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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. ISCCP reduced resolution satellite radiance data

    NASA Technical Reports Server (NTRS)

    Rossow, W.

    1986-01-01

    The International Satellite Cloud Climatology Project (ISCCP) is the first active project of the World Climate Research Program. It is a multinational data collection project focused on collecting a data set that will improve the ability to predict and/or simulate the radiative effects of clouds on climate. For specified cloud parameters, the goals are to archieve values for 3-hour periods over the whole globe for 5 years at 30 km resolution. The task of collecting and processing radiance data from both geosynchronous and polar orbiting satellites began in July 1983. A diagram was shown illustrating the flow of data from the transmitting satellites to the various receiving institutions that handle it. The various stages of processing were then explained in detail, emphasizing Level B3-normalized, reformatted, reduced raw satellite data. The reduction of data by sampling is an essential step in the flow. By the time the ISCCP data reaches the Global Processing Center at Goddard Institute for Space Studies (GISS), the volume has been reduced by a factor of 1000. The Pilot Climate Data System (PLDS) will provide access to the ISCCP data set. It should prove to be one of the cleanest satellite data sets because it will have been through three filters--that of the operational agency, the Global Processing Center, and the PCDS. The ISCCP data set also includes other correlative data sets delivered in compatible format.

  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. 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.

  9. 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.

  10. Wide swath and high resolution optical imaging satellite of Japan

    NASA Astrophysics Data System (ADS)

    Katayama, Haruyoshi; Kato, Eri; Imai, Hiroko; Sagisaka, Masakazu

    2016-05-01

    The "Advanced optical satellite" (tentative name) is a follow-on mission from ALOS. Mission objectives of the advanced optical satellite is to build upon the existing advanced techniques for global land observation using optical sensors, as well as to promote data utilization for social needs. Wide swath and high resolution optical imager onboard the advanced optical satellite will extend the capabilities of earlier ALOS missions. The optical imager will be able to collect high-resolution (< 1 m) and wide-swath (70 km) images with high geo-location accuracy. This paper introduces a conceptual design of the advanced optical satellite.

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

    PubMed Central

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

    2017-01-01

    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images. PMID:28481287

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

    PubMed

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

    2017-05-07

    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images.

  13. Crop Monitoring Using European and Chinese Medium Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Fan, Jinlong; Defourny, Pierre

    2016-08-01

    The European medium resolution satellite data ENVISAT/MERIS were available in 2002 while the Chinese medium resolution spectrometer data with 5 bands in 250m spatial resolution and 15 bands in 1000m onboard Fengyun 3 series satellites became a new data source at the end of the year 2008. Under the framework of Dragon program 3, both teams demonstrated the utilization of medium resolution satellite data in crop monitoring. The Chinese team has made efforts to improve the processing of the Chinese Medium resolution satellite data (MERSI) in order to promote its applications in crop monitoring. The European team has checked and evaluated the processed FY3A/3B MERSI data and inspiring findings have found in terms of the imaging quality and the performance of retrieving LAI and GAI etc. The Chinese team has mapped the winter wheat area in North China Plain in the growing season from 2009 to 2014 with the finely processed FY3A MERSI 250m data. The LAI retrieval algorithm with the FY3 MERSI data was developed based on the in-situ data and other satellite products. The participation of young scientists is critical for the implementation of the project. 4 Chinese master students were involving in this project and the Chinese team hosted a European young master student to carry out research in China in the spring of 2014. Both research teams are looking forward to successful and productive achievements for this Dragon project and new deep cooperation in Dragon 4.

  14. 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.

  15. A procedure for high resolution satellite imagery quality assessment.

    PubMed

    Crespi, Mattia; De Vendictis, Laura

    2009-01-01

    Data products generated from High Resolution Satellite Imagery (HRSI) are routinely evaluated during the so-called in-orbit test period, in order to verify if their quality fits the desired features and, if necessary, to obtain the image correction parameters to be used at the ground processing center. Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level. Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF). This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites.

  16. A Procedure for High Resolution Satellite Imagery Quality Assessment

    PubMed Central

    Crespi, Mattia; De Vendictis, Laura

    2009-01-01

    Data products generated from High Resolution Satellite Imagery (HRSI) are routinely evaluated during the so-called in-orbit test period, in order to verify if their quality fits the desired features and, if necessary, to obtain the image correction parameters to be used at the ground processing center. Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level. Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF). This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites. PMID:22412312

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

    USDA-ARS?s Scientific Manuscript database

    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...

  18. Tamarisk Mapping and Monitoring Using High Resolution Satellite Imagery

    Treesearch

    Jason W. San Souci; John T. Doyle

    2006-01-01

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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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).

  7. Performance of high-resolution satellite precipitation products over China

    NASA Astrophysics Data System (ADS)

    Shen, Yan; Xiong, Anyuan; Wang, Ying; Xie, Pingping

    2010-01-01

    A gauge-based analysis of hourly precipitation is constructed on a 0.25° latitude/longitude grid over China for a 3 year period from 2005 to 2007 by interpolating gauge reports from ˜2000 stations collected and quality controlled by the National Meteorological Information Center of the China Meteorological Administration. Gauge-based precipitation analysis is applied to examine the performance of six high-resolution satellite precipitation estimates, including Joyce et al.'s (2004) Climate Prediction Center Morphing Technique (CMORPH) and the arithmetic mean of the microwave estimates used in CMORPH; Huffman et al.'s (2007) Tropical Rainfall Measuring Mission (TRMM) precipitation product 3B42 and its real-time version 3B42RT; Turk et al.'s (2004) Naval Research Laboratory blended product; and Hsu et al.'s (1997) Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Network (PERSIANN). Our results showed the following: (1) all six satellite products are capable of capturing the overall spatial distribution and temporal variations of precipitation reasonably well; (2) performance of the satellite products varies for different regions and different precipitation regimes, with better comparison statistics observed over wet regions and for warm seasons; (3) products based solely on satellite observations present regionally and seasonally varying biases, while the gauge-adjustment procedures applied in TRMM 3B42 remove the large-scale bias almost completely; (4) CMORPH exhibits the best performance in depicting the spatial pattern and temporal variations of precipitation; and (5) both the relative magnitude and the phase of the warm season precipitation over China are estimated quite well, but the early morning peak associated with the Mei-Yu rainfall over central eastern China is substantially under-estimated by all satellite products.

  8. 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.

  9. High resolution gravity models combining terrestrial and satellite data

    NASA Technical Reports Server (NTRS)

    Rapp, Richard H.; Pavlis, Nikolaos K.; Wang, Yan M.

    1992-01-01

    Spherical harmonic expansions to degree 360 have been developed that combine satellite potential coefficient information, terrestrial gravity data, satellite altimeter information as a direct tracking data type and topographic information. These models define improved representations of the Earth's gravitational potential beyond that available from just satellite or terrestrial data. The development of the degree 360 models, however, does not imply a uniform accuracy in the determination of the gravity field as numerous geographic areas are devoid of terrestrial data or the resolution of such data is limited to, for example, 100 km. This paper will consider theoretical and numerical questions related to the combination of the various data types. Various models of the combination process are discussed with a discussion of various correction terms for the different models. Various sources of gravity data will be described. The new OSU91 360 model will be discussed with comparisons made to previous 360 models and to other potential coefficient models that are complete to degree 50. Future directions in high degree potential coefficient models will be discussed.

  10. 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.

  11. Performance of high-resolution satellite precipitation products over China

    NASA Astrophysics Data System (ADS)

    Shen, Y.; Xiong, A.; Wang, Y.; Xie, P.; Precipitation Merge Team

    2010-12-01

    A gauge-based analysis of hourly precipitation is constructed on a 0.25°latitude/ longitude grid over China for a 3 year period from 2005 to 2007 by interpolating gauge reports from ~2000 stations (fig.1) collected and quality controlled by the National Meteorological Information Center of the China Meteorological Administration. Gauge-based precipitation analysis is applied to examine the performance of six high-resolution satellite precipitation estimates, including Joyce et al.’s (2004) Climate Prediction Center Morphing Technique (CMORPH) and the arithmetic mean of the microwave estimates used in CMORPH; Huffman et al.’s (2007) Tropical Rainfall Measuring Mission (TRMM) precipitation product 3B42 and its real-time version 3B42RT; Turk et al.’s (2004) Naval Research Laboratory blended product; and Hsu et al.’s (1997) Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Network (PERSIANN). Our results showed the following: (1) all six satellite products are capable of capturing the overall spatial distribution and temporal variations of precipitation reasonably well; (2) performance of the satellite products varies for different regions and different precipitation regimes, with better comparison statistics observed over wet regions and for warm seasons; (3) products based solely on satellite observations present regionally and seasonally varying biases, while the gauge-adjustment procedures applied in TRMM 3B42 remove the large-scale bias almost completely; (4) CMORPH exhibits the best performance in depicting the spatial pattern and temporal variations of precipitation; and (5) both the relative magnitude and the phase of the warm season precipitation over China are estimated quite well, but the early morning peak associated with the Mei-Yu rainfall over central eastern China is substantially under-estimated by all satellite products. The work reported in this paper is an integral part of our efforts to construct an analysis

  12. Determining Small Scale Albedos Using High Resolution Multiangle Satellite Measurements

    NASA Astrophysics Data System (ADS)

    Markowski, G. R.; Davies, R.

    2005-05-01

    Current satellite short-wave (SW) albedo measurements, such as CERES's, have only a broad spatial resolution and cannot by themselves accurately measure reflectance (roughly solar "forcing") on small space and time scales. The major difficulty is that earth's surface reflectivity, including the atmosphere and clouds, is substantially anisotropic. However, accurate regional and time-dependent albedos are needed for studying causes of climate variability and change, and improving models from global to at least cloud resolving scales. A first step to obtain these albedos, for which we show results, is to accurately relate (and verify) the high resolution spatial and angular surface narrow-band MISR (Multi-Angle Imaging Spectroradiometer) radiance measurements aboard the Terra satellite to coincident total shortwave broadband (SWB) low resolution measurements from the onboard CERES instrument. Because MISR measures radiance of the same points along an orbital swath, it becomes possible to check and improve Angular (reflection) Distribution Models (ADMs) at small scales (< 1 km). The ADMs can later be used to invert a measured angular radiance to a local albedo. The difficulty lies in obtaining accurate ADMs for earth's highly varied surface and lighting conditions. We show prediction accuracy examples of CERES SWB vs. single and multiple band MISR data regressions. We include view angle dependence (9 angles: nadir plus 26, 46, 60, and 70 degrees fore and aft) and show improved accuracy when surface data, e.g., solar zenith and scattering angle, and surface type are included. In many cases, we predict angular (bidirectional) reflectance to ~ 0.01, or about 10 watts/sq m in irradiance. We also show examples of "difficult" scene types, such as varying levels of broken clouds, where accuracy degrades by a factor of ~2.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Analysis of smear in high-resolution remote sensing satellites

    NASA Astrophysics Data System (ADS)

    Wahballah, Walid A.; Bazan, Taher M.; El-Tohamy, Fawzy; Fathy, Mahmoud

    2016-10-01

    High-resolution remote sensing satellites (HRRSS) that use time delay and integration (TDI) CCDs have the potential to introduce large amounts of image smear. Clocking and velocity mismatch smear are two of the key factors in inducing image smear. Clocking smear is caused by the discrete manner in which the charge is clocked in the TDI-CCDs. The relative motion between the HRRSS and the observed object obliges that the image motion velocity must be strictly synchronized with the velocity of the charge packet transfer (line rate) throughout the integration time. During imaging an object off-nadir, the image motion velocity changes resulting in asynchronization between the image velocity and the CCD's line rate. A Model for estimating the image motion velocity in HRRSS is derived. The influence of this velocity mismatch combined with clocking smear on the modulation transfer function (MTF) is investigated by using Matlab simulation. The analysis is performed for cross-track and along-track imaging with different satellite attitude angles and TDI steps. The results reveal that the velocity mismatch ratio and the number of TDI steps have a serious impact on the smear MTF; a velocity mismatch ratio of 2% degrades the MTFsmear by 32% at Nyquist frequency when the TDI steps change from 32 to 96. In addition, the results show that to achieve the requirement of MTFsmear >= 0.95 , for TDI steps of 16 and 64, the allowable roll angles are 13.7° and 6.85° and the permissible pitch angles are no more than 9.6° and 4.8°, respectively.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  19. Extraction of dynamical information from high resolution satellite measurements

    NASA Astrophysics Data System (ADS)

    Isern-Fontanet, J.; Chapron, B.; Klein, P.; Collard, F.; Lapeyre, G.; Danioux, E.

    2009-04-01

    Satellite altimetry has significantly advanced the study of ocean variability. However, noise level and track separation has limited the investigation of scales smaller than 100 km. In contrast to altimeters, other sensors such as visible and infrared radiometers and imaging radars such as SAR have demonstrated their capability to provide measurements at high spatial resolutions. Nevertheless, their main limitation for dynamical studies have been the difficulty to extract quantitative information. To further explore this question we have compared sea surface roughness images obtained by SAR with nearly simultaneous Brightness Temperature (BT) images. Results clearly revealed that the most intense patterns observed in the SAR image, when environmental conditions makes roughness unveil the flow topology, were located in the same position as strong thermal gradients. Assuming that hydrodynamic modulation is the main imaging mechanism in our case, our observations implies that strong thermal gradients have associated strong divergences and convergences. To further investigate this hypothesis we have directly estimated the vorticity field from BT images. To this end we have used a new theoretical framework based on an effective version of the Surface Quasi-Geostrophic (eSQG) equations. The comparisons of these fields with the SAR image reveals a very good coincidence between the patterns in the SAR image and vorticity gradients. A dynamical interpretation ofthis result will be discussed.

  20. [Spatial resolution standardization of payload on board of remote sensing satellite based on application requirements].

    PubMed

    Wei, Xiang-qin; Gu, Xing-fa; Yu, Tao; Meng, Qing-yan; Li, Bin; Guo, Hong

    2012-03-01

    Remote sensing application requirements are the starting point for design of payload on board earth observation satellite. The generalization, standardization and serialization of payload are the future development trend for payload design. In the present paper, based on the analysis of remote sensing application requirements, the spatial resolution standardization of satellite remote sensing payload, which is the main concerned indicator, was investigated. The design standards of national payload spatial resolution of earth observation satellite are presented, which are important to the promotion of satellite payload production and saving in design cost.

  1. Utilization of high resolution satellite gravity over the Carlsberg Ridge

    NASA Astrophysics Data System (ADS)

    Chatterjee, S.; Bhattacharyya, R.; Majumdar, T. J.

    2007-12-01

    The Carlsberg Ridge lies between the equator and the Owen fracture zone. It is the most prominent mid-ocean ridge segment of the western Indian Ocean, which contains a number of earthquake epicenters. Satellite altimetry can be used to infer subsurface geological structures analogous to gravity anomaly maps generated through ship-borne survey. In this study, free-air gravity and its 3D image have been generated over the Carlsberg Ridge using a very high resolution data base, as obtained from Geosat GM, ERS-1, Seasat and TOPEX/POSEIDON altimeter data. As observed in this study, the Carlsberg Ridge shows a slow spreading characteristic with a deep and wide graben (average width ˜15 km). The transform fault spacing confirms variable slow to intermediate characteristics with first and second order discontinuities. The isostatically compensated region of the Carlsberg Ridge could be demarcated with near zero contour values in the free-air gravity anomaly images over and along the Carlsberg Ridge axes and over most of the fracture zone patterns. Few profiles have been generated across the Carlsberg Ridge and the characteristics of slow/intermediate spreading ridge of various orders of discontinuity could be identified. It has also been observed in zero contour image as well as in the characteristics of valley patterns along the ridge from NW to SE that different spreading rates, from slow to intermediate, are occurring in different parts of the Carlsberg ridge. It maintains the morphology of a slow spreading ridge in the NW, where the wide and deep axial valley (˜1.5 3 km) also implies the pattern of a slow spreading ridge. However, a change in the morphology/depth of the axial valley from NW to SE indicates the nature of the Carlsberg Ridge as a slow to intermediate spreading ridge.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. (abstract) High-Resolution Satellite Microwave Radar Observation of Climate-Related Sea-Ice Anomalies

    NASA Technical Reports Server (NTRS)

    Drinkwater, Mark R.

    1996-01-01

    Since 1991 a suite of international satellites have collected large amounts of high-resolution microwave radar images over Arctic and Antarctic sea ice. Together with complementary synthetic aperture radar (SAR) 100 m resolution microwave imaging, these data provide a powerful tool for addressing the characteristics of sea ice which directly influence the polar oceans and climate.

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

    Treesearch

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

    2009-01-01

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

  9. 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

  10. 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 ...

  11. 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 ...

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

    PubMed

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

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. 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.

  14. Ground mapping resolution accuracy of a scanning radiometer from a geostationary satellite.

    PubMed

    Stremler, F G; Khalil, M A; Parent, R J

    1977-06-01

    Measures of the spatial and spatial rate (frequency) mapping of scanned visual imagery from an earth reference system to a spin-scan geostationary satellite are examined. Mapping distortions and coordinate inversions to correct for these distortions are formulated in terms of geometric transformations between earth and satellite frames of reference. Probabilistic methods are used to develop relations for obtainable mapping resolution when coordinate inversions are employed.

  15. Identification of mosquito larval habitats in high resolution satellite data

    NASA Astrophysics Data System (ADS)

    Kiang, Richard K.; Hulina, Stephanie M.; Masuoka, Penny M.; Claborn, David M.

    2003-09-01

    Mosquito-born infectious diseases are a serious public health concern, not only for the less developed countries, but also for developed countries like the U.S. Larviciding is an effective method for vector control and adverse effects to non-target species are minimized when mosquito larval habitats are properly surveyed and treated. Remote sensing has proven to be a useful technique for large-area ground cover mapping, and hence, is an ideal tool for identifying potential larval habitats. Locating small larval habitats, however, requires data with very high spatial resolution. Textural and contextual characteristics become increasingly evident at higher spatial resolution. Per-pixel classification often leads to suboptimal results. In this study, we use pan-sharpened Ikonos data, with a spatial resolution approaching 1 meter, to classify potential mosquito larval habitats for a test site in South Korea. The test site is in a predominantly agricultural region. When spatial characteristics were used in conjunction with spectral data, reasonably good classification accuracy was obtained for the test site. In particular, irrigation and drainage ditches are important larval habitats but their footprints are too small to be detected with the original spectral data at 4-meter resolution. We show that the ditches are detectable using automated classification on pan-sharpened data.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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. 

  1. High resolution earth observation satellites and services in the next decade a European perspective

    NASA Astrophysics Data System (ADS)

    Schreier, Gunter; Dech, Stefan

    2005-07-01

    Projects to use very high resolution optical satellite sensor data started in the late 90s and are believed to be the major driver for the commercialisation of earth observation. The global political security situation and updated legislative frameworks created new opportunities for high resolution, dual use satellite systems. In addition to new optical sensors, very high resolution synthetic aperture radars will become in the next few years an important component in the imaging satellite fleet. The paper will review the development in this domain so far, and give perspectives on future emerging markets and opportunities. With dual-use satellite initiatives and new political frameworks agreed between the European Commission and the European Space Agency (ESA), the European market becomes very attractive for both service suppliers and customers. The political focus on "Global Monitoring for Environment and Security" (GMES) and the "European Defence and Security Policy" drive and amplify this demand which ranges from low resolution climate monitoring to very high resolution reconnaissance tasks. In order to create an operational and sustainable GMES in Europe by 2007, the European infrastructure need to be adapted and extended. This includes the ESA SENTINEL and OXYGEN programmes, aiming for a fleet of earth observation satellites and an open and operational earth observation ground segment. The harmonisation of national and regional geographic information is driven by the European Commission's INSPIRE programme. The necessary satellite capacity to complement existing systems in the delivery of space based data required for GMES is currently under definition. Embedded in a market with global competition and in the global political framework of a Global Earth Observation System of Systems, European companies, agencies and research institutions are now contributing to this joint undertaking. The paper addresses the chances, risks and options for the future.

  2. Resolving mesoscale variation in aerosol fields from satellite: Is fine resolution worth the hassle? (Invited)

    NASA Astrophysics Data System (ADS)

    Remer, L. A.; Munchak, L. A.; Huang, J.; Levy, R. C.; Mattoo, S.

    2013-12-01

    In early 2000 we began receiving global aerosol products from the MODerate resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) at nominal 10 km and 17.5 km resolution, respectively. Aerosol products derived from other satellite sensors such as the Ozone Monitoring Instrument (OMI) with spatial resolution nominally at 13 x 12 km later joined these data. Suddenly the global aerosol system popped into focus. For global-scale science, a 10 km product appeared to be adequate. Questions concerning the adequacy of this moderate resolution data set began to arise as the community's interest in satellite-derived aerosol products branched towards more local questions. As of Collection 6, the MODIS aerosol product will now include a fine resolution product at nominal 3 km resolution. What can we learn about mesoscale variation in aerosol fields from this new product? Was the effort worth it? We take advantage of the AERONET DRAGON networks in the mid-Atlantic region of the U.S., in Korea and in California to compare the accuracy of the MODIS 3 km product with the MODIS 10 km product, and just for fun, with the 6 km Visible Infrared Imager Suite (VIIRS) aerosol product. Do the finer resolution aerosol products show us aerosol features unobtainable by the coarser resolution products? Are the finer resolution products worth the hassle?

  3. 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.

  4. 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...

  5. 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...

  6. The significance of spatial resolution: Identifying forest cover from satellite data

    Treesearch

    Dumitru Salajanu; Charles E. Olson

    2001-01-01

    Twenty-five years ago, a National Academy of Sciences report identified species identification as a requirement if satellite data are to reach their full potential in forest inventory and monitoring; the report suggested that improving spatial resolution to 10 meters would probably be required (Committee on Remote Sensing Programs for Earth Resource Surveys [CORSPERS]...

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

    NASA Astrophysics Data System (ADS)

    AlShamsi, Meera R.

    2016-10-01

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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. Digital terrain mapping from multispectral and high-resolution satellite data for defense studies

    NASA Astrophysics Data System (ADS)

    Pandey, Suraj

    2007-04-01

    Multi spectral and high resolution satellite imageries enhancing their resolution capabilities in terms of spatial and spectral reflectance time to time such as LANDSAT, IRS, IKONOS and Digital Globe, these imageries are being used effectively and efficiently in certain applications, whereas to register spectral reflectance in different channels of electromagnetic spectrum is the principal characteristic of multi spectral satellite imageries. The real time nature of remotely sensed data can be of high value for mapping and analyzing surface features. This paper explores the broader application of remote sensing analysis for terrain mapping from multi-spectral satellite data, the accuracy of digital elevation model has been verified from various surface interpolation algorithms in which contouring and point interpolation techniques were extensively used. The study reveals that digital interpretation has become more sharpened on a large scale and terrain mapping with high and multi-spectral satellite data along with GPS Mobile Mapper can be done for any region, on some extent this research work has confirmed that sensor on a satellite can navigate army movements.

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  16. Relative Orientation and Modified Piecewise Epipolar Resampling for High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Gong, K.; Fritsch, D.

    2017-05-01

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

  17. 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

  18. 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

  19. Application requirement analysis of high spectral and high spatial resolution satellite for environment remote sensing monitoring

    NASA Astrophysics Data System (ADS)

    Liu, S. H.; Yang, Y. P.; Zhao, Z. H.; Yao, Y. J.; Mao, X. J.; Wu, Y. T.; Gao, Y. H.

    2016-03-01

    China's environmental situation is still grim, environmental pressure continues to increase. The demand of environmental protection work in the new era for high resolution remote sensing application will continue to increase. Environmental monitoring has multi factor, quantitative inversion and high precision as features, environment department need to use a wide spectrum of remote sensing data with high spectral resolution capability to monitor the total amount of pollutants in macro scale and long time series. The implementation of the high resolution earth observation project provides support for the improvement of the quantitative application of environmental remote sensing. On the basis of sorting out the key work of environmental protection, the application requirements of high spectral resolution and high spatial resolution satellite remote sensing in the field of environmental protection and the building needs of national environmental remote sensing application platform are put forward.

  20. [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.

  1. 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)

  2. 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.

  3. 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.

  4. Chenge Detection Method for Wetland Surface Conditions using NDVI Values of High Spatial Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Takeshita, Shinichi; Suzuki, Kenji

    In this study, a new method has been proposed that can reveal changes of wetland surface condition using high spatial resolution satellite data (IKONOS) for actual wetland managements. The method can detect the wetland surface change based on the NDVI change domain in wetlands using bi-temporal satellite data through analyzing ‘coordinate of NDVI change’. We applied the method to Kawaminami wetland in Miyazaki prefecture for comparing the calculation results and actual state of wetland with observed groundwater level data. As the results, it was able to extract artificial change of the wetland surface precisely and to detect differences of the wetness of the surface in two imageries. For satellite data analysis, it was indicated that utilization of supplementary climate data such as rainfall is important. The proposed method is effective for actual wetland managements, because it is simple and practical.

  5. 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.

  6. Extraction of marine debris in the Sea of Japan using high-spatial-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Aoyama, Takashi

    2016-05-01

    The flow of marine debris in the Sea of Japan causes extensive damage to coastal environments. It is important to understand the debris flow in the ocean for environmental research. The small size of most marine debris in the Sea of Japan makes it impossible to be confirmed directly, even when using high-spatial-resolution satellite imagery. Thus, to extract candidate pixels containing possible marine debris, pixels with spectra that differ from those of the surrounding ocean and wave crests were identified. As a first step towards monitoring marine debris, a previously proposed method for identifying marine debris floating in the Sea of Japan uses a histogram showing the distance from the regression line of the scatter diagram of satellite spectral bands. In this paper, a new method using a spectral angle mapper (SAM) in four- or eight-dimensional space corresponding to satellite spectral bands is proposed. The validity of the method using SAM is also discussed.

  7. Forest cover of insular Southeast Asia mapped from recent satellite images of coarse spatial resolution.

    PubMed

    Stibig, Hans-Jürgen; Malingreau, Jean-Paul

    2003-11-01

    The study provides an example of mapping tropical forest cover from SPOT-Vegetation satellite images of coarse spatial resolution (1 km) for the subregion of insular Southeast Asia. A satellite image mosaic has been generated from satellite images acquired for the period 1998 to 2000. Forest cover has been mapped by unsupervised digital classification. The mapping result has then been compared to selected forest maps from the subregion, demonstrating the potential to provide basic information on forest area extent and distribution, but also on massive forest cover change in the subregional context. Forest area estimates derived from the map for the subregion have been found comparable to those compiled by FAO. The results indicate that many of the remaining tropical forests in Southeast Asia, rich in timber resources and biodiversity, may be lost in the near future if deforestation continues at present or previous rates.

  8. 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

  9. The effect of model resolution and satellite sounding data on GLAS model forecasts

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

    The effect of horizontal model resolution on satellite data impact has been studied for two versions of the GLAS second-order general circulation model: the C-model with a 4-deg latitude by 5-deg longitude resolution and the F-model with a 2.5-deg latitude and 3-deg longitude resolution. It is found that the 48-72 h forecast skill of the GLAS model was significantly improved by the increased resolution. Initial state differences between the SAT and NOSAT cycles using the F-model were on the average smaller than the corresponding differences with the C-model. However, the F-model cycle differences exhibited a smaller scale structure and, in some cases, larger gradients.

  10. 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.

  11. 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.

  12. Research on the flywheel components' disturbance mechanism of a high resolution optical satellite

    NASA Astrophysics Data System (ADS)

    Lin, Li; Dong, Wang; Sitong, Zhou; Tan, Luyang

    2016-10-01

    According to the picture of a sub-meter resolution optical satellite acquired on the orbit, there is a phenomenon of jitter in the process of taking pictures. The flywheel as the main attitude control component of the satellite, the disturbance that it caused has great influence on the high resolution optical satellite in its normal action. This paper has respectively researched the flywheel components' disturbance mechanism from three parts, including uneven rotator, rotator friction, bearing disturbance, builds the mathematics model of disturbance to analysis the characteristic of disturbance. we get that the vibration system is not a fully linear system, the system is linear before the occurrence of rubbing. It also can be seen that the system has a number of different cross rigidity, it will often appear unstable motion that resulting in damage, or becomes the ultimate destruction due to the role of nonlinear damping. When the rolling roll in the surface, it will produce an alternative excitation force if there exist defects or damage in the rolling surface. This research would offer guidance for system optimization design and vibrating isolation compensation of the later type of improved satellite.

  13. Fine-Resolution Satellite-Based Daily Sea Surface Temperatures over the Global Ocean

    DTIC Science & Technology

    2007-05-01

    MODAS with latitudinal extent limited to ±80. Note that only the RTG product includes SST in the Caspian Sea and the Sea of Azov . The plot masks SST...Fine-resolution satellite-based daily sea surface temperatures over the global ocean A. B. Kara1 and C. N. Barron1 Received 18 November 2006; revised...13 February 2007; accepted 27 February 2007; published 22 May 2007. [1] The accuracy and relative merits of two sets of daily global sea surface

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Spatial Resolution of Core Surface Flow Models Derived From Satellite Data

    NASA Astrophysics Data System (ADS)

    Eymin, C.; Hulot, G.

    Core surface flows are usually computed from observations of the internal magnetic field and its secular variation. With observatory based secular variation models, the spatial resolution of core surface flows was mainly limited by the resolution of the secular variation model itself. This resolution dramatically improved with magnetic satellite data and for the first time the main limitation on core surface flow compu- tations comes from the hiding of the smallest length scale of the internal magnetic field by the crust. Indeed, the invisible small scale magnetic field may interact with core flows to produce large scale secular variation. This interaction cannot be taken into account during the flow computation process and may alter the computed flow models, even for large length scales. We investigate here the effects of the truncation of the internal magnetic field with known flow models using two different and inde- pendent core surface flow computation methods. In particular, we try to estimate the amplitude of the error introduced by this truncation and the spatial resolution that can be obtained with the new satellite data for core surface flows.

  19. 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.

  20. High-Spatial-Resolution Thermal Infrared Satellite Images for Lake Studies

    NASA Astrophysics Data System (ADS)

    Steissberg, T. E.; Hook, S. J.; Schladow, G.

    2006-12-01

    Thermal infrared (TIR) satellite images can be used to study transport processes in lakes, such as wind-driven upwelling and surface circulation, providing a measure of spatial variability and horizontal distribution of water temperature that conventional field-based measurements cannot provide. High-spatial-resolution TIR images provide a detailed view of fine-scale processes, such as surface jets, that cannot be clearly resolved in moderate-resolution images, and they enable the accurate measurement of surface transport and circulation patterns. The surface temperature maps derived from high-resolution thermal infrared ASTER and Landsat ETM+ images, in conjunction with moderate-resolution TIR images acquired by MODIS, enabled the characterization of wind-driven upwelling and the measurement of surface currents and circulation at Lake Tahoe, California-Nevada, USA. The images, paired with in situ surface temperature and meteorological data, have shown that wind-driven partial upwelling events occur at least twice monthly throughout the spring and summer stratified period, transporting water from intermediate depths to the surface. These are important events that contribute to the patchiness and heterogeneity that characterize natural aquatic systems. The high spatial resolution of ASTER and ETM+ and the small time separation between their subsequent overpasses allow the surface currents and general circulation in lakes and coastal environments to be accurately quantified using the maximum cross-correlation method. The surface currents and circulation at Lake Tahoe were measured using a pair of cross-platform high-resolution TIR images acquired 38 minutes apart by ETM+ and ASTER. Mean currents of 5--10 cm/s were measured, with maximum currents approaching 35 cm/s. The eastward transport of a surface jet extending from an upwelling front was clearly apparent, with 15--30 cm/s currents. The vector field delineated three gyres, consistent with surface drifter

  1. Comparison between the ESFT method and LBL method of CO2 retrieval for high-resolution satellite

    NASA Astrophysics Data System (ADS)

    Li, Yanfen; Zhang, Chunmin; Wang, Dingyi; Chen, Jie; Liu, Dongdong; Rong, Piao

    2015-02-01

    The spectra of O2 A-band (0.76 μm) and CO2 near-infrared emissions (1.6 μm) for Medium-resolution Satellite (SCIAMACHY) are simulated by the SCIATRAN model (V3.1.29), and compared with the ESFT and LBL method, as the inversion accuracy and time consuming. The time consuming of LBL was more than ESFT with the relative error less than 1%, especially for the CO2 band. But for the CO2 (2.0 um) of High-resolution Satellite, the opposite result was found. That is to say, the LBL method was more suitable for High-resolution Satellite. Different wavelength intervals and integral wavelength steps are applied to the LBL to select the most appropriate combination for High-resolution SatelliteO2 A-band (0.76 μm) and CO2 near-infrared band (1.58 μm).

  2. 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

  3. A high-resolution and observationally constrained OMI NO2 satellite retrieval

    NASA Astrophysics Data System (ADS)

    Goldberg, Daniel L.; Lamsal, Lok N.; Loughner, Christopher P.; Swartz, William H.; Lu, Zifeng; Streets, David G.

    2017-09-01

    This work presents a new high-resolution NO2 dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO2 version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO2 vertical profile shape factors from a 1.25° × 1° (˜ 110 km × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO2 vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km × 1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO2 vertical columns during summertime in the eastern US. In this new product, OMI NO2 tropospheric columns increase by up to 160 % in city centers and decrease by 20-50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO2 and Airborne Compact Atmospheric Mapper (ACAM) NO2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in the new product vs. r2 = 0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NOx emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO2 satellite retrievals.

  4. 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.

  5. 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

  6. 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

  7. 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

  8. High resolution satellite derived erodibility factors for WRF/Chem windblown dust simulations in Argentina

    NASA Astrophysics Data System (ADS)

    Cremades, Pablo Gabriel; Fernandez, Rafael Pedro; Allend, David; Mulena, Celeste; Puliafito, Salvador Enrique

    2017-04-01

    A proper representation of dust sources is critical to accurately predict atmospheric particle concentrations in regional windblown dust simulations. The Weather Research and Forecasting model with Chemistry (WRF/Chem) includes a topographic-based erodibility map originally conceived for global scale modeling, which fails to identify the geographical location of dust sources in many regions of Argentina. Therefore, this study aims at developing a method to obtain a high-resolution erodibility map suitable for regional or local scale modeling using WRF/Chem. We present two independent approaches based on global methods to estimate soil erodibility using satellite retrievals, i.e. topography from the Shuttle Radar Topography Mission (SRTM) and surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). Simulation results of a severe Zonda wind episode in the arid central-west Argentina serve as bases for the analysis of these methods. Simulated dust concentration at surface level is compared with particulate matter measurements at one site in Mendoza city. In addition, we use satellite aerosol optical depth (AOD) retrievals to investigate model performance in reproducing spatial distribution of dust emissions. The erodibility map based on surface reflectance from MODIS improves the representation of small scale features, and increases the overall dust aerosol loading with respect to the standard map included by default. Simulated concentrations are in good agreement with measurements as well as satellite derived dust spatial distribution.

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  12. 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.

  13. 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).

  14. The role of spatial and spectral resolution on the effectiveness of satellite-based vegetation indices

    NASA Astrophysics Data System (ADS)

    Psomiadis, Emmanouil; Dercas, Nicholas; Dalezios, Nicolas R.; Spyropoulos, Nikolaos V.

    2016-10-01

    Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop needs or health problems and provide solutions for a better crop management. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. In the present study, the experimental area is located near the village Eleftherion of Larissa Prefecture in the Thessaly Plain, and consisted of two adjacent agricultural fields of cotton and corn. Imagery from WorldView-2 (WV2) satellite platform was obtained from European Space Imaging and Landsat-8 (L8) free of charge data were downloaded from the United States Geological Survey (USGS) archive. The images were selected for a four month span to evaluate continuity with respect to vegetation growth variation. VIs for each satellite platform data such as the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Fraction Photosynthetically Radiation (FPAR) were calculated. The comparison of these VIs produced from the two satellite systems with different spatial and spectral resolution was made for each growth stage of the crops and their results were analyzed in order to examine their correlation. Utilizing the WV2 new spectral data, several innovative chlorophyll and vegetation indices were created and evaluated so as to reveal their effectiveness in the detection of problematic plant growth areas. The Green Chlorophyll index appeared to be the most efficient index for the delineation of these areas.

  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. 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

  17. 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.

  18. Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming

    NASA Astrophysics Data System (ADS)

    Benzouai, Siham; Smara, Youcef

    2010-12-01

    The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.

  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. Feasibility of using high-resolution satellite imagery to assess vertebrate wildlife populations.

    PubMed

    LaRue, Michelle A; Stapleton, Seth; Anderson, Morgan

    2017-02-01

    Although remote sensing has been used for >40 years to learn about Earth, use of very high-resolution satellite imagery (VHR) (<1-m resolution) has become more widespread over the past decade for studying wildlife. As image resolution increases, there is a need to understand the capabilities and limitations of this exciting new path in wildlife research. We reviewed studies that used VHR to examine remote populations of wildlife. We then determined characteristics of the landscape and the life history of species that made the studies amenable to use of satellite imagery and developed a list of criteria necessary for appropriate use of VHR in wildlife research. From 14 representative articles, we determined 3 primary criteria that must be met for a system and species to be appropriately studied with VHR: open landscape, target organism's color contrasts with the landscape, and target organism is of detectable size. Habitat association, temporal exclusivity, coloniality, landscape differentiation, and ground truthing increase the utility of VHR for wildlife research. There is an immediate need for VHR imagery in conservation research, particularly in remote areas of developing countries, where research can be difficult. For wildlife researchers interested in but unfamiliar with remote sensing resources and tools, understanding capabilities and current limitations of VHR imagery is critical to its use as a conservation and wildlife research tool.

  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. Exploring image data assimilation in the prospect of high-resolution satellite data

    NASA Astrophysics Data System (ADS)

    Verron, J. A.; Duran, M.; Gaultier, L.; Brankart, J. M.; Brasseur, P.

    2016-02-01

    Many recent works show the key importance of studying the ocean at fine scales including the meso- and submesoscales. Satellite observations such as ocean color data provide informations on a wide range of scales but do not directly provide information on ocean dynamics. Satellite altimetry provide informations on the ocean dynamic topography (SSH) but so far with a limited resolution in space and even more, in time. However, in the near future, high-resolution SSH data (e.g. SWOT) will give a vision of the dynamic topography at such fine space resolution. This raises some challenging issues for data assimilation in physical oceanography: develop reliable methodology to assimilate high resolution data, make integrated use of various data sets including biogeochemical data, and even more simply, solve the challenge of handling large amont of data and huge state vectors. In this work, we propose to consider structured information rather than pointwise data. First, we take an image data assimilation approach in studying the feasibility of inverting tracer observations from Sea Surface Temperature and/or Ocean Color datasets, to improve the description of mesoscale dynamics provided by altimetric observations. Finite Size Lyapunov Exponents are used as an image proxy. The inverse problem is formulated in a Bayesian framework and expressed in terms of a cost function measuring the misfits between the two images. Second, we explore the inversion of SWOT-like high resolution SSH data and more especially the various possible proxies of the actual SSH that could be used to control the ocean circulation at various scales. One focus is made on controlling the subsurface ocean from surface only data. A key point lies in the errors and uncertainties that are associated to SWOT data.

  4. 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

  5. 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.

  6. 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

  7. Enhancing the temporal resolution of satellite-based flood extent generation using crowdsourced data for disaster monitoring.

    NASA Astrophysics Data System (ADS)

    Panteras, G.; Cervone, G.

    2016-12-01

    Satellite-based disaster monitoring has been extensively and successfully used for numerous crisis response and impact delineation tasks until nowadays. Remote sensing satellite are routinely used data during disasters for damage assessment and to coordinate relief operations. Although there is a plethora of satellite sensors able to provide actionable data about an event, their temporal resolution is limited by the satellite revisit time and the presence of clouds. These limitations do not allow for an uninterrupted and timely sensitive monitoring, which is crucial during disasters and emergencies. This research presents an approach that leverages the increased temporal resolution of crowdsourced data to partially overcame the limitations of satellite data. The proposed approach focuses on the geostatistical analysis of Tweeter data to help delineate the flood extent on a daily basis. The crowdsourced data are used to augment satellite imagery from EO-1 ALI, Landsat 8, WorldView-2 and WorldView-3 by fusing them together to complement the satellite observations. The proposed methodology was applied to estimate the daily flood extents in Charleston, SC, caused by hurricane Joaquin on October 2015. The results of the proposed methodology indicate that the user-generated data can be utilized adequately to both bridge the temporal gaps in the satellite-based observations and also to increase the spatial resolution of the flood extents.

  8. Fine-Resolution Satellite-Based Sea Surface Temperatures over the Global Ocean

    DTIC Science & Technology

    2007-05-22

    sea -ice the Sea of Azov . The plot masks SST in the Great Lakes that coverage. may otherwise included in RTG. [7] These differences between MODAS and...and relative merits of two sets of daily global sea surface temperature (SST) analyses are examined and compared. The 1/81 Modular Ocean Data Analysis...10.1029/2006JC004021, 2007 ore FuN Awtle Fine-resolution satellite-based daily sea surface f!Tr7 1 UTION STATENT-T!T A temperatures over the global

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

    NASA Technical Reports Server (NTRS)

    Otrio, G.

    1980-01-01

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

  10. 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

  11. 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.

  12. Crosswalk localization from low resolution satellite images to assist visually impaired people.

    PubMed

    Ghilardi, Marcelo; Junior, Julio; Manssour, Isabel

    2016-05-25

    In this paper we propose a model for crosswalk detection and localization by using satellite images captured from Google Maps, for the purpose of assisting visually impaired people. The detection is performed by a SVM classifier, which is combined with Google Road Map to speed up computation time and to eliminate some possible false alarms. We assume that a visually impaired person holds a smartphone with an embedded GPS, which is used to initialize the extraction of images from Google Maps, as well as to assist its user by providing audio feedback of the nearest detected crosswalk. This issue brings forward significant interest and it is also very challenging, mainly due to illumination changes, occlusion, image noise and resolution, besides the quality of crosswalks that sometimes are badly painted in many developing countries. Experimental results indicate that the proposed model works well in low resolution images, effectively detecting and localizing crosswalks in simulated scenarios.

  13. 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.

  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. Developing an efficient technique for satellite image denoising and resolution enhancement for improving classification accuracy

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  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. Using pan-sharpened high resolution satellite data to improve impervious surfaces estimation

    NASA Astrophysics Data System (ADS)

    Xu, Ru; Zhang, Hongsheng; Wang, Ting; Lin, Hui

    2017-05-01

    Impervious surface is an important environmental and socio-economic indicator for numerous urban studies. While a large number of researches have been conducted to estimate the area and distribution of impervious surface from satellite data, the accuracy for impervious surface estimation (ISE) is insufficient due to high diversity of urban land cover types. This study evaluated the use of panchromatic (PAN) data in very high resolution satellite image for improving the accuracy of ISE by various pan-sharpening approaches, with a further comprehensive analysis of its scale effects. Three benchmark pan-sharpening approaches, Gram-Schmidt (GS), PANSHARP and principal component analysis (PCA) were applied to WorldView-2 in three spots of Hong Kong. The on-screen digitization were carried out based on Google Map and the results were viewed as referenced impervious surfaces. The referenced impervious surfaces and the ISE results were then re-scaled to various spatial resolutions to obtain the percentage of impervious surfaces. The correlation coefficient (CC) and root mean square error (RMSE) were adopted as the quantitative indicator to assess the accuracy. The accuracy differences between three research areas were further illustrated by the average local variance (ALV) which was used for landscape pattern analysis. The experimental results suggested that 1) three research regions have various landscape patterns; 2) ISE accuracy extracted from pan-sharpened data was better than ISE from original multispectral (MS) data; and 3) this improvement has a noticeable scale effects with various resolutions. The improvement was reduced slightly as the resolution became coarser.

  18. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    McCabe, Matthew F.; Houborg, Rasmus; Lucieer, Arko

    2016-10-01

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  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. 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.

  1. 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).

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

    SciTech Connect

    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. 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. Furthermore, the method also demonstrates significant potential for further improvement.

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

    DOE PAGES

    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

  4. Determination of global Earth outgoing radiation at high temporal resolution using a theoretical constellation of satellites

    NASA Astrophysics Data System (ADS)

    Gristey, Jake J.; Chiu, J. Christine; Gurney, Robert J.; Han, Shin-Chan; Morcrette, Cyril J.

    2017-01-01

    New, viable, and sustainable observation strategies from a constellation of satellites have attracted great attention across many scientific communities. Yet the potential for monitoring global Earth outgoing radiation using such a strategy has not been explored. To evaluate the potential of such a constellation concept and to investigate the configuration requirement for measuring radiation at a time resolution sufficient to resolve the diurnal cycle for weather and climate studies, we have developed a new recovery method and conducted a series of simulation experiments. Using idealized wide field-of-view broadband radiometers as an example, we find that a baseline constellation of 36 satellites can monitor global Earth outgoing radiation reliably to a spatial resolution of 1000 km at an hourly time scale. The error in recovered daily global mean irradiance is 0.16 W m-2 and -0.13 W m-2, and the estimated uncertainty in recovered hourly global mean irradiance from this day is 0.45 W m-2 and 0.15 W m-2, in the shortwave and longwave spectral regions, respectively. Sensitivity tests show that addressing instrument-related issues that lead to systematic measurement error remains of central importance to achieving similar accuracies in reality. The presented error statistics therefore likely represent the lower bounds of what could currently be achieved with the constellation approach, but this study demonstrates the promise of an unprecedented sampling capability for better observing the Earth's radiation budget.

  5. 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.

  6. 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.

  7. Evaluation of spatial resolution of satellite data on snow cover estimates

    NASA Astrophysics Data System (ADS)

    Porhemmat, J.; Saghafian, B.

    2003-04-01

    Snow cover area is one of the most important components in snowmelt runoff modelling. Snow cover extent and its variation can not be reasonably detected by ground survey. Therefore, remote sensing is an important alternative for snow cover extent estimates and its spatial and temporal variation. Despite having many satellites scanning earth surface, most do not meet the needs of producing time series of daily snow cover needed in hydrology and water resources planning. The satellites such as SPOT and Landsat with high spatial resolution (28.5 and 10-15 meters per pixel) pass over earth every 16 and 26 days, respectively. This means that if a pass was affected by cloudy condition, the time interval of receiving a suitable image could be more than one month. However, the pass made by NOAA is every 12 hours with a nominal resolution of 1100 meters per pixel. Thus the effect of spatial resolution of remotely sensed data on accuracy of snow cover area must be assessed. This research involves selection of a high-resolution and a low-resolution sensor, which are respectively Landsat TM (Thematic Mapper) and NOAA AVHRR (Advanced Very High Resolution Radiometers). Landsat can detect small parcels of snow, which may not be detected by NOAA AVHRR. Zagross high lands, upstream of Karun river basin in southwest of Iran, is a seasonally covered by snow and are selected for the study area. Two simultaneous passes of Landsat and NOAA are chosen for evaluation of snow cover. The dates of these passes are 13 April 1997 and 18 May 1998. The first one corresponds to the early stage of snowmelt period and the second one to the end stage of snowmelt period. The whole study area corresponds to a full scene of Landsat, which cover an area of about 34000 Km2. There were many scattered and separate snow parcels on both dates. Snow area was detected by two methods. First method was interpretation and digitizing snow line on monitor screen and the second one was supervised classification

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

    NASA Astrophysics Data System (ADS)

    Kim, E. J.; Tedesco, M.

    2005-12-01

    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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  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

    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.

  14. 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.

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  18. 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.

  19. Object-based cloud detection of multitemporal high-resolution stationary satellite images

    NASA Astrophysics Data System (ADS)

    Zheng, Lijuan; Wu, Yu; Yu, Tao; Yang, Jian; Zhang, Zhouwei

    2017-07-01

    Satellite remote sensing that utilizes highly accurate cloud detection is important for monitoring natural disasters. The GaoFen-4, China's first high-resolution stationary satellite, was recently launched and acquires imagery at a spatial resolution of 50 m and a high temporal resolution (up to 10 min). An object-based cloud detection method was conducted for a time series of GaoFen-4 images. The cloudy objects were obtained from the individual images, and the outlier detection of multiple temporal objects was further processed for refinement. In the initial cloud detection, the objects were segmented by the mean-shift algorithm, and their morphological features were extracted by extended attribute profiles. The threshold-detected cloudy objects were trained according to spectral and morphological features, and the initial objects were classified as cloudy or clear by a regularized least-squares classifier. Furthermore, the medians and standard deviations of the classified cloudy and clear objects were calculated and subsequently refined by the outlier detection of multiple temporal images. The clear object features deviated more than a multiple of standard deviations from the medians of the clear objects that were classified as cloudy objects. Additionally, the refined clear objects were obtained by a similar outlier detection method. Flood event monitoring using GaoFen-4 images showed that the average overall accuracy of the initial cloud detection was 83.4% and increased to 93.3% after refinement. This object-based cloud detection method was insensitive to variations in land objects and can effectively improve cloud detection within small or thin areas, which can be helpful for the monitoring of natural disasters.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. Automatic cloud detection for high resolution satellite stereo images and its application in terrain extraction

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  6. 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

  7. 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.

  8. [Study on panchromatic band broadening of new high-resolution satellite sensor].

    PubMed

    He, Wen-bin; Zhou, Chuan; Niu, Zheng; Liang, Li-jiao

    2010-07-01

    For developing a remote sensor, the selection of operating waveband is one of the most important factors for detecting and identifying target. In the present paper, the changes of atmospheric effects and imagery quality are simulated due to the increase in the response wave range of optical remote sensor from 0.50-0.85 mm to 0.45-0.90 mm by using MODTRAN4. The experimental results show that there is a slight increase of the adverse factors, including atmospheric transmittance, path radiance, and adjacency effect, after the working waveband has been widened. The disadvantages compared with the improvement in incident radiance, target-background contrast and image quality are negligible. In summary, the scheme of 0.45-0.90 mm is superior to 0.50-0.85 mm and it has been more widely used in the on-orbit operation high-resolution satellite sensor.

  9. 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

  10. 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

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

    USGS Publications Warehouse

    Giri, Chandra; Defourny, Pierre; 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.

  13. Satellite-based high-resolution mapping of rainfall over southern Africa

    NASA Astrophysics Data System (ADS)

    Meyer, Hanna; Drönner, Johannes; Nauss, Thomas

    2017-06-01

    A spatially explicit mapping of rainfall is necessary for southern Africa for eco-climatological studies or nowcasting but accurate estimates are still a challenging task. This study presents a method to estimate hourly rainfall based on data from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Rainfall measurements from about 350 weather stations from 2010-2014 served as ground truth for calibration and validation. SEVIRI and weather station data were used to train neural networks that allowed the estimation of rainfall area and rainfall quantities over all times of the day. The results revealed that 60 % of recorded rainfall events were correctly classified by the model (probability of detection, POD). However, the false alarm ratio (FAR) was high (0.80), leading to a Heidke skill score (HSS) of 0.18. Estimated hourly rainfall quantities were estimated with an average hourly correlation of ρ = 0. 33 and a root mean square error (RMSE) of 0.72. The correlation increased with temporal aggregation to 0.52 (daily), 0.67 (weekly) and 0.71 (monthly). The main weakness was the overestimation of rainfall events. The model results were compared to the Integrated Multi-satellitE Retrievals for GPM (IMERG) of the Global Precipitation Measurement (GPM) mission. Despite being a comparably simple approach, the presented MSG-based rainfall retrieval outperformed GPM IMERG in terms of rainfall area detection: GPM IMERG had a considerably lower POD. The HSS was not significantly different compared to the MSG-based retrieval due to a lower FAR of GPM IMERG. There were no further significant differences between the MSG-based retrieval and GPM IMERG in terms of correlation with the observed rainfall quantities. The MSG-based retrieval, however, provides rainfall in a higher spatial resolution. Though estimating rainfall from satellite data remains challenging, especially at high temporal resolutions, this study showed promising results

  14. 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.

  15. 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.

  16. What is the physical limit for the spatial resolution of satellite observations in the UV, vis, and NIR spectral range?

    NASA Astrophysics Data System (ADS)

    Wagner, Thomas

    2017-04-01

    Since 1995 satellite instruments are in orbit, which observe the sun light scattered back from the Earth with moderate spectral resolution. From these observations, global maps of many important atmospheric trace gases can be derived. While the spatial resolution of the first instrument (GOME-1) was rather coarse (320 x 40 km2) it has strongly improved in recent years (e.g. OMI: 13 x 24 km2) and will be improved further in the near future (Sentinel 5P: 3.5 x 7 km2). These improvements were mainly driven by technical development of the satellite instruments and the available data rates for downlinking the measured spectra. Nevertheless, the ultimate limit for the spatial resolution results from requirements on the signal to noise ratio of the measured spectra, which depend on the wavelength range, observatiom geometry and atmospheric composition (e.g. clouds), but also on the size of the detector and the spectral resolution and coverage of the satellite instruments. In this presentation we discuss these dependencies and estimate the best achievable spatial resolution for different species measured in different spectral ranges by UV, vis, NIR satellite instruments.

  17. 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.

  18. Skeletal muscle satellite cell migration to injured tissue measured with 111In-oxine and high-resolution SPECT imaging

    PubMed Central

    Elster, Jennifer L.; Rathbone, Christopher R.; Liu, Zhonglin; Liu, Xiasong; Barrett, Harrison H.; Rhoads, Robert P.; Allen, Ronald E.

    2014-01-01

    The delivery of adult skeletal muscle stem cells, called satellite cells, to several injured muscles via the circulation would be useful, however, an improved understanding of cell fate and biodistribution following their delivery is important for this goal to be achieved. The objective of this study was to evaluate the ability of systemically delivered satellite cells to home to injured skeletal muscle using single-photon emission computed tomography (SPECT) imaging of 111In-labeled satellite cells. Satellite cells labeled with 111In-oxine and green fluorescent protein (GFP) were injected intravenously after bupivicaine-induced injury to the tibialis anterior muscle. Animals were imaged with a high-resolution SPECT system called FastSPECT II for up to 7 days after transplantation. In vivo FastSPECT II imaging demonstrated a three to five-fold greater number of transplanted satellite cells in bupivicaine-injured muscle as compared to un-injured muscle after transplantation; a finding that was verified through autoradiograph analysis and quantification of GFP expression. Satellite cells also accumulated in other organs including the lung, liver, and spleen, as determined by biodistribution measurements. These data support the ability of satellite cells to home to injured muscle and support the use of SPECT and autoradiograph imaging techniques to track systemically transplanted 111In labeled satellite cells in vivo, and suggest their homing may be improved by reducing their entrapment in filter organs. PMID:24190365

  19. Using very high resolution satellite images to identify coastal zone dynamics at North Western Black Sea

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    The availability of updated information about the extension and characteristics of land cover is a crucial issue in the perspective of a correct landscape planning and management of marine coastal zones. Satellite remote sensing data can provide accurate information about land coverage at different scales and the recent availability of very high resolution images definitely improved the precision of coastal zone spatio-temporal changes. The Romanian North Western coastal and shelf zones of the Black Sea and Danube delta are a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in the Black Sea's ecosystem and resources are due to natural and anthropogenic causes (increase in the nutrient and pollutant load of rivers input, industrial and municipal wastewater pollution along the coast, and dumping on the open sea). A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic processes, coastal erosion, sedimentation dynamics, mapping of macrophyte fields, water quality, and climatic change effects. Use of satellite images is of great help for coastal zone monitoring and environmental impact assessment. Synergetic use of in situ measurements with multisensors satellite data could provide a complex assessment of spatio-temporal changes. In this study was developed a method for extracting coastal zone features information as well as landcover dynamics from IKONOS, very high resolution images for North-Western Black Sea marine coastal zone. The main objective was obtaining reliable data about the spatio-temporal coastal zone changes in two study areas located in Constanta urban area and Danube Delta area. We used an object-oriented approach based on preliminary segmentation and classification of the resulting object. First of all, segmentation parameters were tested and selected comparing segmented polygons with

  20. 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

  1. 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.

  2. Supersampling multiframe blind deconvolution resolution enhancement of adaptive-optics-compensated imagery of LEO satellites

    NASA Astrophysics Data System (ADS)

    Gerwe, David R.; Lee, David J.; Barchers, Jeffrey D.

    2000-10-01

    A post-processing methodology for reconstructing undersampled image sequences with randomly varying blur is described which can provide image enhancement beyond the sampling resolution of the sensor. This method is demonstrated on simulated imagery and on adaptive optics compensated imagery taken by the Starfire Optical Range 3.5 meter telescope that has been artificially undersampled. Also shown are the results of multiframe blind deconvolution of some of the highest quality optical imagery of low earth orbit satellites collected with a ground based telescope to date. The algorithm used is a generalization of multiframe blind deconvolution techniques which includes a representation of spatial sampling by the focal plane array elements in the forward stochastic model of the imaging system. This generalization enables the random shifts and shape of the adaptive compensated PSF to be used to partially eliminate the aliasing effects associated with sub- Nyquist sampling of the image by the focal plane array. The method could be used to reduce resolution loss which occurs when imaging in wide FOV modes.

  3. Hitomi X-ray Astronomy Satellite: Power of High-Resolution Spectroscopy

    NASA Astrophysics Data System (ADS)

    Odaka, Hirokazu

    2017-01-01

    Hitomi (ASTRO-H) is an X-ray observatory developed by an international collaboration led by JAXA. An X-ray microcalorimeter onboard this satellite has opened a new window of high-resolution spectroscopy with an unprecedented energy resolution of 5 eV (FWHM) at 6 keV. The spacecraft was launched on February 17, 2016 from Tanegashima Island, Japan, and we completed initial operations including deployment of the hard X-ray imagers on the extensible optical bench. All scientific instruments had successfully worked until the sudden loss of the mission on March 26. We have obtained a spectrum showing fully resolved emission lines through the first-light observation of the Perseus Cluster. The line-of-sight velocity dispersion of 164 +/- 10 km s-1 reveals the quiescent environment of intracluster medium at the cluster core, implying that measured cluster mass requires little correction for the turbulent pressure. We also discuss observations to the Galactic Center which could be performed with Hitomi.

  4. [Design and study of a high resolution vacuum ultraviolet imaging spectrometer carried by satellite].

    PubMed

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

    2011-12-01

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

  5. 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.

  6. 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.

  7. Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index

    NASA Astrophysics Data System (ADS)

    Yang, Dedi; Chen, Jin; Zhou, Yuan; Chen, Xiang; Chen, Xuehong; Cao, Xin

    2017-06-01

    Plastic greenhouses (PGs) are an important agriculture development technique to protect and control the growing environment for food crops. The extensive use of PGs can change the agriculture landscape and affects the local environment. Accurately mapping and estimating the coverage of PGs is a necessity to the strategic planning of modern agriculture. Unfortunately, PG mapping over large areas is methodologically challenging, as the medium spatial resolution satellite imagery (such as Landsat data) used for analysis lacks spatial details and spectral variations. To fill the gap, the paper proposes a new plastic greenhouse index (PGI) based on the spectral, sensitivity, and separability analysis of PGs using medium spatial resolution images. In the context of the Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, the paper examines the effectiveness and capability of the proposed PGI. The results indicate that PGs in Landsat ETM+ image can be successfully detected by the PGI if the PG fraction is greater than 12% in a mixed pixel. A kappa coefficient of 0.83 and overall accuracy of 91.2% were achieved when applying the proposed PGI in the case of Weifang District, Shandong, China. These results show that the proposed index can be applied to identifying transparent PGs in atmospheric corrected Landsat image and has the potential for the digital mapping of plastic greenhouse coverage over a large area.

  8. 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.

  9. 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

  10. High resolution space characterization of water vapor from satellite measurements and local area model

    NASA Astrophysics Data System (ADS)

    Montopoli, M.; Marzano, F. S.; Pichelli, E.; Cimini, D.; Ferretti, R.; Bonafoni, S.; Perissin, D.; Rocca, F.; Pierdicca, N.

    2009-04-01

    Synthetic Aperture Radar (SAR) is a well established microwave imaging system from which measurements of surface deformations of the order of centimeters can be derived and than several useful land applications (e.g.: the analysis of progressive tectonic motions, or to the improvement of a Digital Terrain Model) can be provided to the community. Among the main limitations affecting the Interferometric SAR (InSAR) measurements, especially at C and X frequency bands, the atmosphere surely plays a relevant role. When two interferometric SAR images are not simultaneously acquired, the electromagnetic wave received from the SAR sensor, mounted on a satellite platform, after interactions with the ground, may be differently affected by the atmosphere which induces an unwanted component on the received signal. In particular, the random nature of the atmospheric state (i.e.: different humidity, temperature and pressure) between the two acquired SAR observations will have a visible and fatal consequences on the interferometric phase. Among others, the water vapor is an important contributor to the error budget of InSAR data and for this reason its spatial and temporal characterization plays an important role. In this work, the spatial characterization of vertical Integrated Water Vapor (IWV), as seen from various satellite sensors, will be dealt with. Data acquired from Envisat-Meris, and Terra-Modis and Aqua-Modis spectrometer, operating at infrared frequencies at spatial resolution of 0.3, 1 and 1 km respectively, will be compared with simulations derived from MM5 weather forecast model at 1km resolution as well. The InSAR signal from ASAR of Envisat platform and RadarSat is also exploited to derive estimates of differential IWV (dIWV) at very high spatial resolutions (about 100 m). dIWV estimates are analyzed as well and compared together with those derived from previously mentioned spectrometers in terms of correlation structures. The results of the comparisons here

  11. Development and Evaluation of Global Wetlands Mappings from Coarse-Resolution Satellite Microwave Remote Sensing

    NASA Astrophysics Data System (ADS)

    Schroeder, R.; McDonald, K. C.; Podest, E.; Willacy, K.; Jones, L. A.; Kimball, J. S.; Zimmermann, R.

    2010-12-01

    Wetlands exert major impacts on global biogeochemistry, hydrology, and biological diversity. The extent and seasonal, interannual, and decadal variation of inundated wetland area play key roles in ecosystem dynamics. Wetlands contribute approximately one fourth of the total methane annually emitted to the atmosphere and are identified as the primary contributor to interannual variations in the growth rate of atmospheric methane concentrations. Despite the importance of these environments in the global cycling of carbon and water and to current and future climate, the extent and dynamics of global wetlands remain poorly characterized and modeled, primarily because of the scarcity of suitable regional-to-global remote-sensing data for characterizing their distribution and dynamics. We present a satellite-based approach for mapping wetlands globally at coarse-resolution (25km). The approach employs a mixture model applied to ~8 years (2002-2009) of daily 18.7 GHz, V and H polarization brightness temperature (Tb) data from the Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and daily Ku-band (13.4 GHz) radar backscatter data from SeaWinds-on-QuikSCAT. The combined passive-active microwave mixture model approach utilizes site-specific MODIS IGBP land cover information to account for the effect of vegetation structure on the microwave remote sensing-based retrieval of surface inundation dynamics. A comparison with coarse-resolution global maps of fractional open water cover (Fw) derived from radiometric inversion of daily AMSR-E 18.7 GHz, V and H polarized Tb observations demonstrates agreement in terms of both spatial distribution and temporal variability of the major global wetland complexes, but differences in the magnitudes of the Fw retrievals. Wetlands products obtained from both satellite-based methods are compared with the high-resolution (250m) land water mask developed from MODIS and SRTM L3 (MOD44W) as well as the global lake and wetland database (GLWD

  12. 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.

  13. PolarCube: A High Resolution Passive Microwave Satellite for Sounding and Imaging at 118 GHz

    NASA Astrophysics Data System (ADS)

    Weaver, R. L.; Gallaher, D. W.; Gasiewski, A. J.; Sanders, B.; Periasamy, L.; Hwang, K.; Alvarenga, G.; Hickey, A. M.

    2013-12-01

    PolarCube is a 3U CubeSat hosting an eight-channel passive microwave spectrometer operating at the 118.7503 GHz oxygen resonance that is currently in development. The project has an anticipated launch date in early 2015. It is currently being designed to operate for approximately12 months on orbit to provide the first global 118-GHz spectral imagery of the Earth over full seasonal cycle and to sound Arctic vertical temperature structure. The principles used by PolarCube for temperature sounding are well established in number of peer-reviewed papers going back more than two decades, although the potential for sounding from a CubeSat has never before been demonstrated in space. The PolarCube channels are selected to probe atmospheric emission over a range of vertical levels from the surface to lower stratosphere. This capability has been available operationally for over three decades, but at lower frequencies and higher altitudes that do not provide the spatial resolution that will be achieved by PolarCube. While the NASA JPSS ATMS satellite sensor provides global coverage at ~32 km resolution, the PolarCube will improve on this resolution by a factor of two, thus facilitating the primary science goal of determining sea ice concentration and extent while at the same time collecting profile data on atmospheric temperature. Additionally, we seek to correlate freeze-thaw line data from SMAP with our near simultaneously collected atmospheric temperature data. In addition to polar science, PolarCube will provide a first demonstration of a very low cost passive microwave sounder that if operated in a fleet configuration would have the potential to fulfill the goals of the Precipitation Atmospheric Temperature and Humidity (PATH) mission, as defined in the NRC Decadal Survey. PolarCube 118-GHz passive microwave spectrometer in deployed configuration

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

    USDA-ARS?s Scientific Manuscript database

    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 ...

  15. High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase.

    Treesearch

    Jeffrey T. Morisette; Jaime E. Nickeson; Paul Davis; Yujie Wang; Yuhong Tian; Curtis E. Woodcock; Nikolay Shabanov; Matthew Hansen; Warren B. Cohen; Doug R. Oetter; Robert E. Kennedy

    2003-01-01

    Phase 1I of the Scientific Data Purchase (SDP) has provided NASA investigators access to data from four different satellite and airborne data sources. The Moderate Resolution Imaging Spectrometer (MODIS) land discipline team (MODLAND) sought to utilize these data in support of land product validation activities with a lbcus on tile EOS Land Validation Core Sites. These...

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

    PubMed

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

    2014-11-25

    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.

  17. 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.

  18. Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    Advancements in satellite sensor technology enabling capturing of geometrically accurate images of earth's surface coupled with DGPS/ETS and GIS technology holds the capability of large scale mapping of land resources at cadastral level. High Resolution Satellite Images depict field bunds distinctly. Thus plot parcels are to be delineated from cloud free ortho-images and obscured/difficult areas are to be surveyed using DGPS and ETS. The vector datasets thus derived through RS/DGPS/ETS survey are to be integrated in GIS environment to generate the base cadastral vector datasets for further settlement/title confirmation activities. The objective of this paper is to illustrate the efficacy of a hybrid methodology employed in Pitambarpur Sasana village under Digapahandi Tahasil of Ganjam district, as a pilot project, particularly in Odisha scenario where the land parcel size is very small. One of the significant observations of the study is matching of Cadastral map area i.e. 315.454 Acres, the image map area i.e. 314.887 Acres and RoR area i.e. 313.815 Acre. It was revealed that 79 % of plots derived by high-tech survey method show acceptable level of accuracy despite the fact that the mode of area measurement by ground and automated method has significant variability. The variations are more in case of Government lands, Temple/Trust lands, Common Property Resources and plots near to river/nalas etc. The study indicates that the adopted technology can be extended to other districts and cadastral resurvey and updating work can be done for larger areas of the country using this methodology.

  19. Validation of High Resolution IMERG Satellite Precipitation over the Global Oceans using OceanRAIN

    NASA Astrophysics Data System (ADS)

    Kucera, Paul; Klepp, Christian

    2017-04-01

    Precipitation is a key parameter of the essential climate variables in the Earth System that is a key variable in the global water cycle. Observations of precipitation over oceans is relatively sparse. Satellite observations over oceans is the only viable means of measuring the spatially distribution of precipitation. In an effort to improve global precipitation observations, the research community has developed a state of the art precipitation dataset as part of the NASA/JAXA Global Precipitation Measurement (GPM) program. The satellite gridded product that has been developed is called Integrated Multi-satelliE Retrievals for GPM (IMERG), which has a maximum spatial resolution of 0.1° x 0.1° and temporal 30 minute. Even with the advancements in retrievals, there is a need to quantify uncertainty of IMERG especially over oceans. To address this need, the OceanRAIN dataset has been used to create a comprehensive database to compare IMERG products. The OceanRAIN dataset was collected using an ODM-470 optical disdrometer that has been deployed on 12 research vessels worldwide with 6 long-term installations operating in all climatic regions, seasons and ocean basins. More than 5.5 million data samples have been collected on the OceanRAIN program. These data were matched to IMERG grids for the study period of 15 March 2014-31 January 2016. This evaluation produced over a 1000 matched pairs with precipitation observed at the surface. These matched pairs were used to evaluate the performance of IMERG for different latitudinal bands and precipitation regimes. The presentation will provide an overview of the study and summary of evaluation results.

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. Research of the on-orbit self-adaptive focusing technology base on the configurational entropy for high resolution satellites

    NASA Astrophysics Data System (ADS)

    Guo, Linghua

    Complex emission state, dynamic orbit space environment, and the imaging requirement of high resolution up to 0.1" for low-contrast targets, make “on-orbit automatic focusing technique" become one of the key technique of the high quality image acquisition for high resolution satellites, especially for long focal length and the large aperture optical remote sensors. Based on the minimum entropy auto-focus (AF) theory, this paper proposed an on-orbit automatic focusing method of configurational entropy criterion for high resolution satellites. The image processing efficiency can be increased by begin{math} 2^2^k times using such technique. On-orbit automatic focusing technique base on configurational entropy reduces the times of focusing movement, it has the character of fast self-adaptive AF speed, high precision, and it can meet the space-exploration acquirement of low-contrast targets.

  6. Exploring image data assimilation in the prospect of high-resolution satellite oceanic observations

    NASA Astrophysics Data System (ADS)

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

    2017-07-01

    Satellite sensors increasingly provide high-resolution (HR) observations of the ocean. They supply observations of sea surface height (SSH) and of tracers of the dynamics such as sea surface salinity (SSS) and sea surface temperature (SST). In particular, the Surface Water Ocean Topography (SWOT) mission will provide measurements of the surface ocean topography at very high-resolution (HR) delivering unprecedented information on the meso-scale and submeso-scale dynamics. This study investigates the feasibility to use these measurements to reconstruct meso-scale features simulated by numerical models, in particular on the vertical dimension. A methodology to reconstruct three-dimensional (3D) multivariate meso-scale scenes is developed by using a HR numerical model of the Solomon Sea region. An inverse problem is defined in the framework of a twin experiment where synthetic observations are used. A true state is chosen among the 3D multivariate states which is considered as a reference state. In order to correct a first guess of this true state, a two-step analysis is carried out. A probability distribution of the first guess is defined and updated at each step of the analysis: (i) the first step applies the analysis scheme of a reduced-order Kalman filter to update the first guess probability distribution using SSH observation; (ii) the second step minimizes a cost function using observations of HR image structure and a new probability distribution is estimated. The analysis is extended to the vertical dimension using 3D multivariate empirical orthogonal functions (EOFs) and the probabilistic approach allows the update of the probability distribution through the two-step analysis. Experiments show that the proposed technique succeeds in correcting a multivariate state using meso-scale and submeso-scale information contained in HR SSH and image structure observations. It also demonstrates how the surface information can be used to reconstruct the ocean state below

  7. A decadal observation of vegetation dynamics using multi-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Chiang, Yang-Sheng; Chen, Kun-Shan; Chu, Chang-Jen

    2012-10-01

    Vegetation cover not just affects the habitability of the earth, but also provides potential terrestrial mechanism for mitigation of greenhouse gases. This study aims at quantifying such green resources by incorporating multi-resolution satellite images from different platforms, including Formosat-2(RSI), SPOT(HRV/HRG), and Terra(MODIS), to investigate vegetation fractional cover (VFC) and its inter-/intra-annual variation in Taiwan. Given different sensor capabilities in terms of their spatial coverage and resolution, infusion of NDVIs at different scales was used to determine fraction of vegetation cover based on NDVI. Field campaign has been constantly conducted on a monthly basis for 6 years to calibrate the critical NDVI threshold for the presence of vegetation cover, with test sites covering IPCC-defined land cover types of Taiwan. Based on the proposed method, we analyzed spatio- temporal changes of VFC for the entire Taiwan Island. A bimodal sequence of VFC was observed for intra-annual variation based on MODIS data, with level around 5% and two peaks in spring and autumn marking the principal dual-cropping agriculture pattern in southwestern Taiwan. Compared to anthropogenic-prone variation, the inter-annual VFC (Aug.-Oct.) derived from HRV/HRG/RSI reveals that the moderate variations (3%) and the oscillations were strongly linked with regional climate pattern and major disturbances resulting from extreme weather events. Two distinct cycles (2002-2005 and 2005-2009) were identified in the decadal observations, with VFC peaks at 87.60% and 88.12% in 2003 and 2006, respectively. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

  8. 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.

  9. 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.

  10. 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

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

    PubMed Central

    Xia, Nan; Wang, YaJun; Xu, Hao; Sun, YueFan; Yuan, Yi; Cheng, Liang; Jiang, PengHui; Li, ManChun

    2016-01-01

    Prime farmland (PF) is defined as high-quality farmland and a prime farmland protection area (PFPA, including related roads, waters and facilities) is a region designated for the special protection of PF. However, rapid urbanization in China has led to a tremendous farmland loss and to the degradation of farmland quality. Based on remote sensing and geographic information system technology, this study developed a semiautomatic procedure for designating PFPAs using high-resolution satellite imagery (HRSI), which involved object-based image analysis, farmland composite evaluation, and spatial analysis. It was found that the HRSIs can provide elaborate land-use information, and the PFPA demarcation showed strong correlation with the farmland area and patch distance. For the benefit of spatial planning and management, different demarcation rules should be applied for suburban and exurban areas around a metropolis. Finally, the overall accuracy of HRSI classification was about 80% for the study area, and high-quality farmlands from evaluation results were selected as PFs. About 95% of the PFs were demarcated within the PFPAs. The results of this study will be useful for PFPA planning and the methods outlined could help in the automatic designation of PFPAs from the perspective of the spatial science. PMID:28000668

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  13. 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.

  14. The P2L method of mismatch detection for push broom high-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Wan, Yi; Zhang, Yongjun

    2017-08-01

    RANSAC-based mismatch detection methods are widely used in the geometric registration of images. Despite their prevalence, setting the detection thresholds for different situations continues to be difficult without an appropriate geometric model. In high-resolution satellite images, simple image-space transformations are commonly influenced by the terrain or elevation errors. This paper introduces a new method, called the P2L method, which uses the distance between the transformed right image point and the segment of the corresponding epipolar line to distinguish the correct matches and mismatches. The affine model of the P2L method is solved to transform the right image points towards the segment of the epipolar line. The images for demonstration were acquired by GeoEye-1, Ikonos-2, and Ziyuan-3; and each type of image pairs had different intersection angles to explore the influence of the elevation error. The correct matches were manually collected and the mismatches were simulated. The experiments in this paper, which used only correct matches, demonstrated that this method was very robust with one specific threshold (five pixels) and was suitable for all the image pairs. The experiments using simulated mismatches and real matching points demonstrated that this method was able to distinguish most of the mismatches; and even for the image pair that had a 54-degree intersection angle, the ratio of mismatches was reduced from 81% to 11%.

  15. 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.

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

    PubMed

    Xia, Nan; Wang, YaJun; Xu, Hao; Sun, YueFan; Yuan, Yi; Cheng, Liang; Jiang, PengHui; Li, ManChun

    2016-12-21

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

  17. A Multi-stage Method to Extract Road from High Resolution Satellite Image

    NASA Astrophysics Data System (ADS)

    Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang

    2014-03-01

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

  18. 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.

  19. 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%.

  20. 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

  1. The Critical Need for Future Mid-Resolution Thermal Infrared Satellite Sensors

    NASA Astrophysics Data System (ADS)

    Vincent, R. K.

    2006-12-01

    Eight future applications of data from mid-resolution thermal infrared satellite sensors are suggested, from least to most significant as follows: 8. Map thin ice unsafe for ice-fishing in the Great Lakes as a warning to winter fishermen; 7. Map ammonia plumes to locate large ammonia stockpiles (Homeland Security) and to monitor concentrated animal feeding operations (CAFOs); 6. Map types of surface algae in ocean, lakes, and rivers, especially those containing surface diatoms; 5. Monitor urban heat islands to determine the cooling affects of painting visibly dark surfaces with bright paints or coatings; 4. Map rock-types and soil-types of non- vegetated regions world-wide, a task which ASTER cannot complete in its current lifetime; 3. Detect surface warming of rocks under increased stress and pressure as an earthquake precursor; 2. Map pollutant gases, especially sulfur dioxide, which is important both for smokestack monitoring and volcanic eruption precursors; 1. Map methane escape into the atmosphere from methane clathrate destabilization as a key warning of imminent and drastic temperature rises in the troposphere. Each of these applications will be briefly discussed and past examples will be given for most of them.

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

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  3. Glacier Inventory of the Cordillera Real - Bolivia using high resolution satellite images ALOS and CBERS-2B

    NASA Astrophysics Data System (ADS)

    Ramirez, E.; Ribeiro, R.; Machaca, A.; Fuertes, R.; Simões, J.

    2012-04-01

    The Andes represent approximately 99% of tropical glaciers worldwide. In Bolivia (South America) the glacier coverage represents 20% of the Andean glaciers. During the last 30 years a dramatic reduction of glacier surfaces in the Bolivian Andes were observed (Ramirez et al. 2001), leading to fears about the disappearance of several small glaciers in the next three decades. The first glacier inventory in this region was made based on aerial photographs for the 70's and 80's using geodetic methods (Jordan 1991). However, the realization of new photogrammetric flights over the Andes is expensive, which made it impossible to update the glacier inventory. Most Bolivian glaciers are less than 1 km2 making it difficult to use conventional satellite imagery with average resolutions (15 m or 30m). The development of new high resolution sensors mounted on observational satellites with stereoscopic capabilities permits the application of photogrammetric techniques for the precise delimitation of glacier boundaries. A new glacier inventory of the Cordillera Real in Bolivia was performed using high-resolution images (2.5 m) from ALOS (Japan) and CBERS-2B (China-Brazil) satellites within the framework of the Andean Regional Project on Climate Change Adaptation (PRAA) supported by the World Bank. The PRISM sensor of ALOS satellite (Panchromatic Remote-sensing Instrument for Stereo Mapping) and HRC of CBERS-2B satellite (High Resolution Panchromatic Camera) were used in this study. 57 ground control points (GCP) were measured along the Cordillera Real through dual-frequency DGPS's. The boundaries of 476 glaciers were identified and digitized by a digital photogrammetric station. The current glacier surface of the Cordillera Real is 185.5 km2. Compared with the previous inventory of the 80's it represent a loss of 43% of the glacier area.

  4. 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.

  5. 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.

  6. The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation

    NASA Astrophysics Data System (ADS)

    Williams, Jason E.; Folkert Boersma, K.; Le Sager, Phillipe; Verstraeten, Willem W.

    2017-02-01

    We provide a comprehensive description of the high-resolution version of the TM5-MP global chemistry transport model, which is to be employed for deriving highly resolved vertical profiles of nitrogen dioxide (NO2), formaldehyde (CH2O), and sulfur dioxide (SO2) for use in satellite retrievals from platforms such as the Ozone Monitoring Instrument (OMI) and the Sentinel-5 Precursor, and the TROPOspheric Monitoring Instrument (tropOMI). Comparing simulations conducted at horizontal resolutions of 3° × 2° and 1° × 1° reveals differences of ±20 % exist in the global seasonal distribution of 222Rn, being larger near specific coastal locations and tropical oceans. For tropospheric ozone (O3), analysis of the chemical budget terms shows that the impact on globally integrated photolysis rates is rather low, in spite of the higher spatial variability of meteorological data fields from ERA-Interim at 1° × 1°. Surface concentrations of O3 in high-NOx regions decrease between 5 and 10 % at 1° × 1° due to a reduction in NOx recycling terms and an increase in the associated titration term of O3 by NO. At 1° × 1°, the net global stratosphere-troposphere exchange of O3 decreases by ˜ 7 %, with an associated shift in the hemispheric gradient. By comparing NO, NO2, HNO3 and peroxy-acetyl-nitrate (PAN) profiles against measurement composites, we show that TM5-MP captures the vertical distribution of NOx and long-lived NOx reservoirs at background locations, again with modest changes at 1° × 1°. Comparing monthly mean distributions in lightning NOx and applying ERA-Interim convective mass fluxes, we show that the vertical re-distribution of lightning NOx changes with enhanced release of NOx in the upper troposphere. We show that surface mixing ratios in both NO and NO2 are generally underestimated in both low- and high-NOx scenarios. For Europe, a negative bias exists for [NO] at the surface across the whole domain, with lower biases at 1° × 1° at only ˜ 20

  7. 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

  8. 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

  9. Identification and classification of structural soil conservation measures based on very high resolution stereo satellite data.

    PubMed

    Eckert, Sandra; Tesfay Ghebremicael, Selamawit; Hurni, Hans; Kohler, Thomas

    2017-05-15

    Land degradation affects large areas of land around the globe, with grave consequences for those living off the land. Major efforts are being made to implement soil and water conservation measures that counteract soil erosion and help secure vital ecosystem services. However, where and to what extent such measures have been implemented is often not well documented. Knowledge about this could help to identify areas where soil and water conservation measures are successfully supporting sustainable land management, as well as areas requiring urgent rehabilitation of conservation structures such as terraces and bunds. This study explores the potential of the latest satellite-based remote sensing technology for use in assessing and monitoring the extent of existing soil and water conservation structures. We used a set of very high resolution stereo Geoeye-1 satellite data, from which we derived a detailed digital surface model as well as a set of other spectral, terrain, texture, and filtered information layers. We developed and applied an object-based classification approach, working on two segmentation levels. On the coarser level, the aim was to delimit certain landscape zones. Information about these landscape zones is useful in distinguishing different types of soil and water conservation structures, as each zone contains certain specific types of structures. On the finer level, the goal was to extract and identify different types of linear soil and water conservation structures. The classification rules were based mainly on spectral, textural, shape, and topographic properties, and included object relationships. This approach enabled us to identify and separate from other classes the majority (78.5%) of terraces and bunds, as well as most hillside terraces (81.25%). Omission and commission errors are similar to those obtained by the few existing studies focusing on the same research objective but using different types of remotely sensed data. Based on our results

  10. Bias Adjustment of high spatial/temporal resolution Satellite Precipitation Estimation relying on Gauge-Based precipitation over China

    NASA Astrophysics Data System (ADS)

    Yu, J.; Pan, Y.; Shen, Y.

    2010-12-01

    Satellite precipitation data has been widely used in the forecasting and research of weather and climate because of its high spatial/temporal resolution, especially in the area of limited access to ground-based measurements. The distribution of gauge stations in China is very uniform with most gauge stations located in Eastern China and few gauge stations located in Western China. So the using of satellite precipitation data in China is very important. Although the satellite precipitation data has a good spatial construction, its estimation value is less accurate and has distinct systematic bias comparing to gauge-based one. The bias of satellite precipitation data should be adjusted before using it. In this paper, the CMORPH (Climate Prediction Center Morphing Technique) 30-min precipitation products is chosen to represent the large-scale precipitation of China and be adjusted based on hourly rain gauge analysis over China by interpolating from more than 10000 stations collected and quality controlled by the National Meteorological Information Center of the China Meteorological by using a probability density function (PDF) matching method (Wang and Xie, 2005). After bias-adjustment by PDF matching, we get a less systematic bias and high-resolution satellite precipitation product, which is hourly precipitation on a 0.1°latitude/longitude grid over China. Adjusted values are more close to the gauge observations, and the probability density function of corrected precipitation products is the same as that of the gauge-based precipitation. In Western China, the quantity value of corrected precipitation estimates is obviously increased comparing to the original estimate value. On the other hand, the spatial construction is still maintenance of satellite products.

  11. [Extraction of buildings three-dimensional information from high-resolution satellite imagery based on Barista software].

    PubMed

    Zhang, Pei-feng; Hu, Yuan-man; He, Hong-shi

    2010-05-01

    The demand for accurate and up-to-date spatial information of urban buildings is becoming more and more important for urban planning, environmental protection, and other vocations. Today's commercial high-resolution satellite imagery offers the potential to extract the three-dimensional information of urban buildings. This paper extracted the three-dimensional information of urban buildings from QuickBird imagery, and validated the precision of the extraction based on Barista software. It was shown that the extraction of three-dimensional information of the buildings from high-resolution satellite imagery based on Barista software had the advantages of low professional level demand, powerful universality, simple operation, and high precision. One pixel level of point positioning and height determination accuracy could be achieved if the digital elevation model (DEM) and sensor orientation model had higher precision and the off-Nadir View Angle was relatively perfect.

  12. Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data

    NASA Astrophysics Data System (ADS)

    Wecht, Kevin J.; Jacob, Daniel J.; Frankenberg, Christian; Jiang, Zhe; Blake, Donald R.

    2014-06-01

    We estimate methane emissions from North America with high spatial resolution by inversion of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite observations using the Goddard Earth Observing System Chemistry (GEOS-Chem) chemical transport model and its adjoint. The inversion focuses on summer 2004 when data from the Intercontinental Chemical Transport Experiment-North America (INTEX-A) aircraft campaign over the eastern U.S. are available to validate the SCIAMACHY retrievals and evaluate the inversion. From the INTEX-A data we identify and correct a water vapor-dependent bias in the SCIAMACHY data. We conduct an initial inversion of emissions on the horizontal grid of GEOS-Chem (1/2° × 2/3°) to identify correction tendencies relative to the Emission Database for Global Atmospheric Research (EDGAR) v4.2 emission inventory used as a priori. We then cluster these grid cells with a hierarchical algorithm to extract the maximum information from the SCIAMACHY observations. A 1000 cluster ensemble can be adequately constrained, providing 100 km resolution across North America. Analysis of results indicates that the Hudson Bay Lowland wetlands source is 2.1 Tg a-1, lower than the a priori but consistent with other recent estimates. Anthropogenic U.S. emissions are 30.1 ± 1.3 Tg a-1, compared to 25.8 Tg a-1 and 28.3 Tg a-1 in the EDGAR v4.2 and Environmental Protection Agency (EPA) inventories, respectively. We find that U.S. livestock emissions are 40% greater than in these two inventories. No such discrepancy is apparent for overall U.S. oil and gas emissions, although this may reflect some compensation between overestimate of emissions from storage/distribution and underestimate from production. We find that U.S. livestock emissions are 70% greater than the oil and gas emissions, in contrast to the EDGAR v4.2 and EPA inventories where these two sources are of comparable magnitude.

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

    NASA Astrophysics Data System (ADS)

    Cross, M.

    2016-12-01

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

  14. 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

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

    DOE PAGES

    Turner, A. J.; Jacob, D. J.; Wecht, K. J.; ...

    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

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

    DOE PAGES

    Turner, A. J.; Jacob, D. J.; Wecht, K. J.; ...

    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

  17. River discharge estimation at daily resolution from satellite altimetry over an entire river basin

    NASA Astrophysics Data System (ADS)

    Tourian, M. J.; Schwatke, C.; Sneeuw, N.

    2017-03-01

    One of the main challenges of hydrological modeling is the poor spatiotemporal coverage of in situ discharge databases which have steadily been declining over the past few decades. It has been demonstrated that water heights over rivers from satellite altimetry can sensibly be used to deal with the growing lack of in situ discharge data. However, the altimetric discharge is often estimated from a single virtual station suffering from coarse temporal resolution, sometimes with data outages, poor modeling and inconsistent sampling. In this study, we propose a method to estimate daily river discharge using altimetric time series of an entire river basin including its tributaries. Here, we implement a linear dynamic model to (1) provide a scheme for data assimilation of multiple altimetric discharge along a river; (2) estimate daily discharge; (3) deal with data outages, and (4) smooth the estimated discharge. The model consists of a stochastic process model that benefits from the cyclostationary behavior of discharge. Our process model comprises the covariance and cross-covariance information of river discharge at different gauges. Combined with altimetric discharge time series, we solve the linear dynamic system using the Kalman filter and smoother providing unbiased discharge with minimum variance. We evaluate our method over the Niger basin, where we generate altimetric discharge using water level time series derived from missions ENVISAT, SARAL/AltiKa, and Jason-2. Validation against in situ discharge shows that our method provides daily river discharge with an average correlation of 0.95, relative RMS error of 12%, relative bias of 10% and NSE coefficient of 0.7. Using a modified NSE-metric, that assesses the non-cyclostationary behavior, we show that our estimated discharge outperforms available legacy mean daily discharge.

  18. 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.

  19. A new ant based distributed framework for urban road map updating from high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Zarrinpanjeh, Nima; Samadzadegan, Farhad; Schenk, Toni

    2013-04-01

    Receiving updated information about the network of roads from high resolution satellite imagery is a crucially important issue in continuously changing developing urban regions. Considering experiences in road extraction and also exploiting distributed evolutionary computational approaches, in this paper a new framework for road map updating from remotely sensed data is proposed. Three main computational entities of ant-agent, seed extractor and algorithm library are designed and road map updating is performed through three main stages of verification of the old map, extraction of possible roads and grouping of the results of both stages. Extracting corresponding pixels to each road element in the map, an object level supervised classification or any available road verification algorithm from the library capable of producing a road likeliness value is applied. Since road extraction is a simple and also a complex problem, more comprehensive algorithms are chosen from library iteratively by ant-agents so the decision about verification and rejection of each road element is finally made. Ant-agents facilitate choosing road elements and moving of ant agents via stigmergic communication by pheromone cast and evaporation. The proposed method is developed and tested using GeoEye-1 pan-sharpen imagery and 1:2000 corresponding digital vector map of the region. As observed, the results are satisfactory in terms of detection, verification and extraction of roads and generation of the updated map specifically in case of inspection of main roads. Besides, some missed road items are reported in case of inspection of bystreets and alleys specially when situated at the margin of the image. Completeness, correctness and quality measures are computed for evaluation of the initial and the resulted updated maps. The computed measures verify the improvement of the updated map.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-05-01

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

  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.

  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. 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.

  6. An Alternative Approach for Registration of High-Resolution Satellite Optical Imagery and ICESat Laser Altimetry Data

    PubMed Central

    Liu, Shijie; Lv, Yi; Tong, Xiaohua; Xie, Huan; Liu, Jun; Chen, Lei

    2016-01-01

    Satellite optical images and altimetry data are two major data sources used in Antarctic research. The integration use of these two datasets is expected to provide more accurate and higher quality products, during which data registration is the first issue that needs to be solved. This paper presents an alternative approach for the registration of high-resolution satellite optical images and ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry data. Due to the sparse distribution characteristic of the ICESat laser point data, it is difficult and even impossible to find same-type conjugate features between ICESat data and satellite optical images. The method is implemented in a direct way to correct the point-to-line inconsistency in image space through 2D transformation between the projected terrain feature points and the corresponding 2D image lines, which is simpler than discrepancy correction in object space that requires stereo images for 3D model construction, and easier than the indirect way of image orientation correction via photogrammetric bundle adjustment. The correction parameters are further incorporated into imaging model through RPCs (Rational Polynomial Coefficients) generation/regeneration for the convenience of photogrammetric applications. The experimental results by using the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images and ZY-3 (Ziyuan-3 satellite) images for registration with ICESat data showed that sub-pixel level registration accuracies were achieved after registration, which have validated the feasibility and effectiveness of the presented approach. PMID:27898048

  7. An Alternative Approach for Registration of High-Resolution Satellite Optical Imagery and ICESat Laser Altimetry Data.

    PubMed

    Liu, Shijie; Lv, Yi; Tong, Xiaohua; Xie, Huan; Liu, Jun; Chen, Lei

    2016-11-27

    Satellite optical images and altimetry data are two major data sources used in Antarctic research. The integration use of these two datasets is expected to provide more accurate and higher quality products, during which data registration is the first issue that needs to be solved. This paper presents an alternative approach for the registration of high-resolution satellite optical images and ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry data. Due to the sparse distribution characteristic of the ICESat laser point data, it is difficult and even impossible to find same-type conjugate features between ICESat data and satellite optical images. The method is implemented in a direct way to correct the point-to-line inconsistency in image space through 2D transformation between the projected terrain feature points and the corresponding 2D image lines, which is simpler than discrepancy correction in object space that requires stereo images for 3D model construction, and easier than the indirect way of image orientation correction via photogrammetric bundle adjustment. The correction parameters are further incorporated into imaging model through RPCs (Rational Polynomial Coefficients) generation/regeneration for the convenience of photogrammetric applications. The experimental results by using the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images and ZY-3 (Ziyuan-3 satellite) images for registration with ICESat data showed that sub-pixel level registration accuracies were achieved after registration, which have validated the feasibility and effectiveness of the presented approach.

  8. Evaluation of Rainfall Satellite Estimates Combined by Hourly Gauge Observations for High Spatial Resolution Over South Brazil

    NASA Astrophysics Data System (ADS)

    Ferreira, R. C.; Herdies, D. L.; Vila, D. A.; Souza, D.; Rozante, J. R.; Biscaro, T.; Vendrasco, E. P.; Beneti, C.

    2016-12-01

    The use of rainfall satellite estimates is widely used in hydrology, for application of water resources and monitoring of natural disasters. The rainfall satellite estimate data is generally applied in large basins as used in the simulations of stream flow. In addition to greater spatial coverage, satellites have less data interruptions when compared to rain gauges and radar, as an alternative to the continuous real-time monitoring even smaller basins. The goal of this work is evaluate different kind of products of satellite rainfall estimate combined with surface observations using the combined scheme technique (CoSch). The results with the current methodology using CMORPH, 3B42RT and GPM data were compared. The area of study covers the west of Southern Brazil and part of Paraguay, using on about 200 telemetric stations and three kinds of rainfall satellite estimation aforementioned. Currently, there are many products and methodologies which does this combination, but most of these products are combined daily. Using the telemetric stations is possible to get the accumulated precipitation in periods from half hour, allowing a really high temporal resolution in the area of study. This new product is able to validate the precipitation in the early hours of the atmospheric model, nowcasting and hydrology. The results show the important advantage in the quality of the final corrected products, which is necessary for hydrological monitoring of the South of Brazil.

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

    USDA-ARS?s Scientific Manuscript database

    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 ...

  10. 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

  11. Suitability of satellite derived and gridded sea surface temperature data sets for calibrating high-resolution marine proxy records

    NASA Astrophysics Data System (ADS)

    Ouellette, G., Jr.; DeLong, K. L.

    2016-02-01

    High-resolution proxy records of sea surface temperature (SST) are increasingly being produced using trace element and isotope variability within the skeletal materials of marine organisms such as corals, mollusks, sclerosponges, and coralline algae. Translating the geochemical variations within these organisms into records of SST requires calibration with SST observations using linear regression methods, preferably with in situ SST records that span several years. However, locations with such records are sparse; therefore, calibration is often accomplished using gridded SST data products such as the Hadley Center's HADSST (5º) and interpolated HADISST (1º) data sets, NOAA's extended reconstructed SST data set (ERSST; 2º), optimum interpolation SST (OISST; 1º), and Kaplan SST data sets (5º). From these data products, the SST used for proxy calibration is obtained for a single grid cell that includes the proxy's study site. The gridded data sets are based on the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) and each uses different methods of interpolation to produce the globally and temporally complete data products except for HadSST, which is not interpolated but quality controlled. This study compares SST for a single site from these gridded data products with a high-resolution satellite-based SST data set from NOAA (Pathfinder; 4 km) with in situ SST data and coral Sr/Ca variability for our study site in Haiti to assess differences between these SST records with a focus on seasonal variability. Our results indicate substantial differences in the seasonal variability captured for the same site among these data sets on the order of 1-3°C. This analysis suggests that of the data products, high-resolution satellite SST best captured seasonal variability at the study site. Unfortunately, satellite SST records are limited to the past few decades. If satellite SST are to be used to calibrate proxy records, collecting modern, living samples is

  12. 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.

  13. 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.

  14. Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Hester, David Barry

    The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. Estimation of terrestrial carbon fluxes with 1km by 1km spatial-resolution using satellite- driven model

    NASA Astrophysics Data System (ADS)

    Sasai, T.; Nasahara, K.; Ito, A.; Saigusa, N.; Hirata, R.; Takagi, K.; Oikawa, T.

    2008-12-01

    Terrestrial carbon cycle is strongly affected by some local natural phenomena and human-induced activities, which bring change to the carbon exchanges via vegetation and soil microbe activities. In order to accurately understand a realistic spatial pattern in carbon exchanges including such an effect of local-scale events, we need to calculate carbon fluxes and storages with as detailed spatial resolution as possible. In response to this, we attempt to estimate terrestrial carbon fluxes with 1km by 1km spatial resolution using satellite-driven model. Study area of the model estimation is the Further East Asia region, which lies at 30-50 north latitude and 125-150 east longitude. The model is the Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data (BEAMS) [Sasai et al., 2005, 2007]. Being aim at simulating terrestrial carbon exchanges under more realistic land surface condition, we applied as many as possible of satellite-observation products such as the standard MODIS, TRMM, and SRTM high-level land products as model inputs. In the model validation, we compared between model estimations and eddy covariance measurements at four flux sites. As a result, a correlation coefficient of the terrestrial carbon fluxes between estimations and measurements were high values, leading up that the model estimations are virtually reasonable. In model analysis, BEAMS was operated with 1km by 1km spatial resolution from 2001 to 2006. Spatial distributions in the annual mean NPP and NEP showed that high values were distributed over the hilly and plateau regions, and they were gradually decreasing towards the urban and high mountain areas, meaning that we could reflect an impact of the local-scale events in the carbon flux estimations. In future, we would extend study area to the East Asia region, and the carbon exchange map with 1km by 1km spatial- resolution is distributed on the website.

  20. Towards High Spa-Temporal Resolution Estimates of Surface Radiative Fluxes from Geostationary Satellite Observations for the Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Niu, X.; Yang, K.; Tang, W.; Qin, J.

    2014-12-01

    Surface Solar Radiation (SSR) plays an important role of the hydrological and land process modeling, which particularly contributes more than 90% to the total melt energy for the Tibetan Plateau (TP) ice melting. Neither surface measurement nor existing remote sensing products can meet that requirement in TP. The well-known satellite products (i.e. ISCCP-FD and GEWEX-SRB) are in relatively low spatial resolution (0.5º-2.5º) and temporal resolution (3-hourly, daily, or monthly). The objective of this study is to develop capabilities to improved estimates of SSR in TP based on geostationary satellite observations from the Multi-functional Transport Satellite (MTSAT) with high spatial (0.05º) and temporal (hourly) resolution. An existing physical model, the UMD-SRB (University of Maryland Surface Radiation Budget) which is the basis of the GEWEX-SRB model, is re-visited to improve SSR estimates in TP. The UMD-SRB algorithm transforms TOA radiances into broadband albedos in order to infer atmospheric transmissivity which finally determines the SSR. Specifically, main updates introduced in this study are: implementation at 0.05º spatial resolution at hourly intervals integrated to daily and monthly time scales; and improvement of surface albedo model by introducing the most recently developed Global Land Surface Broadband Albedo Product (GLASS) based on MODIS data. This updated inference scheme will be evaluated against ground observations from China Meteorological Administration (CMA) radiation stations and three TP radiation stations contributed from the Institute of Tibetan Plateau Research.

  1. High Temperal Resolution AOD Retrieval of Northern China in 2014 Winter Based on Geostationary Satellite Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Chen, X.; Li, Z.; Zhang, Y.; Xu, H.; Ma, Y.; Li, D.; Lv, Y.; Qie, L.; Zhang, Y.; Li, L.; Liu, Y.

    2014-12-01

    Observations from satellite can provide large region, fast and dynamic monitoring of aerosol properties. Polar Satellites provide once a day of observations at most, which is difficult to monitor aerosol temporal variabilities clearly. Only geostationary orbit satellites have the ability to provide both high temporal and spatial resolution observations. The Korea Geostationary Ocean Color Imager (GOCI) onboard COMs-1 (Communication、Ocean & Meteorological Satellite-1) mainly designed for ocean observation, but it has a good potential for land monitoring. Cross calibration between GOCI and the US Moderate Resolution Imaging Spectrometer (MODIS) can improve the land radiation characteristics of GOCI, which can expand its ability in land observation.Cross calibration results show that the simulated TOA (Top Of Atmosphere) radiance from MODIS and GOCI measured TOA radiance agrees well. The geostationary orbit satellite observing characteristics of the nearly constant view geometry and the high temporal resolution were used in aerosol retrieval algorithm. For images of two adjacent time points, the difference of TOA radiance mostly comes from the change caused by aerosol. AOD retrievals were accomplished using a Look-Up Table (LUT) strategy with assumptions of quickly varied aerosol and slowly varied surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of series observations in a short period of time, e.g. several days. GOCI data from January 1, 2014 to April 1, 2014 were used to retrieve AOD, when the haze was very heavy. The monitoring of hourly AOD variations were implemented during this period and the retrieved AOD agrees well with AREONET (AErosol RObotic NETwork) ground-based measurements. The result was also compared with MODIS AOD products. In conclusion, GOCI was calibrated using MODIS data firstly in order to improve the radiation characteristics of land; then, the AOD retrieval algorithm was developed

  2. 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.

  3. 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.

  4. Scaling properties of Arctic sea ice deformation in high-resolution viscous-plastic sea ice models and satellite observations

    NASA Astrophysics Data System (ADS)

    Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

    2017-04-01

    Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

  5. Research on the influence of the disturbance characteristics of the flywheel components on a high resolution optical satellite

    NASA Astrophysics Data System (ADS)

    Li, Lin; Zhou, Sitong; Kong, Lin; Xu, Jing; Wang, Dong

    2016-10-01

    In order to study the influence of flywheel micro vibration on the imaging of a high resolution optical satellite, the flywheel components disturbance model was established, and the flywheel components were tested. The analysis of the measured data shows that there is a series of harmonic at the first order frequency 50Hz, and a series of peaks around the 190Hz and 280Hz. The integration of the angular displacement response that was obtained by exerting the unit sine excitation on the satellite and the flywheel measured disturbance data shows that there is a lot of angular displacement harmonic response frequency in 40Hz 80Hz and 230Hz 280Hz, the maximum angular displacement resonance response amplitude is 2.739" along the vertical direction, the angular displacement resonance response amplitude is 2.617" at 245Hz and 2600rpm, and 0.5" magnitude harmonic amplitude around 245Hz. Flywheel micro vibration has a great influence on the high resolution optical satellite imaging quality. Suggestions on further research on micro vibration of flywheel are proposed.

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

    NASA Astrophysics Data System (ADS)

    Jin, Xiaoying; Davis, Curt H.

    2005-12-01

    High-resolution satellite imagery provides an important new data source for building extraction. We demonstrate an integrated strategy for identifying buildings in 1-meter resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. First, a series of geodesic opening and closing operations are used to build a differential morphological profile (DMP) that provides image structural information. Building hypotheses are generated and verified through shape analysis applied to the DMP. Second, shadows are extracted using the DMP to provide reliable contextual information to hypothesize position and size of adjacent buildings. Seed building rectangles are verified and grown on a finely segmented image. Next, bright buildings are extracted using spectral information. The extraction results from the different information sources are combined after independent extraction. Performance evaluation of the building extraction on an urban test site using IKONOS satellite imagery of the City of Columbia, Missouri, is reported. With the combination of structural, contextual, and spectral information,[InlineEquation not available: see fulltext.] of the building areas are extracted with a quality percentage[InlineEquation not available: see fulltext.].

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

    USGS Publications Warehouse

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

    2016-01-01

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

  8. 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.

  9. Use of surface drifters to increase resolution and accuracy of oceanic geostrophic circulation mapped from satellite only (altimetry and gravimetry)

    NASA Astrophysics Data System (ADS)

    Mulet, Sandrine; Rio, Marie-Hélène; Etienne, Hélène

    2017-04-01

    Strong improvements have been made in our knowledge of the surface ocean geostrophic circulation thanks to satellite observations. For instance, the use of the latest GOCE (Gravity field and steady-state Ocean Circulation Explorer) geoid model with altimetry data gives good estimate of the mean oceanic circulation at spatial scales down to 125 km. However, surface drifters are essential to resolve smaller scales, it is thus mandatory to carefully process drifter data and then to combine these different data sources. In this framework, the global 1/4° CNES-CLS13 Mean Dynamic Topography (MDT) and associated mean geostrophic currents have been computed (Rio et al, 2014). First a satellite only MDT was computed from altimetric and gravimetric data. Then, an important work was to pre-process drifter data to extract only the geostrophic component in order to be consistent with physical content of satellite only MDT. This step include estimate and remove of Ekman current and wind slippage. Finally drifters and satellite only MDT were combined. Similar approaches are used regionally to go further toward higher resolution, for instance in the Agulhas current or along the Brazilian coast. Also, a case study in the Gulf of Mexico intends to use drifters in the same way to improve weekly geostrophic current estimate.

  10. Defining approaches to settlement mapping for public health management in Kenya using medium spatial resolution satellite imagery.

    PubMed

    Tatem, Andrew J; Noor, Abdisalan M; Hay, Simon I

    2004-10-30

    This paper presents an appraisal of satellite imagery types and texture measures for identifying and delineating settlements in four Districts of Kenya chosen to represent the variation in human ecology across the country. Landsat Thematic Mapper (TM) and Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) imagery of the four districts were obtained and supervised per-pixel classifications of image combinations tested for their efficacy at settlement delineation. Additional data layers including human population census data, land cover, and locations of medical facilities, villages, schools and market centres were used for training site identification and validation. For each district, the most accurate approach was determined through the best correspondence with known settlement and non-settlement pixels. The resulting settlement maps will be used in combination with census data to produce medium spatial resolution population maps for improved public health planning in Kenya.

  11. Stratified and automatic information extraction from high-resolution satellite imagery based on an object-oriented method

    NASA Astrophysics Data System (ADS)

    Jiang, Tao; Fang, Lei; Ding, Wenwen

    2009-09-01

    High spatial resolution satellite imagery has been widely used in mapping, environmental monitoring, disaster management, city planning, because of its favorable visual effects, plentiful texture information, accurate positioning etc. Traditional classification methods which face to the medium/low-resolution satellite data have been proved not fit for the high resolution image processing. The object-oriented classification method can resistance the salt and pepper effect, because it based on patches of spectrally similar pixels which have been produced by image segmentation. In this paper, a hierarchical framework that based on the stratified classification idea is proposed and applied to the land cover mapping of city. This stratified framework integrates the object-oriented multi-scale segmentation technology and quantification of image object features. The scale parameter of segmentation is the key factor during the framework building. In the study, Scottsdale, Arizona state, USA, is selected as the study area because of its plentiful spatial features and beautiful sight. The overall accuracy of the land cover classification is 82.58%, the Kappa Coefficient is 0.80 and the user's accuracies of the most land-objects are exceeding 85%. The study is demonstrated using the object-oriented image analysis software, Definiens Developer 7.0, which can be integrated with other spatial data in vector-based geographical information system (GIS) environments.

  12. Use of shadow for enhancing mapping of perennial desert plants from high-spatial resolution multispectral and panchromatic satellite imagery

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

    Satellite remote-sensing techniques face challenges in extracting vegetation-cover information in desert environments. The limitations in detection are attributed to three major factors: (1) soil background effect, (2) distribution and structure of perennial desert vegetation, and (3) tradeoff between spatial and spectral resolutions of the satellite sensor. In this study, a modified vegetation shadow model (VSM-2) is proposed, which utilizes vegetation shadow as a contextual classifier to counter the limiting factors. Pleiades high spatial resolution, multispectral (2 m), and panchromatic (0.5 m) images were utilized to map small and scattered perennial arid shrubs and trees. We investigated the VSM-2 method in addition to conventional techniques, such as vegetation indices and prebuilt object-based image analysis. The success of each approach was evaluated using a root sum square error metric, which incorporated field data as control and three error metrics related to commission, omission, and percent cover. Results of the VSM-2 revealed significant improvements in perennial vegetation cover and distribution accuracy compared with the other techniques and its predecessor VSM-1. Findings demonstrated that the VSM-2 approach, using high-spatial resolution imagery, can be employed to provide a more accurate representation of perennial arid vegetation and, consequently, should be considered in assessments of desertification.

  13. 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

  14. 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.

  15. Stratified and automatic information extraction from high-resolution satellite imagery based on an object-oriented method

    NASA Astrophysics Data System (ADS)

    Jiang, Tao; Fang, Lei; Ding, WenWen

    2010-11-01

    High spatial resolution satellite imagery has been widely used in mapping, environmental monitoring, disaster management, city planning, because of its favorable visual effects, plentiful texture information, accurate positioning etc. Traditional classification methods which face to the medium/low-resolution satellite data have been proved not fit for the high resolution image processing. The object-oriented classification method can resistance the salt and pepper effect, because it based on patches of spectrally similar pixels which have been produced by image segmentation. In this paper, a hierarchical framework that based on the stratified classification idea is proposed and applied to the land cover mapping of city. This stratified framework integrates the object-oriented multi-scale segmentation technology and quantification of image object features. The scale parameter of segmentation is the key factor during the framework building. In the study, Scottsdale, Arizona state, USA, is selected as the study area because of its plentiful spatial features and beautiful sight. The overall accuracy of the land cover classification is 82.58%, the Kappa Coefficient is 0.80 and the user's accuracies of the most land-objects are exceeding 85%. The study is demonstrated using the object-oriented image analysis software, Definiens Developer 7.0, which can be integrated with other spatial data in vector-based geographical information system (GIS) environments.

  16. 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.

  17. 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

  18. Leaf area index retrieval using gap fractions obtained from high resolution satellite data: Comparisons of approaches, scales and atmospheric effects

    NASA Astrophysics Data System (ADS)

    Gonsamo, Alemu

    2010-08-01

    This study is aimed at demonstrating the feasibility of the large scale LAI inversion algorithms using red and near infrared reflectance obtained from high resolution satellite imagery. Radiances in digital counts were obtained in 10 m resolution acquired on cloud free day of August 23, 2007, by the SPOT 5 high resolution geometric (HRG) instrument on mostly temperate hardwood forest located in the Great Lakes - St. Lawrence forest in Southern Quebec. Normalized difference vegetation index (NDVI), scaled difference vegetation index (SDVI) and modified soil-adjusted vegetation index (MSAVI) were applied to calculate gap fractions. LAI was inverted from the gap fraction using the common Beer-Lambert's law of light extinction under forest canopy. The robustness of the algorithm was evaluated using the ground-based LAI measurements and by applying the methods for the independently simulated reflectance data using PROSPECT + SAIL coupled radiative transfer models. Furthermore, the high resolution LAI was compared with MODIS LAI product. The effects of atmospheric corrections and scales were investigated for all of the LAI retrieval methods. NDVI was found to be not suitable index for large scale LAI inversion due to the sensitivity to scale and atmospheric effects. SDVI was virtually scale and atmospheric correction invariant. MSAVI was also scale invariant. Considering all sensitivity analysis, MSAVI performed best followed by SDVI for robust LAI inversion from high resolution imagery.

  19. Processing of high spatial resolution information obtained from satellites of Resource-P series according to the level 1

    NASA Astrophysics Data System (ADS)

    Eremeev, V.; Kuznetcov, A.; Poshekhonov, V.; Presniakov, O.; Zenin, V.; Svetelkin, P.; Kochergin, A.

    2016-10-01

    The present paper has described main functioning principles of imagery instruments of high spatial resolution of Russian satellites "Resource-P". Processing of images obtained from these instruments according to the level 1 includes: relative radiometric correction, stitching of video data obtained from separate CCD-matrices, geometric matching of multitemporal multispectral images from optoelectronic converters (OEC), pansharpening, saving of results in distribution formats. Stages for acquisition of a high-precision model for the Earth surface imagery being a base of processing are considered. Descriptions of algorithms for realization of mentioned processing types, examples of their practical usage and also precise characteristics of outputs are described.

  20. 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.

  1. Super-resolution terrain map enhancement for navigation based on satellite imagery

    NASA Astrophysics Data System (ADS)

    Straub, Jeremy

    2012-01-01

    Super resolution techniques are commonly used to enhance images and video. The techniques have previously been applied to the enhancement of map data via enhancing aerial imagery. This paper proposes the use of super resolution techniques for enhancing topographic data directly. Specifically, a database-driven super resolution algorithm that is trained with domain-specific patterns is used to enhance topographic digital elevation model (DEM) data from NASA/NGIA SRTM. This enhancement process is evaluated using a elevation-difference evaluation technique where downscaled and enhanced DEM data is compared to the origional higher-resolution data. It is also evaluated with a threshold-based elevation difference metric and visually. The benefits that it might have for flight path planning for a UAV application are discussed. The challenges of using super resolution style techniques on non-visual data are also reviewed.

  2. 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.

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

    PubMed

    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-R(2) 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.

  4. 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.

  5. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. An Enhanced Algorithm for Automatic Radiometric Harmonization of High-Resolution Optical Satellite Imagery Using Pseudoinvariant Features and Linear Regression

    NASA Astrophysics Data System (ADS)

    Langheinrich, M.; Fischer, P.; Probeck, M.; Ramminger, G.; Wagner, T.; Krauß, T.

    2017-05-01

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

  7. 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

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

    PubMed Central

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

    2015-01-01

    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 (1 km × 1 km) daily Ta across the southeastern USA for 2000-2014. We calibrated Ts to Ta measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R2 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 R2 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

  9. 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.

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

    PubMed

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

    2008-06-01

    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 to 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.

  11. Development of urban area geospatial information products from high resolution satellite imagery using advanced image analysis techniques

    NASA Astrophysics Data System (ADS)

    Shackelford, Aaron K.

    The latest generation of commercial satellite imaging sensors have a number of characteristics (e.g. high spatial resolution, multispectral bands, and quick revisit time), that make them ideal data sources for a variety of urban area applications. The goal of this doctoral research was to develop advanced automated and semi-automated image analysis and classification techniques for the extraction of urban area geospatial information products from commercial high-resolution satellite imagery. We developed two semi-automated urban land cover classification approaches, as well as fully automated techniques for road network and 2-D building footprint extraction. By utilizing fully automated feature extraction techniques for training data generation, a self-supervised classification approach was also developed. The self-supervised classifier is significantly more accurate than traditional classification approaches, and unlike traditional approaches it is fully automated. The development of automated and semi-automated techniques for generation of urban geospatial information products is of high importance not only for the many applications where they can be used but also because the large volume of data collected by these sensors exceeds the human capacity of trained image specialists to analyze. In addition, many applications, especially those for the military and intelligence communities, require near real time exploitation of the image data.

  12. 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.

  13. Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

    PubMed Central

    Fearns, Peter

    2017-01-01

    The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

  14. Three-dimensional estimates of tree canopies: Scaling from high-resolution UAV data to satellite observations

    NASA Astrophysics Data System (ADS)

    Sankey, T.; Donald, J.; McVay, J.

    2015-12-01

    High resolution remote sensing images and datasets are typically acquired at a large cost, which poses big a challenge for many scientists. Northern Arizona University recently acquired a custom-engineered, cutting-edge UAV and we can now generate our own images with the instrument. The UAV has a unique capability to carry a large payload including a hyperspectral sensor, which images the Earth surface in over 350 spectral bands at 5 cm resolution, and a lidar scanner, which images the land surface and vegetation in 3-dimensions. Both sensors represent the newest available technology with very high resolution, precision, and accuracy. Using the UAV sensors, we are monitoring the effects of regional forest restoration treatment efforts. Individual tree canopy width and height are measured in the field and via the UAV sensors. The high-resolution UAV images are then used to segment individual tree canopies and to derive 3-dimensional estimates. The UAV image-derived variables are then correlated to the field-based measurements and scaled to satellite-derived tree canopy measurements. The relationships between the field-based and UAV-derived estimates are then extrapolated to a larger area to scale the tree canopy dimensions and to estimate tree density within restored and control forest sites.

  15. 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

  16. 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

    2014-12-15

    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.

  17. Satellite-driven estimation of terrestrial carbon flux over Far East Asia with 30-second grid resolution

    NASA Astrophysics Data System (ADS)

    Sasai, T.; Saigusa, N.; Nasahara, K. N.; Ito, A.; Hashimoto, H.; Nemani, R. R.; Hirata, R.; Ichii, K.; Takagi, K.; Saitoh, T. M.; Ohta, T.; Murakami, K.; Oikawa, T.; Yamaguchi, Y.

    2010-12-01

    The terrestrial carbon cycle is strongly affected by local natural phenomena and local human-induced activities that alter carbon exchange via vegetation and soil activities. In order to accurately understand terrestrial carbon cycle mechanisms, it is necessary to estimate spatial and temporal variations in carbon flux and storage using process-based models with the highest possible resolution. We estimated terrestrial carbon fluxes using the biosphere model integrating eco-physiological and mechanistic approaches using Satellite data (BEAMS) and satellite observations with 30-second grid resolution. The study area is the central Far East Asia region, which lies between 30 degree and 50 degree north latitude and 125 degree and 150 degree east longitude. Aiming to simulate terrestrial carbon exchanges under realistic land surface conditions, we applied as many satellite-observation means as possible, such as the standard MODIS, TRMM, and SRTM high-level land products. Validated using gross primary productivity (GPP), net ecosystem production (NEP), net radiation and latent heat with ground measurements at six flux sites, the model estimations showed reasonable seasonal and annual patterns. In extensive analysis, total amounts of GPP and NPP were determined to be 2.1 PgC/year and 0.9 PgC/year. The total NEP estimate was +5.6 TgC/year, meaning that the land area played a role as a carbon sink for these six years. In analyses of areas with complicated topography, the 30-second grid estimation could prove to be an effective product to evaluate the effect of landscape on the terrestrial carbon cycle. The method presented here is an appropriate approach to gain a better understanding of terrestrial carbon exchange, both spatially and temporally.

  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. 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.

  20. 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.

  1. 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.

  2. Monitoring landslide deformation with Pleiades very-high resolution satellite images at decimeter accuracy

    NASA Astrophysics Data System (ADS)

    Stumpf, Andre; Malet, Jean-Philippe; Allemand, Pascal; Ulrich, Patrice

    2014-05-01

    Recent advances in image-matching techniques and VHR satellite imaging theoretically offer the possibility to measure Earth surface displacements with decimetric precision. However, this possibility has yet not been explored and requirements of ground control and external topographic datasets are generally considered as important bottlenecks that hinder the application of optical image correlation for displacement measurements on a regular base. This study combines approaches for spaceborne stereo-photogrammetry, orthorectification and sub-pixel image correlation to analyze a series of Pleiades satellite images and measure the horizontal surface displacement of three large landslides (La Valette, Poche, Super-Sauze) located in the Barcelonnette basin (Southern French Alps). The influence of the number of ground-control points on the accuracy of the image orientation, the extracted surface models and displacement rates is quantified through comparisons with airborne laser scans and global navigation satellite measurements at permanent stations. The comparison shows a maximum error of 0.13 m which is one order of magnitude more accurate than what has been previously reported with spaceborne optical images. A series of 4 stereo-pairs is analyzed to capture the seasonal displacement rates over a period of 1.5 years providing valuable insights into the diverse and dynamic deformation patterns of the three observed landslides. The obtained results indicate that the approach can be applied without significant loss in accuracy when no ground control points are available and, therefore, greatly facilitate regular measurements for a broad range of applications.

  3. 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.

  4. A Reprocessed and Bias-Corrected High-Resolution Satellite Derived Precipitation Record Covering the Entire TRMM/GPM Era

    NASA Astrophysics Data System (ADS)

    Xie, P.; Joyce, R.; Sun, F.; Wu, S.; Yarosh, Y.; Yoo, S.

    2013-12-01

    CMORPH global high-resolution satellite precipitation estimates have been reprocessed and bias-corrected for a 15-year period from January 1998 to the present to cover the entire TRMM/GPM era. As the first step of this project, the CMORPH estimates have been extended backward in time from the December 2002 operational initiation to January 1998 and reprocessed from 2003 to present using the most recent passive microwave (PMW) retrieval algorithm version from all available low earth orbiters and infrared (IR) observations from geostationary platforms. The reprocessed CMORPH precipitation estimates consist of a 15-year homogeneous record of high-resolution precipitation on an 8kmx8km and 30-min resolution covering the globe from 60oS-60oN. Bias correction is then performed for the raw CMORPH over the entire data period from 1998 to the present. Over land, the bias in the raw CMORPH is removed by matching the probability density function (PDF) of the CMORPH with that of the CPC unified daily gauge analysis in two sequential steps. Bias in the raw CMORPH is first removed using PDF tables established for each 0.25olat/lon grid box and for each calendar day using co-located CMORPH - gauge data pairs collected over a sliding window of +/-15 days centered at the target calendar day over a 15-year period from 1998 to 2012 and over a spatial domain centering at the target grid box. The output of this first step is then calibrated against the daily gauge analysis using PDF tables established using data over a 30-day period ending at the target day to remove year-to-year variations of the CMORPH bias. Over ocean, the raw CMORPH satellite estimates are calibrated against a long-term precipitation analysis (pentad GPCP) to ensure temporal homogeneity for climate applications. The high-resolution CMORPH precipitation estimates are integrated to a time / space resolution of pentad / 2.5olat/lon to be compared against the pentad GPCP precipitation analysis. Ratio computed between

  5. Effects of daily, high spatial resolution a priori profiles of satellite-derived NOx emissions

    NASA Astrophysics Data System (ADS)

    Laughner, J.; Zare, A.; Cohen, R. C.

    2016-12-01

    The current generation of space-borne NO2 column observations provides a powerful method of constraining NOx emissions due to the spatial resolution and global coverage afforded by the Ozone Monitoring Instrument (OMI). The greater resolution available in next generation instruments such as TROPOMI and the capabilities of geosynchronous platforms TEMPO, Sentinel-4, and GEMS will provide even greater capabilities in this regard, but we must apply lessons learned from the current generation of retrieval algorithms to make the best use of these instruments. Here, we focus on the effect of the resolution of the a priori NO2 profiles used in the retrieval algorithms. We show that for an OMI retrieval, using daily high-resolution a priori profiles results in changes in the retrieved VCDs up to 40% when compared to a retrieval using monthly average profiles at the same resolution. Further, comparing a retrieval with daily high spatial resolution a priori profiles to a more standard one, we show that emissions derived increase by 100% when using the optimized retrieval.

  6. Visualization tools for extremely high resolution DEM from the LRO and other orbiter satellites

    NASA Astrophysics Data System (ADS)

    Montgomery, J.; McDonald, John

    2012-10-01

    Recent space missions have included laser altimetry instrumentation that provides precise high-resolution global topographic data products. These products are critical in analyzing geomorphological surface processes of planets and moons. Although highly valued, the high-resolution data is often overlooked by researchers due to the high level of IT sophistication necessary to use the high-resolution data products, which can be as large as several hundred gigabytes. Researchers have developed software tools to assist in viewing and manipulating data products derived from altimetry data, however current software tools require substantial off-line processing, provide rudimentary visualization or are not suited for viewing the new high-resolution data. We have adapted mVTK, a novel software visualization tool, to work with NASA's recently acquired Lunar Reconnaissance Orbiter data. mVTK is a software visualization package that dynamically creates cylindrical cartographic map projections from gridded high-resolution altimetry data in real-time. The projections are interactive 2D shade relief, false color maps that allow the user to make simple slope and distance measurements on the actual underlying high-resolution data. We have tested mVTK on several laser altimetry data sets including binned gridded record data from NASA's Mars Global Surveyor and Lunar Reconnaissance Orbiter space missions.

  7. 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.

  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. PMID:27873947

  9. The Use of Coarse Resolution Satellite Imagery to Predict Human Puumala Virus Epidemics in Sweden.

    DTIC Science & Technology

    1992-09-11

    Communications Systems ............... 51 3.3.5.1.3. NOAA-9 Strengths and Limitations ................ 52 vA 3.3.6. PART FOUR: Normalized Difference...106 ix LIST OF FIGURES Fig 3.3.-1. The Components of a Simplified Satellite Remote Sensing System ... 55 Fig 3.3.-2. Major Features of The NOAA-9...is such a system . The AVHRR’s synoptic view, daily frequency of coverage and thus a high potential for cloud-free images, all at a reasonable cost

  10. Retrieval of atmospheric methane from high spectral resolution satellite measurements: a correction for cirrus cloud effects.

    PubMed

    Bril, Andrey; Oshchepkov, Sergey; Yokota, Tatsuya

    2009-04-10

    We assessed the accuracy of methane (CH(4)) retrievals from synthetic radiance spectra particular to Greenhouse Gases Observing Satellite observations. We focused on estimating the CH(4) vertical column amount from an atmosphere that includes thin cirrus clouds, taking into account uncertain meteorological conditions. A photon path-length probability density function (PPDF)-based method was adapted to correct for atmospheric scattering effects in CH(4) retrievals. This method was shown to provide similar retrieval accuracy as compared to a carbon dioxide (CO(2))-proxy-based correction approach. It infers some advantages of PPDF-based method for methane retrievals under high variability of CO(2) abundance.

  11. 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

  12. Using high resolution satellite multi-temporal interferometry for landslide hazard detection in tropical environments: the case of Haiti

    NASA Astrophysics Data System (ADS)

    Wasowski, Janusz; Nutricato, Raffaele; Nitti, Davide Oscar; Bovenga, Fabio; Chiaradia, Maria Teresa; Piard, Boby Emmanuel; Mondesir, Philemon

    2015-04-01

    Synthetic aperture radar (SAR) multi-temporal interferometry (MTI) is one of the most promising satellite-based remote sensing techniques for fostering new opportunities in landslide hazard detection and assessment. MTI is attractive because it can provide very precise quantitative information on slow slope displacements of the ground surface over huge areas with limited vegetation cover. Although MTI is a mature technique, we are only beginning to realize the benefits of the high-resolution imagery that is currently acquired by the new generation radar satellites (e.g., COSMO-SkyMed, TerraSAR-X). In this work we demonstrate the potential of high resolution X-band MTI for wide-area detection of slope instability hazards even in tropical environments that are typically very harsh (eg. coherence loss) for differential interferometry applications. This is done by presenting an example from the island of Haiti, a tropical region characterized by dense and rapidly growing vegetation, as well as by significant climatic variability (two rainy seasons) with intense precipitation events. Despite the unfavorable setting, MTI processing of nearly 100 COSMO-SkyMed (CSK) mages (2011-2013) resulted in the identification of numerous radar targets even in some rural (inhabited) areas thanks to the high resolution (3 m) of CSK radar imagery, the adoption of a patch wise processing SPINUA approach and the presence of many man-made structures dispersed in heavily vegetated terrain. In particular, the density of the targets resulted suitable for the detection of some deep-seated and shallower landslides, as well as localized, very slow slope deformations. The interpretation and widespread exploitation of high resolution MTI data was facilitated by Google EarthTM tools with the associated high resolution optical imagery. Furthermore, our reconnaissance in situ checks confirmed that MTI results provided useful information on landslides and marginally stable slopes that can represent a

  13. Satellite Monitoring of Lead Motion in the Ice Pack of the Beaufort Sea - A Case Study with High Resolution Imagery

    NASA Astrophysics Data System (ADS)

    Denton, A. A.; Graber, H. C.

    2016-02-01

    In September of 2014, the development and evolution of a lead in the ice pack of the Beaufort Sea was observed by TerraSAR-X (TSX) and optical satellites from the Medea Program over the course of five days. The lead opened up amid a cluster of buoys deployed during the ONR Marginal Ice Zone summer ice campaign of that year. We present a high resolution case study tracking the development and drift of this feature, combining SAR, optical, and in-situ measurements as co-validation. Feature-based tracking methods in analysis of five sequential TSX StripMaps (3 m resolution) and 3 coincident optical images (1 m resolution) give motion estimates which are corroborated with buoy motions. Such motion estimates can be used in the calculation of the stresses and strains in the ice pack which are important parameters to sea ice modelers, and are applicable to ship navigation in ice-covered waters. Furthermore, our feature-based case study serves as a comparison to tracking methods used on larger spatial scales, providing insight at a high level of detail into the forces and conditions at play in the evolution and motion of an ice feature in the Arctic.

  14. Evaluation of high resolution global satellite precipitation products using daily raingauge data over the Upper Blue Nile Basin

    NASA Astrophysics Data System (ADS)

    Sahlu, Dejene; Moges, Semu; Anagnostou, Emmanouil; Nikolopoulos, Efthymios; Hailu, Dereje; Mei, Yiwen

    2017-04-01

    Water resources assessment, planning and management in Africa is often constrained by the lack of reliable spatio-temporal rainfall data. Satellite products are steadily growing and offering useful alternative datasets of rainfall globally. The aim of this paper is to examine the error characteristics of the main available global satellite precipitation products with the view of improving the reliability of wet season (June to September) and small rainy season rainfall datasets over the Upper Blue Nile Basin. The study utilized six satellite derived precipitation datasets at 0.25-deg spatial grid size and daily temporal resolution:1) the near real-time (3B42_RT) and gauge adjusted (3B42_V7) products of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), 2) gauge adjusted and unadjusted Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products and 3) the gauge adjusted and un-adjusted product of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center Morphing technique (CMORPH) over the period of 2000 to 2013.The error analysis utilized statistical techniques using bias ratio (Bias), correlation coefficient (CC) and root-mean-square-error (RMSE). Mean relative error (MRE), CC and RMSE metrics are further examined for six categories of 10th, 25th, 50th, 75th, 90thand 95th percentile rainfall thresholds. The skill of the satellite estimates is evaluated using categorical error metrics of missed rainfall volume fraction (MRV), falsely detected rainfall volume fraction (FRV), probability of detection (POD) and False Alarm Ratio (FAR). Results showed that six satellite based rainfall products underestimated wet season (June to September) gauge precipitation, with the exception of non-adjusted PERSIANN that overestimated the initial part of the rainy season (March to May). During the wet season, adjusted CMORPH has relatively better bias ratio (89

  15. The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations

    NASA Astrophysics Data System (ADS)

    Aghedo, A. M.; Bowman, K. W.; Shindell, D. T.; Faluvegi, G.

    2011-07-01

    Ensemble climate model simulations used for the Intergovernmental Panel on Climate Change (IPCC) assessments have become important tools for exploring the response of the Earth System to changes in anthropogenic and natural forcings. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. This paper presents the technical steps required for using nadir sun-synchronous infrared satellite observations for multi-model evaluation and the uncertainties associated with each step. This is motivated by need to use satellite observations to evaluate climate models. We quantified the implications of the effect of satellite orbit and spatial coverage, the effect of variations in vertical sensitivity as quantified by the observation operator and the impact of averaging the operators for use with monthly-mean model output. We calculated these biases in ozone, carbon monoxide, atmospheric temperature and water vapour by using the output from two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI) and the observations from the Tropospheric Emission Spectrometer (TES) instrument on board the NASA-Aura satellite from January 2005 to December 2008. The results show that sampling and monthly averaging of the observation operators produce zonal-mean biases of less than ±3 % for ozone and carbon monoxide throughout the entire troposphere in both models. Water vapour sampling zonal-mean biases were also within the insignificant range of ±3 % (that is ±0.14 g kg-1) in both models. Sampling led to a temperature zonal-mean bias of ±0.3 K over the tropical and mid-latitudes in both models, and up to -1.4 K over the boundary layer in the higher latitudes. Using the monthly average of temperature and water vapour operators lead to large biases over the boundary layer in the southern-hemispheric higher latitudes and in the upper troposphere, respectively. Up to 8 % bias was

  16. The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations

    NASA Astrophysics Data System (ADS)

    Aghedo, A. M.; Bowman, K. W.; Shindell, D. T.; Faluvegi, G.

    2011-03-01

    Ensemble climate model simulations used for the Intergovernmental Panel on Climate Change (IPCC) assessments have become important tools for exploring the response of the Earth System to changes in anthropogenic and natural forcings. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. This paper presents the technical steps required for using nadir sun-synchronous infrared satellite observations for multi-model evaluation and the uncertainties associated with each step. This is motivated by need to use satellite observations to evaluate climate models. We quantified the implications of the effect of satellite orbit and spatial coverage, the effect of variations in vertical sensitivity as quantified by the observation operator and the impact of averaging the operators for use with monthly-mean model output. We calculated these biases in ozone, carbon monoxide, atmospheric temperature and water vapour by using the output from two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI) and the observations from the Tropospheric Emission Spectrometer (TES) satellite from January 2005 to December 2008. The results show that sampling and monthly averaging of the observation operators produce biases of less than ±3% for ozone and carbon monoxide throughout the entire troposphere in both models. Water vapour sampling biases were also within the insignificant range of ±3% (that is ±0.14 g kg-1) in both models. Sampling led to a temperature bias of ±0.3 K over the tropical and mid-latitudes in both models, and up to -1.4 K over the boundary layer in the higher latitudes. Using the monthly average of temperature and water vapour operators lead to large biases over the boundary layer in the southern-hemispheric higher latitudes and in the upper troposphere, respectively. Up to 8% bias was calculated in the upper troposphere water vapour due to monthly

  17. A high resolution satellite view of surface solar radiation over the climatically sensitive region of Eastern Mediterranean

    NASA Astrophysics Data System (ADS)

    Alexandri, G.; Georgoulias, A. K.; Meleti, C.; Balis, D.; Kourtidis, K. A.; Sanchez-Lorenzo, A.; Trentmann, J.; Zanis, P.

    2017-05-01

    In this work, the spatiotemporal variability of surface solar radiation (SSR) is examined over the Eastern Mediterranean region for a 31-year period (1983-2013). The CM SAF SARAH (Satellite Application Facility on Climate Monitoring Solar surfAce RAdiation Heliosat) satellite-based product was found to be homogeneous (based on relative Standard Normal Homogeneity Tests - SNHTs, 95% confidence level) as compared to ground-based observations, and hence appropriate for climatological studies. Specifically, the dataset shows good agreement with monthly observations from five quality assured stations in the region with a mean bias of 7.1 W/m2 or 3.8% and a strong correlation. This high resolution (0.05° × 0.05°) product is capable of revealing various local features. Over land, the SSR levels are highly dependent on the topography, while over the sea, they exhibit a smooth latitudinal variability. SSR varies significantly over the region on a seasonal basis being three times higher in summer (309.6 ± 26.5 W/m2) than in winter (100.2 ± 31.4 W/m2). The CM SAF SARAH product was compared against three satellite-based and one reanalysis products. The satellite-based data from CERES (Cloud and the Earth's Radiant Energy System), GEWEX (Global Energy and Water Cycle Experiment) and ISCCP (International Satellite Cloud Climatology Project) underestimate SSR while the reanalysis data from the ERA-Interim overestimate SSR compared to CM SAF SARAH. Using a radiative transfer model and a set of ancillary data, these biases are attributed to the atmospheric parameters that drive the transmission of solar radiation in the atmosphere, namely, clouds, aerosols and water vapor. It is shown that the bias between CERES and CM SAF SARAH SSR can be explained through the cloud fractional cover and aerosol optical depth biases between these datasets. The CM SAF SARAH SSR trend was found to be positive (brightening) and statistically significant at the 95% confidence level (0.2 ± 0.05 W

  18. On the combined use of high temporal resolution, optical satellite data for flood monitoring and mapping: a possible contribution from the RST approach

    NASA Astrophysics Data System (ADS)

    Faruolo, M.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

    2009-04-01

    Among natural disasters, floods are ones of those more common and devastating, often causing high environmental, economical and social costs. When a flooding event occurs, timely information about precise location, extent, dynamic evolution, etc., is highly required in order to effectively support civil protection activities aimed at managing the emergency. Satellite remote sensing may represent a supplementary information source, providing mapping and continuous monitoring of flooding extent as well as a quick damage assessment. Such purposes need frequently updated satellite images as well as suitable image processing techniques, able to identify flooded areas with reliability and timeliness. Recently, an innovative satellite data analysis approach (named RST, Robust Satellite Technique) has been applied to NOAA-AVHRR (Advanced Very High Resolution Radiometer) satellite data in order to dynamically map flooded areas. Thanks to a multi-temporal analysis of co-located satellite records and an automatic change detection scheme, such an approach allows to overcome major drawbacks related to the previously proposed methods (mostly not automatic and based on empirically chosen thresholds, often affected by false identifications). In this paper, RST approach has been for the first time applied to both AVHRR and EOS/MODIS (Moderate Resolution Imaging Spectroradiometer) data, in order to assess its potential - in flooded area mapping and monitoring - on different satellite packages characterized by different spectral and spatial resolutions. As a study case, the flooding event which hit the Europe in August 2002 has been selected. Preliminary results shown in this study seem to confirm the potential of such an approach in providing reliable and timely information, useful for near real time flood hazard assessment and monitoring, using both MODIS and AVHRR data. Moreover, the combined use of information coming from both satellite packages (easily achievable thanks to the

  19. Analysis of high resolution satellite data for cosmic gamma ray bursts

    NASA Technical Reports Server (NTRS)

    Imhof, W. L.; Nakano, G. H.; Reagan, J. B.

    1976-01-01

    Cosmic gamma ray bursts detected a germanium spectrometer on the low altitude satellite 1972-076B were surveyed. Several bursts with durations ranging from approximately 0.032 to 15 seconds were found and are tabulated. The frequency of occurrence/intensity distribution of these events was compared with the S to the -3/2 power curve of confirmed events. The longer duration events fall above the S to the -3/2 power curve of confirmed events, suggesting they are perhaps not all true cosmic gamma-ray bursts. The narrow duration events fall closely on the S to the -3/2 power curve. The survey also revealed several counting rate spikes, with durations comparable to confirmed gamma-ray bursts, which were shown to be of magnetospheric origin. Confirmation that energetic electrons were responsible for these bursts was achieved from analysis of all data from the complete payload of gamma-ray and energetic particle detectors on board the satellite. The analyses also revealed that the narrowness of the spikes was primarily spatial rather than temporal in character.

  20. High-resolution CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites

    USGS Publications Warehouse

    Jaumann, R.; Stephan, K.; Brown, R.H.; Buratti, B.J.; Clark, R.N.; McCord, T.B.; Coradini, A.; Capaccioni, F.; Filacchione, G.; Cerroni, P.; Baines, K.H.; Bellucci, G.; Bibring, J.-P.; Combes, M.; Cruikshank, D.P.; Drossart, P.; Formisano, V.; Langevin, Y.; Matson, D.L.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, C.; Soderbloom, L.A.; Griffith, C.; Matz, K.-D.; Roatsch, Th.; Scholten, F.; Porco, C.C.

    2006-01-01

    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 from 0.35 to 5.2 ??m, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. As an imaging spectrometer VIMS combines the characteristics of both a spectrometer and an imaging instrument. This makes it possible to analyze the spectrum of each pixel separately and to map the spectral characteristics spatially, which is important to study the relationships between spectral information and geological and geomorphologic surface features. The spatial analysis of the spectral data requires the determination of the exact geographic position of each pixel on the specific surface and that all 352 spectral elements of each pixel show the same region of the target. We developed a method to reproject each pixel geometrically and to convert the spectral data into map projected image cubes. This method can also be applied to mosaic different VIMS observations. Based on these mosaics, maps of the spectral properties for each Saturnian satellite can be derived and attributed to geographic positions as well as to geological and geomorphologic surface features. These map-projected mosaics are the basis for all further investigations. ?? 2006 Elsevier Ltd. All rights reserved.

  1. A Flexible Spatiotemporal Method for Fusing Satellite Images with Different Resolutions

    USDA-ARS?s Scientific Manuscript database

    Studies of land surface dynamics in heterogeneous landscapes often require remote sensing data with high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta ...

  2. A global study of NDVI difference among moderate-resolution satellite sensors

    NASA Astrophysics Data System (ADS)

    Fan, Xingwang; Liu, Yuanbo

    2016-11-01

    Moderate-resolution sensors, including AVHRR (Advanced Very High Resolution Radiometer), MODIS (MODerate-resolution Imaging Spectroradiometer) and VIIRS (Visible-Infrared Imager-Radiometer Suite), have provided over forty years of global scientific data. In the form of NDVI (Normalized Difference Vegetation Index), these data greatly benefit environmental studies. However, their usefulness is compromised by sensor differences. This study investigates the global NDVI difference and its spatio-temporal patterns among typical moderate-resolution sensors, as supported by state-of-the-art remote sensing derived products. Our study demonstrates that the atmosphere plays a secondary role to LULC (Land Use/Land Cover) in inter-sensor NDVI differences. With reference to AVHRR/3, AVHRR/1 and 2 exhibit negative NDVI biases for vegetated land cover types. In summer (July), the area of negative bias shifts northward, and the magnitude increases in the Northern Hemisphere. For most LULC types, the bias generally shifts in the negative direction from winter (January) to summer. A linear regression of the NDVI difference versus NDVI shows a close correlation between the slope value and vegetation phenology. Overall, NDVI differences are controlled by LULC type and vegetation phenology. Our study can be used to generate a long-term, consistent NDVI data set from composite MODIS and AVHRR NDVI data. LULC-dependent and temporally variable correction equations are recommended to reduce inter-sensor NDVI differences.

  3. Mapping day-of-burning with coarse-resolution satellite fire-detection data

    Treesearch

    Sean A. Parks

    2014-01-01

    Evaluating the influence of observed daily weather on observed fire-related effects (e.g. smoke production, carbon emissions and burn severity) often involves knowing exactly what day any given area has burned. As such, several studies have used fire progression maps ­ in which the perimeter of an actively burning fire is mapped at a fairly high temporal resolution -...

  4. A flexible spatiotemporal method for fusing satellite images with different resolutions

    Treesearch

    Xiaolin Zhu; Eileen H. Helmer; Feng Gao; Desheng Liu; Jin Chen; Michael A. Lefsky

    2016-01-01

    Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial...

  5. Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

    NASA Astrophysics Data System (ADS)

    Brown, I.; Wennbom, M.

    2013-12-01

    Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors

  6. High-resolution satellite and airborne thermal infrared imaging of precursory unrest and 2009 eruption of Redoubt Volcano, Alaska

    USGS Publications Warehouse

    Wessels, Rick L.; Vaughan, R. Greg; Patrick, Matthew R.; Coombs, Michelle L.

    2013-01-01

    A combination of satellite and airborne high-resolution visible and thermal infrared (TIR) image data detected and measured changes at Redoubt Volcano during the 2008–2009 unrest and eruption. The TIR sensors detected persistent elevated temperatures at summit ice-melt holes as seismicity and gas emissions increased in late 2008 to March 2009. A phreatic explosion on 15 March was followed by more than 19 magmatic explosive events from 23 March to 4 April that produced high-altitude ash clouds and large lahars. Two (or three) lava domes extruded and were destroyed between 23 March and 4 April. After 4 April, the eruption extruded a large lava dome that continued to grow until at least early July 2009.

  7. Mesoscale spiral vortex embedded within a Lake Michigan snow squall band - High resolution satellite observations and numerical model simulations

    NASA Technical Reports Server (NTRS)

    Lyons, Walter A.; Keen, Cecil S.; Hjelmfelt, Mark; Pease, Steven R.

    1988-01-01

    It is known that Great Lakes snow squall convection occurs in a variety of different modes depending on various factors such as air-water temperature contrast, boundary-layer wind shear, and geostrophic wind direction. An exceptional and often neglected source of data for mesoscale cloud studies is the ultrahigh resolution multispectral data produced by Landsat satellites. On October 19, 1972, a clearly defined spiral vortex was noted in a Landsat-1 image near the southern end of Lake Michigan during an exceptionally early cold air outbreak over a still very warm lake. In a numerical simulation using a three-dimensional Eulerian hydrostatic primitive equation mesoscale model with an initially uniform wind field, a definite analog to the observed vortex was generated. This suggests that intense surface heating can be a principal cause in the development of a low-level mesoscale vortex.

  8. EMAG2: A 2-arc min resolution Earth Magnetic Anomaly Grid compiled from satellite, airborne, and marine magnetic measurements

    USGS Publications Warehouse

    Maus, S.; Barckhausen, U.; Berkenbosch, H.; Bournas, N.; Brozena, J.; Childers, V.; Dostaler, F.; Fairhead, J.D.; Finn, C.; von Frese, R.R.B; Gaina, C.; Golynsky, S.; Kucks, R.; Lu, Hai; Milligan, P.; Mogren, S.; Muller, R.D.; Olesen, O.; Pilkington, M.; Saltus, R.; Schreckenberger, B.; Thebault, E.; Tontini, F.C.

    2009-01-01

    A global Earth Magnetic Anomaly Grid (EMAG2) has been compiled from satellite, ship, and airborne magnetic measurements. EMAG2 is a significant update of our previous candidate grid for the World Digital Magnetic Anomaly Map. The resolution has been improved from 3 arc min to 2 arc min, and the altitude has been reduced from 5 km to 4 km above the geoid. Additional grid and track line data have been included, both over land and the oceans. Wherever available, the original shipborne and airborne data were used instead of precompiled oceanic magnetic grids. Interpolation between sparse track lines in the oceans was improved by directional gridding and extrapolation, based on an oceanic crustal age model. The longest wavelengths (>330 km) were replaced with the latest CHAMP satellite magnetic field model MF6. EMAG2 is available at http://geomag.org/models/EMAG2 and for permanent archive at http://earthref.org/ cgi-bin/er.cgi?s=erda.cgi?n=970. ?? 2009 by the American Geophysical Union.

  9. High-resolution land surface fluxes from satellite and reanalysis data (HOLAPS v1.0): evaluation and uncertainty assessment

    NASA Astrophysics Data System (ADS)

    Loew, Alexander; Peng, Jian; Borsche, Michael

    2016-07-01

    Surface water and energy fluxes are essential components of the Earth system. Surface latent heat fluxes provide major energy input to the atmosphere. Despite the importance of these fluxes, state-of-the-art data sets of surface energy and water fluxes largely differ. The present paper introduces a new framework for the estimation of surface energy and water fluxes at the land surface, which allows for temporally and spatially high-resolved flux estimates at the quasi-global scale (50° S, 50° N) (High resOlution Land Atmosphere Parameters from Space - HOLAPS v1.0). The framework makes use of existing long-term satellite and reanalysis data records and ensures internally consistent estimates of the surface radiation and water fluxes. The manuscript introduces the technical details of the developed framework and provides results of a comprehensive sensitivity and evaluation study. Overall the root mean square difference (RMSD) was found to be 51.2 (30.7) W m-2 for hourly (daily) latent heat flux, and 84 (38) W m-2 for sensible heat flux when compared against 48 FLUXNET stations worldwide. The largest uncertainties of latent heat flux and net radiation were found to result from uncertainties in the solar radiation flux obtained from satellite data products.

  10. An assessment of satellite-based high resolution precipitation datasets for atmospheric composition studies in the maritime continent

    NASA Astrophysics Data System (ADS)

    Turk, F. Joseph; Xian, Peng

    2013-03-01

    The Maritime Continent (MC) region of Southeast Asia is known for land use practices that are modulated by precipitation occurrence and fire activity. The polluted environment may modify cloud/precipitation formation mechanisms, but meteorological or weather patterns may disrupt or otherwise influence these same processes. Since the simultaneous retrieval of precipitation and aerosol properties is not possible from current satellite observations, the choice of the precipitation dataset used for applications such as model assimilation and scavenging in aerosol transport models could provide very different results. In this article, a seven-year (2003-2009) time period was analyzed with five satellite-based high-resolution precipitation products (HRPP), the MERRA model reanalysis, and MODIS-derived aerosol observations within nine Southeast Asia domains. Substantially different trends between the aerosol concentration and precipitation time series were noted for different MC island regions, as well as HRPP differences in the precipitation diurnal variability and their capability to track precipitation extremes. For all regions, the most noticeable change to the diurnal cycle was noted during the genesis phase (Phase 1 in the MC) of the intraseasonal Madden Julian Oscillation (MJO). Since these studies do not take any aerosol transport or precipitation dynamics into account, the use of Lagrangian models is proposed to study non-localized aerosol/precipitation interactions and better establish their veracity in current model simulations.

  11. Low-cost, high-resolution telescopes for imaging low-earth orbit satellites

    SciTech Connect

    Massie, N.A.B.; Oster, Y.; Poe, G.; Seppala, L. ); Shao, M. )

    1989-01-01

    Telescopes designed for non-conventional imaging of near-earth satellites must follow a unique set of design rules. Cost must be reduced substantially and the design must accommodate a technique to circumvent the atmospheric distortions of the image. Apertures to 12 meters and beyond are required along with alt-alt mounts providing high tracking rates. A novel design for such a telescope has been generated which is optimized for speckle imaging. Its mount closely resembles a radar mount and it does not employ the conventional dome. Costs for this design are projected to be considerably reduced compared to conventional designs. Results of a detailed design study will be presented. Applications to astronomy will be discussed.

  12. Assessing Leaf Area Index from High Resolution Satellite Datasets for Maize in Trans Nzoia County, Kenya

    NASA Astrophysics Data System (ADS)

    Bartolomew Thiongo, Kuria; Menz, Gunter; Thonfeld, Frank

    2016-08-01

    The Normalized Differenced Vegetation Index (NDVI) and the two band Enhanced vegetation Index (EVI2) derived from RapidEye and Landsat 8 satellite images were evaluated against the empirically derived terrestrial Leaf Area Index (LAI) acquired during the maize growth season April to November, 2015 and covering the phenological growth stages prescribed in the BBCH code. The results indicate a high correlation of the vegetation indices plotted over the entire maize season with R2 values of 88% and 83% for NDVI and EVI2 respectively. The maximum values were found to occur during the maize vegetative phase in the months of July and August. The correlation between the vegetation indices and the LAI had R2 values of 50% and 49% for NDVI and EVI2 respectively. Alternative methods of estimating and calculating the LAI values may improve the achieved results.

  13. Mapping Urban Tree Canopy Coverage and Structure using Data Fusion of High Resolution Satellite Imagery and Aerial Lidar

    NASA Astrophysics Data System (ADS)

    Elmes, A.; Rogan, J.; Williams, C. A.; Martin, D. G.; Ratick, S.; Nowak, D.

    2015-12-01

    Urban tree canopy (UTC) coverage is a critical component of sustainable urban areas. Trees provide a number of important ecosystem services, including air pollution mitigation, water runoff control, and aesthetic and cultural values. Critically, urban trees also act to mitigate the urban heat island (UHI) effect by shading impervious surfaces and via evaporative cooling. The cooling effect of urban trees can be seen locally, with individual trees reducing home HVAC costs, and at a citywide scale, reducing the extent and magnitude of an urban areas UHI. In order to accurately model the ecosystem services of a given urban forest, it is essential to map in detail the condition and composition of these trees at a fine scale, capturing individual tree crowns and their vertical structure. This paper presents methods for delineating UTC and measuring canopy structure at fine spatial resolution (<1m). These metrics are essential for modeling the HVAC benefits from UTC for individual homes, and for assessing the ecosystem services for entire urban areas. Such maps have previously been made using a variety of methods, typically relying on high resolution aerial or satellite imagery. This paper seeks to contribute to this growing body of methods, relying on a data fusion method to combine the information contained in high resolution WorldView-3 satellite imagery and aerial lidar data using an object-based image classification approach. The study area, Worcester, MA, has recently undergone a large-scale tree removal and reforestation program, following a pest eradication effort. Therefore, the urban canopy in this location provides a wide mix of tree age class and functional type, ideal for illustrating the effectiveness of the proposed methods. Early results show that the object-based classifier is indeed capable of identifying individual tree crowns, while continued research will focus on extracting crown structural characteristics using lidar-derived metrics. Ultimately

  14. Meeting Report: Long Term Monitoring of Global Vegetation using Moderate Resolution Satellites

    NASA Technical Reports Server (NTRS)

    Morisette, Jeffrey; Heinsch, Fath Ann; Running, Steven W.

    2006-01-01

    The international community has long recognized the need to coordinate observations of Earth from space. In 1984, this situation provided the impetus for creating the Committee on Earth Observation Satellites (CEOS), an international coordinating mechanism charged with coordinating international civil spaceborne missions designed to observe and study planet Earth. Within CEOS, its Working Group on Calibration and Validation (WGCV) is tasked with coordinating satellite-based global observations of vegetation. Currently, several international organizations are focusing on the requirements for Earth observation from space to address key science questions and societal benefits related to our terrestrial environment. The Global Vegetation Workshop, sponsored by the WGCV and held in Missoula, Montana, 7-10 August, 2006, was organized to establish a framework to understand the inter-relationships among multiple, global vegetation products and identify opportunities for: 1) Increasing knowledge through combined products, 2) Realizing efficiency by avoiding redundancy, and 3) Developing near- and long-term plans to avoid gaps in our understanding of critical global vegetation information. The Global Vegetation Workshop brought together 135 researchers from 25 states and 14 countries to advance these themes and formulate recommendations for CEOS members and the Global Earth Observation System of Systems (GEOSS). The eighteen oral presentations and most of the 74 posters presented at the meeting can be downloaded from the meeting website (www.ntsg.umt.edu/VEGMTG/). Meeting attendees were given a copy of the July 2006 IEEE Transactions on Geoscience and Remote Sensing Special Issue on Global Land Product Validation, coordinated by the CEOS Working Group on Calibration and Validation (WGCV). This issue contains 29 articles focusing on validation products from several of the sensors discussed during the workshop.

  15. Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

    PubMed

    De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

    2014-12-01

    The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of <5m resolution was acquired in the spring of 2013 for the area around Bruges, Belgium, a region where dairy farms suffer from liver fluke infections transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

  16. An improved geopositioning model of QuickBird high resolution satellite imagery by compensating spatial correlated errors

    NASA Astrophysics Data System (ADS)

    Li, Chuang; Shen, Yunzhong; Li, Bofeng; Qiao, Gang; Liu, Shijie; Wang, Weian; Tong, Xiaohua

    2014-10-01

    A lot of studies have been done for correcting the systematic biases of high resolution satellite images (HRSI), which is a fundamental work in the geometric orientation and the geopositioning of HRSI. All the existing bias-corrected models eliminate the biases in the images by expressing the biases as a function of some deterministic parameters (i.e. shift, drift, or affine transformation models), which is indeed effective for most of the commercial high resolution satellite imagery (i.e. IKONOS, GeoEye-1, WorldView-1/2) except for QuickBird. Studies found that QuickBird is the only one that needs more than a simple shift model to absorb the strong residual systematic errors. To further improve the image geopositioning of QuickBird image, in this paper, we introduce space correlated errors (SCEs) and model them as signals in the bias-corrected rational function model (RFM) and estimate the SCEs at the ground control points (GCPs) together with the bias-corrected parameters using least squares collocation. With these estimated SCEs at GCPs, we then predict the SCEs at the unknown points according to their stochastic correlation with SCEs at the GCPs. Finally, we carry out geopositioning for these unknown points after compensating both the biases and the SCEs. The performance of our improved geopositioning model is demonstrated with a stereo pair of QuickBird cross-track images in the Shanghai urban area. The results show that the SCEs exist in HRSI and the presented geopositioning model exhibits a significant improvement, larger than 20% in both latitude and height directions and about 2.8% in longitude direction, in geopositioning accuracy compared to the common used affine transformation model (ATM), which is not taking SCEs into account. The statistical results also show that our improved geopositioning model is superior to the ATM and the second polynomial model (SPM) in both accuracy and reliability for the geopositioning of HRSI.

  17. Estimating Agricultural Land Use Change in Karamoja, NE. Uganda Using Very High Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Nakalembe, C. L.

    2013-12-01

    Land use information is useful for deriving biophysical variables for effective planning and management of natural resources. Land use information is also needed to understand negative environmental impacts of land use while maintaining economic and social benefits. Recent maps of land cover and land use have been generated for Africa at the continental scale from coarse resolution data (e.g. MODIS, Spot Vegetation, MERIS, and Landsat). In these map products, croplands and rangelands are generally poorly represented, particularly in semi-arid regions like Karamoja. Products derived from coarse resolution data also fail at mapping subsistence croplands and are limited in their use for extraction of land-cover specific temporal profiles for agricultural monitoring in the study area (Fritz, See, & Rembold, 2010). Given the subsistence nature of agriculture, most fields in Karamoja are very small that care not discernible from other land uses in coarse resolution data and data products such as FAO Africover2000. product derived from 30m Landsat data is one such product. There is a high level of disagreement and large errors of omission and omission due to the coarse resolution of the data used to derive the product. In addition population growth and policy changes in the region have resulted in a shift to agro-pastoralism and systematic expansion of cropland area since 2000. This research will produce an updated agricultural land use map for Karamoja. The land cover map will be used to estimate agricultural land use change in the region and as a filter to extract agricultural land use specific temporal profiles specific to agriculture to compare to crop statistics.

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

    DTIC Science & Technology

    2007-03-01

    instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send... extraterrestrial solar intensity can be as high as 0.5 in clean atmospheres but can drop to 0.2-0.3 in polluted areas, indicating that ground-level solar... intelligence . Also, lack of temporal resolution can specifically affect time sensitive operations. These early methods and limitations will be

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  20. AN ACTIVE-PASSIVE COMBINED ALGORITHM FOR HIGH SPATIAL RESOLUTION RETRIEVAL OF SOIL MOISTURE FROM SATELLITE SENSORS (Invited)

    NASA Astrophysics Data System (ADS)

    Lakshmi, V.; Mladenova, I. E.; Narayan, U.

    2009-12-01

    Soil moisture is known to be an essential factor in controlling the partitioning of rainfall into surface runoff and infiltration and solar energy into latent and sensible heat fluxes. Remote sensing has long proven its capability to obtain soil moisture in near real-time. However, at the present time we have the Advanced Scanning Microwave Radiometer (AMSR-E) on board NASA’s AQUA platform is the only satellite sensor that supplies a soil moisture product. AMSR-E coarse spatial resolution (~ 50 km at 6.9 GHz) strongly limits its applicability for small scale studies. A very promising technique for spatial disaggregation by combining radar and radiometer observations has been demonstrated by the authors using a methodology is based on the assumption that any change in measured brightness temperature and backscatter from one to the next time step is due primarily to change in soil wetness. The approach uses radiometric estimates of soil moisture at a lower resolution to compute the sensitivity of radar to soil moisture at the lower resolution. This estimate of sensitivity is then disaggregated using vegetation water content, vegetation type and soil texture information, which are the variables on which determine the radar sensitivity to soil moisture and are generally available at a scale of radar observation. This change detection algorithm is applied to several locations. We have used aircraft observed active and passive data over Walnut Creek watershed in Central Iowa in 2002; the Little Washita Watershed in Oklahoma in 2003 and the Murrumbidgee Catchment in southeastern Australia for 2006. All of these locations have different soils and land cover conditions which leads to a rigorous test of the disaggregation algorithm. Furthermore, we compare the derived high spatial resolution soil moisture to in-situ sampling and ground observation networks

  1. Assessment of radar resolution requirements for soil moisture estimation from simulated satellite imagery. [Kansas

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.

    1982-01-01

    Radar simulations were performed at five-day intervals over a twenty-day period and used to estimate soil moisture from a generalized algorithm requiring only received power and the mean elevation of a test site near Lawrence, Kansas. The results demonstrate that the soil moisture of about 90% of the 20-m by 20-m pixel elements can be predicted with an accuracy of + or - 20% of field capacity within relatively flat agricultural portions of the test site. Radar resolutions of 93 m by 100 m with 23 looks or coarser gave the best results, largely because of the effects of signal fading. For the distribution of land cover categories, soils, and elevation in the test site, very coarse radar resolutions of 1 km by 1 km and 2.6 km by 3.1 km gave the best results for wet moisture conditions while a finer resolution of 93 m by 100 m was found to yield superior results for dry to moist soil conditions.

  2. Exploring New Challenges of High-Resolution SWOT Satellite Altimetry with a Regional Model of the Solomon Sea

    NASA Astrophysics Data System (ADS)

    Brasseur, P.; Verron, J. A.; Djath, B.; Duran, M.; Gaultier, L.; Gourdeau, L.; Melet, A.; Molines, J. M.; Ubelmann, C.

    2014-12-01

    The upcoming high-resolution SWOT altimetry satellite will provide an unprecedented description of the ocean dynamic topography for studying sub- and meso-scale processes in the ocean. But there is still much uncertainty on the signal that will be observed. There are many scientific questions that are unresolved about the observability of altimetry at vhigh resolution and on the dynamical role of the ocean meso- and submesoscales. In addition, SWOT data will raise specific problems due to the size of the data flows. These issues will probably impact the data assimilation approaches for future scientific or operational oceanography applications. In this work, we propose to use a high-resolution numerical model of the Western Pacific Solomon Sea as a regional laboratory to explore such observability and dynamical issues, as well as new data assimilation challenges raised by SWOT. The Solomon Sea connects subtropical water masses to the equatorial ones through the low latitude western boundary currents and could potentially modulate the tropical Pacific climate. In the South Western Pacific, the Solomon Sea exhibits very intense eddy kinetic energy levels, while relatively little is known about the mesoscale and submesoscale activities in this region. The complex bathymetry of the region, complicated by the presence of narrow straits and numerous islands, raises specific challenges. So far, a Solomon sea model configuration has been set up at 1/36° resolution. Numerical simulations have been performed to explore the meso- and submesoscales dynamics. The numerical solutions which have been validated against available in situ data, show the development of small scale features, eddies, fronts and filaments. Spectral analysis reveals a behavior that is consistent with the SQG theory. There is a clear evidence of energy cascade from the small scales including the submesoscales, although those submesoscales are only partially resolved by the model. In parallel

  3. Ground-Truthing Moderate Resolution Satellite Imagery with Near-Surface Canopy Images in Hawai'i's Tropical Cloud Forests

    NASA Astrophysics Data System (ADS)

    Bergstrom, R.; Miura, T.; Lepczyk, C.; Giambelluca, T. W.; Nullet, M. A.; Nagai, S.

    2012-12-01

    Phenological studies are gaining importance globally as the onset of climate change is impacting the timing of green up and senescence in forest canopies and agricultural regions. Many studies use and analyze land surface phenology (LSP) derived from satellite vegetation index time series (VI's) such as those from Moderate Resolution Imaging Spectroradiometer (MODIS) to monitor changes in phenological events. Seasonality is expected in deciduous temperate forests, while tropical regions are predicted to show more static reflectance readings given their stable and steady state. Due to persistent cloud cover and atmospheric interference in tropical regions, satellite VI time series are often subject to uncertainties and thus require near surface vegetation monitoring systems for ground-truthing. This study has been designed to assess the precision of MODIS phenological signatures using above-canopy, down-looking digital cameras installed on flux towers on the Island of Hawai'i. The cameras are part of the expanding Phenological Eyes Network (PEN) which has been implementing a global network of above-canopy, hemispherical digital cameras for forest and agricultural phenological monitoring. Cameras have been installed at two locations in Hawaii - one on a flux tower in close proximity to the Thurston Lave Tube (HVT) in Hawai'i Volcanoes National Park and the other on a weather station in a section of the Hawaiian Tropical Experimental Forest in Laupaphoehoe (LEF). HVT consists primarily of a single canopy species, ohi'a lehua (Metrosideros polymorpha), with an understory of hapu'u ferns (Cibotium spp), while LEF is similarly comprised with an additional dominant species, Koa (Acacia Koa), included in the canopy structure. Given these species' characteristics, HVT is expected to show little seasonality, while LEF has the potential to deviate slightly during periods following dry and wet seasons. MODIS VI time series data are being analyzed and will be compared to images

  4. A model of regional primary production for use with coarse resolution satellite data

    NASA Technical Reports Server (NTRS)

    Prince, S. D.

    1991-01-01

    A model of crop primary production, which was originally developed to relate the amount of absorbed photosynthetically active radiation (APAR) to net production in field studies, is discussed in the context of coarse resolution regional remote sensing of primary production. The model depends on an approximately linear relationship between APAR and the normalized difference vegetation index. A more comprehensive form of the conventional model is shown to be necessary when different physiological types of plants or heterogeneous vegetation types occur within the study area. The predicted variable in the new model is total assimilation (net production plus respiration) rather than net production alone or harvest yield.

  5. High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

    NASA Technical Reports Server (NTRS)

    Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment

  6. Determination of water depth with high-resolution satellite imagery over variable bottom types

    USGS Publications Warehouse

    Stumpf, Richard P.; Holderied, Kristine; Sinclair, Mark

    2003-01-01

    A standard algorithm for determining depth in clear water from passive sensors exists; but it requires tuning of five parameters and does not retrieve depths where the bottom has an extremely low albedo. To address these issues, we developed an empirical solution using a ratio of reflectances that has only two tunable parameters and can be applied to low-albedo features. The two algorithms--the standard linear transform and the new ratio transform--were compared through analysis of IKONOS satellite imagery against lidar bathymetry. The coefficients for the ratio algorithm were tuned manually to a few depths from a nautical chart, yet performed as well as the linear algorithm tuned using multiple linear regression against the lidar. Both algorithms compensate for variable bottom type and albedo (sand, pavement, algae, coral) and retrieve bathymetry in water depths of less than 10-15 m. However, the linear transform does not distinguish depths >15 m and is more subject to variability across the studied atolls. The ratio transform can, in clear water, retrieve depths in >25 m of water and shows greater stability between different areas. It also performs slightly better in scattering turbidity than the linear transform. The ratio algorithm is somewhat noisier and cannot always adequately resolve fine morphology (structures smaller than 4-5 pixels) in water depths >15-20 m. In general, the ratio transform is more robust than the linear transform.

  7. Rotation-and-scale-invariant airplane detection in high-resolution satellite images based on deep-Hough-forests

    NASA Astrophysics Data System (ADS)

    Yu, Yongtao; Guan, Haiyan; Zai, Dawei; Ji, Zheng

    2016-02-01

    This paper proposes a rotation-and-scale-invariant method for detecting airplanes from high-resolution satellite images. To improve feature representation capability, a multi-layer feature generation model is created to produce high-order feature representations for local image patches through deep learning techniques. To effectively estimate airplane centroids, a Hough forest model is trained to learn mappings from high-order patch features to the probabilities of an airplane being present at specific locations. To handle airplanes with varying orientations, patch orientation is defined and integrated into the Hough forest to augment Hough voting. The scale invariance is achieved by using a set of scale factors embedded in the Hough forest. Quantitative evaluations on the images collected from Google Earth service show that the proposed method achieves a completeness, correctness, quality, and F1-measure of 0.968, 0.972, 0.942, and 0.970, respectively, in detecting airplanes with arbitrary orientations and sizes. Comparative studies also demonstrate that the proposed method outperforms the other three existing methods in accurately and completely detecting airplanes in high-resolution remotely sensed images.

  8. Vegetation mapping from high-resolution satellite images in the heterogeneous arid environments of Socotra Island (Yemen)

    NASA Astrophysics Data System (ADS)

    Malatesta, Luca; Attorre, Fabio; Altobelli, Alfredo; Adeeb, Ahmed; De Sanctis, Michele; Taleb, Nadim M.; Scholte, Paul T.; Vitale, Marcello

    2013-01-01

    Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geomorphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum likelihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.

  9. Rapid, High-Resolution Detection of Environmental Change over Continental Scales from Satellite Data - the Earth Observation Data Cube

    NASA Technical Reports Server (NTRS)

    Lewis, Adam; Lymburner, Leo; Purss, Matthew B. J.; Brooke, Brendan; Evans, Ben; Ip, Alex; Dekker, Arnold G.; Irons, James R.; Minchin, Stuart; Mueller, Norman

    2015-01-01

    The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations - the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.

  10. Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Alshehhi, Rasha; Marpu, Prashanth Reddy

    2017-04-01

    Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

  11. New optical sensor systems for high-resolution satellite, airborne and terrestrial imaging systems

    NASA Astrophysics Data System (ADS)

    Eckardt, Andreas; Börner, Anko; Lehmann, Frank

    2007-10-01

    The department of Optical Information Systems (OS) at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR) has more than 25 years experience with high-resolution imaging technology. The technology changes in the development of detectors, as well as the significant change of the manufacturing accuracy in combination with the engineering research define the next generation of spaceborne sensor systems focusing on Earth observation and remote sensing. The combination of large TDI lines, intelligent synchronization control, fast-readable sensors and new focal-plane concepts open the door to new remote-sensing instruments. This class of instruments is feasible for high-resolution sensor systems regarding geometry and radiometry and their data products like 3D virtual reality. Systemic approaches are essential for such designs of complex sensor systems for dedicated tasks. The system theory of the instrument inside a simulated environment is the beginning of the optimization process for the optical, mechanical and electrical designs. Single modules and the entire system have to be calibrated and verified. Suitable procedures must be defined on component, module and system level for the assembly test and verification process. This kind of development strategy allows the hardware-in-the-loop design. The paper gives an overview about the current activities at DLR in the field of innovative sensor systems for photogrammetric and remote sensing purposes.

  12. MULTI-ELEMENT ABUNDANCE MEASUREMENTS FROM MEDIUM-RESOLUTION SPECTRA. II. CATALOG OF STARS IN MILKY WAY DWARF SATELLITE GALAXIES

    SciTech Connect

    Kirby, Evan N.; Cohen, Judith G.; Guhathakurta, Puragra; Rockosi, Constance M.; Geha, Marla C.; Sneden, Christopher; Sohn, Sangmo Tony; Majewski, Steven R.; Siegel, Michael

    2010-12-15

    We present a catalog of Fe, Mg, Si, Ca, and Ti abundances for 2961 stars in eight dwarf satellite galaxies of the Milky Way (MW): Sculptor, Fornax, Leo I, Sextans, Leo II, Canes Venatici I, Ursa Minor, and Draco. For the purposes of validating our measurements, we also observed 445 red giants in MW globular clusters and 21 field red giants in the MW halo. The measurements are based on Keck/DEIMOS medium-resolution spectroscopy (MRS) combined with spectral synthesis. We estimate uncertainties in [Fe/H] by quantifying the dispersion of [Fe/H] measurements in a sample of stars in monometallic globular clusters (GCs). We estimate uncertainties in Mg, Si, Ca, and Ti abundances by comparing to high-resolution spectroscopic abundances of the same stars. For this purpose, a sample of 132 stars with published high-resolution spectroscopy in GCs, the MW halo field, and dwarf galaxies has been observed with MRS. The standard deviations of the differences in [Fe/H] and ([{alpha}/Fe]) (the average of [Mg/Fe], [Si/Fe], [Ca/Fe], and [Ti/Fe]) between the two samples is 0.15 and 0.16, respectively. This catalog represents the largest sample of multi-element abundances in dwarf galaxies to date. The next papers in this series draw conclusions on the chemical evolution, gas dynamics, and star formation histories from the catalog presented here. The wide range of dwarf galaxy luminosity reveals the dependence of dwarf galaxy chemical evolution on galaxy stellar mass.

  13. Analysis of solar radiation on the surface estimated from GWNU solar radiation model with temporal resolution of satellite cloud fraction

    NASA Astrophysics Data System (ADS)

    Zo, Il-Sung; Jee, Joon-Bum; Lee, Kyu-Tae; Kim, Bu-Yo

    2016-08-01

    Preliminary analysis with a solar radiation model is generally performed for photovoltaic power generation projects. Therefore, model accuracy is extremely important. The temporal and spatial resolutions used in previous studies of the Korean Peninsula were 1 km × 1 km and 1-h, respectively. However, calculating surface solar radiation at 1-h intervals does not ensure the accuracy of the geographical effects, and this parameter changes owing to atmospheric elements (clouds, aerosol, ozone, etc.). Thus, a change in temporal resolution is required. In this study, one-year (2013) analysis was conducted using Chollian geostationary meteorological satellite data from observations recorded at 15-min intervals. Observation data from the intensive solar site at Gangneung-Wonju National University (GWNU) showed that the coefficient of determination (R²), which was estimated for each month and season, increased, whereas the standard error (SE) decreased when estimated in 15-min intervals over those obtained in 1-h intervals in 2013. When compared with observational data from 22 solar sites of the Korean Meteorological Administration (KMA), R2 was 0.9 or higher on average, and over- or under-simulated sites did not exceed 3 sites. The model and 22 solar sites showed similar values of annual accumulated solar irradiation, and their annual mean was similar at 4,998 MJ m-2 (3.87 kWh m-2). These results show a difference of approximately ± 70 MJ m-2 (± 0.05 kWh m-2) from the distribution of the Korean Peninsula estimated in 1-h intervals and a higher correlation at higher temporal resolution.

  14. Vegetation classification based on Advanced Very High Resolution Radiometer /AVHRR/ satellite imagery

    NASA Technical Reports Server (NTRS)

    Norwine, J.; Greegor, D. H.

    1983-01-01

    Data from the NOAA-6 spacecraft Advanced Very High Resolution Radiometer (AVHRR) were tested for effectiveness for vegetation classification. Vegetation, climatological, and meteorological data were gathered for three days over 12 locations, and the normalized differences between the AVHRR bands 1 and 2 were determined. A vegetative greenness index was compared with a hydrologic factor and vegetation characteristics as measured by ground truth. A multivariate vegetation gradient model was formulated, incorporating AVHRR and climatological data. The hydrologic factor was calculated in terms of the precipitation, evaporation, maximum and minimum temperatures, and the hydrologic capacity. The observations were taken over Texas, which has a wide range of climates. A high correlation was found in the vegetation-HF index. The AVHRR data are concluded to be an effective tool for analysis of vegetation/climate relationships.

  15. Meteo-Marine Parameters And Their Variability Observed By High Resolution Satellite Radar

    NASA Astrophysics Data System (ADS)

    Jacobsen, Seven; Lehner, Susanne; Pleskachevsky, Andrey; Rosenthal, Wolfgang

    2013-12-01

    An estimation of swell wave energy fluxes is presented based on remote sensing data. The energy flux being the product of wave energy density and group velocity is estimated based on information about local wave height, wavelength and period. Wave parameters are determined from TerraSAR-X high resolution radar images using the newly developed empirical algorithm XWAVE-2. An analysis of the spatial variation of relevant variables is presented for selected areas along the south coast of Java island (Indonesia). Wavelength reduction of shoaling waves moreover yields estimates of the local bathymetry. An examination of sea state parameters in combination with the derived local underwater topography permits the identification of the best-suited locations for wave power plants. The information is a valuable constituent in the site selection process for ocean renewable energy facilities as part of the bilateral Indonesian-German project Science for the Protection of Indonesian Coastal Marine Ecosystems (SPICE).

  16. Estimating babassu palm density using automatic palm tree detection with very high spatial resolution satellite images.

    PubMed

    Dos Santos, Alessio Moreira; Mitja, Danielle; Delaître, Eric; Demagistri, Laurent; de Souza Miranda, Izildinha; Libourel, Thérèse; Petit, Michel

    2017-05-15

    High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale. Copyright

  17. Impact of spatial resolution on cirrus infrared satellite retrievals in the presence of cloud heterogeneity

    NASA Astrophysics Data System (ADS)

    Fauchez, T.; Platnick, S. E.; Meyer, K.; Zhang, Z.; Cornet, C.; Szczap, F.; Dubuisson, P.

    2015-12-01

    Cirrus clouds are an important part of the Earth radiation budget but an accurate assessment of their role remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better accuracy for thin cirrus effective radius retrievals with small effective radii. However, current global operational algorithms for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel Approximation (PPA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on ice cloud retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects in the TIR spectrum are mainly dominated by the PPA bias that primarily depends on the COT subpixel heterogeneity; for solar reflectance channels, in addition to the PPA bias, the IPA can lead to significant retrieval errors due to a significant photon horizontal transport between cloudy columns, as well as brightening and shadowing effects that are more difficult to quantify. Furthermore TIR retrievals techniques have demonstrated better retrieval accuracy for thin cirrus having small effective radii over solar reflectance techniques. The TIR range is thus particularly relevant in order to characterize, as accurately as possible, thin cirrus clouds. Heterogeneity effects in the TIR are evaluated as a function of spatial resolution in order to estimate the optimal spatial resolution for TIR retrieval applications. These investigations are performed using a cirrus 3D cloud generator (3DCloud), a 3D radiative transfer code (3DMCPOL), and two retrieval algorithms, namely the operational MODIS retrieval algorithm (MOD06) and a research-level SWT algorithm.

  18. Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

    NASA Technical Reports Server (NTRS)

    Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

  19. Irrigation water use monitoring at watershed scale using series of high-resolution satellite images

    NASA Astrophysics Data System (ADS)

    Díaz, A.; González-Dugo, M. P.; Escuin, S.; Mateos, L.; Cano, F.; Cifuentes, V.; Tirado, J. L.; Oyonarte, N.

    2009-09-01

    The integration of time series of high-resolution remote sensing images in the FAO crop evapotranspiration (ET) model is receiving growing interest in the last years, specially for operational applications in irrigated areas. In this study, a simplified methodology to estimate actual ET for these areas in large watersheds was developed. Then it was applied to the Guadalquivir river watershed (Southern Spain) in the 2007 and 2008 irrigation seasons. The evolution of vegetation indices, obtained from 10 Landsat and IRS images per season, was used for two purposes. Firstly, it was used for identifying crop types based on a classification algorithm. This algorithm used training data from a screened subset of the information declared by farmers for EU agriculture subsidies purposes. Secondly, the vegetation indices were used to obtain basal crop coefficients (Kcb, the component of the crop coefficient that represents transpiration). The last step was the parameterization of the influence of evaporation from the soil surface, considering the averaged effect of a given rain distribution and irrigation schedule. The results showed only small discrepancies between the crop coefficients calculated using the simplified model and those calculated based on a soil water balance and the dual approach proposed by FAO. Therefore, it was concluded that the simplified method can be applied to large irrigation areas where detailed information about soils and/or water applied by farmers lacks..

  20. 3-Dimentional Mapping Coastal Zone using High Resolution Satellite Stereo Imageries

    NASA Astrophysics Data System (ADS)

    Hong, Zhonghua; Liu, Fengling; Zhang, Yun

    2014-03-01

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

  1. High Resolution Topography of Polar Regions from Commercial Satellite Imagery, Petascale Computing and Open Source Software

    NASA Astrophysics Data System (ADS)

    Morin, Paul; Porter, Claire; Cloutier, Michael; Howat, Ian; Noh, Myoung-Jong; Willis, Michael; Kramer, WIlliam; Bauer, Greg; Bates, Brian; Williamson, Cathleen

    2017-04-01

    Surface topography is among the most fundamental data sets for geosciences, essential for disciplines ranging from glaciology to geodynamics. Two new projects are using sub-meter, commercial imagery licensed by the National Geospatial-Intelligence Agency and open source photogrammetry software to produce a time-tagged 2m posting elevation model of the Arctic and an 8m posting reference elevation model for the Antarctic. When complete, this publically available data will be at higher resolution than any elevation models that cover the entirety of the Western United States. These two polar projects are made possible due to three equally important factors: 1) open-source photogrammetry software, 2) petascale computing, and 3) sub-meter imagery licensed to the United States Government. Our talk will detail the technical challenges of using automated photogrammetry software; the rapid workflow evolution to allow DEM production; the task of deploying the workflow on one of the world's largest supercomputers; the trials of moving massive amounts of data, and the management strategies the team needed to solve in order to meet deadlines. Finally, we will discuss the implications of this type of collaboration for future multi-team use of leadership-class systems such as Blue Waters, and for further elevation mapping.

  2. Advances In very high resolution satellite imagery analysis for Monitoring human settlements

    SciTech Connect

    Vatsavai, Raju; Cheriyadat, Anil M; Bhaduri, Budhendra L

    2014-01-01

    The high rate of urbanization, political conflicts and ensuing internal displacement of population, and increased poverty in the 20th century has resulted in rapid increase of informal settlements. These unplanned, unauthorized, and/or unstructured homes, known as informal settlements, shantytowns, barrios, or slums, pose several challenges to the nations, as these settlements are often located in most hazardous regions and lack basic services. Though several World Bank and United Nations sponsored studies stress the importance of poverty maps in designing better policies and interventions, mapping slums of the world is a daunting and challenging task. In this paper, we summarize our ongoing research on settlement mapping through the utilization of Very high resolution (VHR) remote sensing imagery. Most existing approaches used to classify VHR images are single instance (or pixel-based) learning algorithms, which are inadequate for analyzing VHR imagery, as single pixels do not contain sufficient contextual information (see Figure 1). However, much needed spatial contextual information can be captured via feature extraction and/or through newer machine learning algorithms in order to extract complex spatial patterns that distinguish informal settlements from formal ones. In recent years, we made significant progress in advancing the state of art in both directions. This paper summarizes these results.

  3. Robust Change Vector Analysis (RCVA) for multi-sensor very high resolution optical satellite data

    NASA Astrophysics Data System (ADS)

    Thonfeld, Frank; Feilhauer, Hannes; Braun, Matthias; Menz, Gunter

    2016-08-01

    The analysis of rapid land cover/land use changes by means of remote sensing is often based on data acquired under varying and occasionally unfavorable conditions. In addition, such analyses frequently use data acquired by different sensor systems. These acquisitions often differ with respect to sun position and sensor viewing geometry which lead to characteristic effects in each image. These differences may have a negative impact on reliable change detection. Here, we propose an approach called Robust Change Vector Analysis (RCVA), aiming to mitigate these effects. RCVA is an improvement of the widely-used Change Vector Analysis (CVA), developed to account for pixel neighborhood effects. We used a RapidEye and Kompsat-2 cross-sensor change detection test to demonstrate the efficiency of RCVA. Our analysis showed that RCVA results in fewer false negatives as well as false positives when compared to CVA under similar test conditions. We conclude that RCVA is a powerful technique which can be utilized to reduce spurious changes in bi-temporal change detection analyses based on high- or very-high spatial resolution imagery.

  4. SACRA - a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI

    NASA Astrophysics Data System (ADS)

    Kotsuki, S.; Tanaka, K.

    2015-11-01

    To date, many studies have performed numerical estimations of biomass production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC), which defines the date or month when farmers sow and harvest crops, is an essential input for the numerical estimations. This study aims to present a new global data set, the SAtellite-derived CRop calendar for Agricultural simulations (SACRA), and to discuss advantages and disadvantages compared to existing census-based and model-derived products. We estimate global CC at a spatial resolution of 5 arcmin using satellite-sensed normalized difference vegetation index (NDVI) data, which corresponds to vegetation vitality and senescence on the land surface. Using the time series of the NDVI averaged from three consecutive years (2004-2006), sowing/harvesting dates are estimated for six crops (temperate-wheat, snow-wheat, maize, rice, soybean and cotton). We assume time series of the NDVI represent the phenology of one dominant crop and estimate CCs of the dominant crop in each grid. The dominant crops are determined using harvested areas based on census-based data. The cultivation period of SACRA is identified from the time series of the NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (< 62 days) in most of the areas. A major disadvantage of our method is that the mixture of several crops in a grid is not considered in SACRA. The assumption of one dominant crop in each grid is a major source of discrepancy in crop calendars between SACRA and other products. The disadvantages of our approach may be reduced with future improvements based on finer satellite sensors and crop-type classification studies to consider several dominant crops in each grid. The comparison of the CC also demonstrates that identification of wheat type (sowing in

  5. Evaluation of High-Resolution Satellite Rainfall Products over the Nile Basin for Climatologic and Hydrologic Applications

    NASA Astrophysics Data System (ADS)

    Habib, E. H.; Haile, A.; Elsaadani, M.; Elshamy, M. E.; Amin, D.; Kuligowski, R. J.

    2010-12-01

    This study presents an evaluation of high-resolution rainfall estimates over the Nile Basin in Africa. The focus of the evaluation is two-fold: (1) can the satellite-rainfall products capture the overall climatological patterns and trends over the basin?, and (2) how and under what circumstances do these products support hydrologic predictions when being used as to drive a basin-wide hydrologic forecasting model? The products under examination are: the ‘Tropical Rainfall Measuring Mission (TRMM) and other sources’ (TRMM-3B42) product, and the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) product which is based on the CPC morphing technique (CMORPH). Over most parts of the Nile basin that are situated north of the equator, the CMORPH product shows a wet bias while the TRMM-3B42 product shows a dry bias. The estimates from both products were within the range of the climatologic records over parts of the basin around the equator. Both products reproduced the diurnal cycle of rain occurrence over the Lake Tana basin (the source of the Blue Nile) except over the mountains and the Lake shore. However, the TRMM-3B42 product underestimated the rainfall amounts in this basin. The satellite products captured the contrasting patterns of the diurnal cycles of rain occurrence and amount over the surroundings of Lake Victoria (the source of the White Nile). The second part of the evaluation focused on evaluating the possible improvements in streamflow predictions that are produced by the Nile Forecasting System (NFS) operated by the Nile Forecasting Center in Cairo, Egypt. The results suggest that that the performance of a basin-wide hydrologic model of the Nile river significantly improves when the CMORPH estimates serve as the main rainfall input compared to IR-based estimates traditionally used in the NFS model. In the Blue Nile basin, the relative volume error of the simulated flow decreased from -40 % when IR-based estimates

  6. Improvement of satellite-based gross primary production through incorporation of high resolution input data over east asia

    NASA Astrophysics Data System (ADS)

    Park, Haemi; Im, Jungho; Kim, Miae

    2016-04-01

    Photosynthesis of plants is the main mechanism of carbon absorption from the atmosphere into the terrestrial ecosystem and it contributes to remove greenhouse gases such as carbon dioxide. Annually, 120 Gt of C is supposed to be assimilated through photosynthetic activity of plants as the gross primary production (GPP) over global land area. In terms of climate change, GPP modelling is essential to understand carbon cycle and the balance of carbon budget over various ecosystems. One of the GPP modelling approaches uses light use efficiency that each vegetation type has a specific efficiency for consuming solar radiation related with temperature and humidity. Satellite data can be used to measure various meteorological and biophysical factors over vast areas, which can be used to quantify GPP. NASA Earth Observing System (EOS) program provides Moderate Resolution Imaging Spectroradiometer (MODIS)-derived global GPP product, namely MOD17A2H, on a daily basis. However, significant underestimation of MOD17A2H has been reported in Eastern Asia due to its dense forest distribution and humid condition during monsoon rainy season in summer. The objective of this study was to improve underestimation of MODIS GPP (MOD17A2H) by incorporating meteorological data-temperature, relative humidity, and solar radiation-of higher spatial resolution than data used in MOD17A2H. Landsat-based land cover maps of finer resolution observation and monitoring - global land cover (FROM-GLC) at 30m resolution were used for selection of light use efficiency (LUE). GPP (eq1. GPP = APAR×LUE) is computed by multiplication of APAR (IPAR×fPAR) and LUE (ɛ= ɛmax×T(°C)scalar×VPD(Pa)scalar, where, T is temperature, VPD is vapour pressure deficit) in this study. Meteorological data of Japanese 55-year Reanalysis (JRA-55, 0.56° grid, 3hr) were used for calculation of GPP in East Asia, including Eastern part of China, Korean peninsula, and Japan. Results were validated using flux tower-observed GPP

  7. Field Spectrometry, Sub-Pixel Resolution of Satellite Imagery, and Archeological Potential of the Cryosphere

    NASA Astrophysics Data System (ADS)

    Clarke, B.; Painter, T. H.; Manley, W. F.; Dixon, E. J.

    2003-12-01

    During the 2003 summer field season, a preliminary investigation was conducted with remote sensing to evaluate and determine the archeological potential of glaciers and permanent snowfields in the Wrangell Mountains, southeastern Alaska. In recent years, archeologists have realized that the cryosphere is far from barren of human contact. Rather the cryosphere provides the ideal means to preserve organic cultural material trapped within ice and snow. This preservation gives a unique glimpse of artifacts such as projectile points, wooden shafts, sinew lashing, and other materials that would have otherwise degraded hundreds or thousands of years ago. Through the use of remote sensing, we aim to narrow the enormous search area down to the most probable locations. From observations made at current sites, it is known that archeological artifacts are usually accompanied by windblown plant detritus, accumulated mammal feces, fur, and amorphous organic material melting out of the ice. We measured with a field spectrometer the hyperspectral reflectance of organic material found in situ on the ice in the vicinity of artifacts. Measurements were also made for surrounding land cover classes. By integrating the spectra with Landsat imagery we are able to create custom spectral libraries and an accurate supervised land cover classification. Since the organic material at many sites is not extensive enough to fill an entire pixel, we use sub-pixel resolution techniques to separate organic debris, inorganic debris, snow and ice. The resulting fractional amount of organic material in each pixel, and its spatial relationships with surrounding land cover features, enable an improved quantified model of archeological site potential for snow and ice.

  8. Assimilation of satellite NO2 observations at high spatial resolution using OSSEs

    NASA Astrophysics Data System (ADS)

    Liu, Xueling; Mizzi, Arthur P.; Anderson, Jeffrey L.; Fung, Inez Y.; Cohen, Ronald C.

    2017-06-01

    Observations of trace gases from space-based instruments offer the opportunity to constrain chemical and weather forecast and reanalysis models using the tools of data assimilation. In this study, observing system simulation experiments (OSSEs) are performed to investigate the potential of high space- and time-resolution column measurements as constraints on urban NOx emissions. The regional chemistry-meteorology assimilation system where meteorology and chemical variables are simultaneously assimilated is comprised of a chemical transport model, WRF-Chem, the Data Assimilation Research Testbed, and a geostationary observation simulator. We design OSSEs to investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission updating scheme. We describe the overall model framework and some initial experiments that point out the first steps toward an optimal configuration for improving our understanding of NOx emissions by combining space-based measurements and data assimilation. Among the findings we describe is the dependence of errors in the estimated NOx emissions on the wind forecast errors, showing that wind vectors with a RMSE below 1 m s-1 allow inference of NOx emissions with a RMSE of less than 30 mol/(km2 × h) at the 3 km scale of the model we use. We demonstrate that our inference of emissions is more accurate when we simultaneously update both NOx emissions and NOx concentrations instead of solely updating emissions. Furthermore, based on our analyses, we recommend carrying out meteorology assimilations to stabilize NO2 transport from the initial wind errors before starting the emission assimilation. We show that wind uncertainties (calculated as a spread around a mean wind) are not important for estimating NOx emissions when the wind uncertainties are reduced below 1.5 m s-1. Finally, we present results assessing the role of separate vs. simultaneous chemical and meteorological assimilation in a model

  9. Monitoring Changes in Water Resources Systems Using High Resolution Satellite Observations: Application to Lake Urmia

    NASA Astrophysics Data System (ADS)

    Norouzi, H.; AghaKouchak, A.; Madani, K.; Mirchi, A.; Farahmand, A.; Conway, C.

    2013-12-01

    Lake Urmia with its unique ecosystem in northwestern Iran is the second largest saltwater lake in the world. It is home of more than 300 species of birds, reptiles, and mammals with high salinity level of more than 300 g/l. In recent years, a significant water retreat has occurred in this lake. In this study, we tried to monitor the desiccation of the lake over more than four decades using remote sensing observations. Multi-spectral high-resolution LandSat images of the Lake Urmia region from 1972 to 2012 were acquired to derive the lake area. The composite maps of the lake were created, and a Bayesian Maximum Likelihood classification technique was used to classify land and water in the composite maps. The time series of the lake area reveals that it has shrunk by more than 40% in the past ten years. Moreover, water budget related components such as precipitation, soil moisture, and drought indices from remote sensing of the lake basin were utilized to investigate if droughts or climate change are the primary driving forces behind this phenomenon. These analyses show that the retreat of the lake is not related to droughts or global climate change as it has survived several drought events before year 2000. Similar analyses conducted on Lake Van located about 400 km west of Lake Urmia with very similar climate pattern revealed no significant areal change despite the lake's exposure to similar drought events. These results raise serious concern about the destructive role of unbridled development coupled with supply-oriented water management scheme driven by a classic upstream-downstream competition for water in the Lake Urmia region. There is an urgent need to investigate sustainable restoration initiatives for Lake Urmia in order to prevent an environmental disaster comparable to catastrophic death of Aral Sea.

  10. Comparing high-resolution daily gridded Precipitation data with satellite rainfall estimates of TRMM_3B42 over Iran

    NASA Astrophysics Data System (ADS)

    Javanmard, S.; Yatagai, A.; Kawamoto, H.; Nodzu, M. I.; Jamali, J. B.

    2009-04-01

    Information on spatial and temporal distribution of precipitation is important for drought monitoring, water resource management in agriculture, power generation and etc. In this respect, high-resolution gridded rainfall datasets are useful for regional studies on the hydrological cycle, climate variability, evaluation of regional models as well as satellite rainfall data. Iran receives rainfall from three major air masses throughout the year and the precipitation regime is complicated due to existence of two main mountain chains of the Zagros and the Alborz. High-resolution gridded precipitation can reproduce the precipitation distribution along the complicated topography and they could improve our understanding of precipitation regime as well a weather systems. Here, firstly we will present precipitation analysis over Iran (20°-45° N, 40°-65° E) based on high-resolution gridded rainfall datasets (0.25° × 0.25° lat./long.) from 1998 to 2006 utilizing synoptic observation data network of Islamic Republic of Iran Meteorological Organization (IRIMO). The number of synoptic stations used in this study are 256 and these data have passed quality control operations such as checking location (latitude, longitude and elevation), consistency to other meteorological parameters, test for homogeneity of data, filling data gaps and etc. by IRIMO. The algorithm of interpolation method of gridded precipitation data is based on the Shepard (1968). Secondly, the comparison of the above mentioned interpolated gridded precipitation data and daily rainfall estimates of TRMM(3B42_V6) which is TRMM Merged High Quality (HQ)/Infrared Precipitation without using raingauge data with spatial resolution 0.25 ° × 0.25° will be presented. From the above analysis results we have shown that spatial distribution of average of precipitation over Iran has two main precipitation pattern with maxima about 4 mm/day along Caspian sea and Zagros mountain chains. Moreover, comparison of spatial

  11. High resolution infrared astronomy satellite observations of a selected spiral galaxy

    NASA Technical Reports Server (NTRS)

    Kulkarni, S. R.

    1991-01-01

    evidence for the explanation and for the existence of a broadly distributed dust component. Deconvolved IRAS maps have improved resolution but do not change this finding.

  12. High-Resolution Mapping of Sea Ice, Icebergs and Growlers in Kongsfjorden, Svalbard, using Ground Based Radar, Satellite, and UAV

    NASA Astrophysics Data System (ADS)

    Lauknes, T. R.; Rouyet, L.; Solbø, S. A.; Sivertsen, A.; Storvold, R.; Akbari, V.; Negrel, J.; Gerland, S.

    2016-12-01

    The dynamics of sea ­ice has a well­ recognized role in the climate system and its extent and evolution is impacted by the global warming. In addition, calving of icebergs and growlers at the tidewater glacier fronts is a component of the mass loss in polar regions. Understanding of calving and ice ­ocean interaction, in particular at tidewater glacier front remains elusive, and a problematic uncertainty in climate change projections. Studying the distribution, volumetry and motion of sea ­ice, icebergs and growlers is thus essential to understand their interactions with the environment in order to be able to predict at short­term their drifts, e.g. to mitigate the risk for shipping, and at longer term the multiple relations with climate changes. Here, we present the results from an arctic fieldwork campaign conducted in Kongsfjorden, Svalbard in April 2016, where we used different remote sensing instruments to observe dynamics of sea ice, icebergs, and growlers. We used a terrestrial radar system, imaging the study area every second minute during the observation period. At the front of the Kronebreen glacier, calving events can be detected and the drift of the generated icebergs and growlers tracked with unprecedented spatial and temporal resolution. During the field campaign, we collected four Radarsat-2 quad-pol images, that will be used to classify the different types of sea ice. In addition, we used small unmanned aircraft (UAS) instrumented with high resolution cameras capturing HD video and still pictures. This allows to map and measure the size of icebergs and ice floes. Such information is essential to validate sensitivity and detection limits from the ground and satellite based measurements.

  13. Rapid topographic change measured by high-resolution satellite radar at Soufriere Hills Volcano, Montserrat, 2008-2010

    NASA Astrophysics Data System (ADS)

    Wadge, G.; Cole, P.; Stinton, A.; Komorowski, J.-C.; Stewart, R.; Toombs, A. C.; Legendre, Y.

    2011-01-01

    High-resolution satellite radar observations of erupting volcanoes can yield valuable information on rapidly changing deposits and geomorphology. Using the TerraSAR-X (TSX) radar with a spatial resolution of about 2 m and a repeat interval of 11 days, we show how a variety of techniques were used to record some of the eruptive history of the Soufriere Hills Volcano, Montserrat between July 2008 and February 2010. After a 15-month pause in lava dome growth, a vulcanian explosion occurred on 28 July 2008 from a vent that was hidden by dense cloud. We were able to show the civil authorities using TSX difference images of surface roughness change that this explosion had not disrupted the dome sufficiently to warrant continuation of a previous, precautionary evacuation. Change difference images also proved to be valuable in mapping new pyroclastic flow deposits: the valley-occupying block-and-ash component tended to increase backscatter and the marginal surge deposits to reduce it, with the pattern reversing after the event due to erosion and deposition. By comparing east- and west-looking images acquired 12 h apart, the deposition of some individual pyroclastic flows can be inferred from change differences. Some of the narrow upper sections of valleys draining the volcano received many tens of metres of rockfall and pyroclastic flow deposits over periods of a few weeks. By measuring the changing radar shadows cast by these valleys in TSX images the changing depth of infill by deposits could be estimated. In addition to using the amplitude data from the radar images we also used their phase information within the InSAR technique to calculate the topography during a period of no surface activity. This enabled areas of transient topography, crucial for directing future flows, to be captured.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  15. HIGH-RESOLUTION SATELLITE IMAGING OF THE 2004 TRANSIT OF VENUS AND ASYMMETRIES IN THE CYTHEREAN ATMOSPHERE

    SciTech Connect

    Pasachoff, Jay M.; Schneider, Glenn; Widemann, Thomas

    2011-04-15

    This paper presents the only space-borne optical-imaging observations of the 2004 June 8 transit of Venus, the first such transit visible from Earth since AD 1882. The high-resolution, high-cadence satellite images we arranged from NASA's Transition Region and Coronal Explorer (TRACE) reveal the onset of visibility of Venus's atmosphere and give further information about the black-drop effect, whose causes we previously demonstrated from TRACE observations of a transit of Mercury. The atmosphere is gradually revealed before second contact and after third contact, resulting from the changing depth of atmospheric layers refracting the photospheric surface into the observer's direction. We use Venus Express observations to relate the atmospheric arcs seen during the transit to the atmospheric structure of Venus. Finally, we relate the transit images to current and future exoplanet observations, providing a sort of ground truth showing an analog in our solar system to effects observable only with light curves in other solar systems with the Kepler and CoRoT missions and ground-based exoplanet-transit observations.

  16. Long-term evolution of Wink sinkholes in West Texas observed by high-resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Kim, J. W.; Lu, Z.

    2016-12-01

    Sinkhole is ground depression and/or collapse over the subsurface cavity in the karst terrain underlain by the carbonates, evaporites, and other soluble soils and rocks. The geohazards have been considered as a "hidden threat" to human life, infrastructures, and properties. The Delaware Basin of West Texas in the southwest part of the Permian Basin contains one of the greatest accumulations of evaporites in the United States. Sinkholes in West Texas have been developed by the dissolution of the subsurface evaporite deposits that come in contact with groundwater. Two Wink sinkholes in Wink, Texas, were developed in 1980 and 2002, respectively. However, monitoring the sinkholes in no man's lands has been challenging due to the lack of availability of high-resolution and temporally dense acquisitions. We employ aerial photography and radar satellite imagery to measure the long-term deformation from early 2000 and characterize the inherent hydrogeology that is closely related to sinkhole collapse and subsidence. Furthermore, data on oil/gas production and water injection into the subsurface as well as ground water level are analyzed to study their effects on the concurrent unstable ground surface in Wink sinkholes. Our study will provide invaluable information to understand the mechanism of sinkhole development and mitigate the catastrophic outcomes of the geohazards.

  17. Discrimination of tree species using random forests from the Chinese high-resolution remote sensing satellite GF-1

    NASA Astrophysics Data System (ADS)

    Lv, Jie; Ma, Ting

    2016-10-01

    Tree species distribution is an important issue for sustainable forest resource management. However, the accuracy of tree species discrimination using remote-sensing data needs to be improved to support operational forestry-monitoring tasks. This study aimed to classify tree species in the Liangshui Nature Reserve of Heilongjiang Province, China using spectral and structural remote sensing information in an auto-mated Random Forest modelling approach. This study evaluates and compares the performance of two machine learning classifiers, random forests (RF), support vector machine (SVM) to classify the Chinese high-resolution remote sensing satellite GF-1 images. Texture factor was extracted from GF-1 image with grey-level co-occurrence matrix method. Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Enhanced Vegetation Index (EVI), Difference Vegetation Index (DVI) were calculated and coupled into the model. The result show that the Random Forest model yielded the highest classification accuracy and prediction success for the tree species with an overall classification accuracy of 81.07% and Kappa coefficient value of 0.77. The proposed random forests method was able to achieve highly satisfactory tree species discrimination results. And aerial LiDAR data should be further explored in future research activities.

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

    NASA Astrophysics Data System (ADS)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-04-01

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

  19. Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

    NASA Astrophysics Data System (ADS)

    Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

    2016-09-01

    Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

  20. The Sentinel-2 MSI Can Increase the Temporal Resolution of 30m Satellite-Derived LAI Estimates

    NASA Astrophysics Data System (ADS)

    Dungan, J. L.; Li, S.; Ganguly, S.; Wang, W.; Nemani, R. R.; Ju, J.; Claverie, M.; Masek, J. G.

    2016-12-01

    The successful launch of the European Space Agency (ESA) Sentinel-2A (S2-A) on 23 June 2015 with its MultiSpectral Instrument (MSI) provides an important means to augment Earth-observation capabilities following the legacy of Landsat. After the three-month satellite commissioning campaign, the MSI onboard S-2A is performing very well (ESA, 2015). By 3 December 2015, the sensor data records have achieved provisional maturity status and have been accessed in level-1C Top-Of-Atmosphere (TOA) reflectance by the remote sensing community worldwide. Near-nadir observations by the MSI onboard S-2A and the Operational Land Imager (OLI) onboard Landsat 8 were collected during Simultaneous Nadir Overpasses as well as nearly coincident overpasses. This paper presents a processing chain using harmonized S-2A MSI and Landsat 8 OLI sensors to obtain increased temporal resolution in Leaf Area Index (LAI) estimates using the red-edge band B8A of MSI to replace the NIR band B08. Results demonstrate that LAI estimates from the MSI and OLI are comparable, and, given sufficient preprocessing for atmospheric correction and geometric rectification, can be used interchangeably to improve the frequency with which low LAI canopies can be monitored.

  1. Semi-automatic verification of cropland and grassland using very high resolution mono-temporal satellite images

    NASA Astrophysics Data System (ADS)

    Helmholz, Petra; Rottensteiner, Franz; Heipke, Christian

    2014-11-01

    Many public and private decisions rely on geospatial information stored in a GIS database. For good decision making this information has to be complete, consistent, accurate and up-to-date. In this paper we introduce a new approach for the semi-automatic verification of a specific part of the, possibly outdated GIS database, namely cropland and grassland objects, using mono-temporal very high resolution (VHR) multispectral satellite images. The approach consists of two steps: first, a supervised pixel-based classification based on a Markov Random Field is employed to extract image regions which contain agricultural areas (without distinction between cropland and grassland), and these regions are intersected with boundaries of the agricultural objects from the GIS database. Subsequently, GIS objects labelled as cropland or grassland in the database and showing agricultural areas in the image are subdivided into different homogeneous regions by means of image segmentation, followed by a classification of these segments into either cropland or grassland using a Support Vector Machine. The classification result of all segments belonging to one GIS object are finally merged and compared with the GIS database label. The developed approach was tested on a number of images. The evaluation shows that errors in the GIS database can be significantly reduced while also speeding up the whole verification task when compared to a manual process.

  2. Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

    NASA Astrophysics Data System (ADS)

    Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

    2017-05-01

    Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

  3. Object-oriented feature extraction approach for mapping supraglacial debris in Schirmacher Oasis using very high-resolution satellite data

    NASA Astrophysics Data System (ADS)

    Jawak, Shridhar D.; Jadhav, Ajay; Luis, Alvarinho J.

    2016-05-01

    Supraglacial debris was mapped in the Schirmacher Oasis, east Antarctica, by using WorldView-2 (WV-2) high resolution optical remote sensing data consisting of 8-band calibrated Gram Schmidt (GS)-sharpened and atmospherically corrected WV-2 imagery. This study is a preliminary attempt to develop an object-oriented rule set to extract supraglacial debris for Antarctic region using 8-spectral band imagery. Supraglacial debris was manually digitized from the satellite imagery to generate the ground reference data. Several trials were performed using few existing traditional pixel-based classification techniques and color-texture based object-oriented classification methods to extract supraglacial debris over a small domain of the study area. Multi-level segmentation and attributes such as scale, shape, size, compactness along with spectral information from the data were used for developing the rule set. The quantitative analysis of error was carried out against the manually digitized reference data to test the practicability of our approach over the traditional pixel-based methods. Our results indicate that OBIA-based approach (overall accuracy: 93%) for extracting supraglacial debris performed better than all the traditional pixel-based methods (overall accuracy: 80-85%). The present attempt provides a comprehensive improved method for semiautomatic feature extraction in supraglacial environment and a new direction in the cryospheric research.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  5. LSA-SAF evapotranspiration products based on MSG/SEVIRI: improvement opportunities from moderate spatial resolution satellites sensors for vegetation (SPOT-VGT, MODIS, PROBA-V)

    NASA Astrophysics Data System (ADS)

    Ghilain, N.; De Roo, F.; Arboleda, A.; Gellens-Meulenberghs, F.

    2012-04-01

    The Satellite Application Facility on Land Surface Analysis (LSA-SAF) proposes a panel of land surface related products derived from the EUMETSAT satellites, MSG (Meteosat Second Generation) and EPS/METOP, and produced in near-real time over Europe, Africa and part of South America. With LSA-SAF products, key surface variables are observed, and allows to characterizing the main processes governing land atmosphere processes. Land evapotranspiration (ET) is one of the variables monitored within LSA-SAF. ET at a spatial resolution of approximately 3 km at the sub-satellite point above the equator is derived in near-real time, every 30 minutes, using a simplified land surface model, forced by LSA-SAF radiation products derived from MSG/SEVIRI data. Given that spatial resolution, some smaller scale processes cannot be resolved, though their contribution may affect the total MSG pixel area ET estimates. Besides, information with an increased resolution is expected to have a positive impact on the total accuracy of the modeled ET. A variety of new remote sensing products derived from EO data at a higher spatial resolution are now publicly available. This is an opportunity to assess the improvement that moderate spatial resolution (250 m to 1 km) satellites sensors for surface and vegetation characterization could offer to the evapotranspiration monitoring at the MSG/SEVIRI scale in the context of LSA-SAF. On the basis of a global analysis and on test cases, we show the usefulness of EO data acquired from moderate resolution satellites sensors (SPOT-VGT, MODIS/Terra&Aqua, MERIS) towards the improvement of the LSA-SAF ET products derived from MSG/SEVIRI. In particular, 4 different variables/indices (land cover map, LAI, surface albedo, open water bodies detection) are assessed regarding the LSA-SAF ET products: 1) the investigated processes at small scales unresolved by the geostationary satellite, e.g. open water bodies dynamics, are better taken into account in the final

  6. Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam.

    PubMed

    Kabaria, Caroline W; Molteni, Fabrizio; Mandike, Renata; Chacky, Frank; Noor, Abdisalan M; Snow, Robert W; Linard, Catherine

    2016-07-30

    With more than half of Africa's population expected to live in urban settlements by 2030, the burden of malaria among urban populations in Africa continues to rise with an increasing number of people at risk of infection. However, malaria intervention across Africa remains focused on rural, highly endemic communities with far fewer strategic policy directions for the control of malaria in rapidly growing African urban settlements. The complex and heterogeneous nature of urban malaria requires a better understanding of the spatial and temporal patterns of urban malaria risk in order to design effective urban malaria control programs. In this study, we use remotely sensed variables and other environmental covariates to examine the predictability of intra-urban variations of malaria infection risk across the rapidly growing city of Dar es Salaam, Tanzania between 2006 and 2014. High resolution SPOT satellite imagery was used to identify urban environmental factors associated malaria prevalence in Dar es Salaam. Supervised classification with a random forest classifier was used to develop high resolution land cover classes that were combined with malaria parasite prevalence data to identify environmental factors that influence localized heterogeneity of malaria transmission and develop a high resolution predictive malaria risk map of Dar es Salaam. Results indicate that the risk of malaria infection varied across the city. The risk of infection increased away from the city centre with lower parasite prevalence predicted in administrative units in the city centre compared to administrative units in the peri-urban suburbs. The variation in malaria risk within Dar es Salaam was shown to be influenced by varying environmental factors. Higher malaria risks were associated with proximity to dense vegetation, inland water and wet/swampy areas while lower risk of infection was predicted in densely built-up areas. The predictive maps produced can serve as valuable resources for

  7. On-orbit geometric calibration and geometric quality assessment for the high-resolution geostationary optical satellite GaoFen4

    NASA Astrophysics Data System (ADS)

    Wang, Mi; Cheng, Yufeng; Chang, Xueli; Jin, Shuying; Zhu, Ying

    2017-03-01

    The Chinese GaoFen4 (GF4) remote sensing satellite, launched at the end of December 2015, is China's first civilian high-resolution geostationary optical satellite and has the world's highest resolution from geostationary orbit. High accuracy geometric calibration is the key factor in the geometrical quality of satellite imagery. This paper proposes an on-orbit geometric calibration approach for the high-resolution geostationary optical satellite GF4 in which a stepwise calibration is performed, external parameters are estimated, and internal parameters are then estimated in a generalized camera frame determined by external parameters. First, the correlation of the imaging error sources and the rigorous imaging model of GF4 are introduced. Second, the geometric calibration model based on the two-dimensional detector directional angle and the parameters estimation method for the planar array camera are presented. LandSat 8 digital orthophoto maps (DOM) and GDEM2 digital elevation models (DEM) are used to validate the efficiency of the proposed method and to make a geometric quality assessment of GF4. The results indicate that changing imaging time and imaging area will dramatically affect the absolute positioning accuracy because of the change of the camera's installation angles caused by thermal environment changes around the satellite in a high orbit. After calibration, the internal distortion is well-compensated, and the positioning accuracy with relatively few ground control points (GCPs) is demonstrated to be better than 1.0 pixels for both the panchromatic and near-infrared sensor and the intermediate infrared sensor.

  8. Merging high-resolution satellite-based precipitation fields and point-scale rain gauge measurements—A case study in Chile

    NASA Astrophysics Data System (ADS)

    Yang, Zhongwen; Hsu, Kuolin; Sorooshian, Soroosh; Xu, Xinyi; Braithwaite, Dan; Zhang, Yuan; Verbist, Koen M. J.

    2017-05-01

    With high spatial-temporal resolution, Satellite-based Precipitation Estimates (SPE) are becoming valuable alternative rainfall data for hydrologic and climatic studies but are subject to considerable uncertainty. Effective merging of SPE and ground-based gauge measurements may help to improve precipitation estimation in both better resolution and accuracy. In this study, a framework for merging satellite and gauge precipitation data is developed based on three steps, including SPE bias adjustment, gauge observation gridding, and data merging, with the objective to produce high-quality precipitation estimates. An inverse-root-mean-square-error weighting approach is proposed to combine the satellite and gauge estimates that are in advance adjusted and gridded, respectively. The model is applied and tested with the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) estimates (daily, 0.04° × 0.04°) over Chile, for the 6 year period of 2009-2014. Daily observations from about 90% of collected gauges over the study area are used for model calibration; the rest of the gauged data are regarded as ground "truth" for validation. Evaluation results indicate high effectiveness of the model in producing high-resolution-precision precipitation data. Compared to reference data, the merged data (daily) show correlation coefficients, probabilities of detection, root-mean-square errors, and absolute mean biases that were consistently improved from the original PERSIANN-CCS estimates. The cross-validation evidences that the framework is effective in providing high-quality estimates even over nongauged satellite pixels. The same method can be applied globally and is expected to produce precipitation products in near real time by integrating gauge observations with satellite estimates.

  9. AVHRR/HIRS (Advanced Very High Resolution Radiometer/High Resolution Infra-Red Sounder) operational method for satellite based sea surface temperature determination

    NASA Astrophysics Data System (ADS)

    Walton, C.

    1987-03-01

    A technique is described which was used operationally to produce sea surface temperatures from the NOAA polar orbiting satellites between 1976 and 1981. The single window channel technique used before 1976 is described in NOAA Technical Memorandum NESS 78 while the multiple window channel technique (MCSST) applied since 1981 is well documented in the scientific literature. The report bridges the gap between these two periods and provides a continuous record of the evolution of one of NOAA's primary satellite derived meteorological products.

  10. Spatiotemporal prediction of fine particulate matter using high resolution satellite images in the southeastern U.S 2003–2011

    PubMed Central

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-01-01

    Numerous studies have demonstrated that fine particulate matter (PM2.5, particles smaller than 2.5 μm in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM2.5 to assess personal exposure; however, induces measurement error. Land use regression provides spatially resolved predictions but land use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM2.5 exposures. In this paper, we used AOD data with other PM2.5 variables such as meteorological variables, land use regression, and spatial smoothing to predict daily concentrations of PM2.5 at a 1 km2 resolution of the southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 through 2011. We divided the study area into 3 regions and applied separate mixed-effect models to calibrate AOD using ground PM2.5 measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors (RMSPE) of 2.89, 2.51, and 2.82 μg/m3 for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM2.5 concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM2.5. Our model results will also extend the existing studies on PM2.5 which have mostly focused on urban areas due to the paucity of monitors in rural areas. PMID:26082149

  11. Developing an Ice Volume Estimate of Jarvis Glacier, Alaska, using Ground-Penetrating Radar and High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Wu, N. L.; Campbell, S. W.; Douglas, T. A.; Osterberg, E. C.

    2013-12-01

    Jarvis Glacier is an important water source for Fort Greely and Delta Junction, Alaska. Yet with warming summer temperatures caused by climate change, the glacier is melting rapidly. Growing concern of a dwindling water supply has caused significant research efforts towards determining future water resources from spring melt and glacier runoff which feeds the community on a yearly basis. The main objective of this project was to determine the total volume of the Jarvis Glacier. In April 2012, a centerline profile of the Jarvis Glacier and 15 km of 100 MHz ground-penetrating radar (GPR) profiles were collected in cross sections to provide ice depth measurements. These depth measurements were combined with an interpreted glacier boundary (depth = 0 m) from recently collected high resolution WorldView satellite imagery to estimate total ice volume. Ice volume was calculated at 0.62 km3 over a surface area of 8.82 km2. However, it is likely that more glacier-ice exists within Jarvis Glacier watershed considering the value calculated with GPR profiles accounts for only the glacier ice within the valley and not for the valley side wall ice. The GLIMS glacier area database suggests that the valley accounts for approximately 50% of the total ice covered watershed. Hence, we are currently working to improve total ice volume estimates which incorporate the surrounding valley walls. Results from this project will be used in conjunction with climate change estimates and hydrological properties downstream of the glacier to estimate future water resources available to Fort Greely and Delta Junction.

  12. Mapping Sub-Saharan African Agriculture in High-Resolution Satellite Imagery with Computer Vision & Machine Learning

    NASA Astrophysics Data System (ADS)

    Debats, Stephanie Renee

    Smallholder farms dominate in many parts of the world, including Sub-Saharan Africa. These systems are characterized by small, heterogeneous, and often indistinct field patterns, requiring a specialized methodology to map agricultural landcover. In this thesis, we developed a benchmark labeled data set of high-resolution satellite imagery of agricultural fields in South Africa. We presented a new approach to mapping agricultural fields, based on efficient extraction of a vast set of simple, highly correlated, and interdependent features, followed by a random forest classifier. The algorithm achieved similar high performance across agricultural types, including spectrally indistinct smallholder fields, and demonstrated the ability to generalize across large geographic areas. In sensitivity analyses, we determined multi-temporal images provided greater performance gains than the addition of multi-spectral bands. We also demonstrated how active learning can be incorporated in the algorithm to create smaller, more efficient training data sets, which reduced computational resources, minimized the need for humans to hand-label data, and boosted performance. We designed a patch-based uncertainty metric to drive the active learning framework, based on the regular grid of a crowdsourcing platform, and demonstrated how subject matter experts can be replaced with fleets of crowdsourcing workers. Our active learning algorithm achieved similar performance as an algorithm trained with randomly selected data, but with 62% less data samples. This thesis furthers the goal of providing accurate agricultural landcover maps, at a scale that is relevant for the dominant smallholder class. Accurate maps are crucial for monitoring and promoting agricultural production. Furthermore, improved agricultural landcover maps will aid a host of other applications, including landcover change assessments, cadastral surveys to strengthen smallholder land rights, and constraints for crop modeling

  13. Mapping Soil Organic Carbon Resources Across Agricultural Land Uses in Highland Lesotho Using High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Knight, J.; Adam, E.

    2015-12-01

    Mapping spatial patterns of soil organic carbon (SOC) using high resolution satellite imagery is especially important in inaccessible or upland areas that have limited field measurements, where land use and land cover (LULC) are changing rapidly, or where the land surface is sensitive to overgrazing and high rates of soil erosion and thus sediment, nutrient and carbon export. Here we outline the methods and results of mapping soil organic carbon in highland areas (~2400 m) of eastern Lesotho, southern Africa, across different land uses. Bedrock summit areas with very thin soils are dominated by xeric alpine grassland; terrace agriculture with strip fields and thicker soils is found within river valleys. Multispectral Worldview 2 imagery was used to map LULC across the region. An overall accuracy of 88% and kappa value of 0.83 were achieved using a support vector machine model. Soils were examined in the field from different LULC areas for properties such as soil depth, maturity and structure. In situ soils in the field were also evaluated using a portable analytical spectral device (ASD) in order to ground truth spectral signatures from Worldview. Soil samples were examined in the lab for chemical properties including organic carbon. Regression modeling was used in order to establish a relationship between soil characteristics and soil spectral reflectance. We were thus able to map SOC across this diverse landscape. Results show that there are notable differences in SOC between upland and agricultural areas which reflect both soil thickness and maturity, and land use practices such as manuring of fields by cattle. Soil erosion and thus carbon (nutrient) export is significant issue in this region, which this project will now be examining.

  14. Spatiotemporal prediction of fine particulate matter using high-resolution satellite images in the Southeastern US 2003-2011.

    PubMed

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-06-01

    Numerous studies have demonstrated that fine particulate matter (PM2.5, particles smaller than 2.5 μm in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM2.5 to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM2.5 exposures. In this paper, we used AOD data with other PM2.5 variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM2.5 at a 1-km(2) resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM2.5 measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R(2) values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 μg/m(3) for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM2.5 concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM2.5. Our model results will also extend the existing studies on PM2.5 which have mostly focused on urban areas because of the paucity of monitors in rural areas.

  15. A novel method to retrieve Aerosol Optical Thickness from high-resolution optical satellite images using an extended version of the Haze Optimized Transform (HOTBAR)

    NASA Astrophysics Data System (ADS)

    Wilson, Robin; Milton, Edward; Nield, Joanna

    2016-04-01

    Aerosol Optical Thickness (AOT) data has many important applications including atmospheric correction of satellite imagery and monitoring of particulate matter air pollution. Current data products are generally available at a kilometre-scale resolution, but many applications require far higher resolutions. For example, particulate matter concentrations vary on a metre-scale, and thus data products at a similar scale are required to provide accurate assessments of particle densities and allow effective monitoring of air quality and analysis of local air quality effects on health. A novel method has been developed which retrieves per-pixel AOT values from high-resolution (~30m) satellite data. This method is designed to work over a wide range of land covers - including both bright and dark surfaces - and 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). The HOT was originally designed for assessing areas of thick haze in satellite imagery 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 provide AOT data instead. Significant extensions include Monte Carlo estimation of the 'Clear Line', object-based correction for land cover, and estimation of AOT from the haziness values through radiative transfer modelling. This novel method will enable many new applications of AOT data that were impossible with previously available low-resolution data, and has the potential to contribute significantly to our understanding of the air quality on health, the accuracy of satellite image atmospheric correction and the role of aerosols in the climate system.

  16. Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011.

    PubMed

    Shields, Timothy; Pinchoff, Jessie; Lubinda, Jailos; Hamapumbu, Harry; Searle, Kelly; Kobayashi, Tamaki; Thuma, Philip E; Moss, William J; Curriero, Frank C

    2016-05-31

    Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

  17. Assessment of Intensity-Duration-Frequency curves for the Eastern Mediterranean region derived from high-resolution satellite and radar rainfall estimates

    NASA Astrophysics Data System (ADS)

    Marra, Francesco; Morin, Efrat; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

    2016-04-01

    Intensity-duration-frequency (IDF) curves are used in flood risk management and hydrological design studies to relate the characteristics of a rainfall event to the probability of its occurrence. The usual approach relies on long records of raingauge data providing accurate estimates of the IDF curves for a specific location, but whose representativeness decreases with distance. Radar rainfall estimates have recently been tested over the Eastern Mediterranean area, characterized by steep climatological gradients, showing that radar IDF curves generally lay within the raingauge confidence interval and that radar is able to identify the climatology of extremes. Recent availability of relatively long records (>15 years) of high resolution satellite rainfall information allows to explore the spatial distribution of extreme rainfall with increased detail over wide areas, thus providing new perspectives for the study of precipitation regimes and promising both practical and theoretical implications. This study aims to (i) identify IDF curves obtained from radar rainfall estimates and (ii) identify and assess IDF curves obtained from two high resolution satellite retrieval algorithms (CMORPH and PERSIANN) over the Eastern Mediterranean region. To do so, we derive IDF curves fitting a GEV distribution to the annual maxima series from 23 years (1990-2013) of carefully corrected data from a C-Band radar located in Israel (covering Mediterranean to arid climates) as well as from 15 years (1998-2014) of gauge-adjusted high-resolution CMORPH and 10 years (2003-2013) of gauge-adjusted high-resolution PERSIANN data. We present the obtained IDF curves and we compare the curves obtained from the satellite algorithms to the ones obtained from the radar during overlapping periods; this analysis will draw conclusions on the reliability of the two satellite datasets for deriving rainfall frequency analysis over the region and provide IDF corrections. We compare then the curves obtained

  18. Techniques for Facilitating the Registration and Rectification of Satellite Data with Examples Using Data from the Advanced Very High Resolution Radiometer and the Landsat Multispectral Scanner.

    NASA Astrophysics Data System (ADS)

    Hayes, Ladson

    Available from UMI in association with The British Library. Requires signed TDF. This thesis describes work relating to the mapping of digital satellite image data from its inherent geometry to the geometry of a different reference system. The reference system chosen may correspond to that of a different satellite image, or a map projection. The advantage of this process is that the information contained in the satellite image data may be related to a known reference. Use of information from the Advanced High Resolution Radiometer (AVHRR) on the TIROS-N series of polar-orbiting meteorological satellites for the provision of land cover information is reviewed. The data derived from this satellite is available every day. Attention is given to the use of vegetation indices derived from various combinations of the red and near infrared wavelengths of the AVHRR and the AVHRR is compared with the Landsat Multi-Spectral Scanner (MSS) which has been the instrument commonly associated with land cover studies employing satellite information. Results are provided of direct comparisons of AVHRR and Landsat data gathered over parts of Scotland and Africa. These comparisons represent an attempt to evaluate the utility of AVHRR data for the provision of land cover information over large areas, ground sampling not being possible. Special attention is given to the normalised difference vegetation index. An attempt at mapping within the intertidal zone of the Tay Estuary, Scotland is described as an example of rectifying a series of satellite images to a common projection. The land-water interface was identified in five Landsat MSS scenes, each corresponding to a different state of the tide, and was mapped to provide a bathymetric impression of the intertidal zone. Automation of the procedures for the registration and rectification of satellite data is described. The variable geometry of AVHRR data presents special problems to the automation of this process particularly if optimal

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

    NASA Astrophysics Data System (ADS)

    Limaye, A.; Molthan, A.

    2010-12-01

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

  20. Comparison of the peak resolution and the stationary phase retention between the satellite and the planetary motions using the coil satellite centrifuge with counter-current chromatographic separation of 4-methylumbelliferyl sugar derivatives.

    PubMed

    Shinomiya, Kazufusa; Zaima, Kazumasa; Harada, Yukina; Yasue, Miho; Harikai, Naoki; Tokura, Koji; Ito, Yoichiro

    2017-01-20

    Coil satellite centrifuge (CSC) produces the complex satellite motion consisting of the triplicate rotation of the coiled column around three axes including the sun axis (the angular velocity, ω1), the planet axis (ω2) and the satellite axis (the central axis of the column) (ω3) according to the following formula: ω1=ω2+ω3. Improved peak resolution in the separation of 4-methylumbelliferyl sugar derivatives was achieved using the conventional multilayer coiled columns with ethyl acetate/1-butanol/water (3: 2: 5, v/v) for the lower mobile phase at the combination of the rotation speeds (ω1, ω2, ω3)=(300, 150, 150rpm), and (1:4:5, v/v) for the upper mobile phase at (300:100:200rpm). The effect of the satellite motion on the peak resolution and the stationary phase retention was evaluated by each CSC separation with the different rotation speeds of ω2 and ω3 under the constant revolution speed at ω1=300rpm. With the lower mobile phase, almost constant peak resolution and stationary phase retention were yielded regardless of the change of ω2 and ω3, while with the upper mobile phase these two values were sensitively varied according to the different combination of ω2 and ω3. For example, when ω2=147 or 200rpm is used, no stationary phase was retained in the coiled column while ω2=150rpm could retain enough volume of stationary phase for separation. On the other hand, the combined rotation speeds at (ω1, ω2, ω3)=(300, 300, 0rpm) or (300, 0, 300rpm) produced insufficient peak resolution regardless of the choice of the mobile phase apparently due to the lack of rotation speed except at (300, 0, 300rpm) with the upper mobile phase. At lower rotation speed of ω1=300rpm, better peak resolution and stationary phase retention were obtained by the satellite motion (ω3) than by the planetary motion (ω2), or ω3>ω2. The effect of the hydrophobicity of the two-phase solvent systems on the stationary phase retention was further examined using the n

  1. A High-Resolution Two-Stage Satellite Model to Estimate PM2.5 Concentrations in China

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Ma, Z.; Hu, X.; Yang, K.

    2014-12-01

    With the rapid economic development and urbanization, severe and widespread PM2.5 pollution in China has attracted nationwide attention. Study of the health impact of PM2.5 exposure has been hindered, however, by the limited coverage of ground measurements from recently established regulatory monitoring networks. Estimating ground-level PM2.5 from satellite remote sensing is a promising new method to evaluate the spatial and temporal patterns of PM2.5 exposure. We developed a two-stage spatial statistical model to estimate daily mean PM2.5 concentrations at 10 km resolution in 2013 in China using MODIS Collection 6 AOD, assimilated meteorology, population density, and land use parameters. A custom inverse variance weighting approach was developed to combine MODIS Dark Target (DT) and Deep Blue (DB) AOD to optimize coverage. Compared with the AERONET AOD measurements, our combined AOD (R2=0.80, mean bias = 0.07) performs similarly to MODIS' combined AOD (R2=0.81, mean bias =0.07), but has 90% greater coverage. We used the first-stage linear mixed effect model to represent the temporal variability of PM2.5 and the second-stage generalized additive model to represent its spatial contrast. The overall model cross-validation R2 and relative prediction error are 0.80 and 30%, respectively. PM2.5 levels exhibit strong seasonal patterns, with the highest national mean concentrations in winter (75 µg/m3) and the lowest in summer (30 µg/m3). Elevated annual mean PM2.5 levels are predicted in North China Plain and Sichuan Basin, with the maximum annual PM2.5 concentrations higher than 130 µg/m3 and 110 µg/m3, respectively. Our results also indicates that over 94% of the Chinese population lives in areas that exceed the WHO Air Quality Interim Target-1 standard (35 μg/m3). The exceptions include Taiwan, Hainan, Yunnan, Tibet, and North Inner Mongolia.

  2. Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011

    NASA Technical Reports Server (NTRS)

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-01-01

    Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

  3. Design of a High Resolution Open Access Global Snow Cover Web Map Service Using Ground and Satellite Observations

    NASA Astrophysics Data System (ADS)

    Kadlec, J.; Ames, D. P.

    2014-12-01

    The aim of the presented work is creating a freely accessible, dynamic and re-usable snow cover map of the world by combining snow extent and snow depth datasets from multiple sources. The examined data sources are: remote sensing datasets (MODIS, CryoLand), weather forecasting model outputs (OpenWeatherMap, forecast.io), ground observation networks (CUAHSI HIS, GSOD, GHCN, and selected national networks), and user-contributed snow reports on social networks (cross-country and backcountry skiing trip reports). For adding each type of dataset, an interface and an adapter is created. Each adapter supports queries by area, time range, or combination of area and time range. The combined dataset is published as an online snow cover mapping service. This web service lowers the learning curve that is required to view, access, and analyze snow depth maps and snow time-series. All data published by this service are licensed as open data; encouraging the re-use of the data in customized applications in climatology, hydrology, sports and other disciplines. The initial version of the interactive snow map is on the website snow.hydrodata.org. This website supports the view by time and view by site. In view by time, the spatial distribution of snow for a selected area and time period is shown. In view by site, the time-series charts of snow depth at a selected location is displayed. All snow extent and snow depth map layers and time series are accessible and discoverable through internationally approved protocols including WMS, WFS, WCS, WaterOneFlow and WaterML. Therefore they can also be easily added to GIS software or 3rd-party web map applications. The central hypothesis driving this research is that the integration of user contributed data and/or social-network derived snow data together with other open access data sources will result in more accurate and higher resolution - and hence more useful snow cover maps than satellite data or government agency produced data by

  4. Achieving Superior Tropical Cyclone Intensity Forecasts by Improving the Assimilation of High-Resolution Satellite Data into Mesoscale Prediction Models

    DTIC Science & Technology

    2011-09-01

    intensity fluctuations are governed by internal and environmental processes. Remotely - sensed observations from multiple satellite sources have become...a NASA GNSS proposal: “Improving Tropical Prediction and Analysis using COSMIC Radio Occultation Observations and an Ensemble Data Assimilation

  5. High-Resolution satellite imagery mapping of the Ms 7.9, 11 august 1931 Fuyun earthquake, Northern Xinjiang, China

    NASA Astrophysics Data System (ADS)

    Etchebes, Marie; Klinger, Yann; Tapponnier, Paul

    2010-05-01

    The 11 August 1931 Fuyun earthquake (Ms 7.9), which ruptured about 160 km of the strike-slip Fuyun fault, western front of the Altai Mountains, is part of a series of 5 major events of similar magnitude that occurred in Mongolia in a lapse of 30 yrs. It counts among one of the major continental strike-slip earthquakes of the last hundred years. However, The rupture geometry and the slip distribution, key data to document fault segmentation and faulting recurrence, are poorly known for this event. A new set of high-resolution satellite images (QUICKBIRD, ASTER) provide insights into the surface rupturing process associated with this earthquake. Thanks to the arid climate conditions that prevail in the area, analysis of these images allowed us to constrain the length, the width, and the coseismic horizontal slip distribution of the Fuyun earthquake rupture zone. We have mapped the trace of the fault at the surface with accuracy using this high-resolution (<1m) data set. Detailed mapping reveals a linear right-lateral shear zone striking NNW that can be mapped for about 160 km from the Kayirti River in the north to the Ulungur River in the south. NNE-trending extensive structures as pull apart (Xinshankou pull apart), and NNW-trending compressive structures as thrust faults (Karaxingar thrust fault and Saribastaw feature) are present too and consistent with this strike. According to rupture azimuth changes, the 1931 surface rupture can be divided into four main geometric segments. These segments, with a length ranges from 27 to 55 km, present a mainly right-lateral motion with moderate normal component in the North and minor reverse component in the South. This mapping also suggests that these four first order segments can be further separated into more higher order segments, linked by geometric discontinuities like step-overs, bends, fault branches of different scales. Following Kame and al. [2003], the splay fault angle and spatial distribution of these branches

  6. Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery

    NASA Astrophysics Data System (ADS)

    Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha

    2017-04-01

    A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.

  7. HIRS-AMTS satellite sounding system test - Theoretical and empirical vertical resolving power. [High resolution Infrared Radiation Sounder - Advanced Moisture and Temperature Sounder

    NASA Technical Reports Server (NTRS)

    Thompson, O. E.

    1982-01-01

    The present investigation is concerned with the vertical resolving power of satellite-borne temperature sounding instruments. Information is presented on the capabilities of the High Resolution Infrared Radiation Sounder (HIRS) and a proposed sounding instrument called the Advanced Moisture and Temperature Sounder (AMTS). Two quite different methods for assessing the vertical resolving power of satellite sounders are discussed. The first is the theoretical method of Conrath (1972) which was patterned after the work of Backus and Gilbert (1968) The Backus-Gilbert-Conrath (BGC) approach includes a formalism for deriving a retrieval algorithm for optimizing the vertical resolving power. However, a retrieval algorithm constructed in the BGC optimal fashion is not necessarily optimal as far as actual temperature retrievals are concerned. Thus, an independent criterion for vertical resolving power is discussed. The criterion is based on actual retrievals of signal structure in the temperature field.

  8. Improving satellite quantitative precipitation estimates through the use of high-resolution numerical weather predictions: Similarities and contrasts between the Alps and Blue Nile region

    NASA Astrophysics Data System (ADS)

    Bartsotas, Nikolaos; Nikolopoulos, Efthymios; Anagnostou, Emmanouil; Kallos, George

    2017-04-01

    Estimation of heavy precipitation events (HPEs) over high mountainous terrain is a particularly challenging task due to the limited availability of in-situ observations. Proper analysis and thorough understanding of the charac-teristics of HPE over complex terrain is thus hampered by insufficient precipitation information. Rain gauge networks usually present insufficient density and quality control issues in such areas. Radar rainfall estimates, wherever available, are heavily affected from terrain blockage. In this context, remote sensing has been attributed with a major role. However, this does not come without blemishes, as strong underestimation of precipitation associated with low-level orographic enhancement, introduces significant error in satellite estimates. In this study, we evaluate a satellite precipitation error-correction approach that can be implemented in the ab-sence of ground observations and it is based on utilization of precipitation information from high-resolution (1-2km) NWP simulations. Two quasi-global satellite precipitation products (CMORPH-8km and PERSIANN-4km) are used in more than 20 identified HPEs over two mountainous areas, the Alps and Ethiopia's Blue Nile. High-resolution atmospheric simulations from RAMS/ICLAMS are evaluated against rain gauge networks and radar estimates, then utilized to derive error correction functions for corresponding satellite precipitation data. Consequently, a PDF matching is applied and conclusions on the dependence of the method from synoptic at-mospheric conditions, which reveal to a certain degree the predictability of error properties, as well as the possi-bility of a global approach, are thoroughly discussed.

  9. Improved capabilities of the Chinese high-resolution remote sensing satellite GF-1 for monitoring suspended particulate matter (SPM) in inland waters: Radiometric and spatial considerations

    NASA Astrophysics Data System (ADS)

    Li, Jian; Chen, Xiaoling; Tian, Liqiao; Huang, Jue; Feng, Lian

    2015-08-01

    Dominated by high dynamic and small-scale variability, remote sensing of inland or coastal waters is frequently impended by insufficient spatial resolutions from conventional ocean color sensors. With the urgent need and the rapid progress in high-resolution earth observation systems (HR), it is critical to assess the capabilities of HR in inland water monitoring. In this study, the radiometric and spatial performance of the Chinese high-resolution GF-1 Wide Field Imager (WFI) data for water quality monitoring were evaluated in term of the signal-to-noise ratio (SNR), sensitivity to suspended particulate matter (SPM) variations and spatial depiction ability. The SNR was statistically estimated from variable moving window method, and the radiometric sensitivity was simulated using the Moderate Resolution Atmospheric Transmission (MODTRAN) under varied surface and atmospheric conditions. Results indicated that both the SNR and the radiometric sensitivity of the GF-1 WFI were enhanced by 3-5 times than its predecessor (Chinese HJ-1 CCD) or Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and were comparable to Landsat 8 Operational Land Imager (OLI) and Moderate Resolution Imaging Spectroradiometer (MODIS) medium-resolution bands (250 and 500 m), which have been extensively applied in inland water environment monitoring. Cross comparisons demonstrated high consistency of the spatial distribution and concentration of SPM maps between GF-1 WFI and Landsat 8 OLI. Furthermore, more than 75% of the spatial variations in high turbid waters were resolved from GF-1 WFI data, whereas the ability dropped to 40% when the spatial resolution was degraded to 250 m (MODIS-like sensors). Overall, GF-1 WFI is extraordinarily promising with an enhanced SNR, an increased spectral sensitivity to SPM variations and an advanced spatial resolution. With the ongoing plans of the successive GF series (2-7), the findings would serve as a reference for forthcoming applications, and are critical

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  11. A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data

    USGS Publications Warehouse

    Pengra, Bruce; Long, Jordan; Dahal, Devendra; Stehman, Stephen V.; Loveland, Thomas R.

    2015-01-01

    The methodology for selection, creation, and application of a global remote sensing validation dataset using high resolution commercial satellite data is presented. High resolution data are obtained for a stratified random sample of 500 primary sampling units (5 km  ×  5 km sample blocks), where the stratification based on Köppen climate classes is used to distribute the sample globally among biomes. The high resolution data are classified to categorical land cover maps using an analyst mediated classification workflow. Our initial application of these data is to evaluate a global 30 m Landsat-derived, continuous field tree cover product. For this application, the categorical reference classification produced at 2 m resolution is converted to percent tree cover per 30 m pixel (secondary sampling unit)for comparison to Landsat-derived estimates of tree cover. We provide example results (based on a subsample of 25 sample blocks in South America) illustrating basic analyses of agreement that can be produced from these reference data. Commercial high resolution data availability and data quality are shown to provide a viable means of validating continuous field tree cover. When completed, the reference classifications for the full sample of 500 blocks will be released for public use.

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

    NASA Astrophysics Data System (ADS)

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

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

  13. A sampling procedure to guide the collection of narrow-band, high-resolution spatially and spectrally representative reflectance data. [satellite imagery of earth resources

    NASA Technical Reports Server (NTRS)

    Brand, R. R.; Barker, J. L.

    1983-01-01

    A multistage sampling procedure using image processing, geographical information systems, and analytical photogrammetry is presented which can be used to guide the collection of representative, high-resolution spectra and discrete reflectance targets for future satellite sensors. The procedure is general and can be adapted to characterize areas as small as minor watersheds and as large as multistate regions. Beginning with a user-determined study area, successive reductions in size and spectral variation are performed using image analysis techniques on data from the Multispectral Scanner, orbital and simulated Thematic Mapper, low altitude photography synchronized with the simulator, and associated digital data. An integrated image-based geographical information system supports processing requirements.

  14. A sampling procedure to guide the collection of narrow-band, high-resolution spatially and spectrally representative reflectance data. [satellite imagery of earth resources

    NASA Technical Reports Server (NTRS)

    Brand, R. R.; Barker, J. L.

    1983-01-01

    A multistage sampling procedure using image processing, geographical information systems, and analytical photogrammetry is presented which can be used to guide the collection of representative, high-resolution spectra and discrete reflectance targets for future satellite sensors. The procedure is general and can be adapted to characterize areas as small as minor watersheds and as large as multistate regions. Beginning with a user-determined study area, successive reductions in size and spectral variation are performed using image analysis techniques on data from the Multispectral Scanner, orbital and simulated Thematic Mapper, low altitude photography synchronized with the simulator, and associated digital data. An integrated image-based geographical information system supports processing requirements.

  15. Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

    NASA Technical Reports Server (NTRS)

    Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

    2012-01-01

    Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived

  16. Achieving Superior Tropical Cyclone Intensity Forecasts by Improving the Assimilation of High-Resolution Satellite Data into Mesoscale Prediction Models

    DTIC Science & Technology

    2013-09-30

    how intensity fluctuations are governed by internal and environmental processes. Remotely - sensed observations from multiple satellite sources have...UCAR is related to a NASA GNSS proposal: “Improving Tropical Prediction and Analysis using COSMIC Radio Occultation Observations and an Ensemble Data

  17. Wetland delineation with IKONOS high-resolution satellite imagery, Fort Custer Training Center, Battle Creek, Michigan, 2005

    USGS Publications Warehouse

    Fuller, L.M.; Morgan, T.R.; Aichele, S.S.

    2006-01-01

    The Michigan Army National Guard’s Fort Custer Training Center (FCTC) in Battle Creek, Mich., has the responsibility to protect wetland resources on the training grounds while providing training opportunities, and for future development planning at the facility. The National Wetlands Inventory (NWI) data have been the primary wetland-boundary resource, but a check on scale and accuracy of the wetland boundary information for the Fort Custer Training Center was needed. In cooperation with the FCTC, the U.S. Geological Survey (USGS) used an early spring IKONOS pan-sharpened satellite image to delineate the wetlands and create a more accurate wetland map for the FCTC. The USGS tested automated approaches (supervised and unsupervised classifications) to identify the wetland areas from the IKONOS satellite image, but the automated approaches alone did not yield accurate results. To ensure accurate wetland boundaries, the final wetland map was manually digitized on the basis of the automated supervised and unsupervised classifications, in combination with NWI data, field verifications, and visual interpretation of the IKONOS satellite image. The final wetland areas digitized from the IKONOS satellite imagery were similar to those in NWI; however, the wetland boundaries differed in some areas, a few wetlands mapped on the NWI were determined not to be wetlands from the IKONOS image and field verification, and additional previously unmapped wetlands not recognized by the NWI were identified from the IKONOS image.

  18. Instantaneous Shoreline Extraction Utilizing Integrated Spectrum and Shadow Analysis From LiDAR Data and High-resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Lee, I.-Chieh

    Shoreline delineation and shoreline change detection are expensive processes in data source acquisition and manual shoreline delineation. These costs confine the frequency and interval of shoreline mapping periods. In this dissertation, a new shoreline delineation approach was developed targeting on lowering the data source cost and reducing human labor. To lower the cost of data sources, we used the public domain LiDAR data sets and satellite images to delineate shorelines without the requirement of data sets being acquired simultaneously, which is a new concept in this field. To reduce the labor cost, we made improvements in classifying LiDAR points and satellite images. Analyzing shadow relations with topography to improve the satellite image classification performance is also a brand-new concept. The extracted shoreline of the proposed approach could achieve an accuracy of 1.495 m RMSE, or 4.452m at the 95% confidence level. Consequently, the proposed approach could successfully lower the cost and shorten the processing time, in other words, to increase the shoreline mapping frequency with a reasonable accuracy. However, the extracted shoreline may not compete with the shoreline extracted by aerial photogrammetric procedures in the aspect of accuracy. Hence, this is a trade-off between cost and accuracy. This approach consists of three phases, first, a shoreline extraction procedure based mainly on LiDAR point cloud data with multispectral information from satellite images. Second, an object oriented shoreline extraction procedure to delineate shoreline solely from satellite images; in this case WorldView-2 images were used. Third, a shoreline integration procedure combining these two shorelines based on actual shoreline changes and physical terrain properties. The actual data source cost would only be from the acquisition of satellite images. On the other hand, only two processes needed human attention. First, the shoreline within harbor areas needed to be

  19. Three dimensional monitoring of urban development by means of ortho-rectified aerial photographs and high-resolution satellite images.

    PubMed

    Ayhan, E; Erden, O; Gormus, E T

    2008-12-01

    Nowadays, cities are developing and changing rapidly due to the increases in the population and immigration. Rapid changing brings obligation to control the cities by planning. The satellite images and the aerial photographs enable us to track the urban development and provide the opportunity to get the current data about urban. With the help of these images, cities may have interrogated dynamic structures. This study is composed of three steps. In the first step, orthophoto images have been generated in order to track urban developments by using the aerial photographs and the satellite images. In this step, the panchromatic (PAN), the multi spectral (MS) and the pan-sharpened image of IKONOS satellite have been used as input satellite data and the accuracy of orthophoto images has been investigated in detail, in terms of digital elevation model (DEM), control points, input images and their properties. In the second step, a 3D city model with database has been generated with the help of orthophoto images and the vector layouts. And in the last step, up to date urban information obtained from 3D city model. This study shows that it is possible to detect the unlicensed buildings and the areas which are going to be nationalized and it also shows that it is easy to document the existing alterations in the cities with the help of current development plans and orthophoto images. And since accessing updated data is very essential to control development and monitor the temporal alterations in urban areas, in this study it is proven that the orthophoto images generated by using aerial photos and satellite images are very reliable to use in obtaining topographical information, in change detection and in city planning. When digital orthophoto images used with GIS, they provide quick decision control mechanisms and quick data collection. Besides, they help to find efficient solutions in a short time in the planning applications.

  20. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere using Infrared Sounding and 3D Winds Measurements

    NASA Astrophysics Data System (ADS)

    Maschhoff, K. R.; Polizotti, J. J.; Susskind, J.; Aumann, H. H.

    2015-12-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sun-synchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's Atmospheric Infrared Sounder that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  1. MISTiC Winds: A micro-satellite constellation approach to high resolution observations of the atmosphere using infrared sounding and 3D winds measurements

    NASA Astrophysics Data System (ADS)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-09-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  2. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere Using Infrared Sounding and 3D Winds Measurements

    NASA Technical Reports Server (NTRS)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-01-01

    MISTiC(TM) Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiCs extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenasat much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  3. Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering.

    PubMed

    Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

    2015-09-10

    In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments.

  4. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    NASA Astrophysics Data System (ADS)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  5. Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

    PubMed Central

    Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

    2015-01-01

    In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments. PMID:26378532

  6. Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR), P. R. China

    NASA Astrophysics Data System (ADS)

    Leempoel, K.; Satyaranayana, B.; Bourgeois, C.; Zhang, J.; Chen, M.; Wang, J.; Bogaert, J.; Dahdouh-Guebas, F.

    2013-08-01

    Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc.) to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China) were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively). Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (-36%) was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%), the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements) (August-September, 2009) as well as spectral reflectance values (obtained from pansharpened GeoEye-1), both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73-100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%). In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m) for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e.g. Kandelia obovata

  7. A characterization of intermediate-scale spread F structure from four years of high-resolution C/NOFS satellite data

    NASA Astrophysics Data System (ADS)

    Rino, Charles L.; Carrano, Charles S.; Groves, Keith M.; Roddy, Patrick A.

    2016-06-01

    Power law spectra have been invoked to interpret equatorial scintillation data for decades. Published analyses of intensity and phase scintillation data typically report power law spectra of the form q-p with 2.4 < p < 2.6. However, in situ rocket and satellite measurements of equatorial spread F have shown evidence of spectra with two power law components. Strong scatter simulations and recent theoretical results have shown that two-component power law spectra can reconcile simultaneous equatorial scintillation observations from VHF to S-Band. The Communication/Navigation Outage Forecasting System (C/NOFS) satellite Planar Langmuir Probe generated a multiyear high-resolution sampling of equatorial spread F, but published analyses to date have reported only single-component power laws over scales from tens of kilometers to 70 m. This paper summarizes the analysis of high-resolution C/NOFS data collected over the four year period 2011 to 2014. Following an earlier investigation of several months of C/NOFS data by the authors of this paper, the extended data set revealed a pattern of occurrence of two-component spectra in the most highly disturbed data sets. The results confirm a known inverse correlation between turbulent strength and spectral index. The new results are interpreted as an equatorial spread F life cycle pattern with two-component spectra in the early development phase giving way to single-component spectra in the decay phase.

  8. Seasonal and Intra-Seasonal Variability of Surface Streams Over the West Greenland Ice Sheet from High Resolution Satellite Optical Data.

    NASA Astrophysics Data System (ADS)

    Brown, M. G.; Tedesco, M.

    2014-12-01

    The surface hydrology of the Greenland ice sheet plays a crucial role on surface energy and mass balance, as well as on the englacial and sub-glacial environments. The spatial distribution of these surface streams is poorly understood and their temporal variability is (to our knowledge) unknown. One of the reasons for the lack of knowledge on the temporal variability of such streams is related to the historical unavailability of satellite data that could spatially resolve the presence and associated properties of the streams. In recent years, however, multi-spectral commercial satellite data in the visible and infra-red bands have been made available to the scientific community. These newly accessible data sets are provided at spatial resolutions of the order of 1-2 meters, therefore, allowing to perform accurate spatial and temporal analysis of surface streams (and small lakes and ponds that cannot be resolved with sensors such as MODIS or LANDSAT). In this study, we report results concerning the seasonal and intra-seasonal variability of surface streams over a selected area on the west Greenland ice sheet. Using a combination of ENVI® and ArcGIS® software packages applied to multispectral high resolution imagery from World View 2 and Quickbird satellites, surface streams are identified through multiple approaches (either based on unsupervised classifications, band combinations, band ratio thresholds, or digitization) and vector maps of the surface hydrology network were created. Stream networks created during one melting season (at three different stages of the season) were compared and discussed as well as the networks mapped between two consecutive years for proximate dates.

  9. Seasonal and Intra-Seasonal Variability of Surface Streams over the West Greenland Ice Sheet from High Resolution Satellite Optical Data.

    NASA Astrophysics Data System (ADS)

    Brown, Michael G.; Tedesco, Marco

    2015-04-01

    The surface hydrology of the Greenland ice sheet plays a crucial role on surface energy and mass balance, as well as on the en-glacial and sub-glacial environments. The spatial distribution of these surface streams is poorly understood and their temporal variability is (to our knowledge) unknown. One of the reasons for the lack of knowledge on the temporal variability of such streams is related to the historical unavailability of satellite data that could spatially resolve the presence and associated properties of the streams. In recent years, however, multi-spectral commercial satellite data in the visible and infra-red bands have been made available to the scientific community. These newly accessible data sets are provided at spatial resolutions of the order of 1-2 meters, therefore, allowing to perform accurate spatial and temporal analysis of surface streams (and small lakes and ponds that cannot be resolved with sensors such as MODIS or LANDSAT). In this study, we report results concerning the seasonal and intra-seasonal variability of surface streams over a selected area on the west Greenland ice sheet. Using ArcGIS® software applied to multispectral high resolution imagery from World View 2 and Quickbird satellites, surface streams were identified through band math, threshold classifications, and morphological operations. Raster and vector maps of the surface hydrology network were created. Stream networks created during multiple melt seasons (at several different stages of the season) were compared and discussed as well as the networks mapped between consecutive years for proximate dates.

  10. On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Kingfield, D.; de Beurs, K.

    2014-12-01

    It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

  11. Creating Orthographically Rectified Satellite Multi-Spectral Imagery with High Resolution Digital Elevation Model from LiDAR: A Tutorial

    DTIC Science & Technology

    2014-08-15

    Detection and Ranging (LiDAR) Digital Elevation Models (DEM) and from commercial satellite Multi-Spectral Imagery ( MSI ) in the National Imagery Transmis...processing the original MSI . This generic re- placement sensor model is provided with the distributed imagery to sim- plify the process of removing...The DEM and MSI also become better registered together after producing the orthoimage by using the RPC. This assists feature extraction and

  12. Aerosol Optical Depth Retrievals from High-Resolution Commercial Satellite Imagery Over Areas of High Surface Reflectance

    DTIC Science & Technology

    2006-06-01

    generally composed of clays, alumina - silicates , and various evaporates, however, unique components such as ocean carbonates from deposits underlying...of days to weeks (IPCC 2001). Recent climate research efforts, especially using remote sensing and modeling, have focused on characterizing the...reflectance function, R, when applied to satellite remote sensing, is termed bi-directional reflectance, and is given by: ( ) ( ) ( )0 0 0 0 0; , ; , 0

  13. Integrating Landsat-8, Sentinel-2, and nano-satellite data for deriving atmospherically corrected vegetation indices at enhanced spatio-temporal resolution

    NASA Astrophysics Data System (ADS)

    Houborg, Rasmus; McCabe, Matthew F.; Ershadi, Ali

    2017-04-01

    Flocks of nano-satellites are emerging as an economic resource for overcoming spatio-temporal constraints of conventional single-sensor satellite missions. Planet Labs operates an expanding constellation of currently more than 40 CubeSats (30x10x10 cm3), which will facilitate daily capture of broadband RGB and near-infrared (NIR) imagery for every location on earth at a 3-5 m ground sampling distance. However, data acquired by these miniaturized satellites lack rigorous radiometric corrections and radiance conversions and should be used in synergy with high quality imagery required by conventional large satellites such as Landsat-8 (L8) and Sentinel-2 (S2) in order to realize the full potential of this game changing observational resource. This study integrates L8, S2 and Planet data acquired over sites in Saudi Arabia and the state of California for deriving cross-sensor consistent and atmospherically corrected Vegetation Indices (VI) that may serve as important metrics for vegetation growth, health, and productivity. An automated framework, based on 6S and satellite retrieved atmospheric state and aerosol inputs, is first applied to L8 and S2 at-sensor radiances for the production of atmospherically corrected VIs. Scale-consistent Planet RGB and NIR imagery is then related to the corrected VI data using a selective, scene-specific, and computationally fast machine learning approach. The developed technique uses the closest pair of Planet and L8/S2 scenes in the training of the predictive VI models and accounts for changes in cover conditions over the acquisition timespan. Application of the models to full resolution Planet imagery results in cross-sensor consistent VI estimates at the scale and time of the nano-satellite acquisition. The utility of the approach for reproducing spatial features in L8 and S2 based indices based on Planet imagery is evaluated. The technique is generic, computationally efficient, and extendable and serves well for implementation

  14. High-Resolution Satellite-Derived PM2.5 from Optimal Estimation and Geographically Weighted Regression over North America.

    PubMed

    van Donkelaar, Aaron; Martin, Randall V; Spurr, Robert J D; Burnett, Richard T

    2015-09-01

    We used a geographically weighted regression (GWR) statistical model to represent bias of fine particulate matter concentrations (PM2.5) derived from a 1 km optimal estimate (OE) aerosol optical depth (AOD) satellite retrieval that used AOD-to-PM2.5 relationships from a chemical transport model (CTM) for 2004-2008 over North America. This hybrid approach combined the geophysical understanding and global applicability intrinsic to the CTM relationships with the knowledge provided by observational constraints. Adjusting the OE PM2.5 estimates according to the GWR-predicted bias yielded significant improvement compared with unadjusted long-term mean values (R(2) = 0.82 versus R(2) = 0.62), even when a large fraction (70%) of sites were withheld for cross-validation (R(2) = 0.78) and developed seasonal skill (R(2) = 0.62-0.89). The effect of individual GWR predictors on OE PM2.5 estimates additionally provided insight into the sources of uncertainty for global satellite-derived PM2.5 estimates. These predictor-driven effects imply that local variability in surface elevation and urban emissions are important sources of uncertainty in geophysical calculations of the AOD-to-PM2.5 relationship used in satellite-derived PM2.5 estimates over North America, and potentially worldwide.

  15. Monitoring of the Spatial Distribution and Temporal Dynamics of the Green Vegetation Fraction of Croplands in Southwest Germany Using High-Resolution RapidEye Satellite Images

    NASA Astrophysics Data System (ADS)

    Imukova, Kristina; Ingwersen, Joachim; Streck, Thilo

    2014-05-01

    The green vegetation fraction (GVF) is a key input variable to the evapotranspiration scheme applied in the widely used NOAH land surface model (LSM). In standard applications of the NOAH LSM, the GVF is taken from a global map with a 15 km×15 km resolution. The central objective of the present study was (a) to derive gridded GVF data in a high spatial and temporal resolution from RapidEye images for a region in Southwest Germany, and (b) to improve the representation of the GVF dynamics of croplands in the NOAH LSM for a better simulation of water and energy exchange between land surface and atmosphere. For the region under study we obtained monthly RapidEye satellite images with a resolution 5 m×5 m by the German Aerospace Center (DLR). The images hold five spectral bands: blue, green, red, red-edge and near infrared (NIR). The GVF dynamics were determined based on the Normalized Difference Vegetation Index (NDVI) calculated from the red and near-infrared bands of the satellite images. The satellite GVF data were calibrated and validated against ground truth measurements. Digital colour photographs above the canopy were taken with a boom-mounted digital camera at fifteen permanently marked plots (1 m×1 m). Crops under study were winter wheat, winter rape and silage maize. The GVF was computed based on the red and the green band of the photographs according to Rundquist's method (2002). Based on the obtained calibration scheme GVF maps were derived in a monthly resolution for the region. Our results confirm a linear relationship between GVF and NDVI and demonstrate that it is possible to determine the GVF of croplands from RapidEye images based on a simple two end-member mixing model. Our data highlight the high variability of the GVF in time and space. At the field scale, the GVF was normally distributed with a coefficient of variation of about 32%. Variability was mainly caused by soil heterogeneities and management differences. At the regional scale the GVF

  16. Assessment of a Near-Global 30-meter Resolution DEM Derived from the Publicly Available SRTM Data Set for Use in Orthorectification of Satellite SAR Imagery

    NASA Astrophysics Data System (ADS)

    McDonald, K. C.; Chapman, B.; Podest, E.; Jimenez, A.

    2007-12-01

    The Shuttle Radar Topography Mission (SRTM) utilized an interferometric synthetic aperture radar (InSAR) flown onboard the space shuttle Endeavour to obtain high resolution elevation data of Earth's land surface. Virtually all land surface between +/- 60 degrees latitude was mapped. Regions within these bounds contain some data gaps but this represents less than 0.2 % of the coverage. Standard publicly-available data sets from SRTM include a 3 arc-second (~90 meter) resolution Digital Elevation Model (DEM) with absolute average global vertical accuracy of approximately 4 to 5 meters. A 1 arc-second (~30 meter) resolution DEM has also been developed, but only the portion of the data set covering the United States is publicly available. The finished version of these products has been edited for pixel-level errors and delineation of coastlines and water bodies, although some data voids are still present. Utilizing such DEMs of appropriate resolution in a common framework with satellite synthetic aperture radar (SAR) data allows robust ortho-rectification and geo-referencing of the SAR data sets. We have derived a 1 arc-second resolution DEM over the entire domain of the SRTM coverage using a 3- dimensional interpolation scheme applied to the 3 arc-second SRTM DEM. Development of this product involves (1) translation of SRTM products into the WGS84 datum, (2) interpolation of the lower resolution DEMs to 1 arc- second, and (3) assembly of the global-scale 1 arc-second DEM. We assess effectiveness of this interpolation scheme through comparative statistical analysis of the 3 arc-second finished product, the 1 arc-second finished product, and the 1 arc-second interpolated product over selected test regions within the USA where all products are available. Comparisons are also made to standard GTOPO30 products for regions inside and outside of the USA. Comparisons are presented for regions representative of gentle and complex terrain. Ortho-rectification of SAR data such

  17. High-resolution satellite-derived ocean surface winds in the Nordic-Barents seas region: Implications for ocean modeling (Invited)

    NASA Astrophysics Data System (ADS)

    Dukhovskoy, D. S.; Bourassa, M. A.; Hughes, P. J.

    2010-12-01

    High-resolution (0.25°) ocean surface wind velocity data derived from satellite observations are used to analyze winds in the Nordic-Barents seas during 2007-2008. For the analysis, a Cross-Calibrated, Multi-Platform (CCMP), multi-instrument ocean surface wind velocity data set is utilized. The product has been developed by National Aeronautics and Space Administration (NASA) within Making Earth Science data records for Use in Research Environments (MEaSUREs) Program. A variational method was used to combine wind measurements derived from satellite-born active and passive remote sensing instruments. In the objective procedure, winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) Operational Analysis (DS111.1) were used as the background fields. The ocean surface wind fields are compared with those derived from the National Centers for Environmental Protection/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. The NCEP/NCAR fields are commonly used to provide atmospheric forcing for Arctic Ocean models. The utility of using high-resolution winds in the ocean modeling is discussed. In particular, air-sea heat fluxes estimated from the two wind data sets are compared. It is anticipated that wind fields with higher spatial and temporal resolution will better resolve small-scale, short-lived atmospheric systems. As an example, the ice free region in the Nordic and Barents seas is frequently impacted by very intense cyclones known as “polar lows” with wind speeds near to or above gale force. A polar low forms over the sea and predominantly during the winter months. The size of these cyclones varies greatly from 100 to 1000 km. Presumably small-scale cyclones are misrepresented or not resolved in the NCAR fields leading to biases in the air-sea flux calculations in the ocean models. Inaccurate estimates of the air-sea fluxes eventually lead to biases in the Arctic Ocean model solutions.

  18. Using High Resolution Commercial Satellite Imagery to Quantify Spatial Features of Urban Areas and their Relationship to Quality of Life Indicators in Accra, Ghana

    NASA Astrophysics Data System (ADS)

    Sandborn, A.; Engstrom, R.; Yu, Q.

    2014-12-01

    Mapping urban areas via satellite imagery is an important task for detecting and anticipating land cover and land use change at multiple scales. As developing countries experience substantial urban growth and expansion, remotely sensed based estimates of population and quality of life indicators can provide timely and spatially explicit information to researchers and planners working to determine how cities are changing. In this study, we use commercial high spatial resolution satellite imagery in combination with fine resolution census data to determine the ability of using remotely sensed data to reveal the spatial patterns of quality of life in Accra, Ghana. Traditionally, spectral characteristics are used on a per-pixel basis to determine land cover; however, in this study, we test a new methodology that quantifies spatial characteristics using a variety of spatial features observed in the imagery to determine the properties of an urban area. The spatial characteristics used in this study include histograms of oriented gradients, PanTex, Fourier transform, and line support regions. These spatial features focus on extracting structural and textural patterns of built-up areas, such as homogeneous building orientations and straight line indices. Information derived from aggregating the descriptive statistics of the spatial features at both the fine-resolution