limitations of the intermediate resolution images for mapping small water bodies, a fuzzy classification method can be used to estimate the water area proportion at pixel level and produce the map of continuous percent water area. But generally, fuzzy classifications require a large number of field training sites. In the studies of using the Landsat images to map water features for the Yukon River Basin (YRB) and the Prairie Pothole Region (PPR), we developed a regression-based fuzzy classification technique that is capable of collecting training data from the Landsat image itself. In the regression model, the predictor variables are the averaged reflectance of the 5- by 5-pixels (150- by 150-m) window for all Landsat spectral bands; the response variable is the percent water area calculated based on the number of water and non-water pixels within same window. The regression model based on the 150- by 150-m windows is then applied to the 30-m resolution Landsat image to estimate percent water area for every 30-m pixel in the image. As a result, the water feature map produced using the regression method shows the continuous percent water area at the 30-m level. In the examples of YRB and PPR, the regression models showed very high goodness-of-fit: the R- squares are 0.96 and 0.94, respectively, and root mean squared errors are 7.1% and 8.2%, respectively, for the two regions. To validate this technique, we will use the high spatial resolution QuickBird images (2.4 m at nadir for multispectral images) to derive relatively accurate percent water area, which

  7. Effect of different spatial resolution of satellite image to observe the forest condition using satellite image and National Forest Inventory data

    NASA Astrophysics Data System (ADS)

    Kajisa, T.; Mizoue, N.; Yoshida, S.

    2010-12-01

    One of the most substantial needs in forest management planning is information about the condition of the forest. Strategic decisions concerning timber policies, decisions about timing and spatial extent of forest operations, and operational decisions such as work plans are all examples where accurate information of the forest conditions are required. Landsat has played the important role for land cover observation in the past, but, got a serious problem. Currently, many kinds of satellite image are available to monitor land cover. So, the utility of different types of satellite image have to be evaluated for land cover monitoring. On the other hands, in Japan, National Forest Inventory (NFI) has been conducted since 1999 with the aim of understanding the state and dynamics of various aspects in forests such as wood production and biodiversity throughout the country. However, few studies have been conducted to combine the satellite image and NFI data. Therefore, the objective of this study was to evaluate the effect of different spatial resolution of satellite image to observe the forest condition (forest/non-forest, forest types, forest stand volume) using satellite image and NFI data.

  8. Using multi-satellite data fusion to estimate daily high spatial resolution evapotranspiration over a forested site in North Carolina

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Atmosphere-Land Exchange Inverse model and associated disaggregation scheme (ALEXI/DisALEXI). Satellite-based ET retrievals from both the Moderate Resolution Imaging Spectoradiometer (MODIS; 1km, daily) and Landsat (30m, bi-weekly) are fused with The Spatial and Temporal Adaptive Reflective Fusion ...

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

    NASA Astrophysics Data System (ADS)

    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.

  10. Efficient High-Rate Satellite Clock Estimation for PPP Ambiguity Resolution Using Carrier-Ranges

    PubMed Central

    Chen, Hua; Jiang, Weiping; Ge, Maorong; Wickert, Jens; Schuh, Harald

    2014-01-01

    In order to catch up the short-term clock variation of GNSS satellites, clock corrections must be estimated and updated at a high-rate for Precise Point Positioning (PPP). This estimation is already very time-consuming for the GPS constellation only as a great number of ambiguities need to be simultaneously estimated. However, on the one hand better estimates are expected by including more stations, and on the other hand satellites from different GNSS systems must be processed integratively for a reliable multi-GNSS positioning service. To alleviate the heavy computational burden, epoch-differenced observations are always employed where ambiguities are eliminated. As the epoch-differenced method can only derive temporal clock changes which have to be aligned to the absolute clocks but always in a rather complicated way, in this paper, an efficient method for high-rate clock estimation is proposed using the concept of “carrier-range” realized by means of PPP with integer ambiguity resolution. Processing procedures for both post- and real-time processing are developed, respectively. The experimental validation shows that the computation time could be reduced to about one sixth of that of the existing methods for post-processing and less than 1 s for processing a single epoch of a network with about 200 stations in real-time mode after all ambiguities are fixed. This confirms that the proposed processing strategy will enable the high-rate clock estimation for future multi-GNSS networks in post-processing and possibly also in real-time mode. PMID:25429413

  11. Opportunities for Monitoring Vegetation Structure in River Floodplains Using High-Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Kooistra, Lammert; Romijn, Erika; Verrelst, Jochem

    2010-12-01

    Managers of large river catchments like the Rhine require regular information on the development of the vegetation structure in the river floodplains. The objective of this study was to develop a methodology for monitoring the location and structure properties of plant functional types in a river floodplain ecosystem using satellite-based multi-directional hyperspectral data. In this study we used data from the CHRIS sensor onboard the PROBA satellite acquired in 2005 over the test site Millingerwaard, a river floodplain ecosystem along the river Waal in the Netherlands. CHRIS data are particularly suitable for mapping vegetation structure because of its high spatial resolution (~17 m), spectral coverage (18 bands from 400 nm to 1050 nm) and angular sampling (5 viewing angles). Relevant vegetation structure properties such as leaf area index (LAI) and fractional cover (fCover) were quantified on a pixel-by-pixel basis by using the radiative transfer model FLIGHT that simulates canopy bidirectional reflectance by using Monte Carlo ray tracing. After classification of the nadir image into eight major land use classes, for three main classified plant functional types "herbaceous", "shrubs" and "forest", LAI and fCover maps were computed through model inversion of the CHRIS data. All three vegetation classes were modeled as a turbid medium in the 1D mode. LAI and fCover maps were computed for the nadir viewing direction. In order to assess the quality of the inversion, the resulting vegetation structure maps were validated with in situ LAI measurements that were collected using hemispherical photography and TRAC measurements. As a next step it will be assessed whether the inferred structural maps can be related to hydraulic roughness models and thereby leading to catchment-level water discharge capacity maps which can be used as input for modeling of future climate scenarios.

  12. Efficient high-rate satellite clock estimation for PPP ambiguity resolution using carrier-ranges.

    PubMed

    Chen, Hua; Jiang, Weiping; Ge, Maorong; Wickert, Jens; Schuh, Harald

    2014-01-01

    In order to catch up the short-term clock variation of GNSS satellites, clock corrections must be estimated and updated at a high-rate for Precise Point Positioning (PPP). This estimation is already very time-consuming for the GPS constellation only as a great number of ambiguities need to be simultaneously estimated. However, on the one hand better estimates are expected by including more stations, and on the other hand satellites from different GNSS systems must be processed integratively for a reliable multi-GNSS positioning service. To alleviate the heavy computational burden, epoch-differenced observations are always employed where ambiguities are eliminated. As the epoch-differenced method can only derive temporal clock changes which have to be aligned to the absolute clocks but always in a rather complicated way, in this paper, an efficient method for high-rate clock estimation is proposed using the concept of "carrier-range" realized by means of PPP with integer ambiguity resolution. Processing procedures for both post- and real-time processing are developed, respectively. The experimental validation shows that the computation time could be reduced to about one sixth of that of the existing methods for post-processing and less than 1 s for processing a single epoch of a network with about 200 stations in real-time mode after all ambiguities are fixed. This confirms that the proposed processing strategy will enable the high-rate clock estimation for future multi-GNSS networks in post-processing and possibly also in real-time mode. PMID:25429413

  13. MCM'10: An Experiment for satellite Multispectral Crop Monitoring. From high to low resolution observations

    NASA Astrophysics Data System (ADS)

    Baup, F.; Fieuzal, R.; Marais-Sicre, C.; Dejoux, J. F.; le Dantec, V.; Mordelet, P.; Claverie, M.; Demarez, V.; Hagolle, O.; Lopes, A.; Keravec, P.; Ceschia, E.; Mialon, A.; Kidd, R.

    2012-04-01

    In a changing climate context, it becomes increasingly important to accurately estimate the physical processes involved in the surface-atmosphere interactions in order to predict climate changes and its impact on ecosystems. Increase of human pressure and changes in land use management contribute to alter water and energy budgets and carbon sequestration in the soils. Therefore, it is essential 1) to work towards a better understanding of the different processes governing water, carbon and energy exchanges between the continental biosphere in anthropised areas and the atmosphere, 2) to monitor land use, vegetation (crop) dynamics, soil and crop management. The aim of this presentation is to give an overview of the MCM'10 (Multispectral Crop Monitoring) experiment which has been conducted in 2010 (from February to November) by the CESBIO laboratory, in France. This experiment is based on the use of multispectral satellite acquisitions (radar, thermal and optical) and the associated ground measurements performed over about 400 agricultural fields located in the south west of France (43°29'36''N, 1°14'14''E). Optical data are acquired by FORMOSAT-2 and SPOT4-5 satellites. Radar data are provided by SAR sensors onboard TERRASAR-X (X-band), RADARSAT-2, ENVISAT (C-band) and ALOS (L-band). Thermal data come from the LANDSAT-TM 5 and 7 sensors. Low resolution data have been also collected to further study upscaling and downscaling approaches over a strongly heterogeneous landscape. Analyses of satellite data are performed by comparing them with ground data collected from local to regional scale. At the local scale, 37 fields are systematically monitored for each satellite overpass. Three of them are equipped with meteorological stations (radiations, water and carbon fluxes sensors…). Measures are performed over different soil types (clay, silt, gravels…) and for the main crops encountered in France and Europe (wheat, corn, sunflower, soybean, sorghum…). Soil

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

    NASA Technical Reports Server (NTRS)

    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

  15. Merging raster meteorological data with low resolution satellite images for improved estimation of actual evapotranspiration

    NASA Astrophysics Data System (ADS)

    Cherif, Ines; Alexandridis, Thomas; Chambel Leitao, Pedro; Jauch, Eduardo; Stavridou, Domna; Iordanidis, Charalampos; Silleos, Nikolaos; Misopolinos, Nikolaos; Neves, Ramiro; Safara Araujo, Antonio

    2013-04-01

    Actual evapotranspiration (ETa) can be estimated using Energy Balance models and remotely sensed data. In particular, satellite images acquired in visible, near and thermal infrared parts of the spectrum have been used with the Surface Energy Balance Algorithm for Land (SEBAL) to estimate actual evapotranspiration. This algorithm is solving the Energy Balance Equation using data from a meteorological station present in the vicinity, and assumes the meteorological conditions homogeneous over the study area. Most often, data from a representative weather station are used. This assumption may lead to substantial errors in areas with high spatial variability in weather parameters. In this paper, the ITA-MyWater algorithms (Integrated Thermodynamic Algorithms for MyWater project), an adaptation of SEBAL was merged together with spatially distributed meteorological data to increase the accuracy of ETa estimations at regional scale using MODIS satellite images. The major changes introduced to migrate from point to raster are that (i) air temperature and relative humidity maps are used for the estimation of the Energy Balance terms, including instantaneous net radiation and soil heat flux and (ii) the variability of wind speed is taken into account to generate maps of the aerodynamic resistance, sensible heat flux and difference between soil and air temperature at the boundary conditions (at dry and wet pixels). The approach was applied in the river basin of Tamega in Portugal, where actual evapotranspiration was estimated for several MODIS 8-day periods from spring to winter of the same year. The raster meteorological maps were produced by the MM5 weather forecast model. Daily reference evapotranspiration was calculated with MOHID LAND model. Using a temporal integration technique and the daily reference evapotranspiration maps, the cumulative evapotranspiration over the MODIS 8-day period was estimated and compared to the global evapotranspiration MODIS product (MOD16A2

  16. Improving stream temperature model predictions using high-resolution satellite-derived numerical weather forecasts

    NASA Astrophysics Data System (ADS)

    Pike, A.; Danner, E.; Lindley, S.; Melton, F. S.; Nemani, R. R.; Hashimoto, H.; Rajagopalan, B.; Caldwell, R. J.

    2009-12-01

    In the Central Valley of California, stream temperature is a critical indicator of habitat quality for endangered salmonid species and affects re-licensing of major water projects and dam operations worth billions of dollars. However, many water resource-related decisions in regulated rivers rely upon models using a daily-to-monthly mean temperature standard. Furthermore, current water temperature models are limited by the lack of spatially detailed meteorological forecasts. To address this issue, we utilize the coupled TOPS-WRF (Terrestrial Observation and Prediction System - Weather Research and Forecasting) framework—a high-resolution (15min, 1km) assimilation of satellite-derived meteorological observations and numerical weather forecasts— to improve the spatial and temporal resolution of stream temperature predictions. In this study, we developed a high-resolution mechanistic 1-dimensional stream temperature model (sub-hourly time step, sub-kilometer spatial resolution) for the Upper Sacramento River in northern California. The model uses a heat budget approach to calculate the rate of heat transfer to/from the river. Inputs for the heat budget formulation are atmospheric variables provided by the TOPS-WRF model. The hydrodynamics of the river (flow velocity and channel geometry) are characterized using densely-spaced channel cross-sections and flow data. Water temperatures are calculated by considering the hydrologic and thermal characteristics of the river and solving the advection-diffusion equation in a mixed Eulerian-Lagrangian framework. Modeled hindcasted temperatures for a test period (May - November 2008) substantially improve upon the existing daily-to-monthly mean temperature standards. Modeled values closely approximate both the magnitude and the phase of measured water temperatures. Furthermore, our model results reveal important longitudinal patterns in diel temperature variation that are unique to regulated rivers, and may be critical to

  17. The Role of Orograph and Parallax Corrections on High Resolution Geostationary Satellite Rainfall Estimates for Flash Flood Applications

    NASA Technical Reports Server (NTRS)

    Vicente, Gilberto A.; Davenport, Clay; Scofield, Rod

    1999-01-01

    The current generation of geosynchronous satellites exhibits considerably improved capabilities in the area of resolution, gridding accuracy, and sampling frequency as compared to their predecessors. These improvements have made it possible to accurately observe the life cycle of small scale, short-live phenomenon like rapidly developing thunderstorms, at a very high spatial and temporal resolutions. While the gain in the improved resolution is not significant for synoptic scale cloud systems, it plays a major role on the computation of precipitation values for mesoscale and stonn scale systems. Two of the important factor on the accurate precision of precipitation from satellite imagery are the position of the cloud tops as viewed by the satellite and the influence of orographic effects on the distribution of precipitation. The first problem has to do with the fact that the accurate estimation of precipitation from data collected by a satellite in geosynchronous orbit requires the knowledge of the exact position of the cloud tops with respect to the ground below. This is not a problem when a cloud is located directly below the satellite; at large viewing angles the geographic coordinates on satellite images are dependent on cloud heights and distance from the sub-satellite point. The latitude and longitude coordinates for high convective cloud tops are displaced away from the sub-satellite point and may be shifted by as much as 20 Km from the sea level coordinates. The second problem has to do with the variations in rainfall distribution with elevation. Ground observations have shown that precipitation amounts tend to increase with height and that the slope of the hill or mountain that is facing the prevailing wind normally receives greater rainfall then do the lee slopes. The purpose of the study is to show the recent developments at the Office of Research and Applications (ORA) at the National Oceanic and Atmospheric Administration (NOAA/NESDIS) in Camp Springs

  18. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

    NASA Astrophysics Data System (ADS)

    Turner, A. J.; Jacob, D. J.; Wecht, K. J.; Maasakkers, J. D.; Lundgren, E.; Andrews, A. E.; Biraud, S. C.; Boesch, H.; Bowman, K. W.; Deutscher, N. M.; Dubey, M. K.; Griffith, D. W. T.; Hase, F.; Kuze, A.; Notholt, J.; Ohyama, H.; Parker, R.; Payne, V. H.; Sussmann, R.; Sweeney, C.; Velazco, V. A.; Warneke, T.; Wennberg, P. O.; Wunch, D.

    2015-06-01

    We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a-1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a-1, as compared to 24.9-27.0 Tg a-1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a-1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern-central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29-44 % of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, 20 % to landfills/wastewater, and 11-15 % to coal. Wetlands contribute an additional 9.0-10.1 Tg a-1.

  19. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

    NASA Astrophysics Data System (ADS)

    Turner, A. J.; Jacob, D. J.; Wecht, K. J.; Maasakkers, J. D.; Biraud, S. C.; Boesch, H.; Bowman, K. W.; Deutscher, N. M.; Dubey, M. K.; Griffith, D. W. T.; Hase, F.; Kuze, A.; Notholt, J.; Ohyama, H.; Parker, R.; Payne, V. H.; Sussmann, R.; Velazco, V. A.; Warneke, T.; Wennberg, P. O.; Wunch, D.

    2015-02-01

    We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to constrain global and North American inversions of methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. The GOSAT data are first evaluated with atmospheric methane observations from surface networks (NOAA, TCCON) and aircraft (NOAA/DOE, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. The surface and aircraft data are subsequently used for independent evaluation of the methane source inversions. Our global adjoint-based inversion yields a total methane source of 539 Tg a-1 and points to a large East Asian overestimate in the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide full error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a-1, as compared to 24.9-27.0 Tg a-1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a-1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the South-Central US, the Central Valley of California, and Florida wetlands, large isolated point sources such as the US Four Corners also contribute. We attribute 29-44% of US anthropogenic methane emissions to livestock, 22-31% to oil/gas, 20% to landfills/waste water, and 11-15% to coal with an additional 9.0-10.1 Tg a-1 source from wetlands.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  1. Mapping forest fuels through vegetation phenology: the role of coarse-resolution satellite time-series.

    PubMed

    Bajocco, Sofia; Dragoz, Eleni; Gitas, Ioannis; Smiraglia, Daniela; Salvati, Luca; Ricotta, Carlo

    2015-01-01

    Traditionally fuel maps are built in terms of 'fuel types', thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250 m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000-2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies. PMID:25822505

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  3. Data fusion of high-resolution satellite imagery and GIS data for automatic building extraction

    NASA Astrophysics Data System (ADS)

    Guo, Z.; Luo, L.; Wang, W.; Du, S.

    2013-07-01

    Automatic building extraction in urban areas has become an intensive research as it contributes to many applications. High-resolution satellite (HRS) imagery is an important data source. However, it is a challenge task to extract buildings with only HRS imagery. Additional information and prior knowledge should be incorporated. c A new approach building extraction is proposed in this study. Data sources are QuickBird imagery and GIS data. The GIS data can provide prior knowledge including position and shape information, and the HRS image has rich spectral, texture features. To fuse these two kinds of features, the HRS image is first segmented into image objects. A graph is built according to the connectivity between the adjacent image objects. Second, the position information of GIS data is used to choose a seed region in the image for each GIS building object. Third, the seed region is grown by adding its neighbor regions constrained by the shape of GIS building. The performance is evaluated according to the manually delineated buildings. The results show performance of 0.142 in miss factor and detection percentage of 89.43% (correctness) and the overall quality of 79.35%.

  4. Riparian strip efficiency assessment in agricultural landscapes using stereoscopic very high spatial resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Chokmani, Karem; Novoa, Julio

    2015-04-01

    Riparian strips are used worldwide to protect riverbanks and water quality in agricultural zones because of their several environmental benefits. A metric called the Riparian Strip Quality Index, which is based on the percentage area of riverine vegetation found on the riparian strip, is used to evaluate their ecological condition. This index could be considered an indicator of the potential capacity of riparian strips to filter sediments, retain pollutants, and provide shelter to terrestrial and aquatic species. Thus, in order to know if a riparian strip is truly efficient in agricultural lands, which means that it is fulfilling those ecological functions, it is necessary to understand their ability to intercept surface runoff. The latter is the major cause of water pollution and erosion in these productive areas. Besides vegetation coverage, topographic and hydrologic parameters must be included to model the intensity and spatial distribution of runoff streamflow at local scales. The geospatial information used to assess the ecological efficiency of riparian strips was extracted from very-high-spatial-resolution WorldView-2 satellite imagery. This information was then processed using current geospatial techniques such as object-based image analysis and was used to develop a Riparian Strip Efficiency Index. The results show that this index might be used to assess the efficiency of riparian strips, which will enable land managers to monitor changes occurring over time, identify priority areas for restoration activities. This, in turn, might ensure optimal allocation of private or public funds towards the most inefficient and threatened riparian strips.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  6. Fully Automated Generation of Accurate Digital Surface Models with Sub-Meter Resolution from Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Wohlfeil, J.; Hirschmüller, H.; Piltz, B.; Börner, A.; Suppa, M.

    2012-07-01

    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.

  7. Geostatistical evaluation of satellite radar altimetry for high-resolution mapping of Lambert Glacier, Antarctica

    NASA Technical Reports Server (NTRS)

    Herzfeld, Ute C.; Lingle, Craig S.; Lee, Li-Her

    1993-01-01

    The potential of satellite radar altimetry for high-resolution mapping of Antarctic ice streams is evaluated, using retracked and slope-corrected data from the Lambert Glacier and Amery Ice Shelf area, East Antarctica, acquired by Geosat during the Exact Repeat Mission (ERM), 1986-89. The map area includes lower Lambert Glacier north of 72.18 deg S, the southern Amery Ice Shelf, and the grounded inland ice sheet on both sides. The Geosat ERM altimetry is found to provide substantially more complete coverage than the 1978 Seasat altimetry, due to improved tracking. Variogram methods are used to estimate the noise levels in the data as a function of position throughout the map area. The spatial structure in the data is quantified by constructing experimental variograms using altimetry from the area of the grounding zone of Lambert Glacier, which is the area chiefly of interest in this topographically complex region. Kriging is employed to invert the along-track height measurements onto a fine-scale 3 km grid. The unsmoothed along-track Geosat ERM altimetry yields spatially continuous maps showing the main topographic features of lower Lambert Glacier, upper Amery Ice Shelf and the adjacent inland ice sheet. The probable position of the grounding line of Lambert Glacier is identified from a break in slope at the grounded ice/floating ice transition. The approximate standard error of the kriged map is inferred from the data noise levels.

  8. Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series

    PubMed Central

    Bajocco, Sofia; Dragoz, Eleni; Gitas, Ioannis; Smiraglia, Daniela; Salvati, Luca; Ricotta, Carlo

    2015-01-01

    Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000–2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies. PMID:25822505

  9. Subjective evaluation of the combined influence of satellite temperature sounding data and increased model resolution on numerical weather forecasting

    NASA Technical Reports Server (NTRS)

    Atlas, R.; Halem, M.; Ghil, M.

    1979-01-01

    The present evaluation is concerned with (1) the significance of prognostic differences resulting from the inclusion of satellite-derived temperature soundings, (2) how specific differences between the SAT and NOSAT prognoses evolve, and (3) comparison of two experiments using the Goddard Laboratory for Atmospheric Sciences general circulation model. The subjective evaluation indicates that the beneficial impact of sounding data is enhanced with increased resolution. It is suggested that satellite sounding data posses valuable information content which at times can correct gross analysis errors in data sparse regions.

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

    NASA Astrophysics Data System (ADS)

    Behrangi, Ali

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

  11. Retrieving Forest Structure Variables from Very High Resolution Satellite Images Using AN Automatic Method

    NASA Astrophysics Data System (ADS)

    Beguet, B.; Chehata, N.; Boukir, S.; Guyon, D.

    2012-07-01

    The main goal of this study is to define a method to describe the forest structure of maritime pine stands from Very High Resolution satellite imagery. The emphasis is placed on the automatisation of the process to identify the most relevant image features, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features (derived from Grey Level Co-occurrence Matrix). The main drawback of this well- known texture representation is the underlying parameters (window size, displacement length, orientation and quantification level) which are extremely difficult to set due to the spatial complexity of forest structure. To tackle this major issue, probably the main cause of poor texture analysis in practice, we propose an automatic feature selection process whose originality lies on the use of image test frames of adequate forest samples whose forest structure variables were measured at ground. This method, inspired by camera calibration protocols, selects the best image features via statistical modelling, exploring a wide range of parameter values. Hence, just a few samples are required to build up the test frames but allow a fast assessment of thousands of descriptors, given the large number of tested combinations of parameters values. This method was developed and tested on Quickbird panchromatic and multispectral images. It has been successfully applied to the modelling of 7 typical forest structure variables (age, tree height, crown diameter, diameter at breast height, basal area, density and tree spacing). The coefficient of correlation, R2, of the best single models for 6 of the forest variables of interest, estimated from the test frames, ranges from 0.89 to 0.97. Only the basal area was weakly correlated to the considered image features (0.64). To improve the results, combinations of panchromatic and or multi-spectral features

  12. Assessing change in the earth's land surface albedo with moderate resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Sun, Qingsong

    Land surface albedo describes the proportion of incident solar radiant flux that is reflected from the Earth's surface and therefore is a crucial parameter in modeling and monitoring attempts to capture the current climate, hydrological, and biogeochemical cycles and predict future scenarios. Due to the temporal variability and spatial heterogeneity of land surface albedo, remote sensing offers the only realistic method of monitoring albedo on a global scale. While the distribution of bright, highly reflective surfaces (clouds, snow, deserts) govern the vast majority of the fluctuation, variations in the intrinsic surface albedo due to natural and human disturbances such as urban development, fire, pests, harvesting, grazing, flooding, and erosion, as well as the natural seasonal rhythm of vegetation phenology, play a significant role as well. The development of times series of global snow-free and cloud-free albedo from remotely sensed observations over the past decade and a half offers a unique opportunity to monitor and assess the impact of these alterations to the Earth's land surface. By utilizing multiple satellite records from the MODerate-resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging Spectroradiometer (MISR) and the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments, and developing innovative spectral conversion coefficients and temporal gap-filling strategies, it has been possible to utilize the strengths of the various sensors to improve the spatial and temporal coverage of global land surface albedo retrievals. The availability of these products is particularly important in tropical regions where cloud cover obscures the forest for significant periods. In the Amazon, field ecologists have noted that some areas of the forest ecosystem respond rapidly with foliage growth at the beginning of the dry season, when sunlight can finally penetrate fully to the surface and have suggested this phenomenon can continue until

  13. Small-Scale Fronts in Ultra-High Resolution Level-4 Satellite SST: Validation and Implications

    NASA Astrophysics Data System (ADS)

    Chen, H.; McKinley, G. A.

    2014-12-01

    Submesoscale oceanic fronts have been implicated in the turbulent energy cascade, and in nutrient supply into and carbon export out of the euphotic zone. However, their large-scale extent is unknown due to their characteristic small spatial (1-10km) and short time (~1 day) scales that complicate observations. Current large-scale understanding of fronts from satellite SST and ocean color is limited to a climatological view of occurrence frequency in cloud-free events. We show that useful estimates of frontal spatial coverage and structure can be derived from the recently available, merged satellite Level-4 SST product (G1SST at 1km resolution) using a gradient-based detection method in the North Atlantic subtropical gyre (28o-38oN, -75o- -45oW ). G1SST fronts are validated with in-situ fronts in continuous ship measurements from the Oleander Project. At a matching distance of Δx=5km, 79% of the G1SST fronts are in-situ fronts, and 64% of the in-situ fronts are detected by G1SST; these matches up increase with larger Δx. Comparing with in-situ velocities, ~56% of the fronts are coincident with across-track velocity jets with low-pass filter at scales > 5km,and 70% at scales > 50km, indicating that fronts are in large-scale geostrophic balance. Near-surface vertical shear predicted from thermal-wind relationship is in-phase but much smaller than (<50%) observed shear, indicating large ageostrophic shear is inclined to be co-located with surface baroclinic zones, likely due to interaction between fronts and gravity waves. For the North Atlantic subtropical gyre, we find that submesoscale fronts comprise 57±4.6% of the total surface area. Fronts are found not only in the energetic Gulf Steam region, but also are surprisingly numerous in the quiescent subtropical gyre. This finding is consistent with previous modeling studies that indicate that submesoscale fronts could help to resolve the 'nutrient--primary production' balance in oligotrophic regions.

  14. Surface solar radiation variability over Eastern Mediterranean: A high spatial resolution view from satellite and ground-based observations

    NASA Astrophysics Data System (ADS)

    Alexandri, Georgia; Georgoulias, Aristeidis K.; Meleti, Charikleia; Balis, Dimitris

    2013-04-01

    Surface Solar Radiation (SSR) has been measured for decades from ground-based observations for several spots around the planet. On the other hand, during the last decades, satellite observations made possible the assessment of the spatial variability of the SSR at a global as well as regional scale. In this study, a detailed view of the SSR spatiotemporal variability is presented at a high spatial resolution, focusing on the region of Eastern Mediterranean. This is a region of particular interest since it is affected by aerosols of various origins (continental, sea, dust and biomass burning particles) and encloses countries with significant socioeconomical changes during the last decades. The SSR satellite data used in this study have been obtained from the Satellite Application Facility on Climate Monitoring (CM SAF) (www.cmsaf.eu). The CM SAF SSR dataset is based on reflections in the visible channel of Meteosat First Generation, has a spatial resolution of 0.03ox0.03o and spans from 1983 to 2005. The satellite observations are validated against ground-based measurements for the city of Thessaloniki, a coastal city of ~1 million inhabitants in northern Greece, situated in the heart of Eastern Mediterranean. Measurements from two pyranometers, an Eppley Precision pyranometer (1983-1992) and a Kipp & Zonen CM-11 pyranometer (1993-2005), both located at the center of the city, were homogenized and a uniform time series for the 23 year period was constructed. SSR was also calculated with the use of MODIS level-2 aerosol and cloud satellite data for the region of Thessaloniki and the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. These new satellite-based results are compared to both CM SAF and ground-based observations in order to examine whether SBDART and MODIS could be further used for the investigation of the spatial patterns of SSR in the area.

  15. Shoreline Tracing Using Medium to High-Resolution Satellite Images for Storm Surge Modelling

    NASA Astrophysics Data System (ADS)

    Ladiero, C.; Lagmay, A. M. A.; Santiago, J. T.; Suarez, J. K. B.; Puno, J. V.; Bahala, M. A.

    2014-12-01

    In a developing country like Philippines, which ranks fourth in the longest coastline in the world at 36 289 kilometers, acquiring an updated and finer shoreline at the municipal level is mostly scarce. Previous studies have emphasized the importance of accurately delineating shoreline in coastal management, engineering design, sea-level rise research, coastal hazard map development, boundary definition, coastal change research and monitoring and numerical models. In the context of storm surge modelling, shoreline boundary serves as basis for tidal conditions and requires to be well-defined to generate an accurate simulation result. This paper presents the cost-effective way of shoreline tracing employed by the Storm Surge component under the Department of Science and Technology-Nationwide Operational Assessment of Hazards (DOST-Project NOAH) for use in modelling storm surge hazards in the country, particularly in San Pedro Bay during the Typhoon Haiyan. Project NOAH was tasked to conduct disaster science research and development and recommend innovative information services in government's disaster prevention and mitigation efforts through cutting edge technologies. The Storm Surge component commenced in September 2013 and was mandated by the Philippine government to identify storm surge vulnerable areas and provide high-resolution maps of storm surge inundation in the localities. In the absence of LIDAR data at the time, the Project utilized the freely available medium to high resolution satellite images of Google Earth and digitized the shoreline. To minimize subjectivity, set of digitizing standards were developed for classifying common shoreline features in the country, differentiating image textures and colors and tabulating identified shoreline features. After which, the digitized shoreline were quality checked and corrected for topology using ArcGIS Desktop 10 software. The final output is a vector data that served as boundary for topo-bathy extraction

  16. Improving surface-subsurface water budgeting for Brownfield study sites using high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Dujardin, J.; Boel, S.; Anibas, C.; Batelaan, O.; Canters, F.

    2009-04-01

    Countries around the world have problems with contaminated brownfield sites as resulting from a relatively anarchic economical and industrial development during the 19th and 20th centuries. Since a few decades policy makers and stakeholders have become more aware of the risk posed by these sites because some of these sites present direct public hazards. Water is often the main vector of the mobility of contaminants. In order to propose remediation measures for the contaminated sites, it is required to describe and to quantify as accurately as possible the surface and subsurface water fluxes in the polluted site. In this research a modelling approach with integrated remote sensing analysis has been developed for accurately calculating water and contaminant fluxes on the polluted sites. Groundwater pollution in urban environments is linked to patterns of land use, so to identify the sources of contamination with great accuracy in urban environments it is essential to characterize the land cover in a detailed way. The use of high resolution spatial information is required because of the complexity of the urban land use. An object-oriented classification approach applied on high resolution satellite data has been adopted. Cluster separability analysis and visual interpretation of the image objects belonging to each cluster resulted in the selection of 8 land-cover categories (water, bare soil, meadow, mixed forest, grey urban surfaces, red roofs, bright roofs and shadow).To assign the image objects to one of the 8 selected classes a multiple layer perceptron (MLP) approach was adopted, using the NeuralWorks Predict software. After a post-classification shadow removal and a rule-based classification enhancement a kappa-value of 0.86 was obtained. Once the land cover was characterized, the groundwater recharge has been simulated using the spatially distributed WetSpass model and the subsurface water flow was simulated with GMS 6.0 in order to identify and budget the

  17. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

    DOE PAGESBeta

    Turner, A. J.; Jacob, D. J.; Wecht, K. J.; Maasakkers, J. D.; Biraud, S. C.; Boesch, H.; Bowman, K. W.; Deutscher, N. M.; Dubey, M. K.; Griffith, D. W. T.; et al

    2015-02-18

    We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to constrain global and North American inversions of methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. The GOSAT data are first evaluated with atmospheric methane observations from surface networks (NOAA, TCCON) and aircraft (NOAA/DOE, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. The surface and aircraft data are subsequently usedmore » for independent evaluation of the methane source inversions. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 and points to a large East Asian overestimate in the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide full error characterization. We infer a US anthropogenic methane source of 40.2–42.7 Tg a−1, as compared to 24.9–27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0–44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the South-Central US, the Central Valley of California, and Florida wetlands, large isolated point sources such as the US Four Corners also contribute. We attribute 29–44% of US anthropogenic methane emissions to livestock, 22–31% to oil/gas, 20% to landfills/waste water, and 11–15% to coal with an additional 9.0–10.1 Tg a−1 source from wetlands.« less

  18. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

    DOE PAGESBeta

    Turner, A. J.; Jacob, D. J.; Wecht, K. J.; Maasakkers, J. D.; Lundgren, E.; Andrews, A. E.; Biraud, S. C.; Boesch, H.; Bowman, K. W.; Deutscher, N. M.; et al

    2015-06-30

    We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a totalmore » methane source of 539 Tg a−1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2–42.7 Tg a−1, as compared to 24.9–27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0–44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern–central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29–44 % of US anthropogenic methane emissions to livestock, 22–31 % to oil/gas, 20 % to landfills/wastewater, and 11–15 % to coal. Wetlands contribute an additional 9.0–10.1 Tg a−1.« less

  19. Improving surface-subsurface water budgeting using high resolution satellite imagery applied on a brownfield.

    PubMed

    Dujardin, J; Batelaan, O; Canters, F; Boel, S; Anibas, C; Bronders, J

    2011-01-15

    The estimation of surface-subsurface water interactions is complex and highly variable in space and time. It is even more complex when it has to be estimated in urban areas, because of the complex patterns of the land-cover in these areas. In this research a modeling approach with integrated remote sensing analysis has been developed for estimating water fluxes in urban environments. The methodology was developed with the aim to simulate fluxes of contaminants from polluted sites. Groundwater pollution in urban environments is linked to patterns of land use and hence it is essential to characterize the land cover in a detail. An object-oriented classification approach applied on high-resolution satellite data has been adopted. To assign the image objects to one of the land-cover classes a multiple layer perceptron approach was adopted (Kappa of 0.86). Groundwater recharge has been simulated using the spatially distributed WetSpass model and the subsurface water flow using MODFLOW in order to identify and budget water fluxes. The developed methodology is applied to a brownfield case site in Vilvoorde, Brussels (Belgium). The obtained land use map has a strong impact on the groundwater recharge, resulting in a high spatial variability. Simulated groundwater fluxes from brownfield to the receiving River Zenne were independently verified by measurements and simulation of groundwater-surface water interaction based on thermal gradients in the river bed. It is concluded that in order to better quantify total fluxes of contaminants from brownfields in the groundwater, remote sensing imagery can be operationally integrated in a modeling procedure. PMID:21112074

  20. Towards an automated monitoring of human settlements in South Africa using high resolution SPOT satellite imagery

    NASA Astrophysics Data System (ADS)

    Kemper, T.; Mudau, N.; Mangara, P.; Pesaresi, M.

    2015-04-01

    Urban areas in sub-Saharan Africa are growing at an unprecedented pace. Much of this growth is taking place in informal settlements. In South Africa more than 10% of the population live in urban informal settlements. South Africa has established a National Informal Settlement Development Programme (NUSP) to respond to these challenges. This programme is designed to support the National Department of Human Settlement (NDHS) in its implementation of the Upgrading Informal Settlements Programme (UISP) with the objective of eventually upgrading all informal settlements in the country. Currently, the NDHS does not have access to an updated national dataset captured at the same scale using source data that can be used to understand the status of informal settlements in the country. This pilot study is developing a fully automated workflow for the wall-to-wall processing of SPOT-5 satellite imagery of South Africa. The workflow includes an automatic image information extraction based on multiscale textural and morphological image features extraction. The advanced image feature compression and optimization together with innovative learning and classification techniques allow a processing of the SPOT-5 images using the Landsat-based National Land Cover (NLC) of South Africa from the year 2000 as low-resolution thematic reference layers as. The workflow was tested on 42 SPOT scenes based on a stratified sampling. The derived building information was validated against a visually interpreted building point data set and produced an accuracy of 97 per cent. Given this positive result, is planned to process the most recent wall-to-wall coverage as well as the archived imagery available since 2007 in the near future.

  1. Using Image Segmentation to Identify Tundra Vegetation Variability in High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Lazow, Z.; Roemke, L.; Loranty, M. M.

    2014-12-01

    Arctic tundra ecosystems will play an important role in the global carbon cycle in coming decades and centuries. Amplified climate warming at high northern latitudes has stimulated carbon uptake via plant productivity, while thawing permafrost is releasing carbon to the atmosphere. Accurately quantifying the effect of changing tundra ecosystems on global climate will require detailed understanding of both of these processes. In this context, accounting for the spatial variation of landscape features is critical to creating carbon budgets for ecosystems and regions, and for forecasting the effects of climate change in the tundra. Water tracks and other areas that feature channelized subsurface water flow are landscape features with distinct differences in carbon stocks and fluxes relative to adjacent upland tundra areas. Numerous studies have shown that water tracks and flowpaths have greater water and nutrient availability that leads relatively high carbon stocks and rates of carbon uptake. However a clear understanding of the relative proportion of tundra ecosystems that are comprised of these landscape features is lacking. Recently developed fine-scale remote sensing technology allows for the spatial analysis of tundra landscapes and specifically water tracks. This study automates process of distinguishing water tracks through the use of image classification and segmentation techniques on high-resolution satellite imagery. Both supervised and unsupervised classification techniques identify water tracks as distinctive and tundra landscape features. Unlike the unsupervised classification, edge detection and region-thresholding algorithms in the supervised classification differentiates water tracks from locations with high productivity by assessing connectivity shape. Depending on the area of inquiry, water tracks comprise roughly 10%-25% of the landscape. Field observations indicate that water tracks have greater plant productivity, and rates of carbon cycling

  2. River pollution remediation monitored by optical and infrared high-resolution satellite images.

    PubMed

    Trivero, Paolo; Borasi, Maria; Biamino, Walter; Cavagnero, Marco; Rinaudo, Caterina; Bonansea, Matias; Lanfri, Sofia

    2013-09-01

    The Bormida River Basin, located in the northwestern region of Italy, has been strongly contaminated by the ACNA chemical factory. This factory was in operation from 1892 to 1998, and contamination from the factory has had deleterious consequences on the water quality, agriculture, natural ecosystems and human health. Attempts have been made to remediate the site. The aims of this study were to use high-resolution satellite images combined with a classical remote sensing methodology to monitor vegetation conditions along the Bormida River, both upstream and downstream of the ACNA chemical factory site, and to compare the results obtained at different times before and after the remediation process. The trends of the Normalised Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) along the riverbanks are used to assess the effect of water pollution on vegetation. NDVI and EVI values show that the contamination produced by the ACNA factory had less severe effects in the year 2007, when most of the remediation activities were concluded, than in 2006 and 2003. In 2007, the contamination effects were noticeable up to 6 km downstream of the factory, whereas in 2003 and 2006 the influence range was up to about 12 km downstream of the factory. The results of this study show the effectiveness of remediation activities that have been taking place in this area. In addition, the comparison between NDVI and EVI shows that the EVI is more suitable to characterise the vegetation health and can be considered an additional tool to assess vegetation health and to monitor restoration activities. PMID:23456221

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  5. Using High Resolution Satellite Imagery to Map Black Mangrove on the Texas Gulf Coast

    Technology Transfer Automated Retrieval System (TEKTRAN)

    QuickBird false color satellite imagery was evaluated for distinguishing black mangrove [Avicennia germinans (L.) L.] populations on the south Texas Gulf Coast. The imagery had three bands (green, red, and near-infrared) and contained 11-bit data. Two subsets of the satellite image were extracted ...

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  7. A multi-resolution satellite imagery approach for large area mapping of ericaceous shrubs in Northern Quebec, Canada

    NASA Astrophysics Data System (ADS)

    van Lier, Olivier R.; Fournier, Richard A.; Bradley, Robert L.; Thiffault, Nelson

    2009-10-01

    Invasive ericaceous shrubs (e.g. Kalmia angustifolia, Rhododendron groenlandicum, Vaccinium spp.) may reduce the regeneration and early growth of black spruce ( Picea mariana) seedlings, the most economically important boreal tree species in Quebec. Our study focused, therefore, on developing a method for mapping ericaceous shrubs from satellite images. The method integrates very high resolution satellite imagery (IKONOS) to guide classifiers applied to medium resolution satellite imagery (Landsat-TM). An object-oriented image classification approach was applied using Definiens eCognition software. An independent ground survey revealed 80% accuracy at the very high spatial resolution. We found that the partial use (70%) of classified polygons derived from the IKONOS images were an effective way to guide classification algorithms applied to the Landsat-TM imagery. The results of this latter classification (78.4% overall accuracy) were assessed by the remaining portion (30%) of unused very high resolution classified polygons. We further validated our method (65.5% overall accuracy) by assessing the correspondence of an ericaceous cover classification scheme done with a Landsat-TM image and results of our ground survey using an independent set of 275 sample plots. Discrimination of ericaceous shrub cover from other land cover types was achieved with precision at both spatial resolutions with producer accuracies of 87.7% and 79.4% from IKONOS and Landsat, respectively. The method is weaker for areas with sparse cover of ericaceous shrubs or dense tree cover. Our method is adapted, therefore, for mapping the spatial distribution of ericaceous shrubs and is compatible with existing forest stand maps.

  8. Cold climate mapping using satellite high resolution thermal imagery. [weather forecasting improvement

    NASA Technical Reports Server (NTRS)

    Bartholic, J. F.; Sutherland, R. A.

    1977-01-01

    In an attempt to improve cold climate mapping and freeze forecasting techniques, thermal imagery from the NOAA-2 and -3 satellites and the Synchronous Meteorological Satellite (SMS) were obtained and analyzed. Enhanced image transparencies showed detailed temperature patterns over the peninsula of Florida. The analysis was superior to hand-drawn isotherms drawn from the 300 to 500 thermograph stations presently in use. Satellite data on several cold nights with similar synoptic conditions showed that similar cold patterns existed. Thus, cold climate mapping is possible.

  9. Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method

    NASA Astrophysics Data System (ADS)

    Brovelli, Maria Antonia; Crespi, Mattia; Fratarcangeli, Francesca; Giannone, Francesca; Realini, Eugenio

    Interest in high-resolution satellite imagery (HRSI) is spreading in several application fields, at both scientific and commercial levels. Fundamental and critical goals for the geometric use of this kind of imagery are their orientation and orthorectification, processes able to georeference the imagery and correct the geometric deformations they undergo during acquisition. In order to exploit the actual potentialities of orthorectified imagery in Geomatics applications, the definition of a methodology to assess the spatial accuracy achievable from oriented imagery is a crucial topic. In this paper we want to propose a new method for accuracy assessment based on the Leave-One-Out Cross-Validation (LOOCV), a model validation method already applied in different fields such as machine learning, bioinformatics and generally in any other field requiring an evaluation of the performance of a learning algorithm (e.g. in geostatistics), but never applied to HRSI orientation accuracy assessment. The proposed method exhibits interesting features which are able to overcome the most remarkable drawbacks involved by the commonly used method (Hold-Out Validation — HOV), based on the partitioning of the known ground points in two sets: the first is used in the orientation-orthorectification model (GCPs — Ground Control Points) and the second is used to validate the model itself (CPs — Check Points). In fact the HOV is generally not reliable and it is not applicable when a low number of ground points is available. To test the proposed method we implemented a new routine that performs the LOOCV in the software SISAR, developed by the Geodesy and Geomatics Team at the Sapienza University of Rome to perform the rigorous orientation of HRSI; this routine was tested on some EROS-A and QuickBird images. Moreover, these images were also oriented using the world recognized commercial software OrthoEngine v. 10 (included in the Geomatica suite by PCI), manually performing the LOOCV

  10. Semi-automatic building extraction in informal settlements from high-resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Mayunga, Selassie David

    The extraction of man-made features from digital remotely sensed images is considered as an important step underpinning management of human settlements in any country. Man-made features and buildings in particular are required for varieties of applications such as urban planning, creation of geographical information systems (GIS) databases and Urban City models. The traditional man-made feature extraction methods are very expensive in terms of equipment, labour intensive, need well-trained personnel and cannot cope with changing environments, particularly in dense urban settlement areas. This research presents an approach for extracting buildings in dense informal settlement areas using high-resolution satellite imagery. The proposed system uses a novel strategy of extracting building by measuring a single point at the approximate centre of the building. The fine measurement of the building outlines is then effected using a modified snake model. The original snake model on which this framework is based, incorporates an external constraint energy term which is tailored to preserving the convergence properties of the snake model; its use to unstructured objects will negatively affect their actual shapes. The external constrained energy term was removed from the original snake model formulation, thereby, giving ability to cope with high variability of building shapes in informal settlement areas. The proposed building extraction system was tested on two areas, which have different situations. The first area was Tungi in Dar Es Salaam, Tanzania where three sites were tested. This area is characterized by informal settlements, which are illegally formulated within the city boundaries. The second area was Oromocto in New Brunswick, Canada where two sites were tested. Oromocto area is mostly flat and the buildings are constructed using similar materials. Qualitative and quantitative measures were employed to evaluate the accuracy of the results as well as the performance

  11. Estimation of Land Surface Energy Balance Using Satellite Data of Spatial Reduced Resolution

    NASA Astrophysics Data System (ADS)

    Vintila, Ruxandra; Radnea, Cristina; Savin, Elena; Poenaru, Violeta

    2010-12-01

    The paper presents preliminary results concerning the monitoring at national level of several geo-biophysical variables retrieved by remote sensing, in particular those related to drought or aridisation. The study, which is in progress, represents also an exercise for to the implementation of a Land Monitoring Core Service for Romania, according to the Kopernikus Program and in compliance with the INSPIRE Directive. The SEBS model has been used to retrieve land surface energy balance variables, such as turbulent heat fluxes, evaporative fraction and daily evaporation, based on three information types: (1) surface albedo, emissivity, temperature, fraction of vegetation cover (fCover), leaf area index (LAI) and vegetation height; (2) air pressure, temperature, humidity and wind speed at the planetary boundary layer (PBL) height; (3) downward solar radiation and downward longwave radiation. AATSR and MERIS archived reprocessed images have provided several types of information. Thus, surface albedo, emissivity, and land surface temperature have been retrieved from AATSR, while LAI and fCover have been estimated from MERIS. The vegetation height has been derived from CORINE Land Cover and PELCOM Land Use databases, while the meteorological information at the height of PBL have been estimated from the measurements provided by the national weather station network. Other sources of data used during this study have been the GETASSE30 digital elevation model with 30" spatial resolution, used for satellite image orthorectification, and the SIGSTAR-200 geographical information system of soil resources of Romania, used for water deficit characterisation. The study will continue by processing other AATSR and MERIS archived images, complemented by the validation of SEBS results with ground data collected on the most important biomes for Romania at various phenological stages, and the transformation of evaporation / evapotranspiration into a drought index using the soil texture

  12. Crop Area Estimation Using High Spatial Resolution Satellite Imagery and Area Frame Sampling

    NASA Astrophysics Data System (ADS)

    Marshall, M. T.; Husak, G. J.; Pedreros, D.; Alcaraz v., G.

    2006-12-01

    The amount and extent of cropped area are essential parameters for determining food production and ultimately the state of food security in developing countries. Crop area estimation endeavors at the national- level are limited especially in remote areas of the world, due in part to the cost and time of making ground observations. Approximation of crop area using satellite imagery is a viable alternative though few studies have made use of this technique. In previous studies, misclassification of pure pixels and the presence of mixed pixels in relatively coarse Landsat images led to considerable errors in crop area estimates. This is particularly the case in developing countries where small subsistence farms are more prominent than larger mechanized farms. The aim of this study was to develop regression estimators from interpretation of 0.61 and 1 m resolution Quickbird and Ikonos panchromatic imagery respectively, to reduce bias in the crop area assessment from 30 m Landsat ETM+ images taken during the 2005 growing season of Niger. Eighty-five Ikonos and Quickbird scenes randomly stratified along the six primary livelihood zones of Niger and 30 Landsat ETM+ scenes were used to meet three objectives: 1) comprehensive dot-grid (2 km interval) classification of Landsat data for all potential cropped areas, 2) dot-grid (500 m interval) classification of Ikonos and Quickbird data for subsets of Landsat scenes, 3) area frame bias-estimation for each livelihood zone, and 4) validation of model design and process. Percent cropped area from Quickbird and Ikonos images showed high and significant correlations with percent cropped area from Landsat ETM+ for each livelihood zone. A split sample validation of the regression estimators and relative efficiency of the process shows potential to be used in other developing countries. Future studies should attempt to develop regression estimators involving automated textural-based classification techniques (e.g. image segmentation

  13. The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products

    NASA Technical Reports Server (NTRS)

    Huang, Dong; Yang, Wenze; Tan, Bin; Rautiainen, Miina; Zhang, Ping; Hu, Jiannan; Shabanov, Nikolay V.; Linder, Sune; Knyazikhin, Yuri; Myneni, Ranga B.

    2006-01-01

    The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.

  14. Object-oriented Markov random model for classification of high resolution satellite imagery based on wavelet transform

    NASA Astrophysics Data System (ADS)

    Hong, Liang; Liu, Cun; Yang, Kun; Deng, Ming

    2013-07-01

    The high resolution satellite imagery (HRSI) have higher spatial resolution and less spectrum number, so there are some "object with different spectra, different objects with same spectrum" phenomena. The objective of this paper is to utilize the extracted features of high resolution satellite imagery (HRSI) obtained by the wavelet transform(WT) for segmentation. WT provides the spatial and spectral characteristics of a pixel along with its neighbors. The object-oriented Markov random Model in the wavelet domain is proposed in order to segment high resolution satellite imagery (HRSI). The proposed method is made up of three blocks: (1) WT-based feature extrcation.the aim of extraction of feature using WT for original spectral bands is to exploit the spatial and frequency information of the pixels; (2) over-segmentation object generation. Mean-Shift algorithm is employed to obtain over-segmentation objects; (3) classification based on Object-oriented Markov Random Model. Firstly the object adjacent graph (OAG) can be constructed on the over-segmentation objects. Secondly MRF model is easily defined on the OAG, in which WT-based feature of pixels are modeled in the feature field model and the neighbor system, potential cliques and energy functions of OAG are exploited in the labeling model. Experiments are conducted on one HRSI dataset-QuickBird images. We evaluate and compare the proposed approach with the well-known commercial software eCognition(object-based analysis approach) and Maximum Likelihood(ML) based pixels. Experimental results show that the proposed the method in this paper obviously outperforms the other methods.

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

    NASA Astrophysics Data System (ADS)

    Wang, Shifeng; So, Emily; Smith, Pete

    2015-04-01

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

  16. a Class of Regression-Cum Estimators in Two-Phase Sampling for Utilizing Information from High Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Handique, B. K.

    2012-07-01

    Two-phase sampling design offers a variety of possibilities for effective use of auxiliary information such as those from high resolution remote sensing data. Continuous satellite data with large area coverage provide scope for deriving population values of the auxiliary variables, which can effectively be used for estimating the population parameters of the variable of interest. This study has been made to examine the possibilities of different forms of auxiliary information derived from remote sensing data in two-phase sampling design and suggest an appropriate estimator that will be of broad interest and applications. A new class of regression-cum-ratio estimators has been proposed for two-phase sampling using information on two auxiliary variables derived from high resolution satellite data. The bias and the mean square error (MSE) of the proposed estimators have been obtained up to first order approximation. Efficiency comparison of the proposed estimators has been made with some traditional estimators. The proposed estimator is found to be more efficient than the usual regression and ratio estimators. Numerical illustration has been carried out to examine the efficiency of the estimator in case of forest timber volume estimation utilizing tree crown diameter and tree height as auxiliary variables. It is shown that these estimators can be employed in a variety of conditions where there is strong correlation of satellite derived information with sample based ground measurements and when the cost of ground measurements is relatively high.

  17. OAFlux Satellite-Based High-Resolution Analysis of Air-Sea Turbulent Heat, Moisture, and Momentum Fluxes

    NASA Astrophysics Data System (ADS)

    Yu, Lisan

    2016-04-01

    The Objectively Analyzed air-sea Fluxes (OAFlux) project at the Woods Hole Oceanographic Institution has recently developed a new suite of products: the satellite-based high-resolution (HR) air-sea turbulent heat, moisture, and momentum fluxes over the global ocean from 1987 to the present. The OAFlux-HR fluxes are computed from the COARE bulk algorithm using air-sea variables (vector wind, near-surface humidity and temperature, and ocean surface temperature) derived from multiple satellite sensors and multiple missions. The vector wind time series are merged from 14 satellite sensors, including 4 scatterometers and 10 passive microwave radiometers. The near-surface humidity and temperature time series are retrieved from 11 satellite sensors, including 7 microwave imagers and 4 microwave sounders. The endeavor has greatly improved the depiction of the air-sea turbulent exchange on the frontal and meso-scales. The OAFlux-HR turbulent flux products are valuable datasets for a broad range of studies, including the study of the long-term change and variability in the oean-surface forcing functions, quantification of the large-scale budgets of mass, heat, and freshwater, and assessing the role of the ocean in the change and variability of the Earth's climate.

  18. Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

    PubMed Central

    Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

    2013-01-01

    Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorellamacquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

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

    PubMed

    Bricher, Phillippa K; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M

    2013-01-01

    Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6-96.3%, κ = 0.849-0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  1. A Gauge-Radar-Satellite Merged Analysis of High-Resolution Regional Precipitation over Eastern China: Preliminary Investigation

    NASA Astrophysics Data System (ADS)

    Luo, Y.; Zhao, F.; Shan, Q.; Yang, Z.; Xie, P.

    2011-12-01

    A new technique is being developed at the Zhejiang Meteorological Agency of China Meteorological Administration (CMA) to construct an hourly precipitation analysis over Zhejiang Province of China through merging information from multiple sources. The target precipitation analyses cover the eastern China province of ~100K km2 and its adjacent East China Sea at a very high resolution of 1km by 1km. The precipitation observations used as inputs to the merging system include gauge reports of hourly precipitation at over 1500 automatic stations, radar observations of precipitation, and CMORPH satellite-based estimates. First a gauge-based hourly precipitation analysis is produced on a 1kmx1km grid by interpolating station measurements with consideration of orographic effects. To this end, analyzed fields of hourly precipitation climatology is defined by interpolating gauge observations over a 30 years period from 1981 to 2010 and the adjusted to the PRISM monthly precipitation climatology to reflect the orographic effects. Gridded fields of the ratio between the total hourly precipitation and hourly climatology are then constructed by interpolating corresponding point values at nearby stations using the optimal interpolation (OI) technique. The hourly precipitation analysis is finally defined as the product of the interpolated ratio and the hourly climatology at the grid point. In this preliminary investigation, the high-resolution precipitation analysis is constructed for a 3-year period from 2009 to 2011 and used to examine the error structures of the hourly precipitation fields derived from radar observations and satellite estimates. While the radar and satellite-based precipitation estimates are capable of capturing overall time and space variations associated with major synoptic and meso-scale weather systems, both of them present bias and random error of substantial magnitude. The bias in the radar and satellite precipitation exhibits regional patterns as well as

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

    NASA Astrophysics Data System (ADS)

    Vassilev, Vassil

    2013-12-01

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

  3. High-resolution surface temperature patterns related to urban morphology in a tropical city: A satellite-based study

    SciTech Connect

    Nichol, J.E.

    1996-01-01

    High-resolution thermal data derived from Landsat`s thematic mapper are evaluated for their correspondence to building geometry and landscape features in Singapore`s high-rise housing estates. The image data are sufficiently detailed to reveal that differences in solar azimuth on images taken at different times of year create different thermal patterns due to building geometry and surface materials. Field measurements of surface and adjacent air temperatures in urban canyons at different orientations and at different elevations above ground demonstrate that for Singapore conditions satellite-derived surface temperature patterns are a good indicator of the daytime urban heat island. 18 refs., 11 figs., 2 tabs.

  4. A new map of the vegetation of central European Russia based on high-resolution satellite data.

    PubMed

    Ershov, D V; Gavrilyuk, E A; Karpukhina, D A; Kovganko, K A

    2015-01-01

    The scientific basis of and approaches to regional thematic mapping of vegetation based on high-resolution satellite data have been elaborated. A vegetation map of central European Russia has been compiled. The map includes 12 thematic classes, six of which pertain to forest ecosystems. The map has been compared to the data of the GFC project (University of Maryland, United States) and the official data of the Rosstat Federal Service of State Statistics (Russia). The new vegetation map is currently used in the information system of the remote monitoring of forest fires in Russia. PMID:26530069

  5. Large scale telescopes for high resolution X-ray and gamma-ray astronomy. [using widely separated satellites

    NASA Technical Reports Server (NTRS)

    Hudson, H. S.; Lin, R. P.

    1978-01-01

    This paper shows that angular-resolution, energy-range, and structural constraints on image-modulated X-ray telescopes are not fundamental and that the limits on angular resolution can be overcome by constructing such telescopes on a very large spatial scale. It is proposed that widely separated satellites be used for the modulating mask and detector array. Implementation of this concept is discussed in terms of a simple system consisting of a pinhole camera (i.e., a hole in an opaque mask on one subsatellite and a detector array on another). Advantages and problems of such systems are briefly discussed, and a solar X-ray telescope intended for deployment from a Shuttle orbiter is described. It is noted that such large-scale telescopes can be constructed to image gamma rays and even energetic neutrons as well.

  6. Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

    NASA Astrophysics Data System (ADS)

    Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

    2012-12-01

    Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent

  7. Reducing Uncertainties in Satellite-derived Forest Aboveground Biomass Estimates using a High Resolution Forest Cover Map

    NASA Astrophysics Data System (ADS)

    Zhang, G.; Ganguly, S.; Nemani, R. R.; Milesi, C.; Basu, S.; Kumar, U.

    2014-12-01

    Several studies to date have provided an extensive knowledge base for estimating forest aboveground biomass (AGB) and recent advances in space-based modeling of the 3-D canopy structure, combined with canopy reflectance measured by passive optical sensors and radar backscatter, are providing improved satellite-derived AGB density mapping for large scale carbon monitoring applications. A key limitation in forest AGB estimation from remote sensing, however, is the large uncertainty in forest cover estimates from the coarse-to-medium resolution satellite-derived land cover maps (present resolution is limited to 30-m of the USGS NLCD Program). The uncertainties in forest cover estimates at the Landsat scale result in high uncertainties for AGB estimation, predominantly in heterogeneous forest and urban landscapes. We have successfully developed an approach using a machine learning algorithm and High-Performance-Computing with NAIP air-borne imagery data for mapping tree cover at 1-m over California and Maryland. In a comparison with high resolution LiDAR data available over selected regions in the two states, we found our results to be promising both in terms of accuracy as well as our ability to scale nationally. The generated 1-m forest cover map will be aggregated to the Landsat spatial grid to demonstrate differences in AGB estimates (pixel-level AGB density, total AGB at aggregated scales like ecoregions and counties) when using a native 30-m forest cover map versus a 30-m map derived from a higher resolution dataset. The process will also be complemented with a LiDAR derived AGB estimate at the 30-m scale to aid in true validation.

  8. Assessing the Utility of Satellite Imagery with Differing Spatial Resolutions for Deriving Proxy Measures of Slum Presence in Accra, Ghana

    PubMed Central

    Stoler, Justin; Daniels, Dean; Weeks, John R.; Stow, Douglas A.; Coulter, Lloyd L.; Finch, Brian Karl

    2012-01-01

    Little research has been conducted on how differing spatial resolutions or classification techniques affect image-driven identification and categorization of slum neighborhoods in developing nations. This study assesses the correlation between satellite-derived land cover and census-derived socioeconomic variables in Accra, Ghana to determine whether the relationship between these variables is altered with a change in spatial resolution or scale. ASTER and Landsat TM satellite images are each used to classify land cover using spectral mixture analysis (SMA), and land cover proportions are summarized across Enumeration Areas in Accra and compared to socioeconomic data for the same areas. Correlation and regression analyses compare the SMA results with a Slum Index created from various socio-economic data taken from the Census of Ghana, as well as to data derived from a “hard” per-pixel classification of a 2.4 m Quickbird image. Results show that the vegetation fraction is significantly correlated with the Slum Index (Pearson’s r ranges from −0.33 to −0.51 depending on which image-derived product is compared), and the use of a spatial error model improves results (multivariate model pseudo-R2 ranges from 0.37 to 0.40 by image product). We also find that SMA products derived from ASTER are a sufficient substitute for classification products derived from higher spatial resolution QB data when using land cover fractions as a proxy for slum presence, suggesting that SMA might be more cost-effective for deriving land cover fractions than the use of high-resolution imagery for this type of demographic analysis. PMID:23847453

  9. Estimating daily air temperature across the Southeastern United States using high-resolution satellite data: A statistical modeling study.

    PubMed

    Shi, Liuhua; Liu, Pengfei; Kloog, Itai; Lee, Mihye; Kosheleva, Anna; Schwartz, Joel

    2016-04-01

    Accurate estimates of spatio-temporal resolved near-surface air temperature (Ta) are crucial for environmental epidemiological studies. However, values of Ta are conventionally obtained from weather stations, which have limited spatial coverage. Satellite surface temperature (Ts) measurements offer the possibility of local exposure estimates across large domains. The Southeastern United States has different climatic conditions, more small water bodies and wetlands, and greater humidity in contrast to other regions, which add to the challenge of modeling air temperature. In this study, we incorporated satellite Ts to estimate high resolution (1km×1km) daily Ta across the southeastern USA for 2000-2014. We calibrated Ts-Ta measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R(2) of 0.952 indicated excellent model performance. When satellite Ts were unavailable, linear regression on nearby monitors and spatio-temporal smoothing was used to estimate Ta. The daily Ta estimations were compared to the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) model. A good agreement with an R(2) of 0.969 and a mean squared prediction error (RMSPE) of 1.376°C was achieved. Our results demonstrate that Ta can be reliably predicted using this Ts-based prediction model, even in a large geographical area with topography and weather patterns varying considerably. PMID:26717080

  10. Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

    PubMed Central

    Just, Allan C.; Wright, Robert O.; Schwartz, Joel; Coull, Brent A.; Baccarelli, Andrea A.; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

    2015-01-01

    Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most US and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004–2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross validation R2 of 0.724. Cross-validated root mean squared prediction error (RMSPE) of the model was 5.55 μg/m3. This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City. PMID:26061488

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

    NASA Astrophysics Data System (ADS)

    Navratil, Peter; Wilps, Hans

    2013-01-01

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

  12. Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

    PubMed

    Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

    2015-07-21

    Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City. PMID:26061488

  13. High-resolution satellite image recovery by modulation transfer function (MTF) compensation method using phase congruency estimation

    NASA Astrophysics Data System (ADS)

    Shao, Xiaopeng; Yang, Hong; Zhang, Shaohui; Jin, Zhenhua; Du, Juan

    2013-09-01

    Satellite imagery always has low-resolution causing poor application in practice because the serious degradation in imaging is resulted in many factors such as atmospheric turbulence, cloud, and aberration of optical system. To reconstruct the degraded remote sensing images with a high quality, we designed an algorithm to estimate the system modulation transfer function (MTF) accurately. Phase congruency is employed to detect the edges and corners of the image first, then the significant edges, which are utilized to estimate the edge spread function (ESF) using inclined edge method, are picked up from above features through a certain line detection measurement. An image restoration algorithm based on total variation (TV) is introduced to deconvolute the degraded image with the estimated MTF which is derived from the ESF. The experiments show that this method is adaptive and efficient to recover the remote sensing images taken from a Chinese Satellite. The restored images with a higher resolution and higher signal-to-noise ratio (SNR) will improve the applications greatly.

  14. A geographical sampling method for surveys of mosquito larvae in an urban area using high-resolution satellite imagery

    PubMed Central

    Troyo, Adriana; Fuller, Douglas O.; Calderón-Arguedas, Olger; Beier, John C.

    2008-01-01

    Entomological surveys in urban areas are often biased by selecting houses or locations with known high vector densities. A sampling strategy was developed for Puntarenas, Costa Rica, using high-resolution satellite imagery. Grids from the Advanced Spaceborne Thermal Emission and Reflection Radiometer and a QuickBird classified land cover map were used to determine the optimal final grid area for surveys. A random sample (10% of cells) was selected, and sample suitability was assessed by comparing the mean percentage of tree cover between sample and total cells. Sample cells were used obtain entomological data from 581 locations: 26.3% of all locations positive for mosquito larvae were not households, they contained 29.5% of mosquito-positive habitats and 16% of Aedes aegypti pupae collected. Entomological indices for Ae. aegypti (pupae per person, Breteau index, container index, location index) were slightly lower when only household data were analyzed. High-resolution satellite imagery and geographical information systems appear useful for evaluating urban sites and randomly selecting locations for accurate entomological surveys. PMID:18697301

  15. Post-earthquake road damage assessment using region-based algorithms from high-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Haghighattalab, A.; Mohammadzadeh, A.; Valadan Zoej, M. J.; Taleai, M.

    2010-10-01

    Receiving accurate and comprehensive knowledge about the conditions of roads after earthquake strike are crucial in finding optimal paths and coordinating rescue missions. Continuous coverage of the disaster region and rapid access of high-resolution satellite images make this technology as a useful and powerful resource for post-earthquake damage assessment and the evaluation process. Along with this improved technology, object-oriented classification has become a promising alternative for classifying high-resolution remote sensing imagery, such as QuickBird, Ikonos. Thus, in this study, a novel approach is proposed for the automatic detection and assessment of damaged roads in urban areas based on object based classification techniques using post-event satellite image and vector map. The most challenging phase of the proposed region-based algorithm is the segmentation procedure. The extracted regions are then classified using nearest neighbor classifier making use of textural parameters. Then, an appropriate fuzzy inference system (FIS) is proposed for road damage assessment. Finally, the roads are correctly labeled as 'Blocked road' or 'Unblocked road' in the road damage assessment step. The proposed method was tested on QuickBird pan-sharpened image of Bam, Iran, concerning the devastating earthquake that occurred in December 2003. The visual investigation of the obtained results demonstrates the efficiency of the proposed approach.

  16. Fully constrained linear spectral unmixing based global shadow compensation for high resolution satellite imagery of urban areas

    NASA Astrophysics Data System (ADS)

    Yang, Jian; He, Yuhong; Caspersen, John

    2015-06-01

    Shadows commonly exist in high resolution satellite imagery, particularly in urban areas, which is a combined effect of low sun elevation, off-nadir viewing angle, and high-rise buildings. The presence of shadows can negatively affect image processing, including land cover classification, mapping, and object recognition due to the reduction or even total loss of spectral information in shadows. The compensation of spectral information in shadows is thus one of the most important preprocessing steps for the interpretation and exploitation of high resolution satellite imagery in urban areas. In this study, we propose a new approach for global shadow compensation through the utilization of fully constrained linear spectral unmixing. The basic assumption of the proposed method is that the construction of the spectral scatter plot in shadows is analogues to that in non-shadow areas within a two-dimension spectral mixing space. In order to ensure the continuity of land covers, a smooth operator is further used to refine the restored shadow pixels on the edge of non-shadow and shadow areas. The proposed method is validated using the WorldView-2 multispectral imagery collected from downtown Toronto, Ontario, Canada. In comparison with the existing linear-correlation correction method, the proposed method produced the compensated shadows with higher quality.

  17. A FPGA-based automatic bridge over water recognition in high-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Beulig, Sebastian; von Schönermark, Maria; Huber, Felix

    2012-11-01

    In this paper a novel algorithm for recognizing bridges over water is presented. The algorithm is designed to run on a small reconfigurable microchip, a so called Field Programmable Gate Array (FPGA). Hence, the algorithm is computationally lightweight and high processing speeds can be reached. Furthermore no a-priory knowledge about a bridge is necessary. Even bridges with an irregular shape, e.g. with balconies, can be detected. As a result, the center point of the bridge is marked. Due to the low power consumption of the FPGA and the autonomous performance of the algorithm, it is suitable for an image analysis directly on-board of satellites. Meta-data like the coordinates of recognized bridges are immediately available. This could be useful, e.g. in case of a natural hazard, when quick information about the infrastructure is desired by the disaster management. The algorithm as well as experimental results on real satellite images are presented and discussed.

  18. Learning Scene Categories from High Resolution Satellite Image for Aerial Video Analysis

    SciTech Connect

    Cheriyadat, Anil M

    2011-01-01

    Automatic scene categorization can benefit various aerial video processing applications. This paper addresses the problem of predicting the scene category from aerial video frames using a prior model learned from satellite imagery. We show that local and global features in the form of line statistics and 2-D power spectrum parameters respectively can characterize the aerial scene well. The line feature statistics and spatial frequency parameters are useful cues to distinguish between different urban scene categories. We learn the scene prediction model from highresolution satellite imagery to test the model on the Columbus Surrogate Unmanned Aerial Vehicle (CSUAV) dataset ollected by high-altitude wide area UAV sensor platform. e compare the proposed features with the popular Scale nvariant Feature Transform (SIFT) features. Our experimental results show that proposed approach outperforms te SIFT model when the training and testing are conducted n disparate data sources.

  19. Evaluation of Multi-Resolution Satellite Sensors for Assessing Water Quality and Bottom Depth of Lake Garda

    PubMed Central

    Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E.

    2014-01-01

    In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions. PMID:25517691

  20. Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda.

    PubMed

    Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E

    2014-01-01

    In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions. PMID:25517691

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  2. Automatic, Real-Time Algorithms for Anomaly Detection in High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Srivastava, A. N.; Nemani, R. R.; Votava, P.

    2008-12-01

    Earth observing satellites are generating data at an unprecedented rate, surpassing almost all other data intensive applications. However, most of the data that arrives from the satellites is not analyzed directly. Rather, multiple scientific teams analyze only a small fraction of the total data available in the data stream. Although there are many reasons for this situation one paramount concern is developing algorithms and methods that can analyze the vast, high dimensional, streaming satellite images. This paper describes a new set of methods that are among the fastest available algorithms for real-time anomaly detection. These algorithms were built to maximize accuracy and speed for a variety of applications in fields outside of the earth sciences. However, our studies indicate that with appropriate modifications, these algorithms can be extremely valuable for identifying anomalies rapidly using only modest computational power. We review two algorithms which are used as benchmarks in the field: Orca, One-Class Support Vector Machines and discuss the anomalies that are discovered in MODIS data taken over the Central California region. We are especially interested in automatic identification of disturbances within the ecosystems (e,g, wildfires, droughts, floods, insect/pest damage, wind damage, logging). We show the scalability of the algorithms and demonstrate that with appropriately adapted technology, the dream of real-time analysis can be made a reality.

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

    NASA Astrophysics Data System (ADS)

    Plattner, Alain; Simons, Frederik J.

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Stolle, Claudia; Michaelis, Ingo; Rauberg, Jan

    2016-07-01

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

  5. Selecting the spatial resolution of satellite sensors required for global monitoring of land transformations

    NASA Technical Reports Server (NTRS)

    Townshend, J. R. G.; Justice, C. O.

    1988-01-01

    The paper provides preliminary evidence for the spatial resolutions required to monitor land transformations at broad scales. This is obtained from simulations of imagery at various spatial resolutions between 125 and 4000 m derived from Landsat MSS imagery. Consideration is given to the various types of spatial images detectable by remotely-sensed systems, as well as to the difficulties associated in disentangling permanent land transformations from shorter term changes such as phenological and interannual changes.

  6. Ice shelf flexure at Antarctic grounding lines observed by high resolution satellite and ground measurements

    NASA Astrophysics Data System (ADS)

    Rack, Wolfgang; Wild, Christian; Ryan, Michelle; Marsh, Oliver; McDonald, Adrian; King, Matt; Floricioiu, Dana; Wiesmann, Andreas; Price, Daniel

    2015-04-01

    Climate change is expected to impact Antarctic ice sheets primarily through changes in the oceans. This will be felt most strongly near the grounding line, where the ice sheet first comes into contact with ocean water and becomes an ice shelf. The primary objective of this work is to make use of satellite techniques for better monitoring and interpretation of the link between floating ice shelves and grounded ice. By measuring the flexure of ice due to tides we can obtain critical data to derive information on ice properties. Satellites can measure tidal bending over discrete time intervals and over large areas, whereas ground stations monitor ice dynamics continuously at discrete points. By the combination of the two we derive a complete picture of vertical ice displacement by tides for different grounding line geometries. Our field site is the Southern McMurdo Ice Shelf in the western Ross Sea region at which horizontal ice dynamics can be neglected which simplifies corresponding satellite data analysis. During a field survey in 2014/15, we acquired data of tidal flexure along a straight line perpendicular to the grounding line using 8 ground stations equipped with differential GPS receivers and high precision tiltmeters. The most landward station was located close to the grounding line, and the last station was placed 5 km away at a point which was assumed to be freely floating. Additional data acquired for the flexure analysis are ice thickness, snow and ice stratigraphy and basal ice properties using ground radar systems; as well as information of snow morphology from snow pits and ice cores. During the same period a series of TerraSAR-X 11-day repeat pass satellite data have been acquired to map tidal displacement using differential SAR interferometry (DInSAR). Before the onset of the melting season in December all interferograms show generally high coherence and are suitable for tidal flexure analysis. The ice shelf in the area is around 200m thick, and

  7. High-resolution satellite-based analysis of ground-level PM2.5 for the city of Montreal.

    PubMed

    Wang, Baozhen; Chen, Zhi

    2016-01-15

    Satellite remote sensing offers the opportunity to determine the spatial distribution of aerosol properties and could fill the gap of ground-level observations. Various algorithms have recently been developed in order to retrieve the aerosol optical depth (AOD) at continental scales. However, they are, to some extent, subject to coarse spatial resolutions which are not appropriate for intraurban scales as usually needed in health studies. This paper presents an improved AOD retrieval algorithm for satellite instrument MODIS at 1-km resolution for intraurban scales. The MODIS-retrieved AODs are used to derive the ground-level PM2.5 concentrations using the aerosol vertical profiles and local scale factors obtained from the GEOS-Chem model simulation. The developed method has been applied to retrieve the AODs and to evaluate the ground-level PM2.5 over the city of Montreal, Canada for 2009 on daily, monthly and annual scales. The daily and monthly results are compared with the monitoring values with correlations R(2) ranging from 0.86 to 0.93. Especially, the annual mean PM2.5 concentrations are in good agreement with the measurement values at all monitoring stations (r=0.96, slope=1.0132 ± 0.0025, intercept=0.5739 ± 0.0013). This illustrates that the developed AOD retrieval algorithm can be used to retrieve AODs at a higher spatial resolution than previous studies to further derive the regional full coverage PM2.5 results at finer spatial and temporal scales. The study results are useful in health risk assessment across this region. PMID:26473708

  8. Fine Resolution Air Quality Monitoring from a Small Satellite: CHRIS/PROBA

    PubMed Central

    Nichol, Janet E.; Wong, Man Sing; Chan, Yuk Ying

    2008-01-01

    Current remote sensing techniques fail to address the task of air quality monitoring over complex regions where multiple pollution sources produce high spatial variability. This is due to a lack of suitable satellite-sensor combinations and appropriate aerosol optical thickness (AOT) retrieval algorithms. The new generation of small satellites, with their lower costs and greater flexibility has the potential to address this problem, with customised platform-sensor combinations dedicated to monitoring single complex regions or mega-cities. This paper demonstrates the ability of the European Space Agency's small satellite sensor CHRIS/PROBA to provide reliable AOT estimates at a spatially detailed level over Hong Kong, using a modified version of the dense dark vegetation (DDV) algorithm devised for MODIS. Since CHRIS has no middle-IR band such as the MODIS 2,100 nm band which is transparent to fine aerosols, the longest waveband of CHRIS, the 1,019 nm band was used to approximate surface reflectance, by the subtraction of an offset derived from synchronous field reflectance spectra. Aerosol reflectance in the blue and red bands was then obtained from the strong empirical relationship observed between the CHRIS 1,019 nm, and the blue and red bands respectively. AOT retrievals for three different dates were shown to be reliable, when compared with AERONET and Microtops II sunphotometers, and a Lidar, as well as air quality data at ground stations. The AOT images exhibited considerable spatial variability over the 11 × 11km image area and were able to indicate both local and long distance sources.

  9. Global Precipitation at One-Degree Daily Resolution From Multi-Satellite Observations

    NASA Technical Reports Server (NTRS)

    Huffman, George J.; Adler, Robert F.; Morrissey, Mark M.; Curtis, Scott; Joyce, Robert; McGavock, Brad; Susskind, Joel

    2000-01-01

    The One-Degree Daily (1DD) technique is described for producing globally complete daily estimates of precipitation on a 1 deg x 1 deg lat/long grid from currently available observational data. Where possible (40 deg N-40 deg S), the Threshold-Matched Precipitation Index (TMPI) provides precipitation estimates in which the 3-hourly infrared brightness temperatures (IR T(sub b)) are thresholded and all "cold" pixels are given a single precipitation rate. This approach is an adaptation of the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI), but for the TMPI the IR Tb threshold and conditional rain rate are set locally by month from Special Sensor Microwave/Imager (SSM/I)-based precipitation frequency and the Global Precipitation Climatology Project (GPCP) satellite-gauge (SG) combined monthly precipitation estimate, respectively. At higher latitudes the 1DD features a rescaled daily Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) precipitation. The frequency of rain days in the TOVS is scaled down to match that in the TMPI at the data boundaries, and the resulting non-zero TOVS values are scaled locally to sum to the SG (which is a globally complete monthly product). The time series of the daily 1DD global images shows good continuity in time and across the data boundaries. Various examples are shown to illustrate uses. Validation for individual grid -box values shows a very high root-mean-square error but, it improves quickly when users perform time/space averaging according to their own requirements.

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

    NASA Astrophysics Data System (ADS)

    Champion, Nicolas

    2016-06-01

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