Science.gov

Sample records for landsat satellite imagery

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

    USGS Publications Warehouse

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

    2013-01-01

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

  2. Hydrographic charting from LANDSAT Satellite: A comparison with aircraft imagery

    NASA Technical Reports Server (NTRS)

    Middleton, E. M.; Barker, J. L.

    1976-01-01

    The relative capabilities of two remote-sensing systems in measuring depth and, consequently, bottom contours in sandy-bottomed and sediment-laden coastal waters were determined quantitatively. The multispectral scanner (MSS), orbited on the LANDSAT-2 Satellite, and the ocean color scanner (OCS), flown on U-2 aircraft, were used. Analysis of imagery taken simultaneously indicates a potential for hydrographic charting of marine coastal and shallow shelf areas, even when water turbidity is a factor. Several of the eight optical channels examined on the OCS were found to be sensitive to depth or depth-related information. The greatest sensitivity was in OCS-4(0.544 + or - 0.012 microns) from which contours corresponding to depths up to 12m were determined. The sharpness of these contours and their spatial stability through time suggests that upwelling radiance is a measure of bottom reflectance and not of water turbidity. The two visible channels on LANDSAT's MSS were less sensitive in the discrimination of contours, with depths up to 8m in the high-gain mode (3x) determined in MSS-4(0.5 to 0.6 microns).

  3. Results of 17 Independent Geopositional Accuracy Assessments of Earth Satellite Corporation's GeoCover Landsat Thematic Mapper Imagery. Geopositional Accuracy Validation of Orthorectified Landsat TM Imagery: Northeast Asia

    NASA Technical Reports Server (NTRS)

    Smith, Charles M.

    2003-01-01

    This report provides results of an independent assessment of the geopositional accuracy of the Earth Satellite (EarthSat) Corporation's GeoCover, Orthorectified Landsat Thematic Mapper (TM) imagery over Northeast Asia. This imagery was purchased through NASA's Earth Science Enterprise (ESE) Scientific Data Purchase (SDP) program.

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

    SciTech Connect

    Zimmerman, P.D.

    1993-07-01

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

  5. Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

    NASA Technical Reports Server (NTRS)

    Clark, J.

    1981-01-01

    Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Technical Reports Server (NTRS)

    1982-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Baumann, Matthias

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

  9. Landsat: radiometric and topographic correction of satellite imagery (R package)

    USDA-ARS?s Scientific Manuscript database

    Most Geographic Information System software includes routines for atmospheric and topograhic correction of satellite imagery such as that taken by Landsat. Radiometric correction is an active area of research, and new, improved methods are rarely if ever available for testing and application. The R...

  10. Using Landsat Thematic Mapper and SPOT Satellite Imagery to inventory wetland plants of the Coeur d'Alene Floodplain

    Treesearch

    F. M. Roberts; P. E. Gessler

    2000-01-01

    Landsat Thematic Mapper (TM) and SPOT Satellite Imagery were used to map wetland plant species in thc Coeur d'Alene floodplain in northern Idaho. This paper discusses the methodology used to create a wetland plant species map for the floodplain. Species mapped included common cattail (Typha latifolia); water horse-tail (Equisetum...

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

    SciTech Connect

    Quinn, Nigel W. T.; Epshtein, Olga

    2014-01-09

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

  12. Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

    NASA Technical Reports Server (NTRS)

    Clark, J.

    1981-01-01

    In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

  13. Landsat imagery: a unique resource

    USGS Publications Warehouse

    Miller, H.; Sexton, N.; Koontz, L.

    2011-01-01

    Landsat satellites provide high-quality, multi-spectral imagery of the surface of the Earth. These moderate-resolution, remotely sensed images are not just pictures, but contain many layers of data collected at different points along the visible and invisible light spectrum. These data can be manipulated to reveal what the Earth’s surface looks like, including what types of vegetation are present or how a natural disaster has impacted an area (Fig. 1).

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

    USGS Publications Warehouse

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

    2011-01-01

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

  15. Application of LANDSAT satellite imagery for iron ore prospecting in the Western Desert of Egypt

    NASA Technical Reports Server (NTRS)

    Elshazly, E. M.; Abdelhady, M. A.; Elghawaby, M. A.; Khawasik, S. M.

    1977-01-01

    Prospecting for iron ore occurrences was conducted by the Remote Sensing Center in Bahariya Oasis-El Faiyum area covering some 100,000 km squared in the Western Desert of Egypt. LANDSAT-1 satellite images were utilized as the main tool in the regional prospecting of the iron ores. The delineation of the geological units and geological structure through the interpretation of the images corroborated by field observations and structural analysis led to the discovery of new iron ore occurrences in the area of investigation.

  16. Forest Tree Species Distribution Mapping Using Landsat Satellite Imagery and Topographic Variables with the Maximum Entropy Method in Mongolia

    NASA Astrophysics Data System (ADS)

    Hao Chiang, Shou; Valdez, Miguel; Chen, Chi-Farn

    2016-06-01

    Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled

  17. BOREAS Landsat MSS Imagery: Digital Counts

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Strub, Richard; Newcomer, Jeffrey A.

    2000-01-01

    The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. The Earth Resources Technology Satellite (ERTS) Program launched the first of a series of satellites (ERTS-1) in 1972. Part of the NASA Earth Resources Survey Program, the ERTS Program and the ERTS satellites were later renamed Landsat to better represent the civil satellite program's prime emphasis on remote sensing of land resources. Landsat satellites 1 through 5 carry the Multispectral Scanner (MSS) sensor. Canada for Remote Sensing (CCRS) and BOREAS personnel gathered a set of MSS images of the BOREAS region from Landsat satellites 1, 2, 4, and 5 covering the dates of 21 Aug 1972 to 05 Sep 1988. The data are provided in binary image format files of various formats. The Landsat MSS imagery is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

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

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  19. Application of LANDSAT satellite imagery and oceanographic data for verification of an upwelling mathematical model. [Atlantic Coast of Brazil

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Tanaka, K.; Almeida, E. G.

    1978-01-01

    The author has identified the following significant results. Data obtained during the cruise of the Cabo Frio and from LANDSAT imagery are used to discuss the characteristics of a linear model which simulates wind induced currents calculated from meteorological conditions at the time of the mission. There is a significant correspondance between the model of simulated horizontal water circulation, sea surface temperature, and surface currents observed on LANDSAT imagery. Close approximations were also observed between the simulation of vertical water movement (upwelling) and the oceanographic measurements taken along a series of points of the prevailing currents.

  20. Landsat imagery for hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Taylor, R. S.; Shubinski, R. P.; George, T. S.

    1980-01-01

    The cost and effectiveness of developing land cover information derived from Landsat imagery for hydrologic studies are compared with the cost and effectiveness of conventional sources. The analysis shows that the conventional and Landsat methods are nearly equally effective in providing adequate land cover data for hydrologic studies. The total cost effectiveness analysis demonstrates that the conventional method is cost effective for a study area of less than 26 sq km and that the Landsat method is to be preferred for areas of more than 26 sq km.

  1. Landsat-1 imagery for geologic evaluation

    NASA Technical Reports Server (NTRS)

    Welby, C. W.

    1976-01-01

    The paper reviews the geologic evaluation of the North Carolina coastal plain using Landsat-1 imagery as related to a general study of the geomorphology to assess the imagery as a tool for upgrading the understanding of the coastal plain, along with recognition of subsurface structures. Among the more prominent features displayed on the Landsat imagery are the scarps and beach ridges associated with former positions of the shoreline. Compilations of various types of lineaments reveal two dominant trends, one northwest-southeast and the other northeast-southwest, which are significant in the tectonic development of the Atlantic Coastal Plain. The synoptic view recorded by the satellite allows a perspective that aids geologic studies of the Atlantic Coastal Plain.

  2. Surveying the area of deforestation of the Amazon by LANDSAT satellite imagery. [Mato grosso, Goias and Para, Brazil

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Tardin, A. T.; Dossantos, A. P.; Lee, D. C. L.; Soaresmaia, F. C.; Mendonca, F. J.; Assuncao, G. V.; Rodrigues, J. E.; Demouraabdon, M.; Novaes, R. A.

    1979-01-01

    LANDSAT imagery was used to determine the amount of deforestation in a study area comprising 55 million hectares of the Amazon region. Results show that more than 4 million hectares were deforested. Maps and pictures of the deforested area in relation to the total area of the Amazon are included.

  3. KH-series satellite imagery and Landsat MSS data fusion in support of assessing urban land use growth

    NASA Astrophysics Data System (ADS)

    Civco, Daniel; Chabaeva, Anna; Parent, Jason

    2009-09-01

    Multi-temporal land use data, circa 1990 and 2000, have been analyzed an our urban growth model which identifies three levels of the urban extent - the impervious surface, the urbanized area, and the urban footprint - to account for the differing degrees of open space degradation associated with the city. The model also generates metrics such as cohesion, proximity, population densities, average openness, open space contiguity, and depth which quantify spatial characteristics that are indicative of urban sprawl. We plan on expanding this time-series further, and for additional cities, with mid-decadal, gap-filled Landsat ETM data, as well as resolution-enhanced Landsat MSS data from the 19070's. The cities used in this pilot project consisted of: (a) Kigali, Rwanda; (b) Portland, Oregon; (c) Tacoma, Washington; and (d) Plock, Poland. Based on research done in this project, complemented by results from other efforts, the Ehlers data fusion approach was used in the resolution enhancement of Landsat MSS imagery. In this paper, using Portland and Kigali as the principal examples, we discuss the procedures by which (a) the KH-series declassified military intelligence imagery was geometrically-corrected and registered to Landsat data, (b) the Ehlers Fusion of the KH-data with Landsat MSS, (c) the derivation of 1970's urban land use information, and (d) the calculation of select urban growth metrics. This paper illustrates the power of leveraging the high resolution of the military reconnaissance imagery with the multispectral information contained in the vintage Landsat MSS data in historical land use analyses.

  4. Vector statistics of LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Jayroe, R. R., Jr.; Underwood, D.

    1977-01-01

    A digitized multispectral image, such as LANDSAT data, is composed of numerous four dimensional vectors, which quantitatively describe the ground scene from which the data are acquired. The statistics of unique vectors that occur in LANDSAT imagery are studied to determine if that information can provide some guidance on reducing image processing costs. A second purpose of this report is to investigate how the vector statistics are changed by various types of image processing techniques and determine if that information can be useful in choosing one processing approach over another.

  5. Geopositional Accuracy Validation of Orthorectified Landsat ETM+ Imagery

    NASA Technical Reports Server (NTRS)

    Smith, Charles M.

    2004-01-01

    This report provides the results of two independent evaluations, an absolute and a relative assessment, of the geopositional accuracy of the Earth Satellite (EarthSat) Corporation's GeoCover orthorectified Landsat Enhanced Thematic Mapper Plus (ETM+) imagery. This imagery was purchased through NASA's Earth Science Enterprise (ESE) Scientific Data Purchase (SDP) program.

  6. Satellite-based land use mapping: comparative analysis of Landsat-8, Advanced Land Imager, and big data Hyperion imagery

    NASA Astrophysics Data System (ADS)

    Pervez, Wasim; Uddin, Vali; Khan, Shoab Ahmad; Khan, Junaid Aziz

    2016-04-01

    Until recently, Landsat technology has suffered from low signal-to-noise ratio (SNR) and comparatively poor radiometric resolution, which resulted in limited application for inland water and land use/cover mapping. The new generation of Landsat, the Landsat Data Continuity Mission carrying the Operational Land Imager (OLI), has improved SNR and high radiometric resolution. This study evaluated the utility of orthoimagery from OLI in comparison with the Advanced Land Imager (ALI) and hyperspectral Hyperion (after preprocessing) with respect to spectral profiling of classes, land use/cover classification, classification accuracy assessment, classifier selection, study area selection, and other applications. For each data source, the support vector machine (SVM) model outperformed the spectral angle mapper (SAM) classifier in terms of class discrimination accuracy (i.e., water, built-up area, mixed forest, shrub, and bare soil). Using the SVM classifier, Hyperion hyperspectral orthoimagery achieved higher overall accuracy than OLI and ALI. However, OLI outperformed both hyperspectral Hyperion and multispectral ALI using the SAM classifier, and with the SVM classifier outperformed ALI in terms of overall accuracy and individual classes. The results show that the new generation of Landsat achieved higher accuracies in mapping compared with the previous Landsat multispectral satellite series.

  7. Visualizing Airborne and Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Bierwirth, Victoria A.

    2011-01-01

    Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

  8. Combined synthetic aperture radar/Landsat imagery

    NASA Technical Reports Server (NTRS)

    Marque, R. E.; Maurer, H. E.

    1978-01-01

    This paper presents the results of investigations into merging synthetic aperture radar (SAR) and Landsat multispectral scanner (MSS) images using optical and digital merging techniques. The unique characteristics of airborne and orbital SAR and Landsat MSS imagery are discussed. The case for merging the imagery is presented and tradeoffs between optical and digital merging techniques explored. Examples of Landsat and airborne SAR imagery are used to illustrate optical and digital merging. Analysis of the merged digital imagery illustrates the improved interpretability resulting from combining the outputs from the two sensor systems.

  9. Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production

    USGS Publications Warehouse

    Leslie, Colin R.; Serbina, Larisa O.; Miller, Holly M.

    2017-03-29

    Executive SummaryThe use of Landsat satellite imagery for global agricultural monitoring began almost immediately after the launch of Landsat 1 in 1972, making agricultural monitoring one of the longest-standing operational applications for the Landsat program. More recently, Landsat imagery has been used in domestic agricultural applications as an input for field-level production management. The enactment of the U.S. Geological Survey’s free and open data policy in 2008 and the launch of Landsat 8 in 2013 have both influenced agricultural applications. This report presents two primary sets of case studies on the applications and benefits of Landsat imagery use in agriculture. The first set examines several operational applications within the U.S. Department of Agriculture (USDA) and the second focuses on private sector applications for agronomic management.  Information on the USDA applications is provided in the U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring section of the report in the following subsections:Estimating Crop Production.—Provides an overview of how Landsat satellite imagery is used to estimate crop production, including the spectral bands most frequently utilized in this application.Monitoring Consumptive Water Use.—Highlights the role of Landsat imagery in monitoring consumptive water use for agricultural production. Globally, a significant amount of agricultural production relies on irrigation, so monitoring water resources is a critical component of agricultural monitoring. National Agricultural Statistics Service—Cropland Data Layer.—Highlights the use of Landsat imagery in developing the annual Cropland Data Layer, a crop-specific land cover classification product that provides information on more than 100 crop categories grown in the United States. Foreign Agricultural Service—Global Agricultural Monitoring.—Highlights Landsat’s role in monitoring global agricultural

  10. Land-cover types, shoreline positions, and sand extents derived From Landsat satellite imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2014

    USGS Publications Warehouse

    Bernier, Julie C.; Douglas, Steven H.; Terrano, Joseph F.; Barras, John A.; Plant, Nathaniel G.; Smith, Christopher G.

    2015-12-17

    This report serves as an archive of data that were derived from Landsat 5 and Landsat 8 imagery from 1984 to 2014, including wetland and terrestrial habitat extents; open-ocean, back-barrier, and estuarine mainland shoreline positions; and sand-line positions along the estuarine mainland and barrier shorelines from Assateague Island, Maryland to Metompkin Island, Virginia. The geographic information system data files with accompanying formal Federal Geographic Data Committee metadata can be downloaded from the Data Downloads page.

  11. NASA team algorithm for sea ice concentration retrieval from Defense Meteorological Satellite Program special sensor microwave imager - Comparison with Landsat satellite imagery

    NASA Technical Reports Server (NTRS)

    Steffen, Konrad; Schweiger, Axel

    1991-01-01

    The present study describes the validation of the the NASA team algorithm for the determination of sea ice concentrations from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave ice concentration algorithm for a range of ice concentrations and ice types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat ice concentrations are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young ice, the NASA team algorithm was found to underestimate ice concentrations by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat ice concentrations decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.

  12. NASA team algorithm for sea ice concentration retrieval from Defense Meteorological Satellite Program special sensor microwave imager - Comparison with Landsat satellite imagery

    NASA Technical Reports Server (NTRS)

    Steffen, Konrad; Schweiger, Axel

    1991-01-01

    The present study describes the validation of the the NASA team algorithm for the determination of sea ice concentrations from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave ice concentration algorithm for a range of ice concentrations and ice types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat ice concentrations are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young ice, the NASA team algorithm was found to underestimate ice concentrations by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat ice concentrations decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.

  13. Shorelines extracted from Landsat imagery: Dauphin Island, Alabama

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-01-01

    The deployment of Landsat and other earth-observing satellites within the last few decades has provided an opportunity to observe barrier islands at frequent intervals, often many times a year. A variable of persistent interest as a metric for coastal erosion or change is the shoreline. Shorelines derived from imagery have value to resolve coastal changes. This data release includes shoreline positions extracted from Landsat satellite imagery. The shorelines are released in shapefiles with both line and polygon feature types to support a variety of user needs. The data (lines or polygons) are released as individual shapefiles for each sample date and are also released as combined shapefiles with all dates, again to provide users of these data with more options for selecting data of interest. The methods used to identify the shorelines are presented in Guy (2015).

  14. Shorelines extracted from Landsat imagery: Petit Bois Island, Mississippi

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-01-01

    The deployment of Landsat and other earth-observing satellites within the last few decades has provided an opportunity to observe barrier islands at frequent intervals, often many times a year. A variable of persistent interest as a metric for coastal erosion or change is the shoreline. Shorelines derived from imagery have value to resolve coastal changes. This data release includes shoreline positions extracted from Landsat satellite imagery. The shorelines are released in shapefiles with both line and polygon feature types to support a variety of user needs. The data (lines or polygons) are released as individual shapefiles for each sample date and are also released as combined shapefiles with all dates, again to provide users of these data with more options for selecting data of interest. The methods used to identify the shorelines are presented in Guy (2015).

  15. Shorelines extracted from Landsat imagery: Ship Island, Mississippi

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-01-01

    The deployment of Landsat and other earth-observing satellites within the last few decades has provided an opportunity to observe barrier islands at frequent intervals, often many times a year. A variable of persistent interest as a metric for coastal erosion or change is the shoreline. Shorelines derived from imagery have value to resolve coastal changes. This data release includes shoreline positions extracted from Landsat satellite imagery. The shorelines are released in shapefiles with both line and polygon feature types to support a variety of user needs. The data (lines or polygons) are released as individual shapefiles for each sample date and are also released as combined shapefiles with all dates, again to provide users of these data with more options for selecting data of interest. The methods used to identify the shorelines are presented in Guy (2015).

  16. Shorelines extracted from Landsat imagery: Horn Island, Mississippi

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-01-01

    The deployment of Landsat and other earth-observing satellites within the last few decades has provided an opportunity to observe barrier islands at frequent intervals, often many times a year. A variable of persistent interest as a metric for coastal erosion or change is the shoreline. Shorelines derived from imagery have value to resolve coastal changes. This data release includes shoreline positions extracted from Landsat satellite imagery. The shorelines are released in shapefiles with both line and polygon feature types to support a variety of user needs. The data (lines or polygons) are released as individual shapefiles for each sample date and are also released as combined shapefiles with all dates, again to provide users of these data with more options for selecting data of interest. The methods used to identify the shorelines are presented in Guy (2015).

  17. Shorelines extracted from Landsat imagery: Cat Island, Mississippi

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-01-01

    The deployment of Landsat and other earth-observing satellites within the last few decades has provided an opportunity to observe barrier islands at frequent intervals, often many times a year. A variable of persistent interest as a metric for coastal erosion or change is the shoreline. Shorelines derived from imagery have value to resolve coastal changes. This data release includes shoreline positions extracted from Landsat satellite imagery. The shorelines are released in shapefiles with both line and polygon feature types to support a variety of user needs. The data (lines or polygons) are released as individual shapefiles for each sample date and are also released as combined shapefiles with all dates, again to provide users of these data with more options for selecting data of interest. The methods used to identify the shorelines are presented in Guy (2015).

  18. 75 FR 39701 - Revision of a Currently Approved Collection: Users, Uses, and Benefits of Landsat Satellite Imagery

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-12

    ... telephone at (970) 226-9133. ] SUPPLEMENTARY INFORMATION: I. Abstract In 2008, the USGS's Land Remote Sensing (LRS) Program initiated a study to determine the users, uses, and benefits of Landsat...

  19. Trophic state determination for shallow coastal lakes from Landsat imagery

    NASA Technical Reports Server (NTRS)

    Welby, C. W.; Witherspoon, A. M.; Holman, R. E., III

    1981-01-01

    A study has been carried out to develop a photo-optical technique by which Landsat imagery can be used to monitor trophic states of lakes. The proposed technique uses a single number to characterize the trophic state, and a feature within the satellite scene is used as an internal standard for comparison of the lakes in time. By use of the technique it is possible to assess in retrospect the trophic state of each individual lake.

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

    USGS Publications Warehouse

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

    2007-01-01

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

  1. Combining forces--the use of Landsat TM satellite imagery, soil parameter information, and multiplex PCR to detect Coccidioides immitis growth sites in Kern County, California.

    PubMed

    Lauer, Antje; Talamantes, Jorge; Castañón Olivares, Laura Rosío; Medina, Luis Jaime; Baal, Joe Daryl Hugo; Casimiro, Kayla; Shroff, Natasha; Emery, Kirt W

    2014-01-01

    Coccidioidomycosis is a fungal disease acquired through the inhalation of spores of Coccidioides spp., which afflicts primarily humans and other mammals. It is endemic to areas in the southwestern United States, including the San Joaquin Valley portion of Kern County, California, our region of interest (ROI). Recently, incidence of coccidioidomycosis, also known as valley fever, has increased significantly, and several factors including climate change have been suggested as possible drivers for this observation. Up to date details about the ecological niche of C. immitis have escaped full characterization. In our project, we chose a three-step approach to investigate this niche: 1) We examined Landsat-5-Thematic-Mapper multispectral images of our ROI by using training pixels at a 750 m × 750 m section of Sharktooth Hill, a site confirmed to be a C. immitis growth site, to implement a Maximum Likelihood Classification scheme to map out the locations that could be suitable to support the growth of the pathogen; 2) We used the websoilsurvey database of the US Department of Agriculture to obtain soil parameter data; and 3) We investigated soil samples from 23 sites around Bakersfield, California using a multiplex Polymerase Chain Reaction (PCR) based method to detect the pathogen. Our results indicated that a combination of satellite imagery, soil type information, and multiplex PCR are powerful tools to predict and identify growth sites of C. immitis. This approach can be used as a basis for systematic sampling and investigation of soils to detect Coccidioides spp.

  2. Combining Forces - The Use of Landsat TM Satellite Imagery, Soil Parameter Information, and Multiplex PCR to Detect Coccidioides immitis Growth Sites in Kern County, California

    PubMed Central

    Lauer, Antje; Talamantes, Jorge; Castañón Olivares, Laura Rosío; Medina, Luis Jaime; Baal, Joe Daryl Hugo; Casimiro, Kayla; Shroff, Natasha; Emery, Kirt W.

    2014-01-01

    Coccidioidomycosis is a fungal disease acquired through the inhalation of spores of Coccidioides spp., which afflicts primarily humans and other mammals. It is endemic to areas in the southwestern United States, including the San Joaquin Valley portion of Kern County, California, our region of interest (ROI). Recently, incidence of coccidioidomycosis, also known as valley fever, has increased significantly, and several factors including climate change have been suggested as possible drivers for this observation. Up to date details about the ecological niche of C. immitis have escaped full characterization. In our project, we chose a three-step approach to investigate this niche: 1) We examined Landsat-5-Thematic-Mapper multispectral images of our ROI by using training pixels at a 750 m×750 m section of Sharktooth Hill, a site confirmed to be a C. immitis growth site, to implement a Maximum Likelihood Classification scheme to map out the locations that could be suitable to support the growth of the pathogen; 2) We used the websoilsurvey database of the US Department of Agriculture to obtain soil parameter data; and 3) We investigated soil samples from 23 sites around Bakersfield, California using a multiplex Polymerase Chain Reaction (PCR) based method to detect the pathogen. Our results indicated that a combination of satellite imagery, soil type information, and multiplex PCR are powerful tools to predict and identify growth sites of C. immitis. This approach can be used as a basis for systematic sampling and investigation of soils to detect Coccidioides spp. PMID:25380290

  3. Assessing the value of Landsat imagery: Results from a 2012 comprehensive user survey

    NASA Astrophysics Data System (ADS)

    Miller, H. M.; Richardson, L.; Loomis, J.; Koontz, S.; Koontz, L.

    2012-12-01

    Landsat satellite imagery has long been recognized as unique among remotely sensed data due to the combination of its extensive archive, global coverage, and relatively high spatial and temporal resolution. Since the imagery became available at no cost in 2008, the number of users registered with the U.S. Geological Survey (USGS) has increased tenfold while the number of scenes downloaded annually has increased a hundredfold. It is clear that the imagery is being used extensively, and understanding the benefits provided by this imagery can help inform decisions involving its provision. However, the value of Landsat imagery is difficult to measure for a variety of reasons, one of which stems from the fact that the imagery has characteristics of a public good and does not have a direct market price to reflect its value to society. Further, there is not a clear understanding of the full range of users of the imagery, as well as how these users are distributed across the many different end uses this data is applied to. To assess the value of Landsat imagery, we conducted a survey of users registered with USGS in early 2012. Over 11,000 current users of Landsat imagery responded to the survey. The value of the imagery was measured both qualitatively and quantitatively. To explore the qualitative value of the imagery, users were asked about the importance of the imagery to their work, their dependence on the imagery, and the impacts on their work if there was no Landsat imagery. The majority of users deemed Landsat imagery important to their work and stated they were dependent on Landsat imagery to do their work. Additionally, if Landsat imagery was no longer available, over half of the users would have to discontinue some of their work. On average, these users would discontinue half of their current work if the imagery was no longer available. The focus of this presentation will be the quantitative results of a double-bounded contingent valuation analysis which reveals

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

    USGS Publications Warehouse

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

    2011-01-01

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

  5. Preliminary study for correlation of meteorological satellite (METSAT) data with LANDSAT data

    NASA Technical Reports Server (NTRS)

    Amery-Ryland, J. L. (Principal Investigator)

    1982-01-01

    A data set covering multiyear LANDSAT data correlated with meteorological satellite global area coverage (GAC) is defined. Procedures developed for viewing the METSAT GAS imagery and for geographically locating a Large Area Crop Inventory Experiment segment defined on LANDSAT imagery are described.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  7. Assessment of the spatial variability in tall wheatgrass forage using LANDSAT 8 satellite imagery to delineate potential management zones.

    PubMed

    Cicore, Pablo; Serrano, João; Shahidian, Shakib; Sousa, Adelia; Costa, José Luis; da Silva, José Rafael Marques

    2016-09-01

    Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m(2) in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500 °C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVInov) and 10 December 2014 (NDVIdec) because the potential AB was highly associated with NDVInov and NDVIdec (r (2)  = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVInov and NDVIdec, respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass.

  8. The Next Landsat Satellite: The Landsat Data Continuity Mission

    NASA Technical Reports Server (NTRS)

    Rons, James R.; Dwyer, John L.; Barsi, Julia A.

    2012-01-01

    The Landsat program is one of the longest running satellite programs for Earth observations from space. The program was initiated by the launch of Landsat 1 in 1972. Since then a series of six more Landsat satellites were launched and at least one of those satellites has been in operations at all times to continuously collect images of the global land surface. The Department of Interior (DOI) U.S. Geological Survey (USGS) preserves data collected by all of the Landsat satellites at their Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. This 40-year data archive provides an unmatched record of the Earth's land surface that has undergone dramatic changes in recent decades due to the increasing pressure of a growing population and advancing technologies. EROS provides the ability for anyone to search the archive and order digital Landsat images over the internet for free. The Landsat data are a public resource for observing, characterizing, monitoring, trending, and predicting land use change over time providing an invaluable tool for those addressing the profound consequences of those changes to society. The most recent launch of a Landsat satellite occurred in 1999 when Landsat 7 was placed in orbit. While Landsat 7 remains in operation, the National Aeronautics and Space Administration (NASA) and the DOI/ USGS are building its successor satellite system currently called the Landsat Data Continuity Mission (LDCM). NASA has the lead for building and launching the satellite that will carry two Earth-viewing instruments, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will take images that measure the amount of sunlight reflected by the land surface at nine wavelengths of light with three of those wavelengths beyond the range of human vision. T1RS will collect coincident images that measure light emitted by the land surface as a function of surface temperature at two longer wavelengths well beyond the

  9. Analysis of Decadal-Scale Shoreline Change along the Hamlet of Paulatuk (Canadian Arctic), using Landsat Satellite Imagery and GIS techniques from 1984 to 2014.

    NASA Astrophysics Data System (ADS)

    Sankar, R. D.; Murray, M. S.; Wells, P.

    2016-12-01

    Increased accuracy in estimating coastal change along localized segments of the Canadian Arctic coast is essential, in order to identify plausible adaptation initiatives to deal with the effects of climate change. This paper quantifies rates of shoreline movement along an 11 km segment of the Hamlet of Paulatuk (Northwest Territories, Canada), using an innovative modelling technique - Analyzing Moving Boundaries Using R (AMBUR). Approximately two dozen shorelines, obtained from high-resolution Landsat satellite imagery were analyzed. Shorelines were extracted using the band ratio method and compiled in ArcMapTM to determine decadal trends of coastal change. The unique geometry of Paulatuk facilitated an independent analysis of the western and eastern sections of the study area. Long-term (1984-2014) and short-term (1984-2003) erosion and accretion rates were calculated using the Linear Regression and End Point Rate methods respectively. Results reveal an elevated rate of erosion for the western section of the hamlet over the long-term (-1.1 m/yr), compared to the eastern portion (-0.92 m/yr). The study indicates a significant alongshore increase in the rates of erosion on both portions of the study area, over the short-term period 1984 to 2003. Mean annual erosion rates increased over the short-term along the western segment (-1.4 m/yr), while the eastern shoreline retreated at a rate of -1.3 m/yr over the same period. The analysis indicates that an amalgamation of factors may be responsible for the patterns of land loss experienced along Paulatuk. These include increased sea-surface temperature coupled with dwindling arctic ice and elevated storm hydrodynamics. The analysis further reveals that the coastline along the eastern portion of the hamlet, where the majority of the population reside, is vulnerable to a high rate of shoreline erosion.

  10. Simulation of landsat thematic mapper imagery using AVIRIS hyperspectral imagery

    NASA Technical Reports Server (NTRS)

    Kalman, Linda S.; Peltzer, Gerard R.

    1993-01-01

    In this paper we present a methodology for simulating multispectral imagery (MSI) using hyperspectral imagery (HSI), and present a validation of the technique using one nearly coincident Landsat TM and AVIRIS data set. Generation of MSI from HSI supports several investigations including selection of multispectral sensor band edges, and engineering trade studies related to on-board or ground-based aggregation of HSI to simulate MSI. In addition, the utility of this technique as a potential procedure for monitoring calibration changes in spaceborne instrument is also addressed.

  11. Identification of areas of recharge and discharge using Landsat-TM satellite imagery and aerial photography mapping techniques

    NASA Astrophysics Data System (ADS)

    Salama, R. B.; Tapley, I.; Ishii, T.; Hawkes, G.

    1994-10-01

    Aerial photographs (AP) and Landsat (TM) colour composites were used to map the geomorphology, geology and structures of the Salt River System of Western Australia. Geomorphic features identified are sand plains, dissected etchplain, colluvium, lateritic duricrust and rock outcrops. The hydrogeomorphic units include streams, lakes and playas, palaeochannels and palaeodeltas. The structural features are linear and curvilinear lineaments, ring structures and dolerite dykes. Suture lines control the course of the main river channel. Permeable areas around the circular granitic plutons were found to be the main areas of recharge in the uplands. Recharge was also found to occur in the highly permeable areas of the sandplains. Discharge was shown to be primarily along the main drainage lines, on the edge of the circular sandplains, in depressions and in lakes. The groundwater occurrence and hydrogeological classification of the recharge potential of the different units were used to classify the mapped areas into recharge and discharge zones. The results also show that TM colour composites provide a viable source of data comparable with AP for mapping and delineating areas of recharge and discharge on a regional scale.

  12. LANDSAT data: A new perspective for geology. A review of the utilization of LANDSAT imagery for geological interpretation

    NASA Technical Reports Server (NTRS)

    Baker, R. N.

    1977-01-01

    Areas in which LANDSAT satellite imagery were found most useful include regional interpretations of geological structure, updating verifying of geologic maps, mineral and petroleum exploration, and the monitoring of natural hazards such as large-scale erosion and seismicity. Investigations in these areas of application demonstrated the wide variety of uses presently undertaken or envisioned for the future.

  13. Glaciers change over the last century, Caucasus Mountains, Georgia, observed by the old topographical maps, Landsat and ASTER satellite imagery

    NASA Astrophysics Data System (ADS)

    Tielidze, L. G.

    2015-07-01

    The study of glaciers in the Caucasus began in the first quarter of the 18th century. The first data on glaciers can be found in the works of great Georgian scientist Vakhushti Bagrationi. After almost hundred years the foreign scientists began to describe the glaciers of Georgia. Information about the glaciers of Georgia can be found in the works of W. Abich (1865), D. Freshfield (1869), G. Radde (1873), N. Dinik (1884), I. Rashevskiy (1904), A. Reinhardt (1916, 1917) etc. The first statistical information about the glaciers of Georgia are found in the catalog of the Caucasus glaciers compiled by K. Podozerskiy in 1911 (Podozerkiy, 1911). Then, in 1960s the large-scale (1:25 000, 1:50 000) topographic maps were published, which were compiled in 1955-1960 on the basis of the space images. On the basis of the mentioned maps R. Gobejishvili gave quite detailed statistical information about the glaciers of Georgia (Gobejishvili, 1989). Then in 1975 the glaciological catalog of the former USSR was published (The Catalog of Glaciers of the USSR, Vol. 8-9, 1975), where the statistical information about the glaciers of Georgia was obtained on the basis of the space images of 1970-1975. Thus, complete statistical information on the glaciers of Georgia has not been published for about last 40 years. Data obtained by us by processing of the space images of Landsat and ASTER is the latest material, which is the best tool for identification of the change in the number and area of the glaciers of Georgia during the last one century. The article presents the percentage and quantitative changes in the number and area of the glaciers of Georgia in the years of 1911-1960-1975-2014, according to the individual river basins. The air temperature course of the Georgia's high mountain weather stations has been studied. The river basins have been revealed, where there are the highest indices of the reduction in area and number of the glaciers and the reasons have been explained.

  14. Barrier Island Shorelines Extracted from Landsat Imagery

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-10-13

    The shoreline is a common variable used as a metric for coastal erosion or change (Himmelstoss and others, 2010). Although shorelines are often extracted from topographic data (for example, ground-based surveys and light detection and ranging [lidar]), image-based shorelines, corrected for their inherent uncertainties (Moore and others, 2006), have provided much of our understanding of long-term shoreline change because they pre-date routine lidar elevation survey methods. Image-based shorelines continue to be valuable because of their higher temporal resolution compared to costly airborne lidar surveys. A method for extracting sandy shorelines from 30-meter (m) resolution Landsat imagery is presented here.

  15. LANDSAT world standard catalog, LANDSAT-3. [LANDSAT 3 imagery for October 1978

    NASA Technical Reports Server (NTRS)

    1978-01-01

    Imagery acquired by LANDSAT 3 which was processed and input to the data files during the referenced month is listed. Data, such as data acquired, cloud cover, and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  16. An automated approach to mapping corn from Landsat imagery

    USGS Publications Warehouse

    Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.; Hoffer, R.M.

    2004-01-01

    Most land cover maps generated from Landsat imagery involve classification of a wide variety of land cover types, whereas some studies may only need spatial information on a single cover type. For example, we required a map of corn in order to estimate exposure to agricultural chemicals for an environmental epidemiology study. Traditional classification techniques, which require the collection and processing of costly ground reference data, were not feasible for our application because of the large number of images to be analyzed. We present a new method that has the potential to automate the classification of corn from Landsat satellite imagery, resulting in a more timely product for applications covering large geographical regions. Our approach uses readily available agricultural areal estimates to enable automation of the classification process resulting in a map identifying land cover as ‘highly likely corn,’ ‘likely corn’ or ‘unlikely corn.’ To demonstrate the feasibility of this approach, we produced a map consisting of the three corn likelihood classes using a Landsat image in south central Nebraska. Overall classification accuracy of the map was 92.2% when compared to ground reference data.

  17. Detection of pear thrips damage using satellite imagery data

    Treesearch

    James E. Vogelmann; Barrett N. Rock

    1991-01-01

    This study evaluates the potential of measuring, mapping and monitoring sugar maple damage caused by pear thrips in southern Vermont and northwestern Massachusetts using satellite imagery data. Landsat Thematic Mapper (TM) data were obtained during a major thrips infestation in June 1988, and were compared with satellite data acquired during June 1984 (before pear...

  18. Digital techniques for processing Landsat imagery

    NASA Technical Reports Server (NTRS)

    Green, W. B.

    1978-01-01

    An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.

  19. The effectiveness of texture analysis for mapping forest land using the panchromatic bands of Landsat 7, SPOT, and IRS imagery

    Treesearch

    Michael L. Hoppus; Rachel I. Riemann; Andrew J. Lister; Mark V. Finco

    2002-01-01

    The panchromatic bands of Landsat 7, SPOT, and IRS satellite imagery provide an opportunity to evaluate the effectiveness of texture analysis of satellite imagery for mapping of land use/cover, especially forest cover. A variety of texture algorithms, including standard deviation, Ryherd-Woodcock minimum variance adaptive window, low pass etc., were applied to moving...

  20. Feature Detection Systems Enhance Satellite Imagery

    NASA Technical Reports Server (NTRS)

    2009-01-01

    In 1963, during the ninth orbit of the Faith 7 capsule, astronaut Gordon Cooper skipped his nap and took some photos of the Earth below using a Hasselblad camera. The sole flier on the Mercury-Atlas 9 mission, Cooper took 24 photos - never-before-seen images including the Tibetan plateau, the crinkled heights of the Himalayas, and the jagged coast of Burma. From his lofty perch over 100 miles above the Earth, Cooper noted villages, roads, rivers, and even, on occasion, individual houses. In 1965, encouraged by the effectiveness of NASA s orbital photography experiments during the Mercury and subsequent Gemini manned space flight missions, U.S. Geological Survey (USGS) director William Pecora put forward a plan for a remote sensing satellite program that would collect information about the planet never before attainable. By 1972, NASA had built and launched Landsat 1, the first in a series of Landsat sensors that have combined to provide the longest continuous collection of space-based Earth imagery. The archived Landsat data - 37 years worth and counting - has provided a vast library of information allowing not only the extensive mapping of Earth s surface but also the study of its environmental changes, from receding glaciers and tropical deforestation to urban growth and crop harvests. Developed and launched by NASA with data collection operated at various times by the Agency, the National Oceanic and Atmospheric Administration (NOAA), Earth Observation Satellite Company (EOSAT, a private sector partnership that became Space Imaging Corporation in 1996), and USGS, Landsat sensors have recorded flooding from Hurricane Katrina, the building boom in Dubai, and the extinction of the Aral Sea, offering scientists invaluable insights into the natural and manmade changes that shape the world. Of the seven Landsat sensors launched since 1972, Landsat 5 and Landsat 7 are still operational. Though both are in use well beyond their intended lifespans, the mid

  1. 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.

  2. 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.

  3. Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

    NASA Astrophysics Data System (ADS)

    Lazaridou, M. A.; Karagianni, A. Ch.

    2016-06-01

    Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  4. Evaluation of reforested areas using LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.

    1978-01-01

    The author has identified the following significant results. Visual and automatic interpretation of LANDSAT imagery was used to classify the general Pinus and Eucalyptus according to their age and species. A methodology was derived, based on training areas, to define the legend and spectral characteristics of the analyzed classes. Imager analysis of the training areas show that Pinus taeda is separable from the other Pinus species based on JM distance measurement. No difference of JM measurements was observed among Eucalyptus species. Two classes of Eucalyptus were separated according to their ages: those under and those over two years of age. Channel 6 and 7 were suitable for the discrimination of the reforested classes. Channel 5 was efficient to separated reforested areas from nonforested targets in the region. The automatic analysis shows the highest classification precision was obtained for Eucalyptus over two years of age (95.12 percent).

  5. A comparison of sea ice parameters computed from Advanced Very High Resolution Radiometer and Landsat satellite imagery and from airborne passive microwave radiometry

    NASA Technical Reports Server (NTRS)

    Emery, W. J.; Radebaugh, M.; Fowler, C. W.; Cavalieri, D.; Steffen, K.

    1991-01-01

    AVHRR-derived sea ice parameters from the Bering Sea are compared with those computed from nearly coincident (within 6 hr) Landsat MSS imagery and from the Aircraft Multichannel Microwave Radiometer (AMMR) flown on the NASA DC-8 in order to evaluate the accuracy and reliability of AVHRR-mapped sea-ice concentration and ice edge. Mean ice-concentration differences between AVHRR near-infrared (channel 2) and Landsat MSS data ranged from -0.8 to 1.8 percent with a mean value of 0.5 percent; rms differences ranged from 6.8 to 17.7 percent. Mean differences were larger for AVHRR thermal infrared (channel 4) ice concentrations ranging from -2.2 to 8.4 percent with rms differences from 8.6 to 26.8 percent. Mean differences between AVHRR channel 2 concentrations and the AMMR data ranged from -19.7 to 18.9 percent, while rms values went from 17.0 to 44.8 percent.

  6. 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.

  7. Automated Sargassum Detection for Landsat Imagery

    NASA Astrophysics Data System (ADS)

    McCarthy, S.; Gallegos, S. C.; Armstrong, D.

    2016-02-01

    We implemented a system to automatically detect Sargassum, a floating seaweed, in 30-meter LANDSAT-8 Operational Land Imager (OLI) imagery. Our algorithm for Sargassum detection is an extended form of Hu's approach to derive a floating algae index (FAI) [1]. Hu's algorithm was developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data, but we extended it for use with the OLI bands centered at 655, 865, and 1609 nm, which are comparable to the MODIS bands located at 645, 859, and 1640 nm. We also developed a high resolution true color product to mask cloud pixels in the OLI scene by applying a threshold to top of the atmosphere (TOA) radiances in the red (655 nm), green (561 nm), and blue (443 nm) wavelengths, as well as a method for removing false positive identifications of Sargassum in the imagery. Hu's algorithm derives a FAI for each Sargassum identified pixel. Our algorithm is currently set to only flag the presence of Sargassum in an OLI pixel by classifying any pixel with a FAI > 0.0 as Sargassum. Additionally, our system geo-locates the flagged Sargassum pixels identified in the OLI imagery into the U.S. Navy Global HYCOM model grid. One element of the model grid covers an area 0.125 degrees of latitude by 0.125 degrees of longitude. To resolve the differences in spatial coverage between Landsat and HYCOM, a scheme was developed to calculate the percentage of pixels flagged within the grid element and if above a threshold, it will be flagged as Sargassum. This work is a part of a larger system, sponsored by NASA/Applied Science and Technology Project at J.C. Stennis Space Center, to forecast when and where Sargassum will land on shore. The focus area of this work is currently the Texas coast. Plans call for extending our efforts into the Caribbean. References: [1] Hu, Chuanmin. A novel ocean color index to detect floating algae in the global oceans. Remote Sensing of Environment 113 (2009) 2118-2129.

  8. LANDSAT US standard catalog, 1-31 December 1975. [LANDSAT imagery for December, 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles. Sections 4 and 5 cover LANDSAT-1 and LANDSAT-2 coverage, respectively.

  9. LANDSAT: US standard catalog, 1-31 January 1976. [LANDSAT imagery for January 1976

    NASA Technical Reports Server (NTRS)

    1976-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Section 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles. Sections 4 and 5 cover LANDSAT-1 and LANDSAT-2 coverage, respectively.

  10. LANDSAT US standard catalog, 1-30 April 1976. [LANDSAT imagery for April, 1976

    NASA Technical Reports Server (NTRS)

    1976-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles. Sections 4 and 5 cover LANDSAT-1 and LANDSAT-2 coverage, respectively.

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

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  12. Landsat and water: case studies of the uses and benefits of landsat imagery in water resources

    USGS Publications Warehouse

    Serbina, Larisa O.; Miller, Holly M.

    2014-01-01

    The Landsat program has been collecting and archiving moderate resolution earth imagery since 1972. The number of Landsat users and uses has increased exponentially since the enactment of a free and open data policy in 2008, which made data available free of charge to all users. Benefits from the information Landsat data provides vary from improving environmental quality to protecting public health and safety and informing decision makers such as consumers and producers, government officials and the public at large. Although some studies have been conducted, little is known about the total benefit provided by open access Landsat imagery. This report contains a set of case studies focused on the uses and benefits of Landsat imagery. The purpose of these is to shed more light on the benefits accrued from Landsat imagery and to gain a better understanding of the program’s value. The case studies tell a story of how Landsat imagery is used and what its value is to different private and public entities. Most of the case studies focus on the use of Landsat in water resource management, although some other content areas are included.

  13. Mapping shorelines to subpixel accuracy using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Abileah, Ron; Vignudelli, Stefano; Scozzari, Andrea

    2013-04-01

    A promising method to accurately map the shoreline of oceans, lakes, reservoirs, and rivers is proposed and verified in this work. The method is applied to multispectral satellite imagery in two stages. The first stage is a classification of each image pixel into land/water categories using the conventional 'dark pixel' method. The approach presented here, makes use of a single shortwave IR image band (SWIR), if available. It is well known that SWIR has the least water leaving radiance and relatively little sensitivity to water pollutants and suspended sediments. It is generally the darkest (over water) and most reliable single band for land-water discrimination. The boundary of the water cover map determined in stage 1 underestimates the water cover and often misses the true shoreline by a quantity up to one pixel. A more accurate shoreline would be obtained by connecting the center point of pixels with exactly 50-50 mix of water and land. Then, stage 2 finds the 50-50 mix points. According to the method proposed, image data is interpolated and up-sampled to ten times the original resolution. The local gradient in radiance is used to find the direction to the shore, thus searching along that path for the interpolated pixel closest to a 50-50 mix. Landsat images with 30m resolution, processed by this method, may thus provide the shoreline accurate to 3m. Compared to similar approaches available in the literature, the method proposed discriminates sub-pixels crossed by the shoreline by using a criteria based on the absolute value of radiance, rather than its gradient. Preliminary experimentation of the algorithm shows that 10m resolution accuracy is easily achieved and in some cases is often better than 5m. The proposed method can be used to study long term shoreline changes by exploiting the 30 years of archived world-wide coverage Landsat imagery. Landsat imagery is free and easily accessible for downloading. Some applications that exploit the Landsat dataset and

  14. Protecting rain forests and forager's rights using LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Wilkie, David S.

    1991-01-01

    Creating rain forest reserves is vital given the global decline in biodiversity. Yet, the plants and animals that will be protected from untrammeled commercial exploitation within such reserves constitute essential resources for indigenous foragers and farmers. Balancing the needs of local subsistence level populations with the goals of national and international conservation agencies requires a thorough understanding of the mutual impacts that arise from the interaction of park and people. In the Ituri forest of Zaire, LANDSAT TM image analysis and GPS ground truth data were used to locate human settlements so that boundaries of the proposed Okapi Reserve could be chosen to minimize its impact on the subsistence practices of the local foragers and farmers. Using satellite imagery in conjunction with cultural information should help to ensure traditional resource exploitation rights of indigenous peoples whilst simultaneously protecting the largest contiguous area of undisturbed forest.

  15. Protecting rain forests and forager's rights using LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Wilkie, David S.

    1991-01-01

    Creating rain forest reserves is vital given the global decline in biodiversity. Yet, the plants and animals that will be protected from untrammeled commercial exploitation within such reserves constitute essential resources for indigenous foragers and farmers. Balancing the needs of local subsistence level populations with the goals of national and international conservation agencies requires a thorough understanding of the mutual impacts that arise from the interaction of park and people. In the Ituri forest of Zaire, LANDSAT TM image analysis and GPS ground truth data were used to locate human settlements so that boundaries of the proposed Okapi Reserve could be chosen to minimize its impact on the subsistence practices of the local foragers and farmers. Using satellite imagery in conjunction with cultural information should help to ensure traditional resource exploitation rights of indigenous peoples whilst simultaneously protecting the largest contiguous area of undisturbed forest.

  16. The next Landsat satellite; the Landsat Data Continuity Mission

    USGS Publications Warehouse

    Irons, James R.; Dwyer, John L.; Barsi, Julia A.

    2012-01-01

    The National Aeronautics and Space Administration (NASA) and the Department of Interior United States Geological Survey (USGS) are developing the successor mission to Landsat 7 that is currently known as the Landsat Data Continuity Mission (LDCM). NASA is responsible for building and launching the LDCM satellite observatory. USGS is building the ground system and will assume responsibility for satellite operations and for collecting, archiving, and distributing data following launch. The observatory will consist of a spacecraft in low-Earth orbit with a two-sensor payload. One sensor, the Operational Land Imager (OLI), will collect image data for nine shortwave spectral bands over a 185 km swath with a 30 m spatial resolution for all bands except a 15 m panchromatic band. The other instrument, the Thermal Infrared Sensor (TIRS), will collect image data for two thermal bands with a 100 m resolution over a 185 km swath. Both sensors offer technical advancements over earlier Landsat instruments. OLI and TIRS will coincidently collect data and the observatory will transmit the data to the ground system where it will be archived, processed to Level 1 data products containing well calibrated and co-registered OLI and TIRS data, and made available for free distribution to the general public. The LDCM development is on schedule for a December 2012 launch. The USGS intends to rename the satellite "Landsat 8" following launch. By either name a successful mission will fulfill a mandate for Landsat data continuity. The mission will extend the almost 40-year Landsat data archive with images sufficiently consistent with data from the earlier missions to allow long-term studies of regional and global land cover change.

  17. LANDSAT 2 cumulative US standard catalog. [LANDSAT imagery for January 1976

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The U.S. Standard Catalog lists U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality, are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  18. LANDSAT 1 non US cumulative catalog, 1976/1977. [LANDSAT imagery for 1976/1977

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The LANDSAT 1 non-U. S. Cumulative Catalog lists non-U. S. imagery acquired by LANDSAT 1 which has been processed and input to the data files during the referenced year. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  19. LANDSAT: Non-US standard catalog 1-31 December 1976. [LANDSAT imagery for December 1976

    NASA Technical Reports Server (NTRS)

    1976-01-01

    The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as date required, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found are also given.

  20. LANDSAT: US Standard Catalog, 1-31 December 1976. [LANDSAT imagery for December 1976

    NASA Technical Reports Server (NTRS)

    1976-01-01

    The U.S. Standard Catalog lists U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found are also given.

  1. Application of Landsat imagery to metallic mineral exploration in Utah

    NASA Technical Reports Server (NTRS)

    Anderson, A. T.; Smith, A. F.

    1976-01-01

    Standard interpretive techniques were used to study the mosaic of two Landsat images of north central Utah including several major mining districts. Correlation of major Landsat-identified lineaments with the major metallic mining districts suggests that the Landsat-identified lineaments are fractures and that their distribution may be a valuable guide for identifying other mineralized areas. The imagery provides a more complete understanding of the geological information for identifying major tectonic and structural trends in the area. Several of the major mines are located on or closely adjacent to the intersections of at least two major lineaments. Landsat data should therefore be used to complement current mineral exploration programs.

  2. LANDSAT-4 image data quality analysis. [LANDSAT 5 imagery

    NASA Technical Reports Server (NTRS)

    Anuta, P. E. (Principal Investigator)

    1984-01-01

    Reformatting software to handle LANDSAT 5 data in quadrant format was completed and tested. The sensor two-dimensional point spread function was estimated from scene data. Budget recalculations are discussed. Two publications done under this contract are named.

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  4. IMPROVING BIOGENIC EMISSION ESTIMATES WITH SATELLITE IMAGERY

    EPA Science Inventory

    This presentation will review how existing and future applications of satellite imagery can improve the accuracy of biogenic emission estimates. Existing applications of satellite imagery to biogenic emission estimates have focused on characterizing land cover. Vegetation dat...

  5. IMPROVING BIOGENIC EMISSION ESTIMATES WITH SATELLITE IMAGERY

    EPA Science Inventory

    This presentation will review how existing and future applications of satellite imagery can improve the accuracy of biogenic emission estimates. Existing applications of satellite imagery to biogenic emission estimates have focused on characterizing land cover. Vegetation dat...

  6. Sharpening landsat 8 thermal imagery for field scale ET mapping

    USDA-ARS?s Scientific Manuscript database

    Thermal infrared (TIR) remote sensing provides valuable information for mapping land surface energy flux and evapotranspiration (ET). Landsat 8 carries a TIR instrument with two thermal bands that can provide a more accurate estimate of land surface temperature (LST) than prior landsat satellites. H...

  7. Hydrogeological investigations in the Pampa of Argentina. [using LANDSAT 1 and Skylab imagery

    NASA Technical Reports Server (NTRS)

    Kruck, W.; Kantor, W.

    1975-01-01

    In large areas of the Argentinian Pampa the salinization of ground water creates water supply difficulties. Investigations of satellite imagery (Landsat-1 and Skylab) which were based on an extensive ground survey revealed that differences in the vegetation cover are closely related to depth and salinity of ground water. Narrow elongated depressions called bajos are often the only indication of fresh ground water. They can be easily detected on the imagery. Due to their high resolution, Skylab photos even allow a quantitative estimation of fresh ground water situated below the bajos. In general however Landsat-1 imagery sufficed for evaluation. In the area of the Rio Tercero a fossil drainage pattern was discovered and in Corrientes province, soil types could be discriminated and compared to the Soil Map of the World.

  8. Developing in situ flood estimators using multi-date Landsat imagery

    NASA Technical Reports Server (NTRS)

    Mcleester, J. N.; Philipson, W. R.

    1979-01-01

    Landsat satellite imagery is being used as the primary source of information on flooding in the Black River Basin of northern New York State. Landsat images (Band 7) depicting flood conditions during several flood seasons since 1973 were obtained for analysis. Visual interpretation of these images is providing the basis for quantitatively relating in situ measurements of river discharge with the total area and geographic locations of inundation. This, in turn, will provide real-time estimation of flood losses over the entire river basin. This practical and inexpensive approach can provide sufficiently reliable information, and is applicable in other similar river basins.

  9. Developing in situ flood estimators using multi-date Landsat imagery

    NASA Technical Reports Server (NTRS)

    Mcleester, J. N.; Philipson, W. R.

    1979-01-01

    Landsat satellite imagery is being used as the primary source of information on flooding in the Black River Basin of northern New York State. Landsat images (Band 7) depicting flood conditions during several flood seasons since 1973 were obtained for analysis. Visual interpretation of these images is providing the basis for quantitatively relating in situ measurements of river discharge with the total area and geographic locations of inundation. This, in turn, will provide real-time estimation of flood losses over the entire river basin. This practical and inexpensive approach can provide sufficiently reliable information, and is applicable in other similar river basins.

  10. Parametric and Nonparametric Analysis of LANDSAT TM and MSS Imagery for Detecting Submerged Plant Communities

    NASA Technical Reports Server (NTRS)

    Ackleson, S. G.; Klemas, V.

    1984-01-01

    The spatial, spectral and radiometric characteristics of LANDSAT TM and MSS imagery for detecting submerged aquatic vegetation are assessed. The problem is approached from two perspectives; purely stochastic or nonparametric in a radiative sense and theoretical in which radiative transfer equations are used to predict upwelling radiance at satellite altitude. The spectral and radiometric aspects of the theoretical approach are addressed with which a submerged plant canopy is distinguished from a surrounding bottom of sand or mud.

  11. Parametric and Nonparametric Analysis of LANDSAT TM and MSS Imagery for Detecting Submerged Plant Communities

    NASA Technical Reports Server (NTRS)

    Ackleson, S. G.; Klemas, V.

    1984-01-01

    The spatial, spectral and radiometric characteristics of LANDSAT TM and MSS imagery for detecting submerged aquatic vegetation are assessed. The problem is approached from two perspectives; purely stochastic or nonparametric in a radiative sense and theoretical in which radiative transfer equations are used to predict upwelling radiance at satellite altitude. The spectral and radiometric aspects of the theoretical approach are addressed with which a submerged plant canopy is distinguished from a surrounding bottom of sand or mud.

  12. Get Close to Glaciers with Satellite Imagery.

    ERIC Educational Resources Information Center

    Hall, Dorothy K.

    1986-01-01

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

  13. Get Close to Glaciers with Satellite Imagery.

    ERIC Educational Resources Information Center

    Hall, Dorothy K.

    1986-01-01

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

  14. LANDSAT: US standard catalog no. U-34. [LANDSAT imagery for June 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska, and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles.

  15. LANDSAT: Non-US standard catalog no. N-36. [LANDSAT imagery for August, 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska, and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross reference defining the beginning and ending dates for LANDSAT cycles.

  16. LANDSAT: US standard catalog no. U-35. [LANDSAT imagery for July, 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility in published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska, and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles.

  17. LANDSAT: Non-US standard catalog, 1-31 January 1976. [LANDSAT imagery for

    NASA Technical Reports Server (NTRS)

    1976-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles.

  18. LANDSAT: Non-US standard catalog no. N-30. [LANDSAT imagery for February, 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska, and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles.

  19. LANDSAT non-US standard catalog no. N-35. [LANDSAT imagery July, 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska, and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles.

  20. Essential climatic variables estimation with satellite imagery

    NASA Astrophysics Data System (ADS)

    Kolotii, A.; Kussul, N.; Shelestov, A.; Lavreniuk, M. S.

    2016-12-01

    According to Sendai Framework for Disaster Risk Reduction 2015 - 2030 Leaf Area Index (LAI) is considered as one of essential climatic variables. This variable represents the amount of leaf material in ecosystems and controls the links between biosphere and atmosphere through various processes and enables monitoring and quantitative assessment of vegetation state. LAI has added value for such important global resources monitoring tasks as drought mapping and crop yield forecasting with use of data from different sources [1-2]. Remote sensing data from space can be used to estimate such biophysical parameter at regional and national scale. High temporal satellite imagery is usually required to capture main parameters of crop growth [3]. Sentinel-2 mission launched in 2015 be ESA is a source of high spatial and temporal resolution satellite imagery for mapping biophysical parameters. Products created with use of automated Sen2-Agri system deployed during Sen2-Agri country level demonstration project for Ukraine will be compared with our independent results of biophysical parameters mapping. References Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736 Kolotii, A., Kussul, N., Shelestov, A., Skakun, S., Yailymov, B., Basarab, R., ... & Ostapenko, V. (2015). Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 39-44. Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508.

  1. Landsat and multispectral imagery utilization in the U. S. Army

    SciTech Connect

    Krieger, R.H. Jr. )

    1992-03-01

    The developing use of multispectral imagery (MSI) by the U.S. Army, in particular that produced by Landsat and SPOT, is discussed. The role of MSI in operations Desert Shield and Desert Storm is emphasized. Ongoing projects for future military uses of MSI are addressed.

  2. Application of Unmanned Aerial Systems in Spatial Downscaling of Landsat VIR imageries of Agricultural Fields

    NASA Astrophysics Data System (ADS)

    Torres, A.; Hassan Esfahani, L.; Ebtehaj, A.; McKee, M.

    2016-12-01

    While coarse space-time resolution of satellite observations in visible to near infrared (VIR) is a serious limiting factor for applications in precision agriculture, high resolution remotes sensing observation by the Unmanned Aerial Systems (UAS) systems are also site-specific and still practically restrictive for widespread applications in precision agriculture. We present a modern spatial downscaling approach that relies on new sparse approximation techniques. The downscaling approach learns from a large set of coincident low- and high-resolution satellite and UAS observations to effectively downscale the satellite imageries in VIR bands. We focus on field experiments using the AggieAirTM platform and Landsat 7 ETM+ and Landsat 8 OLI observations obtained in an intensive field campaign in 2013 over an agriculture field in Scipio, Utah. The results show that the downscaling methods can effectively increase the resolution of Landsat VIR imageries by the order of 2 to 4 from 30 m to 15 and 7.5 m, respectively. Specifically, on average, the downscaling method reduces the root mean squared errors up to 26%, considering bias corrected AggieAir imageries as the reference.

  3. Monitoring arctic habitat and goose production by satellite imagery

    USGS Publications Warehouse

    Reeves, H.M.; Cooch, F.G.; Munro, R.E.

    1976-01-01

    Spacecraft imagery, especially from the National Atmospheric and Oceanic Administration's Improved TIROS (Television Infra-Red Observational Satellite) Operational Satellites, permits timely evaluations of snow and ice conditions encountered by arctic nesting geese. Imagery from the TIROS satellite for 5 wide]y scattered locations in arctic North America was obtained for three 3-day intervals in June 1973 and 1974. These pictures were used to expand fragmentary habitat data available from ground observations. Late disappearance of snow and ice may prevent or retard nesting effort and reproductive success. Our immediate aim is to recognize years of catastrophic or very good production; however, supporting information from ground studies, LANDSAT imagery, analyses of banding data, and studies of age ratios in popu]ations and harvests eventua

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

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  5. An operational application of satellite snow cover observations, northwest United States. [using LANDSAT 1

    NASA Technical Reports Server (NTRS)

    Dillard, J. P.

    1975-01-01

    LANDSAT-1 imagery showing extent of snow cover was collected and is examined for the 1973 and 1974 snowmelt seasons for three Columbia River Basins. Snowlines were mapped and the aerial snow cover was determined using satellite data. Satellite snow mapping products were compared products from conventional information sources (computer programming and aerial photography was used). Available satellite data were successfully analyzed by radiance thresholding to determine snowlines and the attendant snow-covered area. Basin outline masks, contour elevation masks, and grid overlays were utilized as satellite data interpretation aids. Verification of the LANDSAT-1 data was generally good although there were exceptions. A major problem was lack of adequate cloud-free satellite imagery of high resolution and determining snowlines in forested areas.

  6. Sun position calculator (SPC) for Landsat imagery with geodetic latitudes

    NASA Astrophysics Data System (ADS)

    Seong, Jeong C.

    2015-12-01

    Landsat imagery comes with sun position information such as azimuth and sun elevation, but they are available only at the center of a scene. To aid in the use of Landsat imagery for various solar radiation applications such as topographic correction, solar power, urban heat island, agriculture, climate and vegetation, it is necessary to calculate the sun position information at every pixel. This research developed a PC application that creates sun position data layers in ArcGIS at every pixel in a Landsat scene. The SPC program is composed of two major routines - converting universal transverse Mercator (UTM) projection coordinates to geographic longitudes and latitudes, and calculating sun position information based on the Meeus' routine. For the latter, an innovative method was also implemented to account for the Earth's flattening on an ellipsoid. The Meeus routine implemented in this research showed about 0.2‧ of mean absolute difference from the National Renewable Energy Laboratory (NREL) Solar Position Algorithm (SPA) routine when solar zenith and azimuth angles were tested with every 30 min data at four city locations (Fairbanks, Atlanta, Sydney and Rio Grande) on June 30, 2014. The Meeus routine was about ten times faster than the SPA routine. Professionals who need the Sun's position information for Landsat imagery will benefit from the SPC application.

  7. LANDSAT: Non-US standard catalog. [LANDSAT imagery for August 1977

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The non-U. S. Standard Catalog lists non-U. S. imagery acquired by LANDSAT 1 and 2 which has been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  8. LANDSAT 3 world standard catalog, 1-30 September 1978. [LANDSAT imagery for September 1978

    NASA Technical Reports Server (NTRS)

    1978-01-01

    Imagery acquired by LANDSAT 3 which was processed and input to the data files during the referenced month is listed. Data, such as data acquired, cloud cover, and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  9. LANDSAT US standard catalog, 1 October - 31 October 1977. [LANDSAT imagery for Oktober 1977

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The U. S. standard catalog lists U. S. imagery acquired by LANDSAT 1 and 2 which has been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  10. LANDSAT 2 world standard catalog, 1-30 September 1978. [LANDSAT imagery for September 1978

    NASA Technical Reports Server (NTRS)

    1978-01-01

    Imagery acquired by LANDSAT 2 which was processed and input to the data files during the referenced month is listed. Data, such as data acquired, cloud cover, and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  11. LANDSAT US standard catalog, 1-30 September 1977. [LANDSAT imagery for September, 1977

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The U. S. Standard Catalog lists U. S. imagery acquired by LANDSAT 1 and 2 which has been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover, and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  12. LANDSAT Non-US standard catalog, 1-31 December 1975. [LANDSAT imagery for December 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by LANDSAT 1 and 2 which has been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  13. Mapping cultivable land from satellite imagery with clustering algorithms

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  14. Applications of Landsat imagery to geological research in Minnesota

    NASA Technical Reports Server (NTRS)

    Weiblen, P. W.; Morey, G. B.; Walton, M. S.

    1975-01-01

    A large part of northeastern Minnesota north of Lake Superior was studied using Landsat images. The area is being studied for its intercontinental rift and for large, low grade, copper-nickel deposits. By using Landsat imagery in conjunction with field data, it is possible to develop a much higher level of continuity and structural resolution in interpretations of the bedrock geology. Preliminary results indicate that it is possible to distinguish various surficial morphological features such as the Vermilion and Highland moraines, the Toimi drumlin field, and an unnamed drumlin field apparently associated with the Highland moraine.

  15. Natural resources research and development in Lesotho using LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Jackson, A. A. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. A map of the drainage of the whole country to include at least third order streams was constructed from LANDSAT imagery. This was digitized and can be plotted at any required scale to provide base maps for other cartographic projects. A suite of programs for the interpretation of digital LANDSAT data is under development for a low cost programmable calculator. Initial output from these programs has proved to have better resolution and detail than the standard photographic products, and was to update the standard topographic map of a particular region.

  16. Comparing Forest/Nonforest Classifications of Landsat TM Imagery for Stratifying FIA Estimates of Forest Land Area

    Treesearch

    Mark D. Nelson; Ronald E. McRoberts; Greg C. Liknes; Geoffrey R. Holden

    2005-01-01

    Landsat Thematic Mapper (TM) satellite imagery and Forest Inventory and Analysis (FIA) plot data were used to construct forest/nonforest maps of Mapping Zone 41, National Land Cover Dataset 2000 (NLCD 2000). Stratification approaches resulting from Maximum Likelihood, Fuzzy Convolution, Logistic Regression, and k-Nearest Neighbors classification/prediction methods were...

  17. An integrated software system for geometric correction of LANDSAT MSS imagery

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Esilva, A. J. F. M.; Camara-Neto, G.; Serra, P. R. M.; Desousa, R. C. M.; Mitsuo, Fernando Augusta, II

    1984-01-01

    A system for geometrically correcting LANDSAT MSS imagery includes all phases of processing, from receiving a raw computer compatible tape (CCT) to the generation of a corrected CCT (or UTM mosaic). The system comprises modules for: (1) control of the processing flow; (2) calculation of satellite ephemeris and attitude parameters, (3) generation of uncorrected files from raw CCT data; (4) creation, management and maintenance of a ground control point library; (5) determination of the image correction equations, using attitude and ephemeris parameters and existing ground control points; (6) generation of corrected LANDSAT file, using the equations determined beforehand; (7) union of LANDSAT scenes to produce and UTM mosaic; and (8) generation of output tape, in super-structure format.

  18. LANDSAT imagery of the Central Andes

    NASA Technical Reports Server (NTRS)

    Komer, C. A.; Morgan, P.

    1986-01-01

    The central Andes of South America extend from approximately 14 deg. S to 28 deg. S as an unbroken chain of mountains and volcanoes over 2000 km long. It is here that the Nazca plate dives under the South American plate at angles varying from 10 deg to 30 deg. Very little is known about the volcanoes comprising this classic, subduction-type plate margin. A catalogue of the volcanoes in the central Andes is being prepared by Dr. P.W. Francis and Dr. C.A. Wood at the NASA Lunar and Planetary Institute. At present, more than 800 volcanoes of Cenozoic age have been recognized in the chain, with an estimated 75-80 major, active Quarternary volcanoes. Approximately one hundred 1536 x 1536 pixel color composite Optronics positives were produced from six full LANDSAT Thermatic Mapper scenes and three partial TM scenes. These positives cover a large portion of the central Andes. The positives were produced from LANDSAT data using the VAX imaging package, LIPS. The scenes were first transferred from magnetic tape to disk. The LIPS package was then used to select volcanically interesting areas which were then electronically enhanced. Finally, the selected areas were transferred back to tape and printed on the Optronics equipment. The pictures are color composites using LANDSAT TM bands 7,4, and 2 in the red, green, and blue filters, respectively.

  19. Spatial reasoning to determine stream network from LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Haralick, R. M.; Wang, S.; Elliott, D. B.

    1983-01-01

    In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, mixed information of material reflectance in the original LANDSAT imagery must be separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. A complete elevation model can be generated by interpolating values for nonridge and non-valley pixels. The small streams not detectable from material reflectance information can be located in the valleys with flow direction known from the elevation model. Finally, the flow directions of big visible rivers can be inferred by solving a consistent labeling problem based on a set of spatial reasoning constraints.

  20. Correction of Satellite Imagery Over Mountainous Terrain

    NASA Astrophysics Data System (ADS)

    Richter, Rudolf

    1998-06-01

    A method for the radiometric correction of satellite imagery over mountainous terrain has been developed to remove atmospheric and topographic effects. The algorithm accounts for horizontally varying atmospheric conditions and also includes the height dependence of the atmospheric radiance and transmittance functions to simulate the simplified properties of a three-dimensional atmosphere. A database has been compiled that contains the results of radiative transfer calculations (atmospheric transmittance, path radiance, direct and diffuse solar flux) for a wide range of weather conditions. A digital elevation model is used to obtain information about surface elevation, slope, and orientation. Based on the Lambertian assumption the surface reflectance in rugged terrain is calculated for the specified atmospheric conditions. Regions with extreme illumination geometries sensitive to BRDF effects can be optionally processed separately. The method is restricted to high spatial resolution satellite sensors with a small swath angle such as the Landsat thematic mapper and Systeme pour l Observation de la Terre high resolution visible, since some simplifying assumptions were made to reduce the required image processing time.

  1. Correction of satellite imagery over mountainous terrain.

    PubMed

    Richter, R

    1998-06-20

    A method for the radiometric correction of satellite imagery over mountainous terrain has been developed to remove atmospheric and topographic effects. The algorithm accounts for horizontally varying atmospheric conditions and also includes the height dependence of the atmospheric radiance and transmittance functions to simulate the simplified properties of a three-dimensional atmosphere. A database has been compiled that contains the results of radiative transfer calculations (atmospheric transmittance, path radiance, direct and diffuse solar flux) for a wide range of weather conditions. A digital elevation model is used to obtain information about surface elevation, slope, and orientation. Based on the Lambertian assumption the surface reflectance in rugged terrain is calculated for the specified atmospheric conditions. Regions with extreme illumination geometries sensitive to BRDF effects can be optionally processed separately. The method is restricted to high spatial resolution satellite sensors with a small swath angle such as the Landsat thematic mapper and Systeme pour l'Observation de la Terre high resolution visible, since some simplifying assumptions were made to reduce the required image processing time.

  2. Utilization of Meteorological Satellite Imagery for World-Wide Environmental Monitoring the Lower Mississippi River Flood of 1979 - Case 1. [St. Louis, Missouri

    NASA Technical Reports Server (NTRS)

    Helfert, M. R.; Mccrary, D. G.; Gray, T. I. (Principal Investigator)

    1981-01-01

    The 1979 Lower Mississippi River flood was selected as a test case of environmental disaster monitoring utilizing NOAA-n imagery. A small scale study of the St. Louis Missouri area comparing ERTS-1 (LANDSAT) and NOAA-2 imagery and flood studies using only LANDSAT imagery for mapping the Rad River of the North, and Nimbus-5 imagery for East Australia show the nonmeteorological applications of NOAA satellites. While the level of NOAA-n imagery detail is not that of a LANDSAT image, for operational environmental monitoring users the NOAA-n imagery may provide acceptable linear resolution and spectral isolation.

  3. Multi-temporal water extent analysis of a hypersaline playa lake using Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Kilic, Ecenur; Kamil Yilmaz, Koray; Lutfi Suzen, Mehmet

    2016-04-01

    Distinguishing inland water bodies from satellite imagery has always been one of the main practices of remote sensing. In some cases this differentiation can directly be obtained by visual interpretation. However, in case of hyper-saline playa lakes, presence of high albedo salt crust in the lake bed hampers visual interpretation and requires further attention. Lake Tuz is a hypersaline playa lake which is ranked as the second largest lake in Turkey. Spatio-temporal changes in lake water extent are important both economically and hydrologically including salt production, lake water balance, drought and over-exploitation issues. This study investigates the spatiotemporal changes in Lake Tuz water extent during the last decade using single-band thresholding and multi-band indices extracted from the multi-temporal Landsat 5 TM and Landsat 7 ETM+ images. The applicability of different satellite-derived indices including Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Automated Water Extraction Index (AWEI) and Tasseled Cap Wetness (TCw) were investigated for the extraction of lake water extent from Landsat imagery. Our analysis indicated that, overall, NDWI is superior to other tested indices in separating wet/dry pixels over the lake bottom covered with salt crust. Using a NDWI thresholding procedure, the annual and seasonal variation in the Lake Tuz water extent were determined and further linked to hydro-meteorological variables such as precipitation.

  4. Application of genetic programming and Landsat multi-date imagery for urban growth monitoring

    NASA Astrophysics Data System (ADS)

    Djerriri, Khelifa; Malki, Mimoun

    2013-10-01

    Monitoring of earth surface changes from space by using multi-date satellite imagery was always a main concern to researchers in the field of remotely sensed image processing. Thus, several techniques have been proposed to saving technicians from interpreting and digitizing hundreds of areas by hand. The exploiting of simple, easy to memorize and often comprehensible mathematical models such band-ratios and indices are one of the widely used techniques in remote sensing for the extraction of particular land-cover/land-use like urban and vegetation areas. The results of these models generally only need the definition of adequate threshold or using simple unsupervised classification algorithms to discriminate between the class of interest and the background. In our work a genetic programming based approach has been adopted to evolve simple mathematical expression to extract urban areas from image series. The model is built from a single image by using a basic set of operators between spectral bands and maximizing a fitness function, which is based on the using of the M-statistic criterion. The model was constructed from the Landsat 5 TM image acquired in 2006 by using training samples extracted with the help of a Quick-bird high spatial resolution satellite image acquired the same day as the Landsat image over the city of Oran, Algeria. The model has been tested to extract urban areas from multi-date series of Landsat TM imagery

  5. Mapping of heavy metal pollution in river water at daily time-scale using spatio-temporal fusion of MODIS-aqua and Landsat satellite imageries.

    PubMed

    Swain, Ratnakar; Sahoo, Bhabagrahi

    2017-05-01

    For river water quality monitoring at 30m × 1-day spatio-temporal scales, a spatial and temporal adaptive reflectance fusion model (STARFM) is developed for estimating turbidity (Tu), total suspended solid (TSS), and six heavy metals (HV) of iron, zinc, copper, chromium, lead and cadmium, by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat (Ls) spectral bands. A combination of regression analysis and genetic algorithm (GA) techniques are applied to develop spectral relationships between Tu-Ls, TSS-Tu, and each HV-TSS. The STARFM algorithm and all the developed relationship models are evaluated satisfactorily by various performance evaluation measures to develop heavy metal pollution index-based vulnerability maps at 1-km resolution in the Brahmani River in eastern India. The Monte-Carlo simulation based analysis of the developed formulations reveals that the uncertainty in estimating Zn and Cd is the minimum (1.04%) and the maximum (5.05%), respectively. Hence, the remote sensing based approach developed herein can effectively be used in many world rivers for real-time monitoring of heavy metal pollution.

  6. Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data

    PubMed Central

    Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

    2015-01-01

    Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate daily synthetic Landsat imagery. This algorithm was designed to avoid the limitations of the conditional spatial temporal data fusion approach (STDFA) including the constant window for disaggregation and the sensor difference. An adaptive window size selection method is proposed in this study to select the best window size and moving steps for the disaggregation of coarse pixels. The linear regression method is used to remove the influence of differences in sensor systems using disaggregated mean coarse reflectance by testing and validation in two study areas located in Xinjiang Province, China. The results show that the MSTDFA algorithm can generate daily synthetic Landsat imagery with a high correlation coefficient (R) ranged from 0.646 to 0.986 between synthetic images and the actual observations. We further show that MSTDFA can be applied to 250 m 16-day MODIS MOD13Q1 products and the Landsat Normalized Different Vegetation Index (NDVI) data by generating a synthetic NDVI image highly similar to actual Landsat NDVI observation with a high R of 0.97. PMID:26393607

  7. Assessing water table dynamics of peatland areas using Landsat TIR imagery

    NASA Astrophysics Data System (ADS)

    Carrión Klier, Carolina; Schuetz, Tobias; Untenecker, Johanna; Bechtold, Michel

    2016-04-01

    Water saturation conditions in peatlands are a driving factor for the emission of greenhouse gases. Thus, the identification of long-term saturation dynamics in peatland areas is a first step towards the quantification of emissions from these ecosystems. Unfortunately, information on groundwater levels is not always available on the necessary spatial or temporal resolution. Publicly available databases of remotely sensed satellite data offer ways to close this lack of information. Previous studies have shown the potential of the thermal signature of the soil surface monitored by thermal infrared imagery to derive information about subsurface hydrology. It is also known that shallow-groundwater systems as wet peatlands are less susceptible to seasonal temperature fluctuations than drained peatlands and soils with deeper groundwater. Hence, wetter peatlands will be characterized by a smoother seasonal surface temperature curve, being cooler in the summer and warmer in the winter. Due to the strong influence of the vegetation cover on thermal infrared radiative transfer, we here analyze temperature dynamics as relative differences between comparable vegetation cover in the same region. As satellite data we used remotely sensed Landsat TIR imagery. The archive of Landsat TIR imagery compiles records on a 16 days cycle since 1984. The present study seeks to use this archive to reconstruct the water saturation conditions in the peatland areas of the state of Baden-Wuerttemberg, Germany, over the last three decades. We restricted our analysis on grassland vegetation because of its predominance in the study area and its relative low vegetation height. Preliminary results for selected peatlands are 1) peatland characteristic annual patterns of TIR temperature differences, and 2) intra-annual variability over the years of available Landsat imagery within these patterns. In our presentation, we will further compare the resulting time series with available groundwater level

  8. Landsat Imagery Enables Global Studies of Surface Trends

    NASA Technical Reports Server (NTRS)

    2015-01-01

    Landsat 8 is the latest in the NASA-developed series of satellites that have provided a continuous picture of Earth for more than 40 years. Mountain View, California-based Google has incorporated Landsat data into several products, most recently generating a cloud-free view of Earth. Google has also teamed up with researchers at the University of Maryland and Goddard Space Flight Center to create a global survey showing changes in forest cover over many years-the first of its kind.

  9. Techniques for Producing Coastal Land Water Masks from Landsat and Other Multispectral Satellite Data

    NASA Technical Reports Server (NTRS)

    Spruce, Joseph P.; Hall, Callie

    2005-01-01

    Coastal erosion and land loss continue to threaten many areas in the United States. Landsat data has been used to monitor regional coastal change since the 1970s. Many techniques can be used to produce coastal land water masks, including image classification and density slicing of individual bands or of band ratios. Band ratios used in land water detection include several variations of the Normalized Difference Water Index (NDWI). This poster discusses a study that compares land water masks computed from unsupervised Landsat image classification with masks from density-sliced band ratios and from the Landsat TM band 5. The greater New Orleans area is employed in this study, due to its abundance of coastal habitats and its vulnerability to coastal land loss. Image classification produced the best results based on visual comparison to higher resolution satellite and aerial image displays. However, density sliced NDWI imagery from either near infrared (NIR) and blue bands or from NIR and green bands also produced more effective land water masks than imagery from the density-sliced Landsat TM band 5. NDWI based on NIR and green bands is noteworthy because it allows land water masks to be generated from multispectral satellite sensors without a blue band (e.g., ASTER and Landsat MSS). NDWI techniques also have potential for producing land water masks from coarser scaled satellite data, such as MODIS.

  10. Techniques for Producing Coastal Land Water Masks from Landsat and Other Multispectral Satellite Data

    NASA Technical Reports Server (NTRS)

    Spruce, Joe; Hall, Callie

    2005-01-01

    Coastal erosion and land loss continue to threaten many areas in the United States. Landsat data has been used to monitor regional coastal change since the 1970's. Many techniques can be used to produce coastal land water masks, including image classification and density slicing of individual bands or of band ratios. Band ratios used in land water detection include several variations of the Normalized Difference Water Index (NDWI). This poster discusses a study that compares land water masks computed from unsupervised Landsat image classification with masks from density-sliced band ratios and from the Landsat TM band 5. The greater New Orleans area is imployed in this study, due to its abundance of coastal habitats and ist vulnerability to coastal land loss. Image classification produced the best results based on visual comparison to higher resolution satellite and aerial image displays. However, density-sliced NDWI imagery from either near infrared (NIR) and blue bands or from NIR and green bands also produced more effective land water masks than imagery from the density-sliced Landsat TM band 5. NDWI based on NIR and green bands is noteworthy because it allows land water masks to be generated form multispectral satellite sensors without a blue band (e.g., ASTER and Landsat MSS). NDWI techniques also have potential for producing land water masks from coarser scaled satellite data, such as MODIS.

  11. Are clear-cut areas estimated from LANDSAT imagery reliable?

    NASA Technical Reports Server (NTRS)

    Lee, Y. J.

    1975-01-01

    The reliability of LANDSAT imagery for estimation of clear-cut areas was evaluated by comparison with data obtained from high-altitude photos and logging historical map and from field inspections. A mature forest was selected as a test site because of its continuous clear-cut operation. The forest is about 50 km northwest of Victoria, British Columbia, Canada, and consists of 9092 ha. Areas clear-cut within the past year were overestimated by 12.9%, those clear-cut 1-year or more by 2.2%, whereas uncut mature timber was underestimated by 3.6%. Three clear-cut areas were missed in the logging map and two in the LANDSAT enhancement. The difference between area estimates was significant when all 26 areas were included but not when 2 overestimated areas were excluded from the analysis. The study indicates that LANDSAT imagery color enhancement is a useful tool in up-dating clear-cut areas for long-term planning in forest management.

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

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  13. Test of the use of LANDSAT imagery to detect changes in the area of forests in the tropics

    SciTech Connect

    Woodwell, G.M.; Hobbie, J.E.; Houghton, R.A.; Melillo, J.M.; Stone, T.A.

    1983-09-01

    Rates of change in the area of tropical moist forest in the Brazilian State of Rondonia in the southwestern Amazon Basin were measured over several years using LANDSAT data. The purpose was to test in the tropics a technique of change detection developed in temperate forests. The entire procedure was tested from the availability of imagery on computer tapes through the details of the analysis. Imagery was available and obtained readily from the Brazilian Institute of Space Studies (INPE). Three LANDSAT scenes were used to detect and measure change: June 1976, August 1978 and May 1981. Results showed within the area of one LANDSAT scene (34,000 km/sup 2/) rates of deforestation of 26,900 ha/y from 1976 to 1978 and 55,200 ha/y from 1978 to 1981. The LANDSAT data were used with 1981 data from the NOAA7 satellite (1 km resolution) to show in a preliminary estimate that 12,650 km/sup 2/ of forest had been cleared in Rondonia prior to 1981. A survey of LANDSAT data available from tropical regions around the world showed that there is ample data for a LANDSAT-based evaluation of deforestation for the period 1972 to 1982 for Amazonia, Central Africa and mainland Southeast Asia. The evaluation of deforestation in insular Southeast Asia would be more difficult by LANDSAT currently due to high cloud cover in the region. 10 references, 10 figures, 2 tables.

  14. Mapping the Distribution and Biomass of Emergent Aquatic Plants in the Sacramento-San Joaquin River Delta of California Using Landsat Imagery Analysis

    NASA Technical Reports Server (NTRS)

    Potter, Christopher

    2015-01-01

    This study evaluated the cost-effective and timely use of Landsat imagery to map and monitor emergent aquatic plant biomass and to filter satellite image products for the most probable locations of water hyacinth coverage in the Delta based on field observations collected immediately after satellite image acquisition.

  15. LANDSAT: US standard catalog, 1 February 1977 - 28 February 1977. [LANDSAT imagery for the month of February 1977

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The U.S. Standard Catalog lists U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as data acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

  16. LANDSAT non-U.S. standard catalog, 1 January 1977 through 31 January 1977. [LANDSAT imagery January 1977

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which was processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover, and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

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

    Treesearch

    Barry Tyler. Wilson

    2015-01-01

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

  18. Structural lineament and pattern analysis of Missouri, using LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Martin, J. A.; Kisvarsanyi, G. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. Major linear, circular, and arcuate traces were observed on LANDSAT imagery of Missouri. Lineaments plotted within the state boundaries range from 20 to nearly 500 km in length. Several extend into adjoining states. Lineaments plots indicate a distinct pattern and in general reflect structural features of the Precambrian basement of the platform. Coincidence of lineaments traced from the imagery and known structural features in Missouri is high, thus supporting a causative relation between them. The lineament pattern apparently reveals a fundamental style of the deformation of the intracontinental craton. Dozens of heretofore unknown linear features related to epirogenic movements and deformation of this segment of the continental crust were delineated. Lineaments and mineralization are interrelated in a geometrically classifiable pattern.

  19. Comparison of machine-learning methods for above-ground biomass estimation based on Landsat imagery

    NASA Astrophysics Data System (ADS)

    Wu, Chaofan; Shen, Huanhuan; Shen, Aihua; Deng, Jinsong; Gan, Muye; Zhu, Jinxia; Xu, Hongwei; Wang, Ke

    2016-07-01

    Biomass is one significant biophysical parameter of a forest ecosystem, and accurate biomass estimation on the regional scale provides important information for carbon-cycle investigation and sustainable forest management. In this study, Landsat satellite imagery data combined with field-based measurements were integrated through comparisons of five regression approaches [stepwise linear regression, K-nearest neighbor, support vector regression, random forest (RF), and stochastic gradient boosting] with two different candidate variable strategies to implement the optimal spatial above-ground biomass (AGB) estimation. The results suggested that RF algorithm exhibited the best performance by 10-fold cross-validation with respect to R2 (0.63) and root-mean-square error (26.44 ton/ha). Consequently, the map of estimated AGB was generated with a mean value of 89.34 ton/ha in northwestern Zhejiang Province, China, with a similar pattern to the distribution mode of local forest species. This research indicates that machine-learning approaches associated with Landsat imagery provide an economical way for biomass estimation. Moreover, ensemble methods using all candidate variables, especially for Landsat images, provide an alternative for regional biomass simulation.

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  1. Stratified estimates of forest area using the k-nearest neighbors technique and satellite imagery

    Treesearch

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

    2002-01-01

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

  2. Simulation of meteorological satellite (METSAT) data using LANDSAT data

    NASA Technical Reports Server (NTRS)

    Austin, W. W.; Ryland, W. E.

    1983-01-01

    The information content which can be expected from the advanced very high resolution radiometer system, AVHRR, on the NOAA-6 satellite was assessed, and systematic techniques of data interpretation for use with meteorological satellite data were defined. In-house data from LANDSAT 2 and 3 were used to simulate the spatial, spectral, and sampling methods of the NOAA-6 satellite data.

  3. PV output variability modeling using satellite imagery.

    SciTech Connect

    Stein, Joshua S.; Ellis, Abraham; Reno, Matthew J.

    2010-11-01

    High frequency irradiance variability measured on the ground is caused by the formation, dissipation, and passage of clouds in the sky. If we can identify and associate different cloud types/patterns from satellite imagery, we may be able to predict irradiance variability in areas lacking sensors. With satellite imagery covering the entire U.S., this allows for more accurate integration planning and power flow modeling over wide areas. Satellite imagery from southern Nevada was analyzed at 15 minute intervals over a year. Methods for image stabilization, cloud detection, and textural classification of clouds were developed and tested. High Performance Computing parallel processing algorithms were also investigated and tested. Artificial Neural Networks using imagery as inputs were trained on ground-based measurements of irradiance to model the variability and were tested to show some promise as a means for predicting irradiance variability.

  4. Users and uses of Landsat 8 satellite imagery—2014 survey results

    USGS Publications Warehouse

    Miller, Holly M.

    2016-04-18

    To explore the effect of the availability of Landsat 8 imagery on Landsat imagery use in general, established users (those who had consistently used Landsat imagery both before and after Landsat 8 imagery became available) using Landsat 8 imagery were asked about changes in the amount of Landsat imagery they used. The majority of established users using Landsat 8 imagery (60 percent) reported an average increase of 51 percent in the number of scenes obtained after Landsat 8 imagery became available. Landsat 8 users were asked if they had encountered challenges in using Landsat 8 whereas non-Landsat 8 users were asked if such challenges had played a role in why they were not using Landsat 8 imagery. Although many users did not encounter challenges when using or trying to use Landsat 8 data, slightly less than 30 percent did encounter issues with processing the data to a usable point. The most common issue reported was not being able to create or have access to a surface reflectance corrected product. Other challenges were related to the file sizes of images being too large to download, store, or analyze. There were no statistically significant differences between Landsat 8 and non-Landsat 8 users in terms of challenges encountered when using or trying to use the imagery, which indicates that users were not unduly discouraged by the challenges they may have encountered. When asked about potential consequences of not using Landsat 8, more than half of the non-Landsat 8 users did not report detrimental effects on their work from not using the imagery. Of those who did report detrimental effects, decreased quality of work, decreased scope of work, and increased time spent on work were the most common.   

  5. Direct determination of surface albedos from satellite imagery

    NASA Technical Reports Server (NTRS)

    Mekler, Y.; Joseph, J. H.

    1983-01-01

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

  6. Direct determination of surface albedos from satellite imagery

    NASA Technical Reports Server (NTRS)

    Mekler, Y.; Joseph, J. H.

    1983-01-01

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

  7. On vegetation mapping in Alaska using LANDSAT imagery with primary concerns for method and purpose in satellite image-based vegetation and land-use mapping and the visual interpretation of imagery in photographic format

    NASA Technical Reports Server (NTRS)

    Anderson, J. H. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. A simulated color infrared LANDSAT image covering the western Seward Peninsula was used for identifying and mapping vegetation by direct visual examination. The 1:1,083,400 scale print used was prepared by a color additive process using positive transparencies from MSS bands 4, 5, and 7. Seven color classes were recognized. A vegetation map of 3200 sq km area just west of Fairbanks, Alaska was made. Five colors were recognized on the image and identified to vegetation types roughly equivalent to formations in the UNESCO classification: orange - broadleaf deciduous forest; gray - needleleaf evergreen forest; light violet - subarctic alpine tundra vegetation; violet - broadleaf deciduous shrub thicket; and dull violet - bog vegetation.

  8. Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and SPOT imagery

    NASA Technical Reports Server (NTRS)

    Cohen, Warren B.; Spies, Thomas A.

    1992-01-01

    Relationships between spectral and texture variables derived from SPOT HRV 10 m panchromatic and Landsat TM 30 m multispectral data and 16 forest stand structural attributes is evaluated to determine the utility of satellite data for analysis of hemlock forests west of the Cascade Mountains crest in Oregon and Washington, USA. Texture of the HRV data was found to be strongly related to many of the stand attributes evaluated, whereas TM texture was weakly related to all attributes. Data analysis based on regression models indicates that both TM and HRV imagery should yield equally accurate estimates of forest age class and stand structure. It is concluded that the satellite data are a valuable source for estimation of the standard deviation of tree sizes, mean size and density of trees in the upper canopy layers, a structural complexity index, and stand age.

  9. Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and SPOT imagery

    NASA Technical Reports Server (NTRS)

    Cohen, Warren B.; Spies, Thomas A.

    1992-01-01

    Relationships between spectral and texture variables derived from SPOT HRV 10 m panchromatic and Landsat TM 30 m multispectral data and 16 forest stand structural attributes is evaluated to determine the utility of satellite data for analysis of hemlock forests west of the Cascade Mountains crest in Oregon and Washington, USA. Texture of the HRV data was found to be strongly related to many of the stand attributes evaluated, whereas TM texture was weakly related to all attributes. Data analysis based on regression models indicates that both TM and HRV imagery should yield equally accurate estimates of forest age class and stand structure. It is concluded that the satellite data are a valuable source for estimation of the standard deviation of tree sizes, mean size and density of trees in the upper canopy layers, a structural complexity index, and stand age.

  10. EROS Data Center Landsat digital enhancement techniques and imagery availability

    USGS Publications Warehouse

    Rohde, Wayne G.; Lo, Jinn Kai; Pohl, Russell A.

    1978-01-01

    The US Geological Survey's EROS Data Center (EDC) is experimenting with the production of digitally enhanced Landsat imagery. Advanced digital image processing techniques are used to perform geometric and radiometric corrections and to perform contrast and edge enhancements. The enhanced image product is produced from digitally preprocessed Landsat computer compatible tapes (CCTs) on a laser beam film recording system. Landsat CCT data have several geometric distortions which are corrected when NASA produces the standard film products. When producing film images from CCT's, geometric correction of the data is required. The EDC Digital Image Enhancement System (EDIES) compensates for geometric distortions introduced by Earth's rotation, variable line length, non-uniform mirror scan velocity, and detector misregistration. Radiometric anomalies such as bad data lines and striping are common to many Landsat film products and are also in the CCT data. Bad data lines or line segments with more than 150 contiguous bad pixels are corrected by inserting data from the previous line in place of the bad data. Striping, caused by variations in detector gain and offset, is removed with a destriping algorithm applied after digitally enhancing the data. Image enhancement is performed by applying a linear contrast stretch and an edge enhancement algorithm. The linear contrast enhancement algorithm is designed to expand digitally the full range of useful data recorded on the CCT over the range of 256 digital counts. This minimizes the effect of atmospheric scattering and saturates the relative brightness of highly reflecting features such as clouds or snow. It is the intent that no meaningful terrain data are eliminated by the digital processing. The edge enhancement algorithm is designed to enhance boundaries between terrain features that exhibit subtle differences in brightness values along edges of features. After the digital data have been processed, data for each Landsat band

  11. Evaluating Landsat 8 Satellite Sensor Data for Improved Vegetation Mapping Accuracy of the New Hampshire Coastal Watershed Area

    NASA Astrophysics Data System (ADS)

    Ledoux, Lindsay

    Remote sensing is a technology that has been used for many years to generate land cover maps. These maps provide insight as to the landscape, and features that are on the ground. One way in which this is useful is through the visualization of forest cover types. The forests of New England have been notoriously difficult to map, due to their high complexity and fine-scale heterogeneity. In order to be able to better map these features, the newest satellite imagery available may be the best technology to use. Landsat 8 is the newest satellite created by a team of scientists and engineers from the United States Geological Survey and the National Aeronautics and Space Administration, and was launched in February of 2013. The Landsat 8 satellite sensor is considered an improvement over previous Landsat sensors, as it has three additional bands: (1) a coastal/ aerosol band, band 1, that senses light in deep blue, (2) a cirrus band, band 9, that provides detection of wispy clouds that may interfere with analysis, and (3) a Quality Assessment band whose bits contain information regarding conditions that may affect the quality and applicability of certain image pixels. In addition to these added bands, the data generated by Landsat 8 are delivered at an increased radiometric resolution compared with previous Landsat sensors, increasing the dynamic range of the data the sensor can retrieve. In order to investigate the satellite sensor data, a novel approach to classifying Landsat 8 imagery was used. Object-Based Image Analysis was employed, along with the random forest machine learning classifier, to segment and classify the land cover of the Coastal Watershed of southeastern New Hampshire. In order to account strictly for band improvements, supervised classification using the maximum likelihood classifier was completed, on imagery created: (1) using all of the original bands provided by Landsat 8, and (2) an image created using Landsat 8 bands that were only available on

  12. Application of LANDSAT imagery for snow mapping in Norway

    NASA Technical Reports Server (NTRS)

    Odegaard, H. (Principal Investigator); Ostrem, G.

    1977-01-01

    The author has identified the following significant results. It was shown that if the snow cover extent was determined from all four LANDSAT bands, there were significant differences in results. The MSS 4 gave the largest snow cover, but only slightly more than MSS 5, whereas MSS 6 and 7 gave the smallest snow area. A study was made to show that there was a relationship between the last date of snow fall and the area covered with snow, as determined from different bands. Imagery obtained shortly after a snow fall showed no significant difference in the snow-covered area when the four bans were compared, whereas, pronounced differences in the snow-covered area were found in images taken after a long period without precipitation.

  13. Land Cover and Permafrost Change Mapping Using Dense Time Stacks of Landsat and Quickbird Imagery

    NASA Astrophysics Data System (ADS)

    Nyland, K. E.; Streletskiy, D. A.; Shiklomanov, N. I.

    2014-12-01

    Climate change is especially pronounced in the Arctic, and regions on permafrost are at the frontier of these changes. Increasing air temperatures affect the extent, type, and characteristics of permafrost which is critical to many natural phenomena and northern infrastructure. In areas of discontinuous permafrost certain land cover types are indicative of permafrost conditions making satellite imagery an important tool for assessing environmental change in these remote areas. In arctic environments remote sensing can be particularly challenging due to consistently high cloud cover, data gaps, and landscape heterogeneity. However, there has been success at dealing with such challenges in lower latitude regions using the emerging dense time stack methodology. In place of using an anniversary date for land cover comparisons from different years, this methodology includes scenes from all seasons in addition to imagery normally rejected due to data gaps and high amounts of cloud cover. The incorporation of all available data creates a "dense time stack" which provides both a more complete dataset and more nuanced spectral signatures for classification. This work applied the dense time stack method to mapping five drainage basins in the close vicinity of the city of Igarka, Russia using both Landsat and Quickbird satellite imagery. The resulting map series proved this method to be effective within the Arctic for multiscalar mapping both temporally (annual and seasonal) and spatially (at the resolutions of Landsat and Quickbird). The time series of observed land cover changes produced allowed areas of permafrost degradation to be identified. These maps will be applied in the future to ongoing hydrological research in the region investigating the sources of increased run off and its relation to permafrost degradation.

  14. Remodeling census population with spatial information from Landsat TM imagery

    USGS Publications Warehouse

    Yuan, Y.; Smith, R.M.; Limp, W.F.

    1997-01-01

    In geographic information systems (GIS) studies there has been some difficulty integrating socioeconomic and physiogeographic data. One important type of socioeconomic data, census data, offers a wide range of socioeconomic information, but is aggregated within arbitrary enumeration districts (EDs). Values reflect either raw counts or, when standardized, the mean densities in the EDs. On the other hand, remote sensing imagery, an important type of physiogeographic data, provides large quantities of information with more spatial details than census data. Based on the dasymetric mapping principle, this study applies multivariable regression to examine the correlation between population counts from census and land cover types. The land cover map is classified from LandSat TM imagery. The correlation is high. Census population counts are remodeled to a GIS raster layer based on the discovered correlations coupled with scaling techniques, which offset influences from other than land cover types. The GIS raster layer depicts the population distribution with much more spatial detail than census data offer. The resulting GIS raster layer is ready to be analyzed or integrated with other GIS data. ?? 1998 Elsevier Science Ltd. All rights reserved.

  15. LANDSAT 2 world standard catalog, 1 May - 31 July 1978. [LANDSAT imagery for May through July 1978

    NASA Technical Reports Server (NTRS)

    1978-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles.

  16. Evaluating the Ability to Monitor Eastern U.S. Forest Regrowth with IKONOS Stereo Imagery and Landsat Disturbance History

    NASA Astrophysics Data System (ADS)

    Neigh, C. S.; Masek, J. G.; Bourget, P.; Diabate, M.

    2012-12-01

    Eastern U.S. forests have been estimated to be a net carbon sink from disturbance regeneration. We develop and present a sampling procedure to acquire forest stand heights from digital elevation models (DEMs) and satellite imagery. Our method combines Landsat disturbance history from 1984 - 2010 using the vegetation change tracker (VCT) algorithm, IKONOS stereo imagery, and laser detection and ranging (LIDAR) derived bare earth DEM from the National Elevation Dataset. A space for time substitution was investigated by applying the Landsat forest disturbance history to the IKONOS forest canopy height model (CHM). We compiled age versus height data to understand the spatial distribution of forest regrowth patterns and evaluate the limitations of this approach.

  17. Case studies on the geological application of LANDSAT imagery in Brazil. [Sao Domingos Range, Pocos de Caldas, and Araguaia and Tocantins Rivers

    NASA Technical Reports Server (NTRS)

    Demendonca, F. (Principal Investigator); Correa, A. C.; Liu, C. C.

    1975-01-01

    The author has identified the following significant results. Sao Domingos Range, Pocos de Caldas, and Araguaia and Tocantins Rivers in Brazil were selected as test sites for LANDSAT imagery. The satellite images were analyzed using conventional photointerpretation techniques, and the results indicate the application of small scale image data in regional structural data analysis, geological mapping, and mineral exploration.

  18. Monitoring crop and vegetation condition using the fused dense time-series landsat-like imagery

    USDA-ARS?s Scientific Manuscript database

    Since the launch of the first Landsat satellite in the early 1970s, Landsat has been widely used in many applications such as land cover and land use change monitoring, crop yield estimation, forest fire detection, and global ecosystem carbon cycle studies. Medium resolution sensors like Landsat hav...

  19. The utilization of LANDSAT imagery in nuclear power plant siting. [in Pakistan, South Carolina, and Spain

    NASA Technical Reports Server (NTRS)

    Eggenberger, A. J.; Rowlands, D.; Rizzo, P. C.

    1975-01-01

    LANDSAT imagery was used primarily to map geologic features such as lineaments, linears, faults, and other major geologic structures which affect site selection for a nuclear power plant. Areas studied include Pakistan, the South Carolina Piedmont, and Huelva, Spain.

  20. Environmental assessment of resource development in the Alaska coastal zone based on LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Belon, A. E.; Miller, J. M.; Stringer, W. J.

    1975-01-01

    LANDSAT imagery was interpreted to derive color coded maps of the physical parameters of the Alaskan coastal zone. Synoptic overviews depict sea surface circulation, sediment transport, and ice cover dimensions.

  1. The utilization of LANDSAT imagery in nuclear power plant siting. [in Pakistan, South Carolina, and Spain

    NASA Technical Reports Server (NTRS)

    Eggenberger, A. J.; Rowlands, D.; Rizzo, P. C.

    1975-01-01

    LANDSAT imagery was used primarily to map geologic features such as lineaments, linears, faults, and other major geologic structures which affect site selection for a nuclear power plant. Areas studied include Pakistan, the South Carolina Piedmont, and Huelva, Spain.

  2. Satellite imagery for volcanic hazards mitigation

    USGS Publications Warehouse

    Helz, R.T.; Ellrod, G.A.; Wadge, G.

    2002-01-01

    The Committee on Earth Observation Satellites (CEOS) seeks to foster cooperation to increase the usefulness and accessibility of satellite imagery. In 1997, CEOS initiated the Disaster Management Support Project to assess the present and potential use of satellite-derived information for volcanic hazards mitigation. The final report of the CEOS Volcanic Hazards Working Group reviews current use of satellite data for mitigation of volcanic hazards. The report specifies the minimum spectral channels needed for effective remote sensing of volcanic hazards, together with recommendations for threshold and optimum spatial and temporal resolutions.

  3. Preliminary analysis of the potential of LANDSAT imagery to study desertification. [Xique-Xique, Brazil

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Decarvalho, V. C.

    1980-01-01

    The use of LANDSAT imagery to define and delimit areas under process of desertification was investigated. Imagery for two different years (1973 and 1978) and two different seasons (dry and rainy seasons in 1976), were used to identify terrain morphology and vegetation cover. The analysis of LANDSAT interpretation, combined with geological and soil information obtained from published literature, allowed the identification of eleven ecological units which were classified corresponding to the degree of the Xique Xique region of Rio Sao Francisco.

  4. Operational data fusion framework for building frequent Landsat-like imagery in a cloudy region

    USDA-ARS?s Scientific Manuscript database

    An operational data fusion framework is built to generate dense time-series Landsat-like images for a cloudy region by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) data products and Landsat imagery. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is integrated in ...

  5. Investigation of LANDSAT imagery on correlations between ore deposits and major shield structures in Finland

    NASA Technical Reports Server (NTRS)

    Tuominen, H. V. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. Half of the 24 lineaments found in the LANDSAT winter mosaic have not been recorded in earlier literature. Some distinct fracture zones of the basement seem not to be observable as lineaments in the LANDSAT imagery.

  6. Crop classification using temporal stacks of multispectral satellite imagery

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  7. Summary of space imagery studies in Utah and Nevada. [using LANDSAT 1, EREP, and Skylab imagery

    NASA Technical Reports Server (NTRS)

    Jensen, M. L.; Laylander, P.

    1975-01-01

    LANDSAT-1, Skylab, and RB-57 imagery acquired within days of each other of the San Rafael swell enabled geological mapping of individual formations of the southern portion of this broad anticlinal feature in eastern Utah. Mapping at a scale of 1/250,000 on an enhanced and enlarged S-190B image resulted in a geological map showing correlative mappable features that are indicated on the geological map of Utah at the same scale. An enhanced enlargement of an S-190B color image at a scale of 1/19,200 of the Bingham Porphyry Copper deposit allowed comparison of a geological map of the area with the space imagery map as fair for the intrusion boundaries and total lack of quality for mapping the sediments. Hydrothermal alteration is only slightly evident on space imagery at Bingham but in the Tintic mining district and the volcanic piles of the Keg and Thomas ranges, Utah, hydrothermal alteration is readily mapped on color enlargements of S-190B (SL-3, T3-3N Tr-2). A mercury soil-gas analyzer was developed for locating hidden mineralized zones which were suggested from space imagery.

  8. Using LANDSAT imagery as a basis for the understanding of the physiographic regions of the United States

    NASA Technical Reports Server (NTRS)

    Blair, R. W., Jr.

    1981-01-01

    An undergraduate level course in regional geology is described in which map exercises using LANDSAT composite images are required. From these exercises, students lean to appreciate LANDSAT imagery, learn elementary skills in imagery reading and interpretation, in addition to making the association of geography, geology, maps, and imagery.

  9. Satellite Imagery Production and Processing Using Apache Hadoop

    NASA Astrophysics Data System (ADS)

    Hill, D. V.; Werpy, J.

    2011-12-01

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

  10. Combining DEM parameters with Landsat MSS and TM imagery in a GIS for mountain glacier characterization

    NASA Astrophysics Data System (ADS)

    Gratton, Denis J.; Howarth, Philip J.; Marceau, Danielle J.

    1990-07-01

    The building of a glaciological database is explored as an answer to the management of multisource and multiscale information required for the study of mountain glacier variations. Topographic information is derived from the 1:250,000 scale digital elevation model (DEM) of the Surveys and Mapping Branch of Energy, Mines and Resources, Canada. The interfacing of a geographic information system (GIS) and an image-analysis system (IAS) permits the inclusion of ancillary glaciological information in the automated sampling of training and test data for multispectral classification of Landsat MSS and TM imagery. The combination of visually and automatically classified covers increases the classification accuracy of MSS and TM data by 24 percent and 13 percent, respectively. Slope and aspect coverages are extracted from the raster DEM. The integration of satellite image classifications and DEM features in SPANS permits the subdivision of glacier basin covers into physiographic units. An example is presented for the ablation zone covers of the Columbia Icefield.

  11. Investigation of Satellite Imagery for Regional Planning

    NASA Technical Reports Server (NTRS)

    Harting, W. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. Satellite multispectral imagery was found to be useful in regional planning for depicting general developed land patterns, wooded areas, and newly constructed highways by using visual photointerpretation methods. Other characteristics, such as residential and nonresidential development, street patterns, development density, and some vacant land components cannot be adequately detected using these standard methods.

  12. A Commercial Architecture for Satellite Imagery

    DTIC Science & Technology

    2006-09-01

    amount of risk as well as production time. A constellation of commercial satellites that are reconstituted on a monthly or quarterly cycle could also...potential limitations with geolocation accuracy and data rate downlink transmission capability. This thesis evaluates constellation design factors...a commercial system would be able to fulfill national imagery collection requirements. Eight different constellation types were created, ranging

  13. Overall evaluation of LANDSAT (ERTS) follow on imagery for cartographic application

    NASA Technical Reports Server (NTRS)

    Colvocoresses, A. P. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. LANDSAT imagery can be operationally applied to the revision of nautical charts. The imagery depicts shallow seas in a form that permits accurate planimetric image mapping of features to 20 meters of depth where the conditions of water clarity and bottom reflection are suitable. LANDSAT data also provide an excellent simulation of the earth's surface, for such applications as aeronautical charting and radar image correlation in aircraft and aircraft simulators. Radiometric enhancement, particularly edge enhancement, a technique only marginally successful with aerial photographs has proved to be high value when applied to LANDSAT data.

  14. Satellite Imagery Via Personal Computer

    NASA Technical Reports Server (NTRS)

    1989-01-01

    Automatic Picture Transmission (APT) was incorporated by NASA in the Tiros 8 weather satellite. APT included an advanced satellite camera that immediately transmitted a picture as well as low cost receiving equipment. When an advanced scanning radiometer was later introduced, ground station display equipment would not readily adjust to the new format until GSFC developed an APT Digital Scan Converter that made them compatible. A NASA Technical Note by Goddard's Vermillion and Kamoski described how to build a converter. In 1979, Electro-Services, using this technology, built the first microcomputer weather imaging system in the U.S. The company changed its name to Satellite Data Systems, Inc. and now manufactures the WeatherFax facsimile display graphics system which converts a personal computer into a weather satellite image acquisition and display workstation. Hardware, antennas, receivers, etc. are also offered. Customers include U.S. Weather Service, schools, military, etc.

  15. APPLICATION OF MULTI-DATE LANDSAT 5 TIM IMAGERY FOR WETLAND IDENTIFICATION

    EPA Science Inventory

    Multi-temporal Landsat 5 Thematic Mapper (TM) imagery was evaluated for the identification and monitoring of potential jurisdictional wetlands located in the states of Maryland and Delaware. A wetland map prepared from single-date TM imagery was compared to a hybrid map develope...

  16. APPLICATION OF MULTI-DATE LANDSAT 5 TIM IMAGERY FOR WETLAND IDENTIFICATION

    EPA Science Inventory

    Multi-temporal Landsat 5 Thematic Mapper (TM) imagery was evaluated for the identification and monitoring of potential jurisdictional wetlands located in the states of Maryland and Delaware. A wetland map prepared from single-date TM imagery was compared to a hybrid map develope...

  17. Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts

    NASA Technical Reports Server (NTRS)

    Hilbert, Kent; Pagnutti, Mary; Ryan, Robert; Zanoni, Vicki

    2002-01-01

    This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (<30-m ground sampling distance (GSD)). Previously published literature indicated that areas with the African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (<5-m GSD) IKONOS multispectral data collected over sites in Libya and Mali. Fine-resolution imagery over a Libyan site exhibited less than 1 percent nonuniformity. The research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

  18. LANDSAT imagery analysis: An aid for predicting landslide prone areas for highway construction. [in Arkansas

    NASA Technical Reports Server (NTRS)

    Macdonald, H. C.; Grubbs, R. S.

    1975-01-01

    The most obvious landform features of geologic significance revealed on LANDSAT imagery are linear trends or lineaments. These trends were found to correspond, at least to a large degree, with unmapped faults or complex fracture zones. LANDSAT imagery analysis in northern Arkansas revealed a lineament complex which provides a remarkable correlation with landslide-prone areas along major highway routes. The weathering properties of various rock types, which are considered in designing stable cut slopes and drainage structures, appear to be adversely influenced by the location and trends of LANDSAT defined lineaments. Geologic interpretation of LANDSAT imagery, where applicable and utilized effectively, provides the highway engineer with a tool for predicting and evaluating landslide-prone areas.

  19. Vertical eddy diffusion coefficient from the LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Viswanadham, Y. (Principal Investigator); Torsani, J. A.

    1982-01-01

    Analysis of five stable cases of the smoke plumes that originated in eastern Cabo Frio (22 deg 59'S; 42 deg 02'W), Brazil using LANDSAT imagery is presented for different months and years. From these images the lateral standard deviation (sigma sub y) and the lateral eddy diffusion coefficient (K sub y) are obtained from the formula based on Taylor's theory of diffusion by continuous moment. The rate of kinetic energy dissipation (e) is evaluated from the diffusion parameters sigma sub y and K sub y. Then, the vertical diffusion coefficient (K sub z) is estimated using Weinstock's formulation. These results agree well with the previous experimental values obtained over water surfaces by various workers. Values of e and K sub z show the weaker mixing processes in the marine stable boundary layer. The data sample is apparently to small to include representative active turbulent regions because such regions are so intermittent in time and in space. These results form a data base for use in the development and validation of mesoscale atmospheric diffusion models.

  20. Comparing Landsat-7 ETM+ and ASTER Imageries to Estimate Daily Evapotranspiration Within a Mediterranean Vineyard Watershed

    NASA Technical Reports Server (NTRS)

    Montes, Carlo; Jacob, Frederic

    2017-01-01

    We compared the capabilities of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imageries for mapping daily evapotranspiration (ET) within a Mediterranean vineyard watershed. We used Landsat and ASTER data simultaneously collected on four dates in 2007 and 2008, along with the simplified surface energy balance index (S-SEBI) model. We used previously ground-validated good quality ASTER estimates as reference, and we analyzed the differences with Landsat retrievals in light of the instrumental factors and methodology. Although Landsat and ASTER retrievals of S-SEBI inputs were different, estimates of daily ET from the two imageries were similar. This is ascribed to the S-SEBI spatial differencing in temperature, and opens the path for using historical Landsat time series over vineyards.

  1. Feasibility Study of LANDSAT-8 Imagery for Retrieving Sea Surface Temperature (case Study Persian Gulf)

    NASA Astrophysics Data System (ADS)

    Bayat, F.; Hasanlou, M.

    2016-06-01

    Sea surface temperature (SST) is one of the critical parameters in marine meteorology and oceanography. The SST datasets are incorporated as conditions for ocean and atmosphere models. The SST needs to be investigated for various scientific phenomenon such as salinity, potential fishing zone, sea level rise, upwelling, eddies, cyclone predictions. On the other hands, high spatial resolution SST maps can illustrate eddies and sea surface currents. Also, near real time producing of SST map is suitable for weather forecasting and fishery applications. Therefore satellite remote sensing with wide coverage of data acquisition capability can use as real time tools for producing SST dataset. Satellite sensor such as AVHRR, MODIS and SeaWIFS are capable of extracting brightness values at different thermal spectral bands. These brightness temperatures are the sole input for the SST retrieval algorithms. Recently, Landsat-8 successfully launched and accessible with two instruments on-board: (1) the Operational Land Imager (OLI) with nine spectral bands in the visual, near infrared, and the shortwave infrared spectral regions; and (2) the Thermal Infrared Sensor (TIRS) with two spectral bands in the long wavelength infrared. The two TIRS bands were selected to enable the atmospheric correction of the thermal data using a split window algorithm (SWA). The TIRS instrument is one of the major payloads aboard this satellite which can observe the sea surface by using the split-window thermal infrared channels (CH10: 10.6 μm to 11.2 μm; CH11: 11.5 μm to 12.5 μm) at a resolution of 30 m. The TIRS sensors have three main advantages comparing with other previous sensors. First, the TIRS has two thermal bands in the atmospheric window that provide a new SST retrieval opportunity using the widely used split-window (SW) algorithm rather than the single channel method. Second, the spectral filters of TIRS two bands present narrower bandwidth than that of the thermal band on board on

  2. Application of multispectral radar and LANDSAT imagery to geologic mapping in death valley

    NASA Technical Reports Server (NTRS)

    Daily, M.; Elachi, C.; Farr, T.; Stromberg, W.; Williams, S.; Schaber, G.

    1978-01-01

    Side-Looking Airborne Radar (SLAR) images, acquired by JPL and Strategic Air Command Systems, and visible and near-infrared LANDSAT imagery were applied to studies of the Quaternary alluvial and evaporite deposits in Death Valley, California. Unprocessed radar imagery revealed considerable variation in microwave backscatter, generally correlated with surface roughness. For Death Valley, LANDSAT imagery is of limited value in discriminating the Quaternary units except for alluvial units distinguishable by presence or absence of desert varnish or evaporite units whose extremely rough surfaces are strongly shadowed. In contrast, radar returns are most strongly dependent on surface roughness, a property more strongly correlated with surficial geology than is surface chemistry.

  3. Net primary productivity of forest stands in New Hampshire estimated from Landsat and MODIS satellite data

    PubMed Central

    Potter, Christopher; Gross, Peggy; Genovese, Vanessa; Smith, Marie-Louise

    2007-01-01

    Background A simulation model that relies on satellite observations of vegetation cover from the Landsat 7 sensor and from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate net primary productivity (NPP) of forest stands at the Bartlett Experiment Forest (BEF) in the White Mountains of New Hampshire. Results Net primary production (NPP) predicted from the NASA-CASA model using 30-meter resolution Landsat inputs showed variations related to both vegetation cover type and elevational effects on mean air temperatures. Overall, the highest predicted NPP from the NASA-CASA model was for deciduous forest cover at low to mid-elevation locations over the landscape. Comparison of the model-predicted annual NPP to the plot-estimated values showed a significant correlation of R2 = 0.5. Stepwise addition of 30-meter resolution elevation data values explained no more than 20% of the residual variation in measured NPP patterns at BEF. Both the Landsat 7 and the 250-meter resolution MODIS derived mean annual NPP predictions for the BEF plot locations were within ± 2.5% of the mean of plot estimates for annual NPP. Conclusion Although MODIS imagery cannot capture the spatial details of NPP across the network of closely spaced plot locations as well as Landsat, the MODIS satellite data as inputs to the NASA-CASA model does accurately predict the average annual productivity of a site like the BEF. PMID:17941989

  4. Net primary productivity of forest stands in New Hampshire estimated from Landsat and MODIS satellite data.

    PubMed

    Potter, Christopher; Gross, Peggy; Genovese, Vanessa; Smith, Marie-Louise

    2007-10-17

    A simulation model that relies on satellite observations of vegetation cover from the Landsat 7 sensor and from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate net primary productivity (NPP) of forest stands at the Bartlett Experiment Forest (BEF) in the White Mountains of New Hampshire. Net primary production (NPP) predicted from the NASA-CASA model using 30-meter resolution Landsat inputs showed variations related to both vegetation cover type and elevational effects on mean air temperatures. Overall, the highest predicted NPP from the NASA-CASA model was for deciduous forest cover at low to mid-elevation locations over the landscape. Comparison of the model-predicted annual NPP to the plot-estimated values showed a significant correlation of R2 = 0.5. Stepwise addition of 30-meter resolution elevation data values explained no more than 20% of the residual variation in measured NPP patterns at BEF. Both the Landsat 7 and the 250-meter resolution MODIS derived mean annual NPP predictions for the BEF plot locations were within +/- 2.5% of the mean of plot estimates for annual NPP. Although MODIS imagery cannot capture the spatial details of NPP across the network of closely spaced plot locations as well as Landsat, the MODIS satellite data as inputs to the NASA-CASA model does accurately predict the average annual productivity of a site like the BEF.

  5. Eulusmap: An international land resources map utilizing satellite imagery

    NASA Technical Reports Server (NTRS)

    Paludan, T.; Csati, E.

    1978-01-01

    In 1972, the International Geographical Union's Commission on World Land Use Survey adopted a project for a land-use map of Europe. Such a map, under the name Eulusmap was started earlier under sponsorship of several government offices in Hungary. Although there was great response from a number of contributors in many countries, it became evident by mid-1974 that the map would contain gaps and some inaccuracies unless additional data sources were utilized. By then, the satellite Landsat-1 had obtained imagery of most of Europe. Using theme extraction techniques, the map was completed in draft form and portions of it displayed at the 23d International Geographical Congress in Moscow during July 1976. Printing of the completed map was accomplished in May 1978.

  6. Landsat imagery evidences great recent land cover changes induced by wild fires in central Siberia*

    NASA Astrophysics Data System (ADS)

    Antamoshkina, O. A.; Trofimova, N. V.; Antamoshkin, O. A.

    2016-04-01

    The article discusses the methods of satellite image classification to determine general types of forest ecosystems, as well as the long-term monitoring of ecosystems changes using satellite imagery of medium spatial resolution and the daily data of space monitoring of active fires. The area of interest of this work is 100 km footprint of the Zotino Tall Tower Observatory (ZOTTO), located near the Zotino settlement, Krasnoyarsk region. The study area is located in the middle taiga subzone of Western Siberia, are presented by the left and right banks of the Yenisei river. For Landsat satellite imagery supervised classification by the maximum likelihood method was made using ground-based studies over the last fifteen years. The results are the identification of the 10 aggregated classes of land surface and composition of the study area thematic map. Operational satellite monitoring and analysis of spatial information about ecosystem in the 100-kilometer footprint of the ZOTTO tall tower allows to monitor the dynamics of forest disturbance by fire and logging over a long time period and to estimate changes in forest ecosystems of the study area. Data on the number and area of fires detected in the study region for the 2000-2014 received in the work. Calculations show that active fires have burned more than a quarter of the footprint area over the study period. Fires have a significant impact on the redistribution of classes of land surface. Area of all types of vegetation ecosystems declined dramatically under the influence of fires, whereas industrial logging does not impact seriously on it. The results obtained in our work indicate the highest occurrence of fires for lichen forest types within study region, probably due to their high natural fire danger, which is consistent with other studies. The least damage the fire caused to the wetland ecosystem due to high content of moisture and the presence of a large number of fire breaks in the form of open water.

  7. LANDSAT language at our reach. First Swedish satellite. Civilization detectors

    NASA Technical Reports Server (NTRS)

    Wayne, D. L.; Bravo, V.

    1981-01-01

    Information on the use of LANDSAT data by Argentina is presented. Details on a Swedish satellite to be completed in 1984 and to be called VIKING are reported. Attempts to contact other civilizations in space by the use of radiotelescopes are discussed.

  8. Mapping Glacial Lakes on the Tibetan Plateau with Landsat TM/ETM+ Imagery

    NASA Astrophysics Data System (ADS)

    Li, J.; Sheng, Y.

    2009-12-01

    With a pronounced temperature rise of 0.16oC per decade, the Tibetan plateau is one of the world’s most vulnerable areas responding to global change. Glaciers and glacial lakes serve as sensitive indicators to these regional climate and water cycle variations. Recent study shows that glaciers on the plateau have retreated dramatically, leading to the expansion of the existing glacial lakes and the emergence ofnew glacial lakes. The existence of these lakes increases the possibility of outburst floods to the downstream areas during the ice melting season. Mapping and monitoring these glacial lakes will facilitate our understanding of the glacier-related hazards and regional climate changes. However, rigorous field surveys of glacial lake dynamics are prohibitive in high-mountainous areas on the plateau due to their low accessibility. Satellite remote sensing provides an efficient and objective tool to analyze the status and variations of glacial lakes. Theoretically, lakes and other surface open water bodies are readily identified in satellite images owing to their very low reflectance in near-infrared (NIR) channels of Landsat sensors. In the mountain regions where glacial lakes are located, cloud shadows, mountain shadows, melting glaciers or even lakes under different conditions (e.g., ice lakes, salt lakes, turbid lakes) could become disturbing factors and create problems to glacial lake delineation. We use normalized difference water index (NDWI), the normalized ratio index between the green and near infrared spectral bands, to differentiate water bodies from other land features. As lake features are on the relatively flat areas, topographic features such as terrain slope and hill shades derived from digital elevation model (DEM) are also used to remove the shadows from lakes. Based on NDWI and topographic characteristics, We have developed an automated hierarchical method to monitor glacial lakes using Landsat TM/ETM+ imagery. Firstly, lakes are roughly

  9. Ecological site classification of semiarid rangelands: Synergistic use of Landsat and Hyperion imagery

    NASA Astrophysics Data System (ADS)

    Blanco, Paula D.; del Valle, Héctor F.; Bouza, Pablo J.; Metternicht, Graciela I.; Hardtke, Leonardo A.

    2014-06-01

    Ecological sites are the basic entity used in rangeland health assessment. This study evaluates the synergistic use of multi- and hyper-spectral satellite imagery for sub-pixel classification of ecological sites in semiarid rangelands. Hyperion and Landsat enhanced thematic mapper (ETM) data are included in a two-step procedure to mapping ecological sites in Patagonian rangelands of Argentina. Firstly, mixture tuned matched filtering and logistic regression analyses are used for Hyperion data processing to obtain ecological site probability images in the area covered by hyperspectral imagery. Secondly, artificial neural networks are applied to model the relationships between the spectral response patterns of Landsat and the probability images from Hyperion, and used to map ecological sites over the entire study area. Overall classification accuracy was 81% (kappa = 0.77) with relatively high accuracies for all ecological sites demonstrating that their spectral signatures are sufficiently distinct to be detectable. Better accuracies were obtained for shrub steppes with desert pavement (producer's and user's accuracies of 89% and 84%, respectively), and shrub-grass steppes associated to tertiary calcareous outcrops (producer's and user's accuracies of 100% and 86%, respectively), while poorer accuracies resulted for shrub-grass steppes on old alluvial plains (producer's and user's accuracies of 75% and 56%, respectively). Fuzzy maps of ecological sites as presented in this research can provide rangeland managers with a tool to stratify the landscape and organize ecological information for rangeland health assessment and monitoring, prioritizing and selecting appropriate management actions, and promoting the recovery of areas degraded in these environments.

  10. Postfire regrowth trajectories of chamise chaparral based on multi-temporal Landsat imagery

    NASA Astrophysics Data System (ADS)

    Storey, Emanual A.

    Assessments of postfire recovery outcomes for the chamise chaparral shrublands of southern California provide a basis for land managers and ecologists to identify long-term changes in this sensitive ecosystem. Postfire vegetation recovery assessments based on fieldplot vegetation sampling and aerial image analysis have proven to be limited in coverage and inefficient for large areas of this landscape type. This study evaluates the potential of remotely sensed regrowth trajectories based on multi-temporal Landsat 4, 5, 7, and 8 satellite image observations for the postfire recovery assessment of chamise. Methods included: 1) an a priori determination of postfire shrub fractional cover changes based on multi-date high spatial resolution orthoimagery, 2) statistical testing to assess the sensitivity of regrowth trajectories based on several spectral vegetation indices and applied metrics to the recovery outcomes, and 3) an examination of regrowth trajectories which extend 19-29 years postfire relative to field-based measurements from other studies. Results provide a basis for interpretations about the sensitivities of the postfire regrowth trajectories derived from Landsat surface reflectance data to changes in the shrub matrix at various spatial and temporal scales. A primary finding was that several measures, including the Regeneration Index and another proposed here which is termed the Scaled Recovery Metric, enhanced the signals of postfire recovery derived from the multi-temporal trajectories and increased their comparability. Findings indicate that several of the spectral vegetation indices (NDVI, NDMI, NBR, and NBR2) were sensitive to long-term postfire changes in chamise, and that these same indices were statistically significant indicators of postfire recovery outcomes when certain metrics were applied. This study provides an overview of some advantages, limitations, and technical considerations of deriving postfire regrowth trajectories from Landsat imagery

  11. Recommended satellite imagery capabilities for disaster management

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  12. Recommended satellite imagery capabilities for disaster management

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  14. Impervious Surface Area Mapping using Landsat Imagery: Applications to Hydrology and Land Use Change Monitoring

    NASA Astrophysics Data System (ADS)

    Smith, A.; Goetz, S. J.; Mazzacato, M. E.; Jantz, C.; Wright, R.

    2002-12-01

    Impervious surfaces include rooftops, roads, parking lots and other areas that are impermeable to moisture. As the amount of built environment around urban areas has increased, it has been widely recognized that more impervious surface area (ISA) results in greater volume and intensity of stream flow, which can degrade stream health and require expensive modifications to flood control structures. Other effects include increased urban "heat island" influences and changes in local weather. If impervious areas could be accurately mapped using satellite imagery, it would provide valuable input to many applications, from hydrologic modeling to land use planning. We have developed a method to map subpixel ISA with Landsat Thematic Mapper (TM) imagery and classification - regression tree algorithms. This approach provides highly accurate (90+ percent) maps of ISA, but also permits estimation of the proportion of each cell occupied by impervious materials (between 0-100 percent). We report on a recently completed a map of ISA for the entire 163,000 km2 Chesapeake Bay watershed, a region of highly altered land cover and rapid land use change. We also report on the mapping of change patterns, indicated by ISA changes between 1986 - 2001, in an 18,000 km2 area centered on Baltimore - Washington, D.C. We review the methods, issues, technical challenges, results, accuracy, and advantages of this approach, and provide an overview of various applications for which the products are currently being used.

  15. Results of agroclimatological studies using multiple satellite sensors like NOAA AVHRR; GMS IR and LANDSAT MSS and TM

    NASA Astrophysics Data System (ADS)

    Choudhury, A. M.

    1992-07-01

    Bangladesh Space Research and Remote Sensing Organization (SPARRSO) routinely receives NOAA and GMS imagery and uses them in agrometeorological monitoring, it also uses LANDSAT MSS and TM data for this purpose. Analysis of multiple satellite sensor data shows advantages for high resolution sensors. However, in the ease of crop monitoring, a good correlation has been obtained between results obtained with NOAA AVHRR and LANDSAT MSS for vegetation index. Crop estimation has been made using all kinds of sensors and it has been found that higher resolution data always give more accurate results. Permanent address : Space Research and Remote Sensing Organization (SPARRSO), Mohakash Biggyan Bhaban, G.P.O. Box No. 529, Dhaka, Bangladesh.

  16. Satellite technology. [Landsat 1 and ITOS

    NASA Technical Reports Server (NTRS)

    Branchflower, G. A.

    1974-01-01

    An exposure to satellite design and fabrication techniques used in unmanned satellite programs is provided. Spacecraft configurations of the earth resources technology satellite (ERTS) and the improved ITOS operational satellite, which are typical of the construction and layout techniques presently in use, are discussed. Support and service subsystems are described taking the ERTS subsystems as representative. The subsystems explained comprise: power, attitude control, orbit adjustment, wideband telemetry, tracking-telemetry-command, auxiliary processing, electrical integration, and spaceborne recording devices. A number of photographs, renditions and diagrams illustrates the text.

  17. Mapping of Landsat satellite and gravity lineaments in west Tennessee

    NASA Technical Reports Server (NTRS)

    Argialas, Demetre P.; Stearns, Richard G.; Shahrokhi, Firouz

    1988-01-01

    The analysis of earthquake fault lineament patterns within the alluvial valley of west Tennessee, which is often made difficult by the presence of unconsolidated sediments, is presently undertaken through a synergistic use of Landsat satellite images in conjunction with gravity anomaly data, which were quantitatively analyzed and compared by means of two-dimensional histograms and rose diagrams. The northeastern trend revealed for the lineaments corresponds to faults and is in keeping with reactivation of the Reelfoot rift near the Mississippi River; this suggests that deeper features, perhaps at earthquake focal depth, may extend to the land surface as Landsat-detectable lineaments.

  18. Mapping of Landsat satellite and gravity lineaments in west Tennessee

    NASA Technical Reports Server (NTRS)

    Argialas, Demetre P.; Stearns, Richard G.; Shahrokhi, Firouz

    1988-01-01

    The analysis of earthquake fault lineament patterns within the alluvial valley of west Tennessee, which is often made difficult by the presence of unconsolidated sediments, is presently undertaken through a synergistic use of Landsat satellite images in conjunction with gravity anomaly data, which were quantitatively analyzed and compared by means of two-dimensional histograms and rose diagrams. The northeastern trend revealed for the lineaments corresponds to faults and is in keeping with reactivation of the Reelfoot rift near the Mississippi River; this suggests that deeper features, perhaps at earthquake focal depth, may extend to the land surface as Landsat-detectable lineaments.

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

    Treesearch

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

    2002-01-01

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

  20. A study of atmospheric diffusion from the LANDSAT imagery. [pollution transport over the ocean

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Viswanadham, Y.; Torsani, J. A.

    1981-01-01

    LANDSAT multispectral scanner data of the smoke plumes which originated in eastern Cabo Frio, Brazil and crossed over into the Atlantic Ocean, are analyzed to illustrate how high resolution LANDSAT imagery can aid meteorologists in evaluating specific air pollution events. The eleven LANDSAT images selected are for different months and years. The results show that diffusion is governed primarily by water and air temperature differences. With colder water, low level air is very stable and the vertical diffusion is minimal; but water warmer than the air induces vigorous diffusion. The applicability of three empirical methods for determining the horizontal eddy diffusivity coefficient in the Gaussian plume formula was evaluated with the estimated standard deviation of the crosswind distribution of material in the plume from the LANDSAT imagery. The vertical diffusion coefficient in stable conditions is estimated using Weinstock's formulation. These results form a data base for use in the development and validation of meso scale atmospheric diffusion models.

  1. Diazo processing of LANDSAT imagery: A low-cost instructional technique

    NASA Technical Reports Server (NTRS)

    Lusch, D. P.

    1981-01-01

    Diazo processing of LANDSAT imagery is a relatively simple and cost effective method of producing enhanced renditions of the visual LANDSAT products. This technique is capable of producing a variety of image enhancements which have value in a teaching laboratory environment. Additionally, with the appropriate equipment, applications research which relys on accurate and repeatable results is possible. Exposure and development equipment options, diazo materials, and enhancement routines are discussed.

  2. Mapping fire scars in a southern African savannah using Landsat imagery

    Treesearch

    A. T. Hudak; B. H. Brockett

    2004-01-01

    The spectral, spatial and temporal characteristics of the Landsat data record make it appropriate for mapping fire scars. Twenty-two annual fire scar maps from 1972-­2002 were produced from historical Landsat imagery for a semi-arid savannah landscape on the South Africa-­Botswana border, centred over Madikwe Game Reserve (MGR) in South Africa. A principal components...

  3. Application of Landsat imagery to regional-scale assessments of lake clarity.

    PubMed

    Kloiber, Steven M; Brezonik, Patrick L; Bauer, Marvin E

    2002-10-01

    A procedure that uses Landsat imagery to estimate Secchi disk transparency (SDT) of lakes was developed and applied to approximately 500 lakes with surface areas > 10 ha in the seven-county metropolitan area of Minneapolis and St. Paul, MN, USA, to assess spatial patterns and temporal trends in lake clarity. Thirteen Landsat MSS and TM images over the period 1973-1998 were used for the analysis. Satellite brightness values from lake surfaces were calibrated against available historical data on SDT (n = approximately 20-40) measured nearly contemporaneously with the acquisition date of each image. Calibration regression equations for the late-summer TM images had a range of r2 from 0.72 to 0.93. Regression analysis for three late-summer MSS images yielded r2 values ranging from 0.60 to 0.79. Results indicate that a single late-summer image yields a reliable estimate of regional lake clarity and reasonably accurate estimates of SDT for individual lakes. An analysis of seasonal patterns on a large lake water-quality database was used to develop a model that adjusts synoptic satellite SDT estimates from different dates to a common reference, making them more comparable from year-to-year. Analysis of long-term trends shows that in spite of the large land-use changes within the region over the study period, only 49 (about 10%) of assessed lakes in the region showed significant temporal trends in SDT over the period, and more lakes had increasing SDT (34) than decreasing SDT (15).

  4. Cumulus cloud properties derived using Landsat satellite data

    NASA Technical Reports Server (NTRS)

    Wielicki, B. A.; Welch, R. M.

    1986-01-01

    Landsat Multispectral Scanner (MSS) digital data are used to remotely sense cumulus cloud properties such as cloud fraction and cloud reflectance, along with the distribution of cloud number and cloud fraction as a function of cloud size. The analysis is carried out for four cumulus fields covering regions approximately 150 km square. Results for these initial cloud fields indicate that: (1) the common intuitive model of clouds as nearly uniform reflecting surfaces is a poor representation of cumulus clouds, (2) the cumulus clouds were often multicelled, even for clouds as small as 1 km in diameter, (3) cloud fractional coverage derived using a simple reflectance threshold is sensitive to the chosen threshold even for 57-meter resolution Landsat data, (4) the sensitivity of cloud fraction to changes in satellite sensor resolution is less sensitive than suggested theoretically, and (5) the Landsat derived cloud size distributions show encouraging similarities among the cloud fields examined.

  5. US Standard Catalog no. U-20. [LANDSAT imagery for April 1974

    NASA Technical Reports Server (NTRS)

    1974-01-01

    Information regarding the availability of LANDSAT imagery processed and input to the data files by the NASA Data Processing Facility is published on a monthly basis. The U.S. Standard Catalog includes imagery covering the continental United States, Alaska and Hawaii. The Non-U.S. Standard Catalog identifies all the remaining coverage. Sections 1 and 2 describe the contents and format for the catalogs and the associated microfilm. Section 3 provides a cross-reference defining the beginning and ending dates for LANDSAT cycles.

  6. Monitoring land degradation in southern Tunisia: A test of LANDSAT imagery and digital data

    NASA Technical Reports Server (NTRS)

    Hellden, U.; Stern, M.

    1980-01-01

    The possible use of LANDSAT imagery and digital data for monitoring desertification indicators in Tunisia was studied. Field data were sampled in Tunisia for estimation of mapping accuracy in maps generated through interpretation of LANDSAT false color composites and processing of LANDSAT computer compatible tapes respectively. Temporal change studies were carried out through geometric registration of computer classified windows from 1972 to classified data from 1979. Indications on land degradation were noted in some areas. No important differences, concerning results, between the interpretation approach and the computer processing approach were found.

  7. EOS-WEBSTER - Providing Satellite Imagery for Everyone

    NASA Astrophysics Data System (ADS)

    Schloss, A. L.; Moore, B.; Braswell, R.; Hurtt, G.; Armstrong, W.; Blaha, D.; Carmell, T.; Freuder, R.; Routhier, M.; Spencer, S.

    2002-12-01

    The University of New Hampshire's WEB-based System for Terrestrial Ecosystem Research (EOS-WEBSTER) distributes a special collection of data and imagery products for the Earth Science community. This collection includes satellite imagery from several sensors including the MODIS instrument aboard TERRA. Our services have been designed so that different types of users can access and use only the data that they want. Users can search EOS-WEBSTER's collections, create spatial and temporal subsets, and order data in ASCII or binary formats. We have developed a suite of MODIS products covering Amazonia. These products serve the Large Scale Biosphere-Atmosphere Project in Amazonia (LBA), a joint project of the Brazilian government and NASA. Products include 8-day reflectances (MOD09A1), daily fire potential (MOD14A1), and 16-day NDVIs (MOD13Q1), starting in January 2001. EOS-WEBSTER takes care of obtaining the 14 MODIS tiles that cover Amazonia and stitching them together into a seamless regional coverage. Users can cookie-cut the regional data into smaller areas of interest, such as a field site, a political boundary, or a watershed, then choose an output format such as GrADS and retrieve their order by ftp or on CD-ROM. EOS-WEBSTER delivers MODIS to users whether or not they can manipulate the HDF-EOS format. These regional data sets were developed in cooperation with Eros Data Center to facilitate use of MODIS products by the LBA community. Other products and regions can be developed for other user communities if there is enough interest. Please contact us at support@eos-webster.sr.unh.edu for more information. MODIS is only one of a variety of imagery products available from EOS-WEBSTER. Other platforms include Landsat, SPOT-VEGETATION and IKONOS. We provide Landsat imagery data access to educators by supporting the Forest Watch program, an educational project that includes K-12 teachers and students in UNH research activities that assess the state-of-health of local

  8. Peatland classification of West Siberia based on Landsat imagery

    NASA Astrophysics Data System (ADS)

    Terentieva, I.; Glagolev, M.; Lapshina, E.; Maksyutov, S. S.

    2014-12-01

    Increasing interest in peatlands for prediction of environmental changes requires an understanding of its geographical distribution. West Siberia Plain is the biggest peatland area in Eurasia and is situated in the high latitudes experiencing enhanced rate of climate change. West Siberian taiga mires are important globally, accounting for about 12.5% of the global wetland area. A number of peatland maps of the West Siberia was developed in 1970s, but their accuracy is limited. Here we report the effort in mapping West Siberian peatlands using 30 m resolution Landsat imagery. As a first step, peatland classification scheme oriented on environmental parameter upscaling was developed. The overall workflow involves data pre-processing, training data collection, image classification on a scene-by-scene basis, regrouping of the derived classes into final peatland types and accuracy assessment. To avoid misclassification peatlands were distinguished from other landscapes using threshold method: for each scene, Green-Red Vegetation Indices was used for peatland masking and 5th channel was used for masking water bodies. Peatland image masks were made in Quantum GIS, filtered in MATLAB and then classified in Multispec (Purdue Research Foundation) using maximum likelihood algorithm of supervised classification method. Training sample selection was mostly based on spectral signatures due to limited ancillary and high-resolution image data. As an additional source of information, we applied our field knowledge resulting from more than 10 years of fieldwork in West Siberia summarized in an extensive dataset of botanical relevés, field photos, pH and electrical conductivity data from 40 test sites. After the classification procedure, discriminated spectral classes were generalized into 12 peatland types. Overall accuracy assessment was based on 439 randomly assigned test sites showing final map accuracy was 80%. Total peatland area was estimated at 73.0 Mha. Various ridge

  9. Detecting biotic and hydrogeochemical processes in large peat basins with Landsat TM imagery

    NASA Technical Reports Server (NTRS)

    Glaser, Paul H.

    1989-01-01

    A survey was made of three large peat basins in boreal North America with Landsat TM imagery and field sampling. False-color composites composed of Bands 2, 3, and 4 are particularly effective in discriminating the major vegetation types and the important hydrogeochemical processes in these peatlands. This imagery indicates that the discharge of alkaline groundwater provides one of the most important regional and local controls on peatland development.

  10. Utilization of LANDSAT imagery for mapping vegetation on the millionth scale

    NASA Technical Reports Server (NTRS)

    Williams, D. L.; Coiner, J. C.

    1977-01-01

    To determine if the information content of the imagery is sufficient to permit mapping according to the Unesco classification, a series of test sites were examined. These sites include examples from the humid tropics, arid, and semi-arid subtropics and temperature zones. In every case, the feasibility of this application of LANDSAT imagery was verified. The agricultural significance of several sites is discussed to indicate how the vegetation maps may be interpreted for agricultural evaluation.

  11. 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.

  12. 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

  13. Monitoring flood damage with satellite imagery

    NASA Technical Reports Server (NTRS)

    Benson, L. A.; Waltz, F. A.

    1973-01-01

    During analysis of ERTS-1 imagery for land use patterns a large impoundment of water was observed in a location that was normally farmland. Subsequent investigation revealed that the satellite had recorded the remaining floodwaters from a severe local rainstorm that had occurred four days prior to the overpass. The inundated area was measured using the automatic planimeter associated with the signal analysis and dissemination equipment located at the Remote Sensing Institute. The area measurement coupled with estimates of the land use and productivity of the region permitted an estimate of the crop damage loss for the inundated area.

  14. Automated mesoscale winds determined from satellite imagery

    NASA Technical Reports Server (NTRS)

    1987-01-01

    A new automated technique for extracting mesoscale fields from GOES visible/infrared satellite imagery was developed. Quality control parameters were defined to allow objective editing of the wind fields. The system can produce equivalent or superior cloud wind estimates compared to the time consuming manual methods used on various interactive meteorological processing systems. Analysis of automated mesoscale cloud wind for a test case yields an estimated random error value one meter per second and produces both regional and mesoscale vector wind field structure and divergence patterns that are consistent in time and highly correlated with subsequent severe thunderstorm development.

  15. Fluctuating snow line altitudes in the Hunza basin (Karakoram) using Landsat OLI imagery

    NASA Astrophysics Data System (ADS)

    Racoviteanu, Adina; Rittger, Karl; Brodzik, Mary J.; Painter, Thomas H.; Armstrong, Richard

    2016-04-01

    Snowline altitudes (SLAs) on glacier surfaces are needed for separating snow and ice as input for melt models. When measured at the end of the ablation season, SLAs are used for inferring stable-state glacier equilibrium line altitudes (ELAs). Direct measurements of snowlines are rarely possible particularly in remote, high altitude glacierized terrain, but remote sensing data can be used to separate these snow and ice surfaces. Snow lines are commonly visible on optical satellite images acquired at the end of the ablation season if the images are contrasted enough, and are manually digitized on screen using various satellite band combinations for visual interpretation, which is a time-consuming, subjective process. Here we use Landsat OLI imagery at 30 m resolution to estimate glacier SLAs for a subset of the Hunza basin in the Upper Indus in the Karakoram. Clean glacier ice surfaces are delineated using a standardized semi-automated band ratio algorithm with image segmentation. Within the glacier surface, snow and ice are separated using supervised classification schemes based on regions of interest, and glacier SLAs are extracted on the basis of these areas. SLAs are compared with estimates from a new automated method that relies on fractional snow covered area rather than on band ratio algorithms for delineating clean glacier ice surfaces, and on grain size (instead of supervised classification) for separating snow from glacier ice on the glacier surface. The two methods produce comparable snow/ice outputs. The fSCA-derived glacierized areas are slightly larger than the band ratio estimates. Some of the additional area is the result of better detection in shadows from spectral mixture analysis (true positive) while the rest is shallow water, which is spectrally similar to snow/ice (false positive). On the glacier surface, a thresholding the snow grain size image (grain size > 500μm) results in similar glacier ice areas derived from the supervised

  16. The Combination of Uav Survey and Landsat Imagery for Monitoring of Crop Vigor in Precision Agriculture

    NASA Astrophysics Data System (ADS)

    Lukas, V.; Novák, J.; Neudert, L.; Svobodova, I.; Rodriguez-Moreno, F.; Edrees, M.; Kren, J.

    2016-06-01

    Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as above-ground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of above-ground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 - 0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower

  17. Multiple temporal mosaicing for Landsat satellite images

    NASA Astrophysics Data System (ADS)

    Guo, Yi; Li, Feng; Caccetta, Peter; Devereux, Drew

    2017-01-01

    Cloud removal is a very important preprocessing step when using aerial and spaceborne optical sensors for land surface and cover applications. Methods that have been proposed for identifying cloud-affected pixels range from classification and segmentation type approaches applied to individual images to outlier detection type methods applied to time-series of images. The choice of method is influenced by considerations including the requirements of the application, the image characteristics, and how frequently images over a given area are acquired. When many images are acquired in a period where land surface cover exhibits negligible change, an image formed by compositing from a series of images taken in a relatively short period of time will suffice for further analysis. It is highly desirable to fully automate this compositing process. To this end, we propose the multiple temporal mosaicing (MTM) algorithm. It uses, in the first instance, a cloud score for each pixel in the images to separate/partially separate cloud-affected pixels from noncloud pixels. These cloud scores are then combined with the output from existing cloud identification methods and date preference to determine the likelihood of given pixels being considered as good candidates to be included in the final image. Moreover, the spatial smoothness is incorporated to ensure that the pixels of a small neighborhood are from the same image so that the final image looks smoother. We apply MTM to two Landsat scenes. The resulting images show the effectiveness of this method. The methodology can be applied to images acquired from other sensors.

  18. Perspectives of Maine Forest Cover Change from Landsat Imagery and Forest Inventory Analysis (FIA)

    Treesearch

    Steven Sader; Michael Hoppus; Jacob Metzler; Suming Jin

    2005-01-01

    A forest change detection map was developed to document forest gains and losses during the decade of the 1990s. The effectiveness of the Landsat imagery and methods for detecting Maine forest cover change are indicated by the good accuracy assessment results: forest-no change, forest loss, and forest gain accuracy were 90, 88, and 92% respectively, and the good...

  19. Use of landsat thermal imagery in monitoring evapotranspiration and managing water resources

    USDA-ARS?s Scientific Manuscript database

    Freshwater resources are becoming increasingly limited in many parts of the world, and decision makers are demanding new tools for monitoring water availability and rates of consumption. Remotely sensed thermal-infrared imagery collected by Landsat provides estimates of land-surface temperature tha...

  20. Evaluation of landsat imagery for detecting ice storm damage in upland forests of Eastern Kentucky

    Treesearch

    Henry W. McNab; Tracy Roof; Jeffrey F. Lewis; David L. Loftis

    2007-01-01

    Two categories of forest canopy damage (none to light vs. moderate to heavy) resulting from a 2003 ice storm in eastern Kentucky could be identified on readily available Landsat Thematic Mapper imagery using change detection techniques to evaluate the ratio of spectral bands 4 and 5. Regression analysis was used to evaluate several model formulations based on the...

  1. Landsat Imagery: A Tool for Updating Land Use in Gulf Coast Mexico

    ERIC Educational Resources Information Center

    Harnapp, Vern

    1978-01-01

    Explores the use of Landsat imagery in mapping and updating land use for the purpose of planning. Examines Gulf Coast Mexico as a case study, because modern agricultural techniques used to expand the ranching industry have significantly altered the landscape. (Author/BC)

  2. Using Landsat imagery and FIA data to examine wood supply uncertainty

    Treesearch

    Curtis A. Collins; Ruth C. Seawell

    2009-01-01

    As members of the forest products industry continue to reduce their landholdings, monitoring reliable future timber supplies becomes an increasingly important issue. This issue requires both spatial and forest inventory information to meet the strategic planning needs of these entities. Increased depth in the archival span of imagery available from the Landsat program...

  3. Landsat Imagery: A Tool for Updating Land Use in Gulf Coast Mexico

    ERIC Educational Resources Information Center

    Harnapp, Vern

    1978-01-01

    Explores the use of Landsat imagery in mapping and updating land use for the purpose of planning. Examines Gulf Coast Mexico as a case study, because modern agricultural techniques used to expand the ranching industry have significantly altered the landscape. (Author/BC)

  4. Validation of VIIRS Land Surface Phenology using Field Observations, PhenoCam Imagery, and Landsat data

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Jayavelu, S.; Wang, J.; Henebry, G. M.; Gray, J. M.; Friedl, M. A.; Liu, Y.; Schaaf, C.; Shuai, A.

    2016-12-01

    A large number of land surface phenology (LSP) products have been produced from various detection algorithms applied to coarse resolution satellite datasets across regional to global scales. However, validation of the resulting LSP products is very challenging because in-situ observations at comparable spatiotemporal scales are generally not available. This research focuses on efforts to evaluate and validate the global 500m LSP product produced from Visible Infrared Imaging Radiometer Suite (VIIRS) NBAR time series for 2013 and 2014. Specifically, we used three different datasets to evaluate six VIIRS LSP metrics of greenup onset, mid-point of greenup phase, maturity onset, senescence onset, mid-point of senescence phase, and dormancy onset. First, we obtained the field observations from the USA National Phenology Network that has gathered extensive phenological data on individual species. Although it is inappropriate to compare these data directly with the LSP footprints, this large and spatially distributed dataset allows us to evaluate the overall quality of VIIRS LSP results. Second, we gathered PhenoCam imagery from 164 sites, which was used to extract the daily green chromatic coordinate (GCC) and vegetation contrast index (VCI)values. Utilizing these PhenoCam time series, the phenological events were quantified using a hybrid piecewise logistic models for each site. Third, we detected the phenological timing at the landscape scale (30m) from surface reflectance simulated by fusing MODIS data and Landsat 8 OLI observations in an agricultural area (in the central USA) and from overlap zones of OLI scenes in semiarid areas (California and Tibetan Plateau). The phenological timing from these three datasets was used to compare with VIIRS LSP data. Preliminary results show that the VIIRS LSP are generally comparable with phenological data from the USA-NPN, PhenoCam, and Landsat data, with differences arising in specific phenological events and land cover types.

  5. Satellite Nighttime Imagery Assists in Flossie Track

    NASA Image and Video Library

    2017-09-27

    The enhanced capabilities of the Suomi NPP satellite's day-night band are really becoming clear, as was seen this week when Tropical Storm Flossie was heading toward Hawaii. On Monday, July 29th, the lack of organization of the system made it difficult to understand the storm’s central circulation. Infrared data, though able to provide cloud imagery during the night, is best at measuring cloud-top properties. Flossie, however, had a lower-level circulation that was evident in visible imagery earlier in the day. At nighttime that information was lost using traditional satellite technology, such as GOES West. The day-night-band on Suomi NPP provides visible-like information during nighttime hours when only moonlight is available. When Suomi NPP passed over the storm around 1:00am (local), the day-night band imagery allowed forecasters to identify a center of circulation that was more north than previously estimated. Two passes from Suomi NPP (at 11 and 12z, respectively) are shown here. The spiral of the lower level clouds and center of circulation can be seen northwest of Hawaii, whereas the more detailed and higher cloud top areas are due east of the Big Island. Also visible are the nighttime lights of Honolulu on Oahu, along with other cities throughout the island chain. Credit NASA/NOAA An unlabeled version may be downloaded here: 1.usa.gov/1bOjhN6 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

  6. Mapping the Snow Line Altitude for Large Glacier Samples from Multitemporal Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Rastner, P.; Nicholson, L. I.; Notarnicola, C.; Prinz, R.; Sailer, R.

    2015-12-01

    The cryosphere of mountain regions is fastly changing in response to climate change. This is particularly evident in global-scale glacier retreat. Trends in snow cover, however, are more difficult to determine, as annual fluctuations can be very large. Snow is an important parameter in the energy and mass balance of glaciers and the snow line altitude (SLA) at the end of the melting period can be considered as a proxy for the equilibrium line altitude (ELA). By frequently observing the SLA from satellite, region-wide monitoring of glaciers and improved calibration and validation of transient glacier (mass balance) models is possible. In the near future, frequent mapping of the SLA will be strongly facilitated by satellite missions like Sentinel 2A/B, where the same region will be covered every 5 days with 10 m spatial resolution. For this study we have developed an automated tool to derive the SLA for large glacier samples from remote sensing data. The method is first applied in the Ötztal Alps (Austria) where reliable in-situ data of mass balance and ELA are available for several glaciers over a 30-years period. The algorithm currently works with multi-temporal Landsat imagery (1972-2015), digital glacier outlines and a high-quality national DEM. All input datasets are atmospherically and topographically pre-processed before the SLA is automatically retrieved for each glacier. The remote-sensing derived SLA is generally about 200 m lower than the ELA, however, a clear trend in the altitude of the end of summer snow line is detectable (~ 200 m), which is in agreement with the ELA trend observed in the field. After bias correction and conversion to mass balance, the variability in observed mass balance can be well reproduced from the satellite-derived SLA time series. This is promising for application of the approach in other regions.

  7. Lakes without Landsat? An alternative approach to remote lake monitoring with MODIS 250 m imagery

    USGS Publications Warehouse

    Ian M. McCullough,; Loftin, Cynthia S.; Steven A. Sader,

    2013-01-01

    We evaluated use of MODIS 250 m imagery for remote lake monitoring in Maine. Despite limited spectral resolution (visible red and near infrared bands), the twice daily image capture has a potential advantage over conventionally used, often cloudy Landsat imagery (16 day interval) when short time windows are of interest. We analyzed 364 eligible (≥100 ha) Maine lakes during late summer (Aug–early Sep) 2000–2011. The red band was strongly correlated with natural log-transformed Secchi depth (SD), and the addition of ancillary lake and watershed variables explained some variability in ln(SD) (R2= 0.68–0.85; 9 models). Weak spectral resolution and variable lake conditions limited accurate lake monitoring to relatively productive periods in late summer, as indicated by inconsistent, sometimes weak regressions during June and July when lakes were clearer and less stable (R2 = 0.19–0.74; 8 models). Additionally, SD estimates derived from 2 sets of concurrent MODIS and Landsat imagery generally did not agree unless Landsat imagery (30 m) was resampled to 250 m, likely owing to various factors related to scale. Average MODIS estimates exceeded those of Landsat by 0.35 and 0.49 m on the 2 dates. Overall, MODIS 250 m imagery are potentially useful for remote lake monitoring during productive periods when Landsat data are unavailable; however, analyses must occur when algal communities are stable and well-developed, are biased toward large lakes, may overestimate SD, and accuracy may be unreliable without non-spectral lake predictors.

  8. Lakes without Landsat? An alternative approach to remote lake monitoring with MODIS 250 m imagery

    USGS Publications Warehouse

    Loftin, Cyndy; Ian M. McCullough,; Steven A. Sader,

    2013-01-01

    We evaluated use of MODIS 250 m imagery for remote lake monitoring in Maine. Despite limited spectral resolution (visible red and near infrared bands), the twice daily image capture has a potential advantage over conventionally used, often cloudy Landsat imagery (16 day interval) when short time windows are of interest. We analyzed 364 eligible (≥100 ha) Maine lakes during late summer (Aug–early Sep) 2000–2011. The red band was strongly correlated with natural log-transformed Secchi depth (SD), and the addition of ancillary lake and watershed variables explained some variability in ln(SD) (R2 = 0.68–0.85; 9 models). Weak spectral resolution and variable lake conditions limited accurate lake monitoring to relatively productive periods in late summer, as indicated by inconsistent, sometimes weak regressions during June and July when lakes were clearer and less stable (R2 = 0.19–0.74; 8 models). Additionally, SD estimates derived from 2 sets of concurrent MODIS and Landsat imagery generally did not agree unless Landsat imagery (30 m) was resampled to 250 m, likely owing to various factors related to scale. Average MODIS estimates exceeded those of Landsat by 0.35 and 0.49 m on the 2 dates. Overall, MODIS 250 m imagery are potentially useful for remote lake monitoring during productive periods when Landsat data are unavailable; however, analyses must occur when algal communities are stable and well-developed, are biased toward large lakes, may overestimate SD, and accuracy may be unreliable without non-spectral lake predictors.

  9. Tamarisk (Salt Cedar) Infestations in Northwestern Nevada Mapped Using Landsat TM Imagery and GIS Layers

    NASA Astrophysics Data System (ADS)

    Sengupta, D.; Geraci, C.; Kolkowitz, S.

    2004-12-01

    Tamarisk, also known as salt cedar (Tamarix sp.) is a prevalent invasive species that has infested many riparian areas in the southwestern United States. Mature salt cedar plants are resistant to high stress environments and fare well in drought conditions, mainly due to their extensive root systems that derive much of their sustenance from the water table rather than surface water and precipitation. The salt cedar root systems have altered hydrological patterns by tapping into underlying aquifers. This has decreased water available for recreational use, regional ecology and plant diversity. Many states have implemented salt cedar monitoring programs at the local level, but the problem of large-scale mapping of this invasive species has continued to be a challenge to land management agencies. Furthermore, inaccessible and unexplored areas continue to be absent in the mapping process. In August 2004, using field data consisting of large areas as training sets for classification of Landsat TM imagery, the DEVELOP student research team at NASA Ames Research Center generated a preliminary map of areas that that were susceptible to salt cedar growth for a region in northwestern Nevada. In addition to the remote sensing-based classification of satellite imagery, the team used the variables of elevation and estimated distance to the water table in conjunction with collected field data and knowledge of salt cedar growth habits to further refine the map. The team has further extended the mapping of key environmental factors of water availability for salt cedar, soil types and species distribution in regions infested by salt cedar. The investigation was carried out by 1) improving an existing GIS layer for water access using a suitable interpolation method, 2) including a GIS layer for soils associated with salt cedar growth and 3) completing field work to evaluate species distribution and regions of presence or absence of salt cedar. The outcome of this project served to

  10. Determination of turbidity patterns in Lake Chicot from LANDSAT MSS imagery

    NASA Technical Reports Server (NTRS)

    Lecroy, S. R.

    1982-01-01

    A historical analysis of all the applicable LANDSAT imagery was conducted on the turbidity patterns of Lake Chicot, located in the southeastern corner of Arkansas. By examining the seasonal and regional turbidity patterns, a record of sediment dynamics and possible disposition can be obtained. Sketches were generated from the suitable imagery, displaying different intensities of brightness observed in bands 5 and 7 of LANDSAT's multispectral scanner data. Differences in and between bands 5 and 7 indicate variances in the levels of surface sediment concentrations. High sediment loads are revealed when distinct patterns appear in the band 7 imagery. Additionally, the upwelled signal is exponential in nature and saturates in band 5 at low wavelengths for large concentrations of suspended solids.

  11. Utilization of LANDSAT orbital imagery in the soil survey processes at Rio Grande do Norte state

    NASA Technical Reports Server (NTRS)

    Formaggio, A. R. (Principal Investigator)

    1984-01-01

    Pedologic photointerpretative criteria adapted to LANDSAT orbital imagery were used: drainage (pattern, integration degree, density and uniformity degree); relief (pattern, dissection degree and crest lines); photographic texture, photographic tonnality, and the land use (type, glebas size and intensity of use). The performance of the imagery as an auxiliar tool in the soil survey processes, at Rio Grande do Norte State was evaluated. The drainage and relief elements were easily extracted from the imagery and also ones that provided the greatest deductive possibility about pedologic boundaries. Other analyzed criteria were considered only auxiliaries, corroborating some soil limits in the evidences convergence phase. The principal pedologic dominions of the 30,000 sq km are covered by the same LANDSAT image (WRS 359/16) were delimited with good precision: (1) fluvial plains, beaches, dunes and coastal mangroves; (2) North Coast line Plateau; (3) Acu Sandstone Zone; (4) residual plateaus of the Tertiary; and (6) plains of the embasement.

  12. Determination of turbidity patterns in Lake Chicot from LANDSAT MSS imagery

    NASA Technical Reports Server (NTRS)

    Lecroy, S. R. (Principal Investigator)

    1982-01-01

    A historical analysis of all the applicable LANDSAT imagery was conducted on the turbidity patterns of Lake Chicot, located in the southeastern corner of Arkansas. By examining the seasonal and regional turbidity patterns, a record of sediment dynamics and possible disposition can be obtained. Sketches were generated from the suitable imagery, displaying different intensities of brightness observed in bands 5 and 7 of LANDSAT's multispectral scanner data. Differences in and between bands 5 and 7 indicate variances in the levels of surface sediment concentrations. High sediment loads are revealed when distinct patterns appear in the band 7 imagery. Additionally, the upwelled signal is exponential in nature and saturates in band 5 at low wavelengths for large concentrations of suspended solids.

  13. Assessing shoreline response to three submerged breakwaters at Kerteh Bay, Terengganu, Malaysia using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Qayoom Tunji, Lawal Abdul; Yusof, Khamaruzaman Wan; Mustafa Hashim, Ahmad; Sapari, Nasiman

    2014-06-01

    As part of a project to determine the exact structural and environmental parameters governing the mode and magnitude of salient formation behind a submerged breakwater, a remote sensing technique is being adopted to assess the extent of erosion/accretion at Kerteh Bay, T errengganu, Malaysia. Multi-temporal Landsat satellite images of coarse resolution for the years of 1994, 2000, 2006, 2009 and 2012 were acquired for this purpose. The images were subsets divided into smaller areas of interest and classified using supervised classification of support vector machine. The classified image is then vectorized to extract shoreline based on waterline in each of the subset rasters images. Tidal correction were adopted to correct the waterline/shoreline to the mean sea level (MSL) datum. Comparison of corrected shorelines was carried to obtain the extent of erosion/accretion at the Kerteh Bay, Terrenganu, Malaysia. It was observed that substantial accretion was observed between the years 1994-2006 at the upper part of the study area, the part between northern part and the southern part also experienced accretion but not as much as compared to northern part for the same year. Erosion was noted between the years 2006-2012 for all of the areas of the study area but the rate slowed down between the years 2009-2012 for all the areas. Slope estimated from the imageries were compared with in situ slope of the same area, this served as a validation for the method used.

  14. The LANDSAT story: Module U-2

    NASA Technical Reports Server (NTRS)

    1980-01-01

    A review of the various LANDSAT program elements which are relevant to user participation is provided. Sources for additional information and assistance where potential users may acquire more details and further guidance in using LANDSAT data are identified. The multispectral imagery capability of the LANDSAT satellites is emphasized.

  15. Mapping paddy rice using multi-temporal Landsat imagery in the Sanjiang Plain, Northeast China

    NASA Astrophysics Data System (ADS)

    Jin, C.; Xiao, X.; Dong, J.; Wang, Z.; Song, K.

    2013-12-01

    Accurate information on cultivation area and spatial distribution of paddy rice is required for the regional food security, agriculture water management, and methane emission estimate. The 500m MODIS-based paddy rice mapping algorithm has been well applied to map rice cropping area and intensity through identifying the unique phenology phase during the growing season - field flooding/seedling transplanting using the time-series datasets of Normalized Difference Vegetation Index (NDVI), Enhance Vegetation index (EVI), and Land Surface Water Index (LSWI). In this study, a total number of 119 scenes of Landsat imagery were collected over the entire Sanjiang Plain, Northeast China in 2010-2012. Paddy rice has shown distinct phenological and spectral characteristics against other land types from the multi-temporal Landsat imagery during the flooding/transplanting (early-May to late-June) and ripening (late-August to Mid-September) periods, respectively. A 30m Landsat paddy rice map of the Sanjiang Plain was generated by composing flooding/transplanting and ripening based algorithms using the multi-temporal vegetation indices (NDVI, EVI, LSWI) as input. The resultant Landsat-based paddy rice map has been evaluated and compared using other four paddy rice datasets: (1) ground truth points collected during 2011 field campaign; (2) 2011 agricultural census data of counties; (3) the National Land Cover Dataset (1: 100, 000 scale) derived from the Landsat and CBERS-2 in 2010/2011; and (4) 500m paddy rice map generated from the multi-temporal MODIS vegetation indices imagery. We found that the Landsat paddy rice map has high accuracy (both producer and user accuracy is above 85%) on the basis of ground truth point validation. Agricultural census data tended to underestimate paddy rice area by 60% compared the rice area summarized from the Landsat paddy rice map. In addition, the Landsat paddy rice map had good consistency with the MODIS paddy rice map with the correlation

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

    NASA Astrophysics Data System (ADS)

    Jenerowicz, Agnieszka; Woroszkiewicz, Malgorzata

    2016-10-01

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

  17. Ocean Color Retrieval Using LANDSAT-8 Imagery in Coastal Case 2 Waters (case Study Persian and Oman Gulf)

    NASA Astrophysics Data System (ADS)

    Moradi, N.; Hasanlou, M.; Saadatseresht, M.

    2016-06-01

    . Despite the high importance of the Persian Gulf and Oman Sea which can have up basin countries, to now few studies have been done in this area. The focus of this article on the northern part of Oman Sea and Persian Gulf, the shores of neighboring Iran (case 2 water). In this paper, by using Landsat 8 satellite imageries, we have discussed chla concentrations and customizing different OC algorithms for this new dataset (Landsat-8 imagery). This satellite was launched in 2013 and its data using two sensors continuously are provided operating one sensor imager land (OLI: Operational Land Imager) and the Thermal Infrared Sensor (TIRS: Thermal InfraRed Sensor) and are available. This sensors collect image data, respectively, for the nine-band short wavelength in the range of 433-2300 nm and dual-band long wavelength thermal. Seven band of the nine band picked up by the sensor information of OLI to deal with sensors TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) in previous satellite Landsat compatible and two other band, the band of coastal water (433 to 453 nm) and Cirrus band (1360 to 1390 nm), short wave infrared provides to measure water quality and high thin clouds. Since OLI sensor in Landsat satellite 8 compared with other sensors to study OC have been allocated a much better spatial resolution can be more accurate to determine changes in OC. To evaluate the results of the image sensor MODIS (Moderate Resolution Imaging Spectroradiometer) at the same time satellite images Landsat 8 is used. The statistical parameters used in order to evaluate the performance of different algorithms, including root mean square error (RMSE) and coefficient of determination (R2), and on the basis of these parameters we choose the most appropriate algorithm for the area. Extracted results for implementing different OC algorithms clearly shows superiority of utilized method by R2=0.71 and RMSE=0.07.

  18. A comparison of radiometric normalization methods when filling cloud gaps in Lansat imagery.

    Treesearch

    E. H. Helmer

    2007-01-01

    Mapping persistently cloudy tropical landscapes with optical satellite imagenery usually requires assembling the clear imagery from several dates. this study compares methods for normalizing image data when filling cloud gaps in Landsat imagery with imagery from other dates.

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

    NASA Technical Reports Server (NTRS)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

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

  20. Automated Detection of Clouds in Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary

    2010-01-01

    Many different approaches have been used to automatically detect clouds in satellite imagery. Most approaches are deterministic and provide a binary cloud - no cloud product used in a variety of applications. Some of these applications require the identification of cloudy pixels for cloud parameter retrieval, while others require only an ability to mask out clouds for the retrieval of surface or atmospheric parameters in the absence of clouds. A few approaches estimate a probability of the presence of a cloud at each point in an image. These probabilities allow a user to select cloud information based on the tolerance of the application to uncertainty in the estimate. Many automated cloud detection techniques develop sophisticated tests using a combination of visible and infrared channels to determine the presence of clouds in both day and night imagery. Visible channels are quite effective in detecting clouds during the day, as long as test thresholds properly account for variations in surface features and atmospheric scattering. Cloud detection at night is more challenging, since only courser resolution infrared measurements are available. A few schemes use just two infrared channels for day and night cloud detection. The most influential factor in the success of a particular technique is the determination of the thresholds for each cloud test. The techniques which perform the best usually have thresholds that are varied based on the geographic region, time of year, time of day and solar angle.

  1. Extraction of Suspended Sediments from Landsat Imagery in the Northern Gulf of Mexico

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Drewry, M.; He, M. Y.; Ebersole, S.

    2011-12-01

    The Sediment Analysis Network for Decision Support (SANDS) project is utilizing enhancement methods to highlight suspended sediment in remotely sensed data and imagery of the Northern Gulf of Mexico. The analysis thus far has shown that areas of suspended sediments can be extracted from Landsat imagery. In addition, although not an original goal of SANDS, the analysis techniques have revealed oil floating on the water's surface. Detection of oil floating on the surface through remotely sensed imagery can be helpful in identifying and understanding the geographic distribution and movement of oil for environmental concerns. Data from Landsat, and MODIS were obtained from NASA Earth Science Data Centers by the Information Technology and Systems Center at the University of Alabama in Huntsville and prepared for analysis by subsetting to the region of interest and converting from HDF-EOS format (in the case of MODIS) to GeoTiff. Analysts at the Geological Survey of Alabama (GSA) working with Landsat data initially, employed enhancement methods, including false color composites, spectral ratios, and other spectral enhancements based on the mineral composition of sediments, to combinations of visible and infrared bands of data. Initial results of this approach revealed suspended sediments. The analysis technique also revealed areas of oil floating on the surface of the Gulf near Chandeleur Island immediately after Hurricane Katrina in 2005. True color Landsat imagery compares the original Landsat scene to the same region after enhancement. The areas of floating oil are clearly visible. The oil washed out from oil spills on land. This paper will present the intermediate result of the SANDS project thus far.

  2. Estimating vegetative biomass from LANDSAT-1 imagery for range management

    NASA Technical Reports Server (NTRS)

    Seevers, P. M.; Drew, J. V.; Carlson, M. P.

    1975-01-01

    Evaluation of LANDSAT-1, band 5 data for use in estimation of vegetative biomass for range management decisions was carried out for five selected range sites in the Sandhills region of Nebraska. Analysis of sets of optical density-vegetative biomass data indicated that comparisons of biomass estimation could be made within one frame but not between frames without correction factors. There was high correlation among sites within sets of radiance value-vegetative biomass data and also between sets, indicating comparisons of biomass could be made within and between frames. Landsat-1 data are shown to be a viable alternative to currently used methods of determining vegetative biomass production and stocking rate recommendations for Sandhills rangeland.

  3. BOREAS RSS-8 Snow Maps Derived from Landsat TM Imagery

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy; Chang, Alfred T. C.; Foster, James L.; Chien, Janeet Y. L.; Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-8 team utilized Landsat Thematic Mapper (TM) images to perform mapping of snow extent over the Southern Study Area (SSA). This data set consists of two Landsat TM images that were used to determine the snow-covered pixels over the BOREAS SSA on 18 Jan 1993 and on 06 Feb 1994. The data are stored in binary image format files. The RSS-08 snow map data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  4. Using satellite imagery for stormwater pollution management with Bayesian networks.

    PubMed

    Park, Mi-Hyun; Stenstrom, Michael K

    2006-10-01

    Urban stormwater runoff is the primary source of many pollutants to Santa Monica Bay, but its monitoring and modeling is inherently difficult and often requires land use information as an intermediate process. Many approaches have been developed to estimate stormwater pollutant loading from land use. This research investigates an alternative approach, which estimates stormwater pollutant loadings directly from satellite imagery. We proposed a Bayesian network approach to classify a Landsat ETM(+) image of the Marina del Rey area in the Santa Monica Bay watershed. Eight water quality parameters were examined, including: total suspended solids, chemical oxygen demand, nutrients, heavy metals, and oil and grease. The pollutant loads for each parameter were classified into six levels: very low, low, medium low, medium high, high, and very high. The results provided spatial estimates of each pollutant load as thematic maps from which the greatest pollutant loading areas were identified. These results may be useful in developing best management strategies for stormwater pollution at regional and global scales and in establishing total maximum daily loads in the watershed. The approach can also be used for areas without ground-survey land use data.

  5. Quantifying River Widths of North America from Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    River width is a fundamental predictor variable in many hydrologic, geomorphic, and biogeochemical models, yet current large-scale models rely on theoretical hydraulic geometry relationships that do not fully capture natural variability in river form. Here we present the first high-resolution dataset of long-term mean width of North American rivers wider than 30 m. The dataset contains 7.93 million georeferenced width measurements derived from Landsat TM and ETM+ imagery that were acquired when rivers were most likely to be at mean discharge. We built the dataset by developing an automated procedure that selects and downloads raw imagery, creates cloud-free normalized difference water index images, histogram balances and mosaics them together, and produces a water mask using a dynamic water-land threshold technique. We then visually inspected and corrected the mask for errors and used RivWidth software to calculate river width at each river centerline pixel. We validated our dataset using >1000 United States Geological Survey and Water Survey of Canada in situ gauge station measurements. Error analysis shows a robust relationship between the remotely sensed widths and in situ gauge measurements with an r 2 = 0.86 (Spearman's = 0.81) and a mean absolute error of 27.5 m. We find that North American river widths lie on logarithmic frequency curve with some notable exceptions at widths <100 m. This dataset can be used to improve our understanding of the water, carbon, and nitrogen cycles, as well as large-scale landscape evolution models. Our results also allow for the characterization of the extent of rivers likely to be observable by the planned Surface Water and Ocean Topography (SWOT) satellite mission.

  6. A qualitative evaluation of Landsat imagery of Australian rangelands

    USGS Publications Warehouse

    Graetz, R.D.; Carneggie, David M.; Hacker, R.; Lendon, C.; Wilcox, D.G.

    1976-01-01

    The capability of multidate, multispectral ERTS-1 imagery of three different rangeland areas within Australia was evaluated for its usefulness in preparing inventories of rangeland types, assessing on a broad scale range condition within these rangeland types, and assessing the response of rangelands to rainfall events over large areas. For the three divergent rangeland test areas, centered on Broken W, Alice Springs and Kalgoorlie, detailed interpretation of the imagery only partially satisfied the information requirements set. It was most useful in the Broken Hill area where fenceline contrasts in range condition were readily visible. At this and the other sites an overstorey of trees made interpretation difficult. Whilst the low resolution characteristics and the lack of stereoscopic coverage hindered interpretation it was felt that this type of imagery with its vast coverage, present low cost and potential for repeated sampling is a useful addition to conventional aerial photography for all rangeland types.

  7. Evaluation of the U.S. Geological Survey Landsat burned area essential climate variable across the conterminous U.S. using commercial high-resolution imagery

    USGS Publications Warehouse

    Vanderhoof, Melanie; Brunner, Nicole M.; Beal, Yen-Ju G.; Hawbaker, Todd J.

    2017-01-01

    The U.S. Geological Survey has produced the Landsat Burned Area Essential Climate Variable (BAECV) product for the conterminous United States (CONUS), which provides wall-to-wall annual maps of burned area at 30 m resolution (1984–2015). Validation is a critical component in the generation of such remotely sensed products. Previous efforts to validate the BAECV relied on a reference dataset derived from Landsat, which was effective in evaluating the product across its timespan but did not allow for consideration of inaccuracies imposed by the Landsat sensor itself. In this effort, the BAECV was validated using 286 high-resolution images, collected from GeoEye-1, QuickBird-2, Worldview-2 and RapidEye satellites. A disproportionate sampling strategy was utilized to ensure enough burned area pixels were collected. Errors of omission and commission for burned area averaged 22 ± 4% and 48 ± 3%, respectively, across CONUS. Errors were lowest across the western U.S. The elevated error of commission relative to omission was largely driven by patterns in the Great Plains which saw low errors of omission (13 ± 13%) but high errors of commission (70 ± 5%) and potentially a region-growing function included in the BAECV algorithm. While the BAECV reliably detected agricultural fires in the Great Plains, it frequently mapped tilled areas or areas with low vegetation as burned. Landscape metrics were calculated for individual fire events to assess the influence of image resolution (2 m, 30 m and 500 m) on mapping fire heterogeneity. As the spatial detail of imagery increased, fire events were mapped in a patchier manner with greater patch and edge densities, and shape complexity, which can influence estimates of total greenhouse gas emissions and rates of vegetation recovery. The increasing number of satellites collecting high-resolution imagery and rapid improvements in the frequency with which imagery is being collected means greater opportunities to utilize these sources

  8. Multi-Temporal Land Use Analysis of AN Ephemeral River Area Using AN Artificial Neural Network Approach on Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Aquilino, M.; Tarantino, E.; Fratino, U.

    2013-01-01

    This paper proposes a change detection analysis method based on multitemporal LANDSAT satellite data, presenting a study performed on the Lama San Giorgio (Bari, Italy) river basin area. Based on its geological and hydrological characteristics, as well as on the number of recent and remote flooding events already occurred, this area seems to be naturally prone to flooding. The historical archive of LANDSAT imagery dating back to the launch of ERTS in 1972 provides a comprehensive and permanent data source for tracking change on the planet‟s land surface. In this study case the imagery acquisition dates of 1987, 2002 and 2011 were selected to cover a time trend of 24 years. Land cover categories were based on classes outlined by the Curve Number method with the aim of characterizing land use according to the level of surface imperviousness. After comparing two land use classification methods, i.e. Maximum Likelihood Classifier (MLC) and Multi-Layer Perceptron (MLP) neural network, the Artificial Neural Networks (ANN) approach was found the best reliable and efficient method in the absence of ground reference data. The ANN approach has a distinct advantage over statistical classification methods in that it is non-parametric and requires little or no a priori knowledge on the distribution model of input data. The results quantify land cover change patterns in the river basin area under study and demonstrate the potential of multitemporal LANDSAT data to provide an accurate and cost-effective means to map and analyse land cover changes over time that can be used as input in land management and policy decision-making.

  9. Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States

    USGS Publications Warehouse

    Jin, Suming; Homer, Collin G.; Yang, Limin; Xian, George; Fry, Joyce; Danielson, Patrick; Townsend, Philip A.

    2013-01-01

    A simple, efficient, and practical approach for detecting cloud and shadow areas in satellite imagery and restoring them with clean pixel values has been developed. Cloud and shadow areas are detected using spectral information from the blue, shortwave infrared, and thermal infrared bands of Landsat Thematic Mapper or Enhanced Thematic Mapper Plus imagery from two dates (a target image and a reference image). These detected cloud and shadow areas are further refined using an integration process and a false shadow removal process according to the geometric relationship between cloud and shadow. Cloud and shadow filling is based on the concept of the Spectral Similarity Group (SSG), which uses the reference image to find similar alternative pixels in the target image to serve as replacement values for restored areas. Pixels are considered to belong to one SSG if the pixel values from Landsat bands 3, 4, and 5 in the reference image are within the same spectral ranges. This new approach was applied to five Landsat path/rows across different landscapes and seasons with various types of cloud patterns. Results show that almost all of the clouds were captured with minimal commission errors, and shadows were detected reasonably well. Among five test scenes, the lowest producer's accuracy of cloud detection was 93.9% and the lowest user's accuracy was 89%. The overall cloud and shadow detection accuracy ranged from 83.6% to 99.3%. The pixel-filling approach resulted in a new cloud-free image that appears seamless and spatially continuous despite differences in phenology between the target and reference images. Our methods offer a straightforward and robust approach for preparing images for the new 2011 National Land Cover Database production.

  10. Assessing Field-Specific Risk of Soybean Sudden Death Syndrome Using Satellite Imagery in Iowa.

    PubMed

    Yang, S; Li, X; Chen, C; Kyveryga, P; Yang, X B

    2016-08-01

    Moderate resolution imaging spectroradiometer (MODIS) satellite imagery from 2004 to 2013 were used to assess the field-specific risks of soybean sudden death syndrome (SDS) caused by Fusarium virguliforme in Iowa. Fields with a high frequency of significant decrease (>10%) of the normalized difference vegetation index (NDVI) observed in late July to middle August on historical imagery were hypothetically considered as high SDS risk. These high-risk fields had higher slopes and shorter distances to flowlines, e.g., creeks and drainages, particularly in the Des Moines lobe. Field data in 2014 showed a significantly higher SDS level in the high-risk fields than fields selected without considering NDVI information. On average, low-risk fields had 10 times lower F. virguliforme soil density, determined by quantitative polymerase chain reaction, compared with other surveyed fields. Ordinal logistic regression identified positive correlations between SDS and slope, June NDVI, and May maximum temperature, but high June maximum temperature hindered SDS. A modeled SDS risk map showed a clear trend of potential disease occurrences across Iowa. Landsat imagery was analyzed similarly, to discuss the ability to utilize higher spatial resolution data. The results demonstrated the great potential of both MODIS and Landsat imagery for SDS field-specific risk assessment.

  11. Pre-processing methods of satellite imagery for coastal wetlands studies in the southeastern United States

    SciTech Connect

    Harris, M.; Caldwell, M.; Althausen, J.D.

    1997-06-01

    Southeastern United States coastal wetlands in Florida and South Carolina are being analyzed using historical remotely sensed data to determine long term changes in wetland vegetation. A time series of Landsat imagery from 1972 to 1996 is being acquired and pre-processed to facilitate change detection analysis. This paper presents the pre-processing techniques being applied to the imagery for the Florida study area. Landsat Thematic Mapper (TM) and Multi-Spectral Scanner (MSS) imagery were chosen from the optimal seasonal periods when biomass could be determined, before dormancy or after spring leaf-out. The rectification of each scene to the UTM (Universal Transverse Mercator) coordinate system is based on field collected GPS (Global Positioning System) control, standardized for each region. Map accuracy equivalent of 1:50,000 is achieved for the time series in each region and inter-image registration is consistently one pixel or better. Normalization of imagery reflectance values is achieved with radiometric enhancements and atmospheric corrections. These satellite image time series will serve as input to a model which will identify the sensitivity of tidal marshes to combinations of natural and human impacts.

  12. Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

    NASA Technical Reports Server (NTRS)

    Welch, R. M.; Sengupta, S. K.; Chen, D. W.

    1990-01-01

    Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

  13. Digital image correlation techniques applied to LANDSAT multispectral imagery

    NASA Technical Reports Server (NTRS)

    Bonrud, L. O. (Principal Investigator); Miller, W. J.

    1976-01-01

    The author has identified the following significant results. Automatic image registration and resampling techniques applied to LANDSAT data achieved accuracies, resulting in mean radial displacement errors of less than 0.2 pixel. The process method utilized recursive computational techniques and line-by-line updating on the basis of feedback error signals. Goodness of local feature matching was evaluated through the implementation of a correlation algorithm. An automatic restart allowed the system to derive control point coordinates over a portion of the image and to restart the process, utilizing this new control point information as initial estimates.

  14. The value of earth observations: methods and findings on the value of Landsat imagery

    USGS Publications Warehouse

    Miller, Holly; Serbina, Larisa O.; Richardson, Leslie A.; Ryker, Sarah J.; Newman, Timothy R.

    2016-01-01

    Data from Earth observation systems are used extensively in managing and monitoring natural resources, natural hazards, and the impacts of climate change, but the value of such data can be difficult to estimate, particularly when it is available at no cost. Assessing the socioeconomic and scientific value of these data provides a better understanding of the existing and emerging research, science, and applications related to this information and contributes to the decision making process regarding current and future Earth observation systems. Recent USGS research on Landsat data has advanced the literature in this area by using a variety of methods to estimate value. The results of a 2012 survey of Landsat users, a 2013 requirements assessment, and 2013 case studies of applications of Landsat imagery are discussed.

  15. Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

    USGS Publications Warehouse

    Xian, G.; Homer, C.; Fry, J.

    2009-01-01

    The recent release of the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001, which represents the nation's land cover status based on a nominal date of 2001, is widely used as a baseline for national land cover conditions. To enable the updating of this land cover information in a consistent and continuous manner, a prototype method was developed to update land cover by an individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season in 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, land cover classifications at the full NLCD resolution for 2006 areas of change were completed by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain several metropolitan areas including Seattle, Washington; San Diego, California; Sioux Falls, South Dakota; Jackson, Mississippi; and Manchester, New Hampshire. Results from the five study areas show that the vast majority of land cover change was captured and updated with overall land cover classification accuracies of 78.32%, 87.5%, 88.57%, 78.36%, and 83.33% for these areas. The method optimizes mapping efficiency and has the potential to provide users a flexible method to generate updated land cover at national and regional scales by using NLCD 2001 as the baseline. ?? 2009 Elsevier Inc.

  16. Mapping the Philippines' mangrove forests using Landsat imagery

    USGS Publications Warehouse

    Long, Jordan; Giri, Chandra

    2011-01-01

    Current, accurate, and reliable information on the areal extent and spatial distribution of mangrove forests in the Philippines is limited. Previous estimates of mangrove extent do not illustrate the spatial distribution for the entire country. This study, part of a global assessment of mangrove dynamics, mapped the spatial distribution and areal extent of the Philippines’ mangroves circa 2000. We used publicly available Landsat data acquired primarily from the Global Land Survey to map the total extent and spatial distribution. ISODATA clustering, an unsupervised classification technique, was applied to 61 Landsat images. Statistical analysis indicates the total area of mangrove forest cover was approximately 256,185 hectares circa 2000 with overall classification accuracy of 96.6% and a kappa coefficient of 0.926. These results differ substantially from most recent estimates of mangrove area in the Philippines. The results of this study may assist the decision making processes for rehabilitation and conservation efforts that are currently needed to protect and restore the Philippines’ degraded mangrove forests.

  17. Automatic and improved radiometric correction of Landsat imagery using reference values from MODIS surface reflectance images

    NASA Astrophysics Data System (ADS)

    Pons, X.; Pesquer, L.; Cristóbal, J.; González-Guerrero, O.

    2014-12-01

    Radiometric correction is a prerequisite for generating high-quality scientific data, making it possible to discriminate between product artefacts and real changes in Earth processes as well as accurately produce land cover maps and detect changes. This work contributes to the automatic generation of surface reflectance products for Landsat satellite series. Surface reflectances are generated by a new approach developed from a previous simplified radiometric (atmospheric + topographic) correction model. The proposed model keeps the core of the old model (incidence angles and cast-shadows through a digital elevation model [DEM], Earth-Sun distance, etc.) and adds new characteristics to enhance and automatize ground reflectance retrieval. The new model includes the following new features: (1) A fitting model based on reference values from pseudoinvariant areas that have been automatically extracted from existing reflectance products (Terra MODIS MOD09GA) that were selected also automatically by applying quality criteria that include a geostatistical pattern model. This guarantees the consistency of the internal and external series, making it unnecessary to provide extra atmospheric data for the acquisition date and time, dark objects or dense vegetation. (2) A spatial model for atmospheric optical depth that uses detailed DEM and MODTRAN simulations. (3) It is designed so that large time-series of images can be processed automatically to produce consistent Landsat surface reflectance time-series. (4) The approach can handle most images, acquired now or in the past, regardless of the processing system, with the exception of those with extremely high cloud coverage. The new methodology has been successfully applied to a series of near 300 images of the same area including MSS, TM and ETM+ imagery as well as to different formats and processing systems (LPGS and NLAPS from the USGS; CEOS from ESA) for different degrees of cloud coverage (up to 60%) and SLC

  18. Registering Ground and Satellite Imagery for Visual Localization

    DTIC Science & Technology

    2012-08-01

    Registering Ground and Satellite Imagery for Visual Localization by Philip David and Sean Ho ARL-TR-6105 August 2012...Registering Ground and Satellite Imagery for Visual Localization Philip David and Sean Ho Computational and Information Sciences Directorate...PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Philip David and Sean Ho 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING

  19. Measuring phenological variability from satellite imagery

    USGS Publications Warehouse

    Reed, Bradley C.; Brown, Jesslyn F.; Vanderzee, D.; Loveland, Thomas R.; Merchant, James W.; Ohlen, Donald O.

    1994-01-01

    Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large- area land cover mapping and monitoring. The utility of re- motely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

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

    USGS Publications Warehouse

    Salamonowicz, P.H.

    1986-01-01

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

  1. LANDSAT imagery of the Venetian Lagoon: A multitemporal analysis

    NASA Technical Reports Server (NTRS)

    Alberotanza, L.; Zandonella, A. (Principal Investigator)

    1980-01-01

    The use of LANDSAT multispectral scanner images from 1975 to 1979 to determine pollution dispersion in the central basin of the lagoon under varying tidal conditions is described. Images taken during the late spring and representing both short and long range tidal dynamics were processed for partial haze removal and removal of residual striping. Selected spectral bands were correlated to different types of turbid water. The multitemporal data was calibrated, classified considering sea truth data, and evaluated. The classification differentiated tide diffusion, algae belts, and industrial, agricultural, and urban turbidity distributions. Pollution concentration is derived during the short time interval between inflow and outflow and from the distance between the two lagoon inlets and the industrial zones. Increasing pollution of the lagoon is indicated.

  2. The Use of False Color Landsat Imagery with a Fifth Grade Class.

    ERIC Educational Resources Information Center

    Harnapp, Vern R.

    Fifth grade students can become familiar with images of earth generated by space sensor Landsat satellites which sense nearly all surfaces of the earth once every 18 days. Two false color composites in which different colors represent various geographic formations were obtained for the northern Ohio region where the students live. The class had no…

  3. Effects of atmospheric correction of Landsat imagery on lake water clarity assessment

    NASA Astrophysics Data System (ADS)

    Bonansea, Matias; Ledesma, C.; Rodríguez, C.; Pinotti, L.; Antunes, M. Homem

    2015-12-01

    Empirical relationships between Landsat data and water clarity expressed in terms of Secchi disk transparency (SDT) have been widely used for monitoring and assessment of water quality. The atmosphere affects differently sensor bands depending on the waveband, thus affecting the relationships obtained from top-of-atmosphere reflectance. The objective of this study was to evaluate whether the reliability of water clarity can be improved applying atmospheric correction of Landsat imagery. Further, a general predictive algorithm to determine water clarity in the reservoir was developed. Samples of SDT were taken from Río Tercero reservoir (Argentina). Landsat images were atmospheric corrected using the 6S code. Estimated values of SDT with and without atmospheric correction were compared for their differences. Results suggested that atmospheric corrected values of Landsat band 3 and the ratio 1/3 proved to be the best predictor of water clarity in the reservoir (R2 = 0.84). Using the 6S code we demonstrate the usefulness of atmospheric correction to Landsat data since water clarity algorithm using surface reflectance was more reliable than the top-of atmosphere reflectance model.

  4. BOREAS TE-18, 30-m, Radiometrically Rectified Landsat TM Imagery

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Knapp, David

    2000-01-01

    The BOREAS TE-18 team used a radiometric rectification process to produce standardized DN values for a series of Landsat TM images of the BOREAS SSA and NSA in order to compare images that were collected under different atmospheric conditions. The images for each study area were referenced to an image that had very clear atmospheric qualities. The reference image for the SSA was collected on 02-Sep-1994, while the reference image for the NSA was collected on 21-Jun-1995. the 23 rectified images cover the period of 07-Jul-1985 to 18 Sep-1994 in the SSA and from 22-Jun-1984 to 09-Jun-1994 in the NSA. Each of the reference scenes had coincident atmospheric optical thickness measurements made by RSS-11. The radiometric rectification process is described in more detail by Hall et al. (199 1). The original Landsat TM data were received from CCRS for use in the BOREAS project. The data are stored in binary image-format files. Due to the nature of the radiometric rectification process and copyright issues, these full-resolution images may not be publicly distributed. However, a spatially degraded 60-m resolution version of the images is available on the BOREAS CD-ROM series. See Sections 15 and 16 for information about how to possibly acquire the full resolution data. Information about the full-resolution images is provided in an inventory listing on the CD-ROMs. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

  5. BOREAS TE-18, 60-m, Radiometrically Rectified Landsat TM Imagery

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Knapp, David

    2000-01-01

    The BOREAS TE-18 team used a radiometric rectification process to produce standardized DN values for a series of Landsat TM images of the BOREAS SSA and NSA in order to compare images that were collected under different atmospheric conditions. The images for each study area were referenced to an image that had very clear atmospheric qualities. The reference image for the SSA was collected on 02-Sep-1994, while the reference image for the NSA was collected on 2 1 Jun-1995. The 23 rectified images cover the period of 07-Jul-1985 to 18-Sep-1994 in the SSA and 22-Jun-1984 to 09-Jun-1994 in the NSA. Each of the reference scenes had coincident atmospheric optical thickness measurements made by RSS-11. The radiometric rectification process is described in more detail by Hall et al. (1991). The original Landsat TM data were received from CCRS for use in the BOREAS project. Due to the nature of the radiometric rectification process and copyright issues, the full-resolution (30-m) images may not be publicly distributed. However, this spatially degraded 60-m resolution version of the images may be openly distributed and is available on the BOREAS CD-ROM series. After the radiometric rectification processing, the original data were degraded to a 60-m pixel size from the original 30-m pixel size by averaging the data over a 2- by 2-pixel window. The data are stored in binary image-format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

  6. Spatial characterization of bark beetle infestations by a multidate synergy of SPOT and Landsat imagery.

    PubMed

    Latifi, Hooman; Schumann, Bastian; Kautz, Markus; Dech, Stefan

    2014-01-01

    Biological infestations in forests, e.g. the insect outbreaks, have been shown as favoured by future climate change trends. In Europe, the European spruce bark beetle (Ips typographus L.) is one of the main agents causing substantial economic disturbances in forests. Therefore, studies on spatio-temporal characterization of the area affected by bark beetle are of major importance for rapid post-attack management. We aimed at spatially detecting damage classes by combining multidate remote sensing data and a non-parametric classification. As study site served a part of the Bavarian Forest National Park (Germany). For the analysis, we used 10 geometrically rectified scenes of Landsat and SPOT sensors in the period between 2001 and 2011. The main objective was to explore the potential of medium-resolution data for classifying the attacked areas. A further aim was to explore if the temporally adjacent infested areas are able to be separated. The random forest (RF) model was applied using the reference data drawn from high-resolution aerial imagery. The results indicate that the sufficiently large patches of visually identifiable damage classes can be accurately separated from non-attacked areas. In contrast to those, the other mortality classes (current year, current year 1 and current year 2 infested classes) were mostly classified with higher commission or omission errors as well as higher classification biases. The available medium-resolution satellite images, combined with properly acquired reference data, are concluded to be adequate tools to map area-based infestations at advanced stages. However, the quality of reference data, the size of infested patches and the spectral resolution of remotely sensed data are the decisive factors in case of smaller areas. Further attempts using auxiliary height information and spatially enhanced data may refine such an approach.

  7. Patterns of glacier basal motion across southcentral Alaska from cross-correlation of Landsat imagery

    NASA Astrophysics Data System (ADS)

    Armstrong, W. H., Jr.; Anderson, R. S.; Fahnestock, M. A.; Pope, A.

    2016-12-01

    We document spatial patterns of glacier basal motion by investigating the seasonal-to-annual evolution of surface velocity for a multitude surge- and non-surge type glaciers in the Wrangell-St Elias ranges of southcentral Alaska, USA, over the Landsat 8 record. We employ PyCorr, a Python-implemented image cross-correlation program, to estimate 16-day to annual glacier velocity fields over a regional scale. We ask questions such as: Is there a characteristic spatial pattern of glacier sliding? If so, what does that pattern look like? Does the spatial distribution and magnitude of glacier sliding depend on a glacier's geometry, setting, and/or mass balance environment? Where might we expect greatest glacier erosion to occur and how does this determine the shape of alpine landscapes? We calculate expected ice deformation speeds using the shape factor-modified shallow ice approximation employing several estimated ice thickness profiles. We compare these expected profiles with observed annual surface velocity profiles obtained from PyCorr-derived analysis of satellite imagery. Locations of model misfit are due to contributions of basal motion to surface velocity and/or model error. We further investigate areas of model misfit by documenting seasonal variability in ice surface velocity that results from variations in basal motion. Preliminary data from Nabesna Glacier (Figure 1) show a 20 cm d-1 (30-65%) summer velocity increase over the glacier's terminal 30 km, and a lack of such speed-up over the top 20 km. While longitudinal stress gradient coupling may explain a portion of these velocity variations, local basal motion must contribute, as longitudinal stresses cannot be transmitted over such distances. By comparing many glaciers across the range, we will explore to degree to which summer speed anomalies correlate with both climatic and topographic setting, with relevance to both glacier mechanics and alpine landscape evolution.

  8. An effective modified water extraction method for Landsat-8 OLI imagery of mountainous plateau regions

    NASA Astrophysics Data System (ADS)

    Gao, H.; Wang, L.; Jing, L.; Xu, J.

    2016-04-01

    Water body extraction from remote sensing imagery is an efficient way to investigate and monitor water resources. In the study area of this research, a mountainous plateau near Kashgar, China, sparse vegetation and seasonal rivers affect water body extraction. In order to extract water bodies, a modified water body extraction method is proposed in this paper and tested using Landsat-8 OLI imagery. Following this method, binary images are first generated using a classification, a Tasseled Cap transform, and a normalized difference water index, respectively, and then combined to yield a mask. Next, water bodies are delineated by masking the Landsat-8 OLI imagery and then refined by eliminating false areas using a supervised classification. It is demonstrated from the resulting water body maps that terrain related shadows in imagery were effectively eliminated and river tributaries and artificial ditches were precisely delineated, with accuracy up to 94%. Compared with several current water body extraction methods, the modified method yielded water body maps with better visualization and slightly improved accuracy.

  9. The application of LANDSAT-1 imagery for monitoring strip mines in the new river watershed in northeast Tennessee, part 2

    NASA Technical Reports Server (NTRS)

    Shahrokhi, F. (Principal Investigator); Sharber, L. A.

    1977-01-01

    The author has identified the following significant results. LANDSAT imagery and supplementary aircraft photography of the New River drainage basin were subjected to a multilevel analysis using conventional photointerpretation methods, densitometric techniques, multispectral analysis, and statistical tests to determine the accuracy of LANDSAT-1 imagery for measuring strip mines of common size. The LANDSAT areas were compared with low altitude measurements. The average accuracy over all the mined land sample areas mapped from LANDSAT-1 was 90%. The discrimination of strip mine subcategories is somewhat limited on LANDSAT imagery. A mine site, whether active or inactive, can be inferred by lack of vegetation, by shape, or image texture. Mine ponds are difficult or impossible to detect because of their small size and turbidity. Unless bordered and contrasted with vegetation, haulage roads are impossible to delineate. Preparation plants and refuge areas are not detectable. Density slicing of LANDSAT band 7 proved most useful in the detection of reclamation progress within the mined areas. For most state requirements for year-round monitoring of surface mined land, LANDSAT is of limited value. However, for periodic updating of regional surface maps, LANDSAT may provide sufficient accuracies for some users.

  10. 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.

  11. Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

    NASA Technical Reports Server (NTRS)

    Potter, Christopher S.

    2013-01-01

    Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

  12. Mapping snow depth from stereo satellite imagery

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  13. Estimation of Cirrus and Stratus Cloud Heights Using Landsat Imagery

    NASA Technical Reports Server (NTRS)

    Inomata, Yasushi; Feind, R. E.; Welch, R. M.

    1996-01-01

    A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and anti-sunside of the cloud-shadow pair are apparent. The technique requires some intepretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about +/- 250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semi-automated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals.

  14. Estimation of cirrus and stratus cloud heights using landsat imagery

    SciTech Connect

    Inomata, Yasushi; Feind, R.E.; Welch, R.M.

    1996-03-01

    A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and antisunside of the cloud-shadow pair are apparent. The technique requires some interpretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about {plus_minus}250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semiautomated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals. 22 refs., 13 figs., 4 tabs.

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

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

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

  16. Urban heat evolution in a tropical area utilizing Landsat imagery

    NASA Astrophysics Data System (ADS)

    Amanollahi, Jamil; Tzanis, Chris; Ramli, Mohammad Firuz; Abdullah, Ahmad Makmom

    2016-01-01

    Cloud cover is the main limitation of using remote sensing to study Land Use and Land Cover (LULC) change, and Land Surface Temperature (LST) in tropical area like Malaysia. In order to study LULC change and its effect on LST, the Landsat images were utilized within Geographical Information System (GIS) with the aim of removing the effect of cloud cover and image's gaps on the Digital Number (DN) of the pixels. 5356 points according to pixels coordinate which represent the 960 m to 960 m area were created in GIS environment and matched with thermal bands of the study area in remote sensing environment. The DNs of these points were processed to extract LST and imported in GIS environment to derive the temperature maps. Temperature was found to be generally higher in 2010 than in 2000. The comparison of the highest temperature area in the temperature maps with ground stations data showed that the topographical characteristics of the area, and the wind speed, and direction influence the occurrence of Urban Heat Island (UHI) effect. This study concludes that integration of remote sensing data and GIS is a useful tool in urban LST detection in tropical area.

  17. Generation of uniform chromaticity scale imagery from LANDSAT data

    NASA Technical Reports Server (NTRS)

    Juday, R. D.; Johnson, F.; Abotteen, R. A.; Pore, M. D. (Principal Investigator)

    1979-01-01

    An algorithm is presented for generating uniform chromaticity scale (UCS) imagery from multispectral data. A computer program was written to implement the algorithm, and UCS film products were generated. The colors in the film and their temporal change are consistent with those expected for the particular scaling of Krauth components into the (lab) color space. The film product was not subjected to the practical test of competing with previous transformations. Preliminary examination indicates that the product offers the following possibilities: (1) a single film product that will supplant two film products in current use; (2) improved visibility of data differences in regions in data space that are critical to crop identification; and (3) an analytic route to the determination of data-space transformations that will be optimal for particular discrimination problems.

  18. Comparisons of cloud cover evaluated from LANDSAT imagery and meteorological stations across the British Isles

    NASA Technical Reports Server (NTRS)

    Barrett, E. C. (Principal Investigator); Grant, C. K.

    1976-01-01

    The author has identified the following significant results. This stage of the study has confirmed the initial supposition that LANDSAT data could be analyzed to provide useful data on cloud amount, and that useful light would be thrown thereby on the performance of the ground observer of this aspect of the state of the sky. This study, in comparison with previous studies of a similar nature using data from meteorological satellites, has benefited greatly from the much higher resolution data provided by LANDSAT. This has permitted consideration of not only the overall performance of the surface observer in estimating total cloud cover, but also his performance under different sky conditions.

  19. 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

  20. Fusion of Hyperspectral Hyperion and Multispectral Landsat Time Series Imagery to Improve Results and Capabilities

    NASA Astrophysics Data System (ADS)

    Franks, S.; Neigh, C. S. R.; Campell, P. K.; Sun, G.; Zhang, Q.; Middleton, E.

    2015-12-01

    Since the opening of the USGS archive to no cost Landsat data distribution, time series analysis has grown immensely. With this new era of possibilities, people are able to do science in ways that were never able to be done. The aim of this project is to explore how EO-1 Hyperion data can add value to an already valuable resource. We used a region of interest that had Landsat time series data and coincident Hyperion data to determine how Landsat classifications can be improved by using hyperspectral data with much greater spectral resolution. We hope to find innovative ways to fuse the data sources and come up with new and improved ways to study our changing Earth. With the HyspIRI (Hyperspectral Infrared Imager) satellite being launched shortly, this provides an opportunity to evaluate potential benefits that it may provide when in conjunction with other technologies and missions.

  1. Land cover mapping with emphasis to burnt area delineation using co-orbital ALI and Landsat TM imagery

    NASA Astrophysics Data System (ADS)

    Petropoulos, George P.; Kontoes, Charalambos C.; Keramitsoglou, Iphigenia

    2012-08-01

    In this study, the potential of EO-1 Advanced Land Imager (ALI) radiometer for land cover and especially burnt area mapping from a single image analysis is investigated. Co-orbital imagery from the Landsat Thematic Mapper (TM) was also utilised for comparison purposes. Both images were acquired shortly after the suppression of a fire occurred during the summer of 2009 North-East of Athens, the capital of Greece. The Maximum Likelihood (ML), Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) classifiers were parameterised and subsequently applied to the acquired satellite datasets. Evaluation of the land use/cover mapping accuracy was based on the error matrix statistics. Also, the McNemar test was used to evaluate the statistical significance of the differences between the approaches tested. Derived burnt area estimates were validated against the operationally deployed Services and Applications For Emergency Response (SAFER) Burnt Scar Mapping service. All classifiers applied to either ALI or TM imagery proved flexible enough to map land cover and also to extract the burnt area from other land surface types. The highest total classification accuracy and burnt area detection capability was returned from the application of SVMs to ALI data. This was due to the SVMs ability to identify an optimal separating hyperplane for best classes' separation that was able to better utilise ALI's advanced technological characteristics in comparison to those of TM sensor. This study is to our knowledge the first of its kind, effectively demonstrating the benefits of the combined application of SVMs to ALI data further implying that ALI technology may prove highly valuable in mapping burnt areas and land use/cover if it is incorporated into the development of Landsat 8 mission, planned to be launched in the coming years.

  2. Transformations of Mangrove Forests in Bahia Magdalena, Baja California Sur, Mexico: Two Decade Results Based on Landsat Imageries

    NASA Astrophysics Data System (ADS)

    Suresh Babu, S.; Abdul Rahaman, S.; Muthushankar, G.; Jonathan, M. P.

    2014-12-01

    Mangrove forests which thrive along the tropical and subtropical regions are the most productive ecosystems in the world with a wide range of ecological and economical services to mankind. With the rapid urbanization across the globe, these forests tend to be destroying at an alarming rate. The area of concern for this study, Bahia Magdalena is very important for the economy of the state as nearly 50% of the artisan fisheries are established in the mangrove zone. Henceforth this study is an attempt for a regional assessment and to accurately quantify the mangroves using LANDSAT imageries for over two decades in Bahia Magdalena, Baja California. Satellite imageries from the year 1986 through 2014 were analysed to assess the prolonged changes taking place in and around the mangrove reserve. Using the estimates of land use/cover for all the years, the spatio - temporal data was validated using ArcGIS software. The results revealed that the spatial extent of mangroves are decreasing until 2005 due to the developmental plans such as tourism, shrimp farming and establishment of industries in this part of the country. During the past 10 years (~ after 2005) there is no much change in the area extent of mangrove reserves due to afforestation and conservation efforts. Thus the unbiased dataset generated may be widely used for an improved understanding of the role of mangrove forests in the socio economic aspects, protection from natural disasters, identify possible areas for conservation, restoration and rehabilitation; and improve estimates of the amount of carbon stored in mangrove vegetation and the associated marine environment. Keywords: Mangroves, LANDSAT, Bahia Magdalena, México.

  3. Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China

    NASA Astrophysics Data System (ADS)

    Jin, Cui; Xiao, Xiangming; Dong, Jinwei; Qin, Yuanwei; Wang, Zongming

    2016-03-01

    Information of paddy rice distribution is essential for food production and methane emission calculation. Phenology-based algorithms have been utilized in the mapping of paddy rice fields by identifying the unique flooding and seedling transplanting phases using multi-temporal moderate resolution (500 m to 1 km) images. In this study, we developed simple algorithms to identify paddy rice at a fine resolution at the regional scale using multi-temporal Landsat imagery. Sixteen Landsat images from 2010-2012 were used to generate the 30 m paddy rice map in the Sanjiang Plain, northeast China—one of the major paddy rice cultivation regions in China. Three vegetation indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI), were used to identify rice fields during the flooding/transplanting and ripening phases. The user and producer accuracies of paddy rice on the resultant Landsat-based paddy rice map were 90% and 94%, respectively. The Landsat-based paddy rice map was an improvement over the paddy rice layer on the National Land Cover Dataset, which was generated through visual interpretation and digitalization on the fine-resolution images. The agricultural census data substantially underreported paddy rice area, raising serious concern about its use for studies on food security.

  4. Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China

    PubMed Central

    XIAO, Xiangming; DONG, Jinwei; QIN, Yuanwei; WANG, Zongming

    2016-01-01

    Information of paddy rice distribution is essential for food production and methane emission calculation. Phenology-based algorithms have been utilized in the mapping of paddy rice fields by identifying the unique flooding and seedling transplanting phases using multi-temporal moderate resolution (500 m to 1 km) images. In this study, we developed simple algorithms to identify paddy rice at a fine resolution at the regional scale using multi-temporal Landsat imagery. Sixteen Landsat images from 2010–2012 were used to generate the 30 m paddy rice map in the Sanjiang Plain, northeast China—one of the major paddy rice cultivation regions in China. Three vegetation indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI), were used to identify rice fields during the flooding/transplanting and ripening phases. The user and producer accuracies of paddy rice on the resultant Landsat-based paddy rice map were 90% and 94%, respectively. The Landsat-based paddy rice map was an improvement over the paddy rice layer on the National Land Cover Dataset, which was generated through visual interpretation and digitalization on the fine-resolution images. The agricultural census data substantially underreported paddy rice area, raising serious concern about its use for studies on food security. PMID:27695637

  5. Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China.

    PubMed

    Jin, Cui; Xiao, Xiangming; Dong, Jinwei; Qin, Yuanwei; Wang, Zongming

    2016-03-01

    Information of paddy rice distribution is essential for food production and methane emission calculation. Phenology-based algorithms have been utilized in the mapping of paddy rice fields by identifying the unique flooding and seedling transplanting phases using multi-temporal moderate resolution (500 m to 1 km) images. In this study, we developed simple algorithms to identify paddy rice at a fine resolution at the regional scale using multi-temporal Landsat imagery. Sixteen Landsat images from 2010-2012 were used to generate the 30 m paddy rice map in the Sanjiang Plain, northeast China-one of the major paddy rice cultivation regions in China. Three vegetation indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI), were used to identify rice fields during the flooding/transplanting and ripening phases. The user and producer accuracies of paddy rice on the resultant Landsat-based paddy rice map were 90% and 94%, respectively. The Landsat-based paddy rice map was an improvement over the paddy rice layer on the National Land Cover Dataset, which was generated through visual interpretation and digitalization on the fine-resolution images. The agricultural census data substantially underreported paddy rice area, raising serious concern about its use for studies on food security.

  6. Identification of brome grass infestations in southwest Oklahoma using multi-temporal Landsat imagery

    NASA Astrophysics Data System (ADS)

    Yan, D.; de Beurs, K.

    2013-12-01

    The extensive infestation of brome grasses (Cheatgrass, Rye brome and Japanese brome) in southwest Oklahoma imposes negative impacts on local economy and ecosystem in terms of decreasing crop and forage production and increasing fire risk. Previously proposed methodologies on brome grass detection are found ill-suitable for southwest Oklahoma as a result of similar responses of background vegetation to inter-annual variability of rainfall. In this study, we aim to identify brome grass infestations by detecting senescent brome grasses using the 2011 Cultivated Land Cover Data Sets and the difference Normalized Difference Infrared Index (NDII) derived from multi-temporal Landsat imagery. Landsat imageries acquired on May 18th and June 10th 2013 by Operational Land Imager and Enhanced Thematic Mapper plus were used. The imagery acquisition dates correspond to the peak growth and senescent time of brome grasses, respectively. The difference NDII was calculated by subtracting the NDII image acquired in May from the June NDII image. Our hypotheses is that senescent brome grasses and crop/pasture fields harvested between the two image acquisition dates can be distinguished from background land cover classes because of their increases in NDII due to decreased water absorption by senescent vegetation in the shortwave infrared region. The Cultivated Land Cover Data Sets were used to further separate senescent brome grass patches from newly harvested crop/pasture fields. Ground truth data collected during field trips in June, July and August of 2013 were used to validate the detection results.

  7. Utilization of LANDSAT imagery for mapping vegetation on the millionth scale

    NASA Technical Reports Server (NTRS)

    Williams, D. L.; Coiner, J. C.

    1975-01-01

    A series of test sites were examined to determine if the information content of the LANDSAT imagery that may be obtained of these sites is sufficient to permit their mapping according to the vegetation classification system recently published by Unesco. These sites include examples from the humid tropics, arid and semi-arid subtropics and temperature zones: Western Highlands of Papua New Guinea, Mindoro Island in the Philippines, Great Smoky Mountains of the southeastern United States, East Tennessee Valley, interior of Western Australia, northeastern Uganda, and south-central Kansas. The results of the experiment were presented in the form of vegetation maps and annotated images which serve to illustrate the detectability of various formations. It was concluded that, for the test sites examined, the formations of the Unesco vegetation classification can be satisfactorily distinguished on LANDSAT MSS images, especially when used as color composites and judiciously chosen as to season.

  8. Techniques for the creation of land use maps and tabulations from Landsat imagery

    NASA Technical Reports Server (NTRS)

    Angelici, G. L.; Bryant, N. A.

    1977-01-01

    Methods for creating color thematic maps and land use tabulations, employing both Landsat imagery and computer image processing, are discussed. The system, the Multiple Input Land Use System (MILUS) has been tested in the metropolitan section of Dayton, Ohio. Training areas for land use were first digitized by coordinates and then transformed onto an image of white lines on a black background. This image was added to a Landsat image of the same area. Then multispectral classification was performed. A tape of digitized census tract boundaries was computer interfaced to yield an image of tract boundaries on a background registered to the thematic land-use map. Using a data management system, the data were then used to produce figures for the area and percent of land use in each tract. Future work is expected to convert most of the steps into interactive processing. This would greatly reduce the time needed to edit and register the data sets.

  9. Integrating Landsat Data and High-Resolution Imagery for Applied Conservation Assessment of Forest Cover in Latin American Heterogenous Landscapes

    NASA Astrophysics Data System (ADS)

    Thomas, N.; Rueda, X.; Lambin, E.; Mendenhall, C. D.

    2012-12-01

    Large intact forested regions of the world are known to be critical to maintaining Earth's climate, ecosystem health, and human livelihoods. Remote sensing has been successfully implemented as a tool to monitor forest cover and landscape dynamics over broad regions. Much of this work has been done using coarse resolution sensors such as AVHRR and MODIS in combination with moderate resolution sensors, particularly Landsat. Finer scale analysis of heterogeneous and fragmented landscapes is commonly performed with medium resolution data and has had varying success depending on many factors including the level of fragmentation, variability of land cover types, patch size, and image availability. Fine scale tree cover in mixed agricultural areas can have a major impact on biodiversity and ecosystem sustainability but may often be inadequately captured with the global to regional (coarse resolution and moderate resolution) satellite sensors and processing techniques widely used to detect land use and land cover changes. This study investigates whether advanced remote sensing methods are able to assess and monitor percent tree canopy cover in spatially complex human-dominated agricultural landscapes that prove challenging for traditional mapping techniques. Our study areas are in high altitude, mixed agricultural coffee-growing regions in Costa Rica and the Colombian Andes. We applied Random Forests regression tree analysis to Landsat data along with additional spectral, environmental, and spatial variables to predict percent tree canopy cover at 30m resolution. Image object-based texture, shape, and neighborhood metrics were generated at the Landsat scale using eCognition and included in the variable suite. Training and validation data was generated using high resolution imagery from digital aerial photography at 1m to 2.5 m resolution. Our results are promising with Pearson's correlation coefficients between observed and predicted percent tree canopy cover of .86 (Costa

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

    NASA Astrophysics Data System (ADS)

    Fernandez, Sim Joseph; Milano, Alan

    2016-07-01

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

  11. A comparison of Spectral Angle Mapper and Artificial Neural Network classifiers combined with Landsat TM imagery analysis for obtaining burnt area mapping.

    PubMed

    Petropoulos, George P; Vadrevu, Krishna Prasad; Xanthopoulos, Gavriil; Karantounias, George; Scholze, Marko

    2010-01-01

    Satellite remote sensing, with its unique synoptic coverage capabilities, can provide accurate and immediately valuable information on fire analysis and post-fire assessment, including estimation of burnt areas. In this study the potential for burnt area mapping of the combined use of Artificial Neural Network (ANN) and Spectral Angle Mapper (SAM) classifiers with Landsat TM satellite imagery was evaluated in a Mediterranean setting. As a case study one of the most catastrophic forest fires, which occurred near the capital of Greece during the summer of 2007, was used. The accuracy of the two algorithms in delineating the burnt area from the Landsat TM imagery, acquired shortly after the fire suppression, was determined by the classification accuracy results of the produced thematic maps. In addition, the derived burnt area estimates from the two classifiers were compared with independent estimates available for the study region, obtained from the analysis of higher spatial resolution satellite data. In terms of the overall classification accuracy, ANN outperformed (overall accuracy 90.29%, Kappa coefficient 0.878) the SAM classifier (overall accuracy 83.82%, Kappa coefficient 0.795). Total burnt area estimates from the two classifiers were found also to be in close agreement with the other available estimates for the study region, with a mean absolute percentage difference of ≈ 1% for ANN and ≈ 6.5% for SAM. The study demonstrates the potential of the examined here algorithms in detecting burnt areas in a typical Mediterranean setting.

  12. A Comparison of Spectral Angle Mapper and Artificial Neural Network Classifiers Combined with Landsat TM Imagery Analysis for Obtaining Burnt Area Mapping

    PubMed Central

    Petropoulos, George P.; Vadrevu, Krishna Prasad; Xanthopoulos, Gavriil; Karantounias, George; Scholze, Marko

    2010-01-01

    Satellite remote sensing, with its unique synoptic coverage capabilities, can provide accurate and immediately valuable information on fire analysis and post-fire assessment, including estimation of burnt areas. In this study the potential for burnt area mapping of the combined use of Artificial Neural Network (ANN) and Spectral Angle Mapper (SAM) classifiers with Landsat TM satellite imagery was evaluated in a Mediterranean setting. As a case study one of the most catastrophic forest fires, which occurred near the capital of Greece during the summer of 2007, was used. The accuracy of the two algorithms in delineating the burnt area from the Landsat TM imagery, acquired shortly after the fire suppression, was determined by the classification accuracy results of the produced thematic maps. In addition, the derived burnt area estimates from the two classifiers were compared with independent estimates available for the study region, obtained from the analysis of higher spatial resolution satellite data. In terms of the overall classification accuracy, ANN outperformed (overall accuracy 90.29%, Kappa coefficient 0.878) the SAM classifier (overall accuracy 83.82%, Kappa coefficient 0.795). Total burnt area estimates from the two classifiers were found also to be in close agreement with the other available estimates for the study region, with a mean absolute percentage difference of ∼1% for ANN and ∼6.5% for SAM. The study demonstrates the potential of the examined here algorithms in detecting burnt areas in a typical Mediterranean setting. PMID:22294909

  13. Deriving winds for hurricanes using short interval satellite imagery

    NASA Technical Reports Server (NTRS)

    Gentry, R. C.; Rodgers, E.; Shenk, W. E.; Oliver, V.

    1977-01-01

    Results are presented for a study program designed to develop a better means of obtaining wind data needed by hurricane forecasters and to determine the optimum space and time resolution of satellite data used to obtain such winds. The discussion covers cloud tracking with an image display and manipulation system and analysis of IR imagery of Hurricane Eloise. It is shown that greater resolution in time and space of satellite imagery made it possible to derive up to six times as many low-level winds in a hurricane case, to eliminate 'bad winds' caused by mistaking cloud growth for cloud motion, and to remove ambiguities that would have caused difficulty in tracking clouds using only the imagery taken at 30-min intervals. It is suggested to use short-interval imagery (less than 10 min) for wind determination for future research in areas of tropical cyclones.

  14. Monitoring Urbanization Processes from Space: Using Landsat Imagery to Detect Built-Up Areas at Scale

    NASA Astrophysics Data System (ADS)

    Goldblatt, R.; You, W.; Hanson, G.; Khandelwal, A. K.

    2016-12-01

    Urbanization is one of the most fundamental trends of the past two centuries and a key force shaping almost all dimensions of modern society. Monitoring the spatial extent of cities and their dynamics be means of remote sensing methods is crucial for many research domains, as well as to city and regional planning and to policy making. Yet the majority of urban research is being done in small scales, due, in part, to computational limitation. With the increasing availability of parallel computing platforms with large storage capacities, such as Google Earth Engine (GEE), researchers can scale up the spatial and the temporal units of analysis and investigate urbanization processes over larger areas and over longer periods of time. In this study we present a methodology that is designed to capture temporal changes in the spatial extent of urban areas at the national level. We utilize a large scale ground-truth dataset containing examples of "built-up" and "not built-up" areas from across India. This dataset, which was collected based on 2016 high-resolution imagery, is used for supervised pixel-based image classification in GEE. We assess different types of classifiers and inputs and demonstrate that with Landsat 8 as the classifier`s input, Random Forest achieves a high accuracy rate of around 87%. Although performance with Landsat 8 as the input exceeds that of Landsat 7, with the addition of several per-pixel computed indices to Landsat 7 - NDVI, NDBI, MNDWI and SAVI - the classifier`s sensitivity improves by around 10%. We use Landsat 7 to detect temporal changes in the extent of urban areas. The classifier is trained with 2016 imagery as the input - for which ground truth data is available - and is used the to detect urban areas over the historical imagery. We demonstrate that this classification produces high quality maps of urban extent over time. We compare the classification result with numerous datasets of urban areas (e.g. MODIS, DMSP-OLS and WorldPop) and

  15. Enhancement of LANDSAT imagery by combination of multispectral classification and principal component analysis. [in France

    NASA Technical Reports Server (NTRS)

    Fontanel, A.; Blanchet, C.; Lallemand, C.

    1975-01-01

    Digital enhancement of LANDSAT imagery was obtained by application of principal component analysis separately on each of the classes previously determined in a multispectral classification step. Each part of the image is thus enhanced whatever its spectral signature may be. A document was obtained which is a synthesis between a conventional image and an ordinary computerized classification. The interpreter can, at the same time, take into account not only the classification but also other features such as context and structure. An example is discussed with the help of geological interpretation.

  16. EROS main image file - A picture perfect database for Landsat imagery and aerial photography

    NASA Technical Reports Server (NTRS)

    Jack, R. F.

    1984-01-01

    The Earth Resources Observation System (EROS) Program was established by the U.S. Department of the Interior in 1966 under the administration of the Geological Survey. It is primarily concerned with the application of remote sensing techniques for the management of natural resources. The retrieval system employed to search the EROS database is called INORAC (Inquiry, Ordering, and Accounting). A description is given of the types of images identified in EROS, taking into account Landsat imagery, Skylab images, Gemini/Apollo photography, and NASA aerial photography. Attention is given to retrieval commands, geographic coordinate searching, refinement techniques, various online functions, and questions regarding the access to the EROS Main Image File.

  17. Large Area Crop Inventory Experiment (LACIE). Detection of episodic phenomena on LANDSAT imagery. [Kansas

    NASA Technical Reports Server (NTRS)

    Chesnutwood, C. M. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. Episodic phenomena such as rainfall shortly before data pass, thin translucent clouds, cloud shadows, and aircraft condensation trails and their shadows are responsible for changes in the spectral reflectivities of some surfaces. These changes are readily detected on LANDSAT full-frame imagery. Histograms of selected areas in Kansas show a distinct decrease in mean radiance values, but also, an increase in scene contrast, in areas where recent rains had occurred. Histograms from a few individual fields indicate that the mean radiance values for winter wheat followed a different trend after a rainfall than alfalfa or grasses.

  18. EROS main image file - A picture perfect database for Landsat imagery and aerial photography

    NASA Technical Reports Server (NTRS)

    Jack, R. F.

    1984-01-01

    The Earth Resources Observation System (EROS) Program was established by the U.S. Department of the Interior in 1966 under the administration of the Geological Survey. It is primarily concerned with the application of remote sensing techniques for the management of natural resources. The retrieval system employed to search the EROS database is called INORAC (Inquiry, Ordering, and Accounting). A description is given of the types of images identified in EROS, taking into account Landsat imagery, Skylab images, Gemini/Apollo photography, and NASA aerial photography. Attention is given to retrieval commands, geographic coordinate searching, refinement techniques, various online functions, and questions regarding the access to the EROS Main Image File.

  19. Chernobyl Doses. Volume 2. Conifer Stress near Chernobyl Derived from Landsat Imagery

    DTIC Science & Technology

    1992-12-01

    Defense Nuclear Agency Alexandria, VA 22310-3398 AD-A259 085 S.... IiilII|IlH~l D.A-TR-92-3,,.v2 Chernobyl Doses Volume 2-Conifer Stress Near... Chernobyl Derived from Landsat Imagery Gene E. McClellan Terrence H. Hemmer Ronald N. DeWitt Pacific-Sierra Research Corporation 12340 Santa Monica Boulevard...870929 - 920228 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Chernobyl Doses C - DNA 001-87-C-0104 Volume 2- Conifer Stress Near Chernobyl Derived from

  20. The effects of war on land-use/land-cover change: An analysis of Landsat imagery for northeast Bosnia

    NASA Astrophysics Data System (ADS)

    Witmer, Frank D. W.

    The use of satellite technology by military planners has a relatively long history as a tool of warfare, but little research has used satellite technology to study the effects of war. This research addresses this gap by applying satellite remote sensing imagery to study the effects of war on land-use/land-cover change in northeast Bosnia. The war in Bosnia, 1992-1995, resulted in over 100,000 deaths, many more wounded, and the mass displacement of nearly half the population of 4.2 million. When combined with the destruction of much of the transportation infrastructure and housing stock, widespread mine placement, and loss of agricultural machinery, the impacts to both the people and land were dramatic. Though the most severe war impacts are visible at local scales (e.g. destroyed buildings), this study focuses on impacts to agricultural land, a larger scale visible to satellite sensors. Multispectral Landsat Thematic Mapper (TM) data (30m pixels) from before and during the war in addition to recent imagery from 2004/05 were used to detect abandoned agricultural land. The satellite images were co-registered to enable a perpixel analysis of changes based on the statistical properties of the pixels using multiple change detection methods. Ground reference data were collected in May of 2006 at survey sites selected using a stratified random sampling approach based on the derived map of abandoned agricultural land. Fine resolution (60cm) Quickbird imagery was also used to verify the accuracy of the classification. The remote sensing analysis results were then used to test two hypotheses related to war outcomes: (a) land abandonment is due to wartime minefields and (b) land abandonment is greater in pre-war Croat areas and areas where ethnic cleansing was heaviest. The effects of minefields on land abandonment was first tested in a geographic information system (GIS), and then by using multiple regression models that account for spatial autocorrelation among observations

  1. Vegetation Cover Change in Yosemite National Park (California) Detected using Landsat Satellite Image Analysis

    NASA Technical Reports Server (NTRS)

    Potter, Christopher

    2015-01-01

    Landsat image analysis over the past 20+ years showed that consistent increases in the satellite normalized difference vegetation index (NDVI) during relatively dry years were confined to large wildfire areas that burned in the late 1980s and 1990s.

  2. Oceanographic applications of color-enhanced satellite imageries.

    NASA Technical Reports Server (NTRS)

    Szekielda, K.-H.; Mitchell, W. F.

    1972-01-01

    Black and white infrared imageries obtained from satellites over the oceans were transformed into color presentations. Investigations in different regions (Persian Gulf, Arabian Coast, Somali Coast and the Northwest Coast of Australia) revealed that temperature gradients and temperature differences of two degrees Celsius can be displayed by the color process from the imageries. This data display can be used for a rapid analysis of information obtained with an APT station.

  3. [Cross-comparison between ASTER and Landsat-7 ETM+ multispectral imagery].

    PubMed

    Li, Chun-hua; Xu, Han-qiu; Chen, Li-cong

    2010-09-01

    Up to present, no study has been published with respect to the cross-comparison between ASTER and Landsat-7 ETM+ imagery. Therefore, the present paper has implemented the complementary study on the images between these two sensors. The study firstly conducted the sensors characteristics comparison, including orbit characteristic, sensor scanning mode and imagery spectral characteristic. Further comparison was implemented to get the relation equations between corresponding VNIR and SWIR bands of these two sensors based on the apparent reflectance of the three pairs of synchronization images and large common ground regions. The validation has been done to verify the effectiveness of the proposed corresponding bands relation equations and matching coefficients. The result shows that the provided relation equations have high accuracy.

  4. Processing of satellite imagery at the National Environmental Satellite Service

    NASA Technical Reports Server (NTRS)

    Crowe, M.

    1977-01-01

    The National Environmental Satellite Service (NESS) image product processing system is described. Other topics discussed include: (1) image processing of polar-orbiter satellite data; (2) image processing of geostationary satellite data; and (3) quality assurance and product monitoring.

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

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  6. HCMM and LANDSAT imagery for geological mapping in northwest Queensland. [Australia

    NASA Technical Reports Server (NTRS)

    Cole, M. M.; Edmiston, D. J. (Principal Investigator)

    1980-01-01

    The author has identified the following significant results. Photographic prints made from negatives of day-visible and day-IR cover of selected areas were compared with enhanced color composites generated from LANDSAT computer compatible tapes and films. For geological mapping purposes, HCMM imagery is of limited value. While large scale features like the Mikadoodi anticlinorium, contrasting lithological units, and major structures may be distinguished on day-visible and day-IR cover, the spectral bands are too broad and the resolution too coarse even for regional mapping purposes. The imagery appears to be most useful for drainage studies. Where drainage is seasonal, sequential imagery permits monitoring of broad scale water movement while the day-IR imagery yields valuable information on former channels. In plains areas subject to periodic change of stream courses, comparable IR cover at a larger scale would offer considerable potential for reconstruction of former drainage patterns essential for the correct interpretation of geochemical data relative to mineral exploration.

  7. Classification of small agricultural fields using combined Landsat-8 and RapidEye imagery: case study of northern Serbia

    NASA Astrophysics Data System (ADS)

    Crnojević, Vladimir; Lugonja, Predrag; Brkljač, Branko; Brunet, Borislav

    2014-01-01

    A pixel-based cropland classification study based on the fusion of data from satellite images with different resolutions is presented. It is based on a time series of multispectral images acquired at different resolutions by different imaging instruments, Landsat-8 and RapidEye. The proposed data fusion method capabilities are explored with the aim of overcoming the shortcomings of different instruments in the particular cropland classification scenario characterized by the very small size of crop fields over the chosen agricultural region situated in the plains of Vojvodina in northern Serbia. This paper proposes a data fusion method that is successfully utilized in combination with arobust random forest classifier in improving the overall classification performance, as well as in enabling application of satellite imagery with a coarser spatial resolution in the given specific cropland classification task. The developed method effectively exploits available data and provides an improvement over the existing pixel-based classification approaches through the combination of different data sources. Another contribution of this paper is the employment of crowdsourcing in the process of reference data collection via dedicated smartphone application.

  8. Fire seasonality changes in Côte d'Ivoire revealed through Landsat imagery

    NASA Astrophysics Data System (ADS)

    Pavlovic, N. R.; Bassett, T. J.; Greenberg, J. A.

    2014-12-01

    Fire plays a significant role in the savanna systems of West Africa, where a large proportion of the landscape burns annually. Previous research has suggested that shifts in land use and agricultural practices have modified the fire regime of Cote d'Ivoire over the past 30 years. Specifically, increasing pastoralism in north-central Cote d'Ivoire has been shown to coincide with a shift in fire seasonality toward fires earlier in the dry season. We investigated decadal trends in monthly fire occurrence across Cote d'Ivoire to determine whether similar processes of shifting fire seasonality are at play at the national scale. We assessed fire occurrence using remotely sensed Landsat imagery covering the entire extent of Cote d'Ivoire across a 30-year period from 1984 to 2014. The fine resolution of Landsat imagery makes possible the detection of small fires that commonly occur in heavily managed West African savannas. We investigated trends in the timing of both active fires and burned areas. Active fires were detected using shortwave infrared emissions of fire, and burned areas were identified based on spectral and temporal patterns distinctive to burn scars. The timing of fire occurrence influences fire intensity, and shifting fire seasonality has implications for land cover and terrestrial carbon budgets. Our findings point to temporal-spatial shifts in fire regimes over the past three decades and advance understanding of the contribution of West Africa's savannas to global greenhouse gas emissions.

  9. Spatio-Temporal Analysis of Forest Fire Risk and Danger Using LANDSAT Imagery

    PubMed Central

    Sağlam, Bülent; Bilgili, Ertuğrul; Durmaz, Bahar Dinç; Kadıoğulları, Ali İhsan; Küçük, Ömer

    2008-01-01

    Computing fire danger and fire risk on a spatio-temporal scale is of crucial importance in fire management planning, and in the simulation of fire growth and development across a landscape. However, due to the complex nature of forests, fire risk and danger potential maps are considered one of the most difficult thematic layers to build up. Remote sensing and digital terrain data have been introduced for efficient discrete classification of fire risk and fire danger potential. In this study, two time-series data of Landsat imagery were used for determining spatio-temporal change of fire risk and danger potential in Korudag forest planning unit in northwestern Turkey. The method comprised the following two steps: (1) creation of indices of the factors influencing fire risk and danger; (2) evaluation of spatio-temporal changes in fire risk and danger of given areas using remote sensing as a quick and inexpensive means and determining the pace of forest cover change. Fire risk and danger potential indices were based on species composition, stand crown closure, stand development stage, insolation, slope and, proximity of agricultural lands to forest and distance from settlement areas. Using the indices generated, fire risk and danger maps were produced for the years 1987 and 2000. Spatio-temporal analyses were then realized based on the maps produced. Results obtained from the study showed that the use of Landsat imagery provided a valuable characterization and mapping of vegetation structure and type with overall classification accuracy higher than 83%. PMID:27879918

  10. Improving estimates of streamflow characteristics using LANDSAT-1 (ERTS-1) imagery. [Delmarva Peninsula

    NASA Technical Reports Server (NTRS)

    Hollyday, E. F. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. Streamflow characteristics in the Delmarva Peninsula derived from the records of daily discharge of 20 gaged basins are representative of the full range in flow conditions and include all of those commonly used for design or planning purposes. They include annual flood peaks with recurrence intervals of 2, 5, 10, 25, and 50 years, mean annual discharge, standard deviation of the mean annual discharge, mean monthly discharges, standard deviation of the mean monthly discharges, low-flow characteristics, flood volume characteristics, and the discharge equalled or exceeded 50 percent of the time. Streamflow and basin characteristics were related by a technique of multiple regression using a digital computer. A control group of equations was computed using basin characteristics derived from maps and climatological records. An experimental group of equations was computed using basin characteristics derived from LANDSAT imagery as well as from maps and climatological records. Based on a reduction in standard error of estimate equal to or greater than 10 percent, the equations for 12 stream flow characteristics were substantially improved by adding to the analyses basin characteristics derived from LANDSAT imagery.

  11. Identification and spectral characteristics of hydrothermal alteration on Landsat TM imagery of north Chile

    NASA Technical Reports Server (NTRS)

    Baker, Michael C. W.

    1987-01-01

    This study examines the application of Landsat TM data to the identification of hydrothermal alteration in the arid terrain of the El Salvador region of north Chile. Numerical reflectance values were extracted from the digital Landsat TM data for a variety of rock surfaces, including four parts of the El Salvador gossan, for each of six spectral bands. These reflectance values were analyzed statistically in order to select the three spectral bands, combined as a color composite image, that are most efficient in discriminating different varieties of alteration and for general geological interpretation. The most cost effective composite image for this area is a combination of bands 1, 4 and 7 as the blue, green and red components respectively, with simple contrast enhancement. This image is superior to some much more expensive enhancement techniques and allows unambiguous identification of areas of hydrothermal alteration larger than about 50 m. The display includes a practical guide to the use of Landsat TM imagery for volcanic gold exploration.

  12. Spatiotemporal Water body Change Detection Using Multi-temporal Landsat Imagery: Case Studies of Lake Enriquillo and Lake Azuei

    NASA Astrophysics Data System (ADS)

    Moknatian, M.; Piasecki, M.

    2015-12-01

    One of the most valuable sources of data is Landsat imagery when in-situ data is absent. The Landsat satellite observations are also among the most widely used sources of data in remote sensing of water resources. The purpose of this study is to investigate the water body changes of the two biggest lakes of Hispaniola Island for the past 30 years, using remote sensing techniques when there are no in-situ measurements available. Lake Azuei in Haiti and Lake Enriquillo in the Dominican Republic both have been changing constantly in their quality and quantity. Unexpected growth of the two lakes has been observed since 2003, leaving the area with many ecological and socio-economic complications affecting thousands of local peoples' lives during the past 12 years. Such phenomena are expected to be due to the influence of climate change on the lakes. One of the main key components to investigate this hypothesis is first to detect and map the patterns of changes of the lakes over time. 100 Landsat 4-5 TM and 192 Landsat 7-ETM+ scenes acquired from 1984 to 2014 were analyzed to investigate the surface area changes for each lake. Almost 60% of the images are fully or partially cloudy which makes it difficult to picture the full extent of the lakes and consequently calculate their surface area. Moreover, 65% of images have gaps due to the failure of the ETM+ scan line corrector (SLC) since 2003 which adds to the problem. To solve this problem, we developed an algorithm to identify and classify clouds and cloud shadows using blue and Thermal bands; remove them from the scene and then detect water body using Normalized Difference Water Index (NDWI) using Green and NIR bands. The next step was to fill the gaps which were created after removing clouds and stripes from the scenes. Toward this end, we decided to complete each image using the previous or next available image. 95% of the images have been processed and surface area has been calculated for both lakes. Using the

  13. Classifying and monitoring water quality by use of satellite imagery

    NASA Technical Reports Server (NTRS)

    Scherz, J. P.; Crane, D. R.; Rogers, R. H.

    1975-01-01

    A technique in which LANDSAT measurements from very clear lakes are subtracted from measurements from other lakes in order to remove atmospheric and surface noise effects to obtain a residual signal dependent only on the material suspended in the water is described. This residual signal is used by the Multispectral Data Analysis System as a basis for producing color categorized imagery showing lakes by type and concentration of suspended material. Several hundred lakes in the Madison and Spooner, Wisconsin area were categorized for tannin or non-tannin waters and for the degree of algae, silt, weeds, and bottom effects.

  14. Preliminary Classification of Water Areas Within the Atchafalaya Basin Floodway System by Using Landsat Imagery

    USGS Publications Warehouse

    Allen, Yvonne C.; Constant, Glenn C.; Couvillion, Brady R.

    2008-01-01

    The southern portion of the Atchafalaya Basin Floodway System (ABFS) is a large area (2,571 km2) in south central Louisiana bounded on the east and west sides by a levee system. The ABFS is a sparsely populated area that includes some of the Nation's most significant extents of bottomland hardwoods, swamps, bayous, and backwater lakes, holding a rich abundance and diversity of terrestrial and aquatic species. The seasonal flow of water through the ABFS is critical to maintaining its ecological integrity. Because of strong interdependencies among species, habitat quality, and water flow in the ABFS, there is a need to better define the paths by which water moves at various stages of the hydrocycle. Although river level gages have collected a long historical record of water level variation, very little synoptic information has been available regarding the distribution and character of water at more remote locations in the basin. Most water management plans for the ABFS strive to improve water quality by increasing water flow and circulation from the main stem of the Atchafalaya River into isolated areas. To describe the distribution of land and water on a basin-wide scale, we chose to use Landsat 5 and Landsat 7 imagery to determine the extent of water distribution from 1985 to 2006 and at a variety of river stages. Because the visual signature of river water is high turbidity, we also used Landsat imagery to describe the distribution of turbid water in the ABFS. The ability to track water flow patterns by tracking turbid waters will enhance the characterization of water movement and aid in planning.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  16. Determination of stack plume properties from satellite imagery

    NASA Technical Reports Server (NTRS)

    Staylor, W. F.

    1977-01-01

    LANDSAT imagery data were analyzed to determine the quantitative properties of a stack plume emitted from a moderate-sized pulp mill. Overlapping, consecutive-day MSS data provided plume/no plume radiances upwelling from the area of interest. These values from both the plume and its shadow were used to evaluate plume radius, height, particle concentration and scattering function, and total particle loading. Imagery data from a 10 by 10 km region in the vicinity of the mill were normalized to correct for minor atmospheric, solar and viewing angle changes for the two observation days, and cloud shadow data were used to evaluate sky radiance. The effects of the Sun angle, surface reflectance, SNR and spatial resolution are treated in the paper.

  17. Using Landsat satellite data to support pesticide exposure assessment in California.

    PubMed

    Maxwell, Susan K; Airola, Matthew; Nuckols, John R

    2010-09-16

    The recent U.S. Geological Survey policy offering Landsat satellite data at no cost provides researchers new opportunities to explore relationships between environment and health. The purpose of this study was to examine the potential for using Landsat satellite data to support pesticide exposure assessment in California. We collected a dense time series of 24 Landsat 5 and 7 images spanning the year 2000 for an agricultural region in Fresno County. We intersected the Landsat time series with the California Department of Water Resources (CDWR) land use map and selected field samples to define the phenological characteristics of 17 major crop types or crop groups. We found the frequent overpass of Landsat enabled detection of crop field conditions (e.g., bare soil, vegetated) over most of the year. However, images were limited during the winter months due to cloud cover. Many samples designated as single-cropped in the CDWR map had phenological patterns that represented multi-cropped or non-cropped fields, indicating they may have been misclassified. We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.

  18. Using Landsat satellite data to support pesticide exposure assessment in California

    PubMed Central

    2010-01-01

    Background The recent U.S. Geological Survey policy offering Landsat satellite data at no cost provides researchers new opportunities to explore relationships between environment and health. The purpose of this study was to examine the potential for using Landsat satellite data to support pesticide exposure assessment in California. Methods and Results We collected a dense time series of 24 Landsat 5 and 7 images spanning the year 2000 for an agricultural region in Fresno County. We intersected the Landsat time series with the California Department of Water Resources (CDWR) land use map and selected field samples to define the phenological characteristics of 17 major crop types or crop groups. We found the frequent overpass of Landsat enabled detection of crop field conditions (e.g., bare soil, vegetated) over most of the year. However, images were limited during the winter months due to cloud cover. Many samples designated as single-cropped in the CDWR map had phenological patterns that represented multi-cropped or non-cropped fields, indicating they may have been misclassified. Conclusions We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation. PMID:20846438

  19. Mapping areas invaded by Prosopis juliflora in Somaliland on Landsat 8 imagery

    NASA Astrophysics Data System (ADS)

    Rembold, Felix; Leonardi, Ugo; Ng, Wai-Tim; Gadain, Hussein; Meroni, Michele; Atzberger, Clement

    2015-10-01

    Prosopis juliflora is a fast growing tree species originating from South and Central America with a high invasion potential in semi-arid areas around the globe. It was introduced to East Africa for the stabilization of dune systems and for providing fuel wood after prolonged droughts and deforestation in the 1970s and 1980s. In many dry lands in East Africa the species has expanded rapidly and has become challenging to control. The species generally starts its colonization on deep soils with high water availability while in later stages or on poorer soils, its thorny thickets expand into drier grasslands and rangelands. Abandoned or low input farmland is also highly susceptible for invasion as P. juliflora has competitive advantages to native species and is extremely drought tolerant. In this work we describe a rapid approach to detect and map P. juliflora invasion at country level for the whole of Somaliland. Field observations were used to delineate training sites for a supervised classification of Landsat 8 imagery collected during the driest period of the year (i.e., from late February to early April). The choice of such a period allowed to maximise the spectral differences between P. juliflora and other species present in the area, as P. juliflora tends to maintain a higher vigour and canopy water content than native vegetation, when exposed to water stress. The results of our classification map the current status of invasion of Prosopis in Somaliland showing where the plant is invading natural vegetation or agricultural areas. These results have been verified for two spatial subsets of the whole study area with very high resolution (VHR) imagery, proving that Landsat 8 imagery is highly adequate to map P. juliflora. The produced map represents a baseline for understanding spatial distribution of P. juliflora across Somaliland but also for change detection and monitoring of long term dynamics in support to P. juliflora management and control activities.

  20. Automated mapping of sub-pixel impervious surface area from landsat imagery

    NASA Astrophysics Data System (ADS)

    Kamphaus, Benjamin D.

    The past few decades have seen rapid, global urbanization. Remotely sensed imagery is the best source of information about the extent of urbanization, but extracting urban extent from remotely sensed imagery is often an intensive, supervised task for analysts to perform. This project presents a fully automated method to extract impervious surface area (ISA), an important component of urban expansion, from Landsat TM and similar sensors. These moderate resolution sensors have a multi-decade collection archive, sub-monthly revisit rate and have served as a model for other national and commercial programs. The unsupervised methodology proposed herein, termed the PEEL process (pre-processing, endmember extraction and labeling), is an SMA (spectral mixture analysis) technique that uses as inputs endmembers that have been labeled by a SVM (support vector machine) classification through the fusion of the PanTex GLCM-based texture measure and endmembers drawn from the SMACC (sequential maximum angle convex cone) algorithm. Labels are provided to endmembers with an overall accuracy of 94% across 13 Landsat scenes from different sensor types and of several regions and urban forms. Multiple unmixing methods are tested, with BNMESMA (brightness normalized multiple endmember spectral mixture analysis) performing the best with a RMSE of 0.276. Caution is given regarding the value of RMSE as a metric for comparing method accuracy and more detailed error metrics are introduced. The method is shown as a viable template for mapping ISA across multiple scenes and as a useful framework for analyzing large archives of imagery with a common, automatable methodology.

  1. 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...

  2. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 7 Agriculture 6 2012-01-01 2012-01-01 false Availability of satellite imagery. 611.22 Section 611.22 Agriculture Regulations of the Department of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Cartographic Operations...

  3. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 7 Agriculture 6 2014-01-01 2014-01-01 false Availability of satellite imagery. 611.22 Section 611.22 Agriculture Regulations of the Department of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Cartographic Operations...

  4. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 6 2011-01-01 2011-01-01 false Availability of satellite imagery. 611.22 Section 611.22 Agriculture Regulations of the Department of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Cartographic Operations...

  5. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 7 Agriculture 6 2013-01-01 2013-01-01 false Availability of satellite imagery. 611.22 Section 611.22 Agriculture Regulations of the Department of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Cartographic Operations...

  6. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Availability of satellite imagery. 611.22 Section 611.22 Agriculture Regulations of the Department of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Cartographic Operations...

  7. Satellite imagery tracks currents in Gulf of Mexico

    SciTech Connect

    Huh, O.K. . Coastal Studies Inst.); Schaudt, K.J. )

    1990-05-07

    With the onset of drilling in the Gulf of Mexico at water depths in excess of 300m, detection and location of the boundaries of high speed current zones has become important in preventing downtime in drilling and production operations. This article reports on the use of satellite imagery to track currents in the Gulf of Mexico.

  8. 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...

  9. Burn severity mapping using simulation modeling and satellite imagery

    Treesearch

    Eva C. Karau; Robert E. Keane

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Graesser, J.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  12. Detection of rotating thunderstorms using satellite imagery

    NASA Technical Reports Server (NTRS)

    Anderson, C. E.; Schlesinger, R.

    1985-01-01

    In the case of the Carolina tornadoes, researchers prepared visible and IR GOES imagery covering the period 2000 Z when the storm entered South Carolina from Georgia until it exited North Carolina at 0200 Z into Virginia. The GOES IR imagery clearly demonstrated that this storm was imbedded in a continuously propagating mesolow with a well defined cold dome. The ground damage track paralleled exactly with the cold dome throughout the storm's life across the Carolinas. There were no advanced very high resolution radiometer (AVHRR) data during the period to allow researchers to inspect the cloud top for warm temperature anomalies. The Carolina storm did exhibit rightward deviating outflow which was oriented about 60 degrees to the 300 mb streamlines. The tornadoes of April 27, 1984 were part of a tornado producing cold front which stretched from Oklahoma to Minnesota. As the front moved eastward it touched off numerous tornadoes in eastern Wisconsin. GOES imagery for this data was prepared and it was strikingly clear that all along the North-South oriented squall line, the individual tunderstorms had cirrus plumes which had remarkable right deviation to the upper air flow. Unlike the Carolina long track supercell cell-mesolow system, these storms were isolated individual thunderstorms which touched off at least 16 tornadoes in eastern Wisconsin stretching from the Milwaukee area on the south to Vilas County in the north. The monster tornado of June 8, 1984 which leveled 90 percent of the village of Barneveld, Wisconsin and killed 9 persons is also discussed.

  13. Detection of rotating thunderstorms using satellite imagery

    NASA Technical Reports Server (NTRS)

    Anderson, C. E.; Schlesinger, R.

    1985-01-01

    In the case of the Carolina tornadoes, researchers prepared visible and IR GOES imagery covering the period 2000 Z when the storm entered South Carolina from Georgia until it exited North Carolina at 0200 Z into Virginia. The GOES IR imagery clearly demonstrated that this storm was imbedded in a continuously propagating mesolow with a well defined cold dome. The ground damage track paralleled exactly with the cold dome throughout the storm's life across the Carolinas. There were no advanced very high resolution radiometer (AVHRR) data during the period to allow researchers to inspect the cloud top for warm temperature anomalies. The Carolina storm did exhibit rightward deviating outflow which was oriented about 60 degrees to the 300 mb streamlines. The tornadoes of April 27, 1984 were part of a tornado producing cold front which stretched from Oklahoma to Minnesota. As the front moved eastward it touched off numerous tornadoes in eastern Wisconsin. GOES imagery for this data was prepared and it was strikingly clear that all along the North-South oriented squall line, the individual tunderstorms had cirrus plumes which had remarkable right deviation to the upper air flow. Unlike the Carolina long track supercell cell-mesolow system, these storms were isolated individual thunderstorms which touched off at least 16 tornadoes in eastern Wisconsin stretching from the Milwaukee area on the south to Vilas County in the north. The monster tornado of June 8, 1984 which leveled 90 percent of the village of Barneveld, Wisconsin and killed 9 persons is also discussed.

  14. A TECHNIQUE FOR ASSESSING THE ACCURACY OF SUB-PIXEL IMPERVIOUS SURFACE ESTIMATES DERIVED FROM LANDSAT TM IMAGERY

    EPA Science Inventory

    We developed a technique for assessing the accuracy of sub-pixel derived estimates of impervious surface extracted from LANDSAT TM imagery. We utilized spatially coincident
    sub-pixel derived impervious surface estimates, high-resolution planimetric GIS data, vector--to-
    r...

  15. A TECHNIQUE FOR ASSESSING THE ACCURACY OF SUB-PIXEL IMPERVIOUS SURFACE ESTIMATES DERIVED FROM LANDSAT TM IMAGERY

    EPA Science Inventory

    We developed a technique for assessing the accuracy of sub-pixel derived estimates of impervious surface extracted from LANDSAT TM imagery. We utilized spatially coincident
    sub-pixel derived impervious surface estimates, high-resolution planimetric GIS data, vector--to-
    r...

  16. Landsat: building a strong future

    USGS Publications Warehouse

    Loveland, Thomas R.; Dwyer, John L.

    2012-01-01

    Conceived in the 1960s, the Landsat program has experienced six successful missions that have contributed to an unprecedented 39-year record of Earth Observations that capture global land conditions and dynamics. Incremental improvements in imaging capabilities continue to improve the quality of Landsat science data, while ensuring continuity over the full instrument record. Landsats 5 and 7 are still collecting imagery. The planned launch of the Landsat Data Continuity Mission in December 2012 potentially extends the Landsat record to nearly 50 years. The U.S. Geological Survey (USGS) Landsat archive contains nearly three million Landsat images. All USGS Landsat data are available at no cost via the Internet. The USGS is committed to improving the content of the historical Landsat archive though the consolidation of Landsat data held in international archives. In addition, the USGS is working on a strategy to develop higher-level Landsat geo- and biophysical datasets. Finally, Federal efforts are underway to transition Landsat into a sustained operational program within the Department of the Interior and to authorize the development of the next two satellitesLandsats 9 and 10.

  17. Investigating the Dynamics of Wandoo Crown Decline with Time Series Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Zdunic, K.; Behn, G.; van Dongen, R.

    2012-08-01

    In the forests of south west Western Australia dramatic declines in tree health have been observed in recent years. The species Eucalyptus wando has exhibited loss of crown foliage in increasing stages of severity; this condition is referred to as wandoo crown decline and can lead to death. Determining the extent and timing of these declines is difficult on the ground due to the large distribution of E. wandoo and the observation of tree declines at a range of locations and dates over the last 40 years. Understanding the distribution, severity and timing of these declines is essential to the identification of the causes of these impacts. Investigation of time series Landsat imagery can inform on locations of crown foliage loss and the time periods these losses occurred in. Applying a vegetation index to a 20 year sequence of imagery enabled periods of decline to be identified. Employment of trend analysis of four date time series demonstrated the dynamics of wandoo crown cover. Comparisons of periods of decline with the variations of cover density over the entire image sequence facilitated the identification of possible locations and timing of wandoo crown decline impacts. Changes in crown cover observed by the imagery analysis were compared to field surveys.

  18. Water Area Extraction Using RADARSAT SAR Imagery Combined with Landsat Imagery and Terrain Information

    PubMed Central

    Hong, Seunghwan; Jang, Hyoseon; Kim, Namhoon; Sohn, Hong-Gyoo

    2015-01-01

    This paper exploits an effective water extraction method using SAR imagery in preparation for flood mapping in unpredictable flood situations. The proposed method is based on the thresholding method using SAR amplitude, terrain information, and object-based classification techniques for noise removal. Since the water areas in SAR images have the lowest amplitude value, the thresholding method using SAR amplitude could effectively extract water bodies. However, the reflective properties of water areas in SAR imagery cannot distinguish the occluded areas caused by steep relief and they can be eliminated with terrain information. In spite of the thresholding method using SAR amplitude and terrain information, noises which interfered with users’ interpretation of water maps still remained and the object-based classification using an object size criterion was applied for the noise removal and the criterion was determined by a histogram-based technique. When only using SAR amplitude information, the overall accuracy was 83.67%. However, using SAR amplitude, terrain information and the noise removal technique, the overall classification accuracy over the study area turned out to be 96.42%. In particular, user accuracy was improved by 46.00%. PMID:25808768

  19. Water area extraction using RADARSAT SAR imagery combined with Landsat imagery and terrain information.

    PubMed

    Hong, Seunghwan; Jang, Hyoseon; Kim, Namhoon; Sohn, Hong-Gyoo

    2015-03-19

    This paper exploits an effective water extraction method using SAR imagery in preparation for flood mapping in unpredictable flood situations. The proposed method is based on the thresholding method using SAR amplitude, terrain information, and object-based classification techniques for noise removal. Since the water areas in SAR images have the lowest amplitude value, the thresholding method using SAR amplitude could effectively extract water bodies. However, the reflective properties of water areas in SAR imagery cannot distinguish the occluded areas caused by steep relief and they can be eliminated with terrain information. In spite of the thresholding method using SAR amplitude and terrain information, noises which interfered with users' interpretation of water maps still remained and the object-based classification using an object size criterion was applied for the noise removal and the criterion was determined by a histogram-based technique. When only using SAR amplitude information, the overall accuracy was 83.67%. However, using SAR amplitude, terrain information and the noise removal technique, the overall classification accuracy over the study area turned out to be 96.42%. In particular, user accuracy was improved by 46.00%.

  20. Image analysis techniques with special reference to analysis and interpretation of geological features from LANDSAT imagery. [India

    NASA Technical Reports Server (NTRS)

    Kamat, D. S.; Majumder, K. L.; Naik, S. D.; Swaminathan, V. L.

    1977-01-01

    The principal component analysis enhances the contrast existing between the different cover types present in an imagery. A procedure is presented with regards to the determination of the principal components. The method is tested for a portion of the LANDSAT imagery pertaining to Anantapur region. Another technique, using the concept of non-linear contrast stretching is defined and developed and carried out on the same imagery. The results are presented as photographs. An interpretation of the geology of the region is derived from these photographs.

  1. The Next Step in Ice Flow Measurement from Optical Imagery: Comprehensive Mapping Of Ice Sheet Flow in Landsat 8 Imagery Using Spatial Frequency Filtering, Enabled by High Radiometric Sensitivity

    NASA Astrophysics Data System (ADS)

    Fahnestock, M. A.; Scambos, T. A.; Klinger, M. J.

    2014-12-01

    The advent of large area satellite coverage in the visible spectrum enabled satellite-based tracking of ice sheet flow just over twenty years ago. Following this, rapid development of techniques for imaging radar data enabled the wide-area mapping and time series coverage that SAR has brought to the documentation of changing ice discharge. We report on the maturation of feature tracking in visible-band satellite imagery of the ice sheets enabled by the high radiometric resolution and accurate geolocation delivered by Landsat 8, and apply this to mapping ice flow in the interiors of Antarctica and Greenland. The high radiometric resolution of Landsat 8 enables one to track subtle patterns on the surface of the ice sheet, unique at spatial scales of a few hundred meters, between images separated by multiple orbit cycles. In areas with significant dynamic topography generated by ice flow, this requires use of simple spatial filtering techniques first applied by Scambos et al. 1992. The result is densely sampled maps of surface motion that begin to rival the coverage available from SAR speckle tracking and interferometry. Displacement accuracy can approach one tenth of a pixel for reasonable chip sizes using conventional normalized cross-correlation; this can exceed the geolocation accuracy of the scenes involved, but coverage is sufficient to allow correction strategies based on very slow moving ice. The advance in radiometry, geo-location, and tracking tools is augmented by an increased rate of acquisition by Landsat 8. This helps mitigate the issue of cloud cover, as much of every 16-day orbit cycle over ice is acquired, maximizing the acquisition of clear-sky scenes. Using the correlation techniques common to IMCORR and later software, modern libraries, and single-cpu hardware, we are able to process full Landsat 8 scene pairs in a few minutes, allowing comprehensive analysis of ~1K available ice sheet image pairs in a few days.

  2. Estimation of water clarity in Taihu Lake and surrounding rivers using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Zhao, Dehua; Cai, Ying; Jiang, Hao; Xu, Delin; Zhang, Wenguang; An, Shuqing

    2011-02-01

    In China, the increase in exogenous-source pollutants from rivers is one of the most important causes of lake eutrophication. The application of remote sensing technology to water quality monitoring of rivers connected to these lakes has special significance for lake management at regional scales. Many research studies have estimated water clarity using Landsat imagery. However, most of this work focused on lakes or reservoirs, for which abundant water-only pixels (i.e., pure pixels of water, PPW) were available. Few of these studies have addressed rivers, especially rivers with an average width less than 100 m. In our study, we sought to determine whether water clarity in the rivers connected to Taihu Lake could be estimated using Landsat imagery. We obtained 18 Enhanced Thematic Mapper Plus (ETM+) images from 2009 for 13 rivers ranging from an average of 37.3 to 173.6 m wide. Three field campaigns conducted in May 2009, September 2009, and January 2010 were used to obtain field measurements of Secchi disk depth (SDD). Our results suggested that the widely used model, a(TM1/TM3) + b(TM1) + c, was suitable for the estimation of SDD for Taihu Lake. The brightness of the panchromatic band of ETM+ showed significant correlations with TM1, TM3 and TM1/TM3 ( p < 0.001). As a result, SDD in the lake could also be estimated using the Landsat panchromatic band. The multispectral image of ETM+ did not provide adequate PPW for estimation of water clarity in rivers. However, PPW derived from the panchromatic image captured about 93% of the variation in SDD, on average, for the every worst-case scenario in the 13 rivers. Using the PPW in rivers, a significant correlation was found between the brightness of the panchromatic image and SDD ( R2 = 0.64, p < 0.001). Our results demonstrate that the panchromatic image of Landsat, but not the multispectral image, can be used to estimate water clarity in rivers with an average width greater than 40 m in the Taihu basin.

  3. Using Landsat satellite data to support pesticide exposure assessment in California

    USGS Publications Warehouse

    Maxwell, Susan K.; Airola, Matthew; Nuckols, John R.

    2010-01-01

    We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.

  4. Phenology from Landsat when data is scarce: Using MODIS and Dynamic Time-Warping to combine multi-year Landsat imagery to derive annual phenology curves

    NASA Astrophysics Data System (ADS)

    Baumann, Matthias; Ozdogan, Mutlu; Richardson, Andrew D.; Radeloff, Volker C.

    2017-02-01

    Green-leaf phenology describes the development of vegetation throughout a growing season and greatly affects the interaction between climate and the biosphere. Remote sensing is a valuable tool to characterize phenology over large areas but doing at fine- to medium resolution (e.g., with Landsat data) is difficult because of low numbers of cloud-free images in a single year. One way to overcome data availability limitations is to merge multi-year imagery into one time series, but this requires accounting for phenological differences among years. Here we present a new approach that employed a time series of a MODIS vegetation index data to quantify interannual differences in phenology, and Dynamic Time Warping (DTW) to re-align multi-year Landsat images to a common phenology that eliminates year-to-year phenological differences. This allowed us to estimate annual phenology curves from Landsat between 2002 and 2012 from which we extracted key phenological dates in a Monte-Carlo simulation design, including green-up (GU), start-of-season (SoS), maturity (Mat), senescence (Sen), end-of-season (EoS) and dormancy (Dorm). We tested our approach in eight locations across the United States that represented forests of different types and without signs of recent forest disturbance. We compared Landsat-based phenological transition dates to those derived from MODIS and ground-based camera data from the PhenoCam-network. The Landsat and MODIS comparison showed strong agreement. Dates of green-up, start-of-season and maturity were highly correlated (r 0.86-0.95), as were senescence and end-of-season dates (r > 0.85) and dormancy (r > 0.75). Agreement between the Landsat and PhenoCam was generally lower, but correlation coefficients still exceeded 0.8 for all dates. In addition, because of the high data density in the new Landsat time series, the confidence intervals of the estimated keydates were substantially lower than in case of MODIS and PhenoCam. Our study thus suggests

  5. 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.

  6. Regional prospecting for iron ores in Bahariya Oasis-El Faiyum area, Egypt, using LANDSAT-1 satellite images

    NASA Technical Reports Server (NTRS)

    Elshazly, E. M.; Abdel-Hady, M. A.; Elghawaby, M. A.; Khawasik, S. M. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. New discoveries of iron deposits were registered as a result of the LANDSAT imagery, and the conditions of the already known iron deposits and occurrences were regionally connected and verified.

  7. Assessment of the availability of the tracking and data relay satellite system for LANDSAT missions

    NASA Technical Reports Server (NTRS)

    1982-01-01

    The telecommunications availability that can realistically be provided by the tracking and data relay satellite system (TDRSS) for LANDSAT D type missions. Although the assessment focusses on the telecommunications requirements of the near Earth orbit missions of the 1985 - 1989 time frame, it emphasizes LANDSAT D and its competing demand for wideband, real-time RF link services from TDRSS. Limitations in availability of communications services are identified, including systematic TDRSS restrictions, conflicting telecommunication requirements and loading problems of all users (missions) which are to be supported by TDRSS. Several telecommunications alternatives for LANDSAT D utilization independent of TDRSS services are discussed.

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

    USGS Publications Warehouse

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

    2002-01-01

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

  9. Using Quickbird and Landsat imagery to analyze temporal changes in mountain resort development: Big Sky, Montana 1990-2005

    NASA Astrophysics Data System (ADS)

    Campos, Natalie; Lawrence, Rick; McGlynn, Brian; Gardner, Kristin

    2011-01-01

    Documenting patterns of land use and land-cover change in mountain resort development (MRD) is important for understanding the effects of these changes of fragile mountain environments. High-spatial-resolution imagery can be useful for mapping MRD, but lack of a long-term record of such imagery hampers our ability to analyze temporal patterns. We use the results from classification of high-spatial-resolution imagery (Quickbird and LiDAR) to calibrate concurrent moderate-resolution imagery (Landsat). We then use historical moderate-resolution imagery to analyze changes in spatial patterns of MRD over time. Analyses revealed that increases in MRD occurred disproportionately close to streams, which raises concerns for impacts on water quality.

  10. Comparison of three methods for long-term monitoring of boreal lake area using Landsat TM and ETM+ imagery

    USGS Publications Warehouse

    Roach, Jennifer K.; Griffith, Brad; Verbyla, David

    2012-01-01

    Programs to monitor lake area change are becoming increasingly important in high latitude regions, and their development often requires evaluating tradeoffs among different approaches in terms of accuracy of measurement, consistency across multiple users over long time periods, and efficiency. We compared three supervised methods for lake classification from Landsat imagery (density slicing, classification trees, and feature extraction). The accuracy of lake area and number estimates was evaluated relative to high-resolution aerial photography acquired within two days of satellite overpasses. The shortwave infrared band 5 was better at separating surface water from nonwater when used alone than when combined with other spectral bands. The simplest of the three methods, density slicing, performed best overall. The classification tree method resulted in the most omission errors (approx. 2x), feature extraction resulted in the most commission errors (approx. 4x), and density slicing had the least directional bias (approx. half of the lakes with overestimated area and half of the lakes with underestimated area). Feature extraction was the least consistent across training sets (i.e., large standard error among different training sets). Density slicing was the best of the three at classifying small lakes as evidenced by its lower optimal minimum lake size criterion of 5850 m2 compared with the other methods (8550 m2). Contrary to conventional wisdom, the use of additional spectral bands and a more sophisticated method not only required additional processing effort but also had a cost in terms of the accuracy and consistency of lake classifications.

  11. Identification of wild areas in southern lower Michigan. [terrain analysis from aerial photography, and satellite imagery

    NASA Technical Reports Server (NTRS)

    Habowski, S.; Cialek, C.

    1978-01-01

    An inventory methodology was developed to identify potential wild area sites. A list of site criteria were formulated and tested in six selected counties. Potential sites were initially identified from LANDSAT satellite imagery. A detailed study of the soil, vegetation and relief characteristics of each site based on both high-altitude aerial photographs and existing map data was conducted to eliminate unsuitable sites. Ground reconnaissance of the remaining wild areas was made to verify suitability and acquire information on wildlife and general aesthetics. Physical characteristics of the wild areas in each county are presented in tables. Maps show the potential sites to be set aside for natural preservation and regulation by the state under the Wilderness and Natural Areas Act of 1972.

  12. Identifying the breeding areas of locusts in the Yellow River estuary using Landsat ETM+ imagery

    NASA Astrophysics Data System (ADS)

    Liu, Qingsheng; Liu, Gaohuan; Yang, Yuzhen; Liu, Peng; Huang, Jianjie

    2006-03-01

    The Yellow River Estuary became an important plague region of locusts because of its special geographic location. Many years' survey data showed that the environment was the chief factor that influenced locust pest occurring. In the recent years, because the amount of water from the Yellow River and precipitation reduced and distributed asymmetrically, and soil salinization became serious much more, and many farmlands went out of cultivation, which improved the habitats for locusts, the plague of locusts happened frequently under condign climate. The field survey data from 1991 to 2000 showed that the plague of locust became more aggravating year after year. Therefore, it is important to monitor and control the plague of locusts. According to many years' investigation data analysis, got the condign habitat conditions for Locusta Migratoria Manilensis (Meyen) in the Yellow River Estuary. So the breeding areas of locusts monitoring with remote sensing imagery was to identify those regions according to the condign habitat conditions. Landsat ETM+ imagery (2000-05-02) data was chosen to identify the breeding areas of locusts in the Yellow River Estuary. Firstly classified Landsat TM imagery (2000-5-2) and extract reed lands and lawn lands and slightly salinized soils. Secondly made mask images through transforming these three raster classes into vector layers, then calculated a anti-atmospheric visible light vegetation index VARIg = (B2-B3)/(B2+B3-B1). According to field investigation data of vegetation fractional cover in 2000, got the relationship between vegetation fractional cover and VARIg values, 70% to 3.0, 50% to 2.3. As a result, the infrequent areas were where VARIg values were great than 3.0, and the moderate areas were where VARIg values were between 2.3 and 3.0, and frequent areas were where VARIg values were under 2.3. According to statistical analysis, the infrequent areas were percent 10 of the lands that have the condign soil salt content for locust

  13. Structural mapping from MSS-LANDSAT imagery: A proposed methodology for international geological correlation studies

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Crepani, E.; Martini, P. R.

    1980-01-01

    A methodology is proposed for international geological correlation studies based on LANDSAT-MSS imagery, Bullard's model of continental fit and compatible structural trends between Northeast Brazil and the West African counterpart. Six extensive lineaments in the Brazilian study area are mapped and discussed according to their regional behavior and in relation to the adjacent continental margin. Among the first conclusions, correlations were found between the Sobral Pedro II Lineament and the megafaults that surround the West African craton; and the Pernambuco Lineament with the Ngaurandere Linemanet in Cameroon. Ongoing research to complete the methodological stages includes the mapping of the West African structural framework, reconstruction of the pre-drift puzzle, and an analysis of the counterpart correlations.

  14. Application of Landsat imagery to problems of petroleum exploration in Qaidam Basin, China

    USGS Publications Warehouse

    Bailey, G.B.; Anderson, P.D.

    1982-01-01

    Tertiary and Quaternary nonmarine, petroleum-bearing sedimentary rocks have been extensively deformed by compressive forces. These forces created many folds which are current targets of Chinese exploration programs. Image-derived interpretations of folds, strike-slip faults, thrust faults, normal or reverse faults, and fractures compared very favorably, in terms of locations and numbers mapped, with Chinese data compiled from years of extensive field mapping. Many potential hydrocarbon trapping structures were precisely located. Orientations of major structural trends defined from Landsat imagery correlate well with those predicted for the area based on global tectonic theory. These correlations suggest that similar orientations exist in the eastern half of the basin where folded rocks are mostly obscured by unconsolidated surface sediments and where limited exploration has occurred.--Modified journal abstract.

  15. Cumulus cloud field morphology and spatial patterns derived from high spatial resolution Landsat imagery

    NASA Technical Reports Server (NTRS)

    Sengupta, S. K.; Welch, R. M.; Navar, M. S.; Berendes, T. A.; Chen, D. W.

    1990-01-01

    Using high-spatial-resolution Landsat MSS imagery, the cumulus cloud morphology, cloud nearest-neighbor distributions, and cloud clumping scales were investigated. It is shown that the cloud-size distribution can be represented by a mixture of two power laws; clouds of diameters less than 1 km have power-law slope range of 1.4-2.3, while larger clouds have slopes from 2.1 to 4.75. The break in power-law slope occurs at the cloud size that makes the largest contribution to cloud cover. Results suggest that larger clouds grow at the expense of smaller clouds. It was also found that the cloud inhomogeneities have significant impact on radiative fluxes.

  16. Evaluation of selected spectral vegetation indices in senescent rangeland canopy using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Striped Face-Collins, Marla

    Grassland birds are diminishing more steadily and rapidly than other North American birds in general. The nesting success of some grassland bird species depends on the amount of nonproductive vegetation (NPV). To estimate NPV land managers are currently using the Robel pole visual obstruction reading methods. Researchers with the USDA Agricultural Research Service's (ARS) Northern Great Plains Research Laboratory in Mandan, ND, recently established statistical relationships between photosynthetic vegetation (PV), NPV and spectral vegetation indices (SVIs) derived from more sensitive and more detailed, but less accessible and more costly hyperspectral aerial imagery. This study is an extension of this previous work using spectral vegetation indices collected using the Landsat TM sensor, including simple ratios SWIR-SR (rho2215/rho 1650) and SR71 (rho2215 /rho485) to estimate the amount of NPV and bare ground cover, respectively.

  17. CCRS Landcover Maps From Satellite Data

    DOE Data Explorer

    Trishchenko, Alexander

    2008-01-15

    The Canadian Centre for Remote Sensing (CCRS) presents several landcover maps over the SGP CART site area (32-40N, 92-102W) derived from satellite data including AVHRR, MODIS, SPOT vegetation data, and Landsat satellite TM imagery.

  18. Temporal validation for landsat-based volume estimation model

    Treesearch

    Renaldo J. Arroyo; Emily B. Schultz; Thomas G. Matney; David L. Evans; Zhaofei Fan

    2015-01-01

    Satellite imagery can potentially reduce the costs and time associated with ground-based forest inventories; however, for satellite imagery to provide reliable forest inventory data, it must produce consistent results from one time period to the next. The objective of this study was to temporally validate a Landsat-based volume estimation model in a four county study...

  19. Analysis of coastal change in Marie Byrd Land and Ellsworth Land, West Antarctica, using Landsat imagery

    USGS Publications Warehouse

    Ferrigno, J.G.; Williams, R.S.; Rosanova, C.E.; Lucchitta, B.K.; Swithinbank, C.

    1998-01-01

    The U.S. Geological Survey is using Landsat imagery from the early 1970s and mid- to late 1980s/early 1990s to analyze glaciological features, compile a glacier inventory, measure surface velocities of outlet glaciers, ice streams and ice shelves, determine coastline change and calculate the area and volume of iceberg calving in Antarctica. Ice-surface velocities in Marie Byrd and Ellsworth Lands, West Antarctica, range from the fast-moving Thwaites, Pine Island, Land and DeVicq Glaciers to the slower-moving ice shelves. The average ice-front velocity during the time interval of Landsat imagery, for the faster-moving outlet glaciers, was 2.9 km a-1 for Thwaites Glacier, 2.4 km a-1 for Pine Island Glacier, 2.0 km a-1 for Land Glacier and 1.4 km a-1 for DeVicq Glacier. Evaluation of coastal change from the early 1970s to the early 1990s shows advance of the floating ice front in some coastal areas and recession in others, with an overall small average advance in the entire coastal study area, but no major trend towards advance or retreat. Comparison of average ice-surface velocities with changes in the ice front has yielded estimates of iceberg calving. The total iceberg calving from the Marie Byrd Land and Ellsworth Land coasts during the study period was greater than 8500 km2 (estimated volume of about 2400 km3) or an average of about 550 km2 a-1 (more than 150 km3 a-1). Almost 70% of this discharge is contributed by Thwaites and Pine Island Glaciers.

  20. Landsat 4 thematic mapper imagery: improved tool for geologic mapping in eastern overthrust

    SciTech Connect

    Miller, J.E.

    1984-04-01

    The central Appalachians were studied using Landsat 4 thematic mapper (TM) data to evaluate the improved spatial resolution (30 x 30 m, 100 x 100 ft) of TM for mapping capabilities. The TM bands 2, 3, and 4 were contrast stretched and edge enhanced using digital processing techniques. Photogeologic analysis of the 1:125,000-scale TM image examined drainage, landform, lineament, and structural features. The study area comprises the junction of the central and southern Appalachians where fold axes change from N30/sup 0/E to N60/sup 0/E. Southeast-dipping thrust faults trend northeastward across the area. Cambrian through Devonian rocks are involved in and exposed by the thrust faults. Recognition of drainage relationships (density and pattern) are important in identifying lithologies. Landforms reflect structure and lithology through characteristic topographic expression. Improved identification and delineation of drainage and landform characteristics on TM imagery support structural and lithologic interpretations. Lineaments were identified by drainage, tonal, and topographic characteristics. Two major lineaments trending N83/sup 0/E and N56/sup 0/W, at the junction of the southern and central Appalachians, were identified. Identified structural features include fold axes, thrust faults, strike-slip faults, and thrust-faulted folds. Detailed lineament and structural mapping on TM imagery aids in unraveling complex surface geologic patterns in this critical area of the eastern overthrust. Digitally enhanced Landsat 4 TM data proved advantageous for accurate mapping of drainage, landform, lineament, and structural features. Improved accuracy on a regional scale allows reliable geologic mapping and therefore subsurface interpretations, benefitting hydrocarbon exploration.

  1. Landsat 4 thematic mapper imagery: improved tool for geologic mapping in eastern overthrust

    SciTech Connect

    Miller, J.E.

    1984-04-01

    The central Appalachians were studied using Landsat 4 thematic mapper (TM) data to evaluate the improved spatial resolution (30 x 30 m, 100 x 100 ft) of TM for mapping capabilities. The TM bands 2, 3, and 4 were contrast stretched and edge enhanced using digital processing techniques. Photogeologic analysis of the 1:125,000-scale TM image examined drainage, landform, lineament, and structural features. The study area comprises the junction of the central and southern Appalachians where fold axes change from N30/sup 0/E to N60/sup 0/E. Southeast-dipping thrust faults trend northeastward across the area. Cambrian through Devonian rocks are involved in and exposed by the thrust faults. Recognition of drainage relationships (density and pattern) are important in identifying lithologies. Landforms reflect structure and lithology through characteristic topographic expression. Improved identification and delineation of drainage and landform characteristics on TM imagery support structural and lithologic interpretations. Lineaments were identified by drainage, tonal, and topographic characteristics. Two major lineaments trending N83/sup 0/E and N56/sup 0/W, at the junction of the southern and central Appalachians, were identified. Identified structural features include fold axes, thrust faults, strike-slip faults, and thrust-faulted folds. Detailed lineament and structural mapping on TM imagery aids in unraveling complex surface geologic patterns in this critical area of the eastern overthrust. Digitally enhanced Landsat 4 TM data proved advantageous for accurate mapping of drainage, landform, lineament, and structural features. Improved accuracy on a regional scale allows reliable geologic mapping and therefore subsurface interpretations, benefiting hydrocarbon exploration.

  2. Mapping of West Siberian taiga wetland complexes using Landsat imagery: implications for methane emissions

    NASA Astrophysics Data System (ADS)

    Evgenievna Terentieva, Irina; Vladimirovich Glagolev, Mikhail; Dmitrievna Lapshina, Elena; Faritovich Sabrekov, Alexandr; Maksyutov, Shamil

    2016-08-01

    High-latitude wetlands are important for understanding climate change risks because these environments sink carbon dioxide and emit methane. However, fine-scale heterogeneity of wetland landscapes poses a serious challenge when generating regional-scale estimates of greenhouse gas fluxes from point observations. In order to reduce uncertainties at the regional scale, we mapped wetlands and water bodies in the taiga zone of The West Siberia Lowland (WSL) on a scene-by-scene basis using a supervised classification of Landsat imagery. Training data consist of high-resolution images and extensive field data collected at 28 test areas. The classification scheme aims at supporting methane inventory applications and includes seven wetland ecosystem types comprising nine wetland complexes distinguishable at the Landsat resolution. To merge typologies, mean relative areas of wetland ecosystems within each wetland complex type were estimated using high-resolution images. Accuracy assessment based on 1082 validation polygons of 10 × 10 pixel size indicated an overall map accuracy of 79 %. The total area of the WSL wetlands and water bodies was estimated to be 52.4 Mha or 4-12 % of the global wetland area. Ridge-hollow complexes prevail in WSL's taiga zone accounting for 33 % of the total wetland area, followed by pine bogs or "ryams" (23 %), ridge-hollow-lake complexes (16 %), open fens (8 %), palsa complexes (7 %), open bogs (5 %), patterned fens (4 %), and swamps (4 %). Various oligotrophic environments are dominant among wetland ecosystems, while poor fens cover only 14 % of the area. Because of the significant change in the wetland ecosystem coverage in comparison to previous studies, a considerable reevaluation of the total CH4 emissions from the entire region is expected. A new Landsat-based map of WSL's taiga wetlands provides a benchmark for validation of coarse-resolution global land cover products and wetland data sets in high latitudes.

  3. Human-induced geomorphology: Modeling slope failure in Dominical, Costa Rica using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Miller, Andrew J.

    Unchecked human development has ravaged the region between Dominical and Uvita, Costa Rica. Much of the development transition has been driven by tourism and further foreign direct investment in residential, service and commercial enterprises. The resulting land-use/land-cover change has removed traditional forest cover in exchange for impervious surfaces, physical structures, and bare ground which is no longer mechanically supported by woody vegetation. Combined with a tropical climate, deeply weathered soils and lithography which are prone to erosion, land cover change has led to an increase in slope failure occurrences. Given the remoteness of the Dominical-Uvita region, its rate of growth and the lack of monitoring, new techniques for monitoring land use and slope failure susceptibility are needed. Two new indices are presented here that employ a Digital Elevation Model (DEM) and widely available Landsat imagery to assist in this endeavor. The first index, or Vegetation Influenced Landslide Index (VILI), incorporates slope derived from a DEM and Lu et al.'s (2007) Surface Cover Index to quantify vegetative cover as a means of mechanical stabilization in landslide prone areas. The second index, or Slope Multiplier Index (SMI), uses individual Landsat data bands and basic Landsat band ratios as environmental proxies to replicate soil, vegetative and hydrologic properties. Both models achieve accuracy over 70% and rival results from more complicated published literature. The accuracy of the indices was assessed with the creation of a landslide inventory developed from field observations occurring in December 2007 and November 2008. The creation of these indices represents an efficient and accurate way of determining landslide susceptibility zonation in data poor areas where environmental protection practitioners may be overextended, under-trained or both.

  4. Mapping burn severity in a disease-impacted forest landscape using Landsat and MASTER imagery

    NASA Astrophysics Data System (ADS)

    Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Meentemeyer, Ross K.

    2015-08-01

    Global environmental change has increased forest vulnerability to the occurrence of interacting disturbances, including wildfires and invasive diseases. Mapping post-fire burn severity in a disease-affected forest often faces challenges because burned and infested trees may exhibit a high similarity in spectral reflectance. In this study, we combined (pre- and post-fire) Landsat imagery and (post-fire) high-spectral resolution airborne MASTER data [MODIS (moderate resolution imaging spectroradiometer)/ASTER (advanced spaceborne thermal emission and reflection radiometer)] to map burn severity in a California coastal forest environment, where a non-native forest disease sudden oak death (SOD) was causing substantial tree mortality. Results showed that the use of Landsat plus MASTER bundle performed better than using the individual sensors in most of the evaluated forest strata from ground to canopy layers (i.e., substrate, shrubs, intermediate-sized trees, dominant trees and average), with the best model performance achieved at the dominant tree layer. The mid to thermal infrared spectral bands (3.0-12.5 μm) from MASTER were found to augment Landsat's visible to shortwave infrared bands in burn severity assessment. We also found that infested and uninfested forests similarly experienced moderate to high degrees of burns where CBI (composite burn index) values were higher than 1. However, differences occurred in the regions with low burn severity (CBI values lower than 1), where uninfested stands revealed a much lower burn effect than that in infested stands, possibly due to their higher resilience to small fire disturbances as a result of higher leaf water content.

  5. Carbonate facies and Landsat imagery of shelf off Belize, central America

    SciTech Connect

    Jordan, C.F. Jr.; Pusey, W.C. III; Belcher, R.C.; Borger, R.L.

    1985-02-01

    A reevaluation of Holocene sediments on the Belize shelf is based on (1) a newly constructed composite of 7 Landsat images, enhanced and registered to form a regional base map, and (2) a Holocene facies map based on a rigorous treatment of compositional and textural parameters for approximately 600 bottom samples. The sediments are mapped in terms usually applied to lithified carbonate rocks, allowing direct comparisons with carbonate facies in the subsurface. By combining Landsat imagery with this facies map, it is possible to point out the following geologic features: (1) major tectonic elements, such as the Maya Mountains, the Yucatan Plateau, several offshore bridges, and 3 large atolls, (2) major physiographic features such as the Belize barrier reef with its reef platform and crest, middle-shelf shoal deposits, middle-shelf patch reefs (including lagoon reefs or rhomboid reefs), (3) Holocene facies patterns with potential reservoir facies of foraminifera-grainstone bars, Halimeda grainstones, and branching-coral, encrusting red-algae boundstones, and (4) nearshore clastics and a sharp transition eastward to carbonate sediments. An understanding of Holocene facies patterns on the Belize shelf is important to the explorationist, because these facies patterns are living examples of exploration fairways and invite comparisons with several petroleum provinces: (1) Cretaceous reefs of Texas, (2) upper Paleozoic skeletal-grainstone bars in west Texas, and (3) Devonian reefs of the Alberta basin.

  6. Vegetation change detection and quantification: linking Landsat imagery and LIDAR data

    USGS Publications Warehouse

    Peterson, Birgit E.; Nelson, Kurtis J.

    2009-01-01

    Measurements of the horizontal and vertical structure of vegetation are helpful for detecting and monitoring change or disturbance on the landscape. Lidar has a unique ability to capture the three-dimensional structure of vegetation canopies. In this preliminary study, we present the results of a series of exploratory data analyses that tested our assumptions about the links between the structural data obtainable from lidar and the change detection products derived from Landsat imagery. Our study area is located in the Sierra National Forest in the Sierra Nevada Mountains of California and covers a wide range of vegetation types. The lidar data used in this study were collected by the Laser Vegetation Imaging System (LVIS) (Blair et al., 1999). LVIS is a largefootprint lidar system optimized to measure canopy structure characteristics. A series of Landsat scenes from 1984 through 2008 was collected for the study area (Path 42, Row 34) and processed to generate maps of disturbance. The preliminary results described here indicate that even simple metrics of height can be useful in assessing changes in structure brought about by disturbance in forest canopies. For example, canopy height values for 2008 were higher on average than those measured for 1999 in undisturbed forest, whereas this trend is not clearly observable for the disturbed forest patches.

  7. Mineral target areas in Nevada from geological analysis of LANDSAT-1 imagery

    NASA Technical Reports Server (NTRS)

    Abdel-Gawad, M.; Tubbesing, L.

    1975-01-01

    Geological analysis of LANDSAT-1 Scene MSS 1053-17540 suggests that certain known mineral districts in east-central Nevada frequently occur near faults or at faults or lineament intersections and areas of complex deformation and flexures. Seventeen (17) areas of analogous characteristics were identified as favorable targets for mineral exploration. During reconnaissance field trips eleven areas were visited. In three areas evidence was found of mining and/or prospecting not known before the field trips. In four areas favorable structural and alteration features were observed which call for more detailed field studies. In one of the four areas limonitic iron oxide samples were found in the regolith of a brecciated dolomite ridge. This area contains quartz veins, granitic and volcanic rocks and lies near the intersection of two linear fault structures identified in the LANDSAT-1 imagery. Semiquantitative spectroscopic analysis of selected portions of the samples showed abnormal contents of arsenic, molybdenum, copper, lead, zinc, and silver. These limonitic samples found were not in situ and further field studies are required to assess their source and significance.

  8. Mineral target areas in Nevada from geological analysis of LANDSAT-1 imagery

    NASA Technical Reports Server (NTRS)

    Abdel-Gawad, M.; Tubbesing, L.

    1975-01-01

    Geological analysis of LANDSAT-1 Scene MSS 1053-17540 suggests that certain known mineral districts in east-central Nevada frequently occur near faults or at faults or lineament intersections and areas of complex deformation and flexures. Seventeen (17) areas of analogous characteristics were identified as favorable targets for mineral exploration. During reconnaissance field trips eleven areas were visited. In three areas evidence was found of mining and/or prospecting not known before the field trips. In four areas favorable structural and alteration features were observed which call for more detailed field studies. In one of the four areas limonitic iron oxide samples were found in the regolith of a brecciated dolomite ridge. This area contains quartz veins, granitic and volcanic rocks and lies near the intersection of two linear fault structures identified in the LANDSAT-1 imagery. Semiquantitative spectroscopic analysis of selected portions of the samples showed abnormal contents of arsenic, molybdenum, copper, lead, zinc, and silver. These limonitic samples found were not in situ and further field studies are required to assess their source and significance.

  9. Evaluating satellite imagery for estimating mountain pine beetle-caused lodgepole pine mortality: Current status

    Treesearch

    B. J. Bentz; D. Endreson

    2004-01-01

    Spatial accuracy in the detection and monitoring of mountain pine beetle populations is an important aspect of both forest research and management. Using ground-collected data, classification models to predict mountain pine beetle-caused lodgepole pine mortality were developed for Landsat TM, ETM+, and IKONOS imagery. Our results suggest that low-resolution imagery...

  10. Using aerial video to train the supervised classification of Landsat TM imagery for coral reef habitats mapping.

    PubMed

    Bello-Pineda, J; Liceaga-Correa, M A; Hernández-Núñez, H; Ponce-Hernández, R

    2005-06-01

    Management of coral reef resources is a challenging task, in many cases, because of the scarcity or inexistence of accurate sources of information and maps. Remote sensing is a not intrusive, but powerful tool, which has been successfully used for the assessment and mapping of natural resources in coral reef areas. In this study we utilized GIS to combine Landsat TM imagery, aerial photography, aerial video and a digital bathymetric model, to assess and to map submerged habitats for Alacranes reef, Yucatán, México. Our main goal was testing the potential of aerial video as the source of data to produce training areas for the supervised classification of Landsat TM imagery. Submerged habitats were ecologically characterized by using a hierarchical classification of field data. Habitats were identified on an overlaid image, consisting of the three types of remote sensing products and the bathymetric model. Pixels representing those habitats were selected as training areas by using GIS tools. Training areas were used to classify the Landsat TM bands 1, 2 and 3 and the bathymetric model by using a maximum likelihood algorithm. The resulting thematic map was compared against field data classification to improve habitats definition. Contextual editing and reclassification were used to obtain the final thematic map with an overall accuracy of 77%. Analysis of aerial video by a specialist in coral reef ecology was found to be a suitable source of information to produce training areas for the supervised classification of Landsat TM imagery in coral reefs at a coarse scale.

  11. Calculating Atmospheric Effects in Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Diner, D. J.; Martonchik, J. V.

    1986-01-01

    Report presents detailed analysis of atmospheric blurring inherent in photographs or other observations of Earth from satellites or aircraft. Blurring result of scattering of radiation, which diffuses sharp image features by causing light from one part of scene to fall on image of adjacent part. In contrast with earlier approaches to atmospheric optics, one presented in report more accurate and versatile and designed for use on minicomputers.

  12. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  13. 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.

  14. Recent field experiments with commercial satellite imagery direct downlink.

    PubMed

    Gonzalez, Anthony R; Amber, Samuel H

    US Pacific Command's strategy includes assistance to United States government relief agencies and nongovernment organizations during humanitarian aid and disaster relief operations in the Asia-Pacific region. Situational awareness during these operations is enhanced by broad interagency access to unclassified commercial satellite imagery. The Remote Ground Terminal-a mobile satellite downlink ground station-has undergone several technology demonstrations and participated in an overseas deployment exercise focused on a natural disaster scenario. This ground station has received new commercial imagery within 20 minutes, hastening a normally days-long process. The Army Geospatial Center continues to manage technology development and product improvement for the Remote Ground Terminal. Furthermore, this ground station is now on a technology transition path into the Distributed Common Ground System-Army program of record.

  15. 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

  16. Detecting changes on coastal primary sand dunes using multi-temporal Landsat imagery

    NASA Astrophysics Data System (ADS)

    Gonçalves, Gil; Duro, Nuno; Sousa, Ercilia; Pinto, Luís.; Figueiredo, Isabel

    2014-10-01

    Due to both natural and anthropogenic causes the coastal primary sand dunes, keeps changing dynamically and continuously their shape, position and extend over time. In this paper we use a case study to show how we monitor the Portuguese coast, between the period 2000 to 2014, using free available multi-temporal Landsat imagery (ETM+ and OLI sensors). First, all the multispectral images are panshaperned to meet the 15 meters spatial resolution of the panchromatic images. Second, using the Modification of Normalized Difference Water Index (MNDWI) and kmeans clustering method we extract the raster shoreline for each image acquisition time. Third, each raster shoreline is smoothed and vectorized using a penalized least square method. Fourth, using an image composed by five synthetic bands and an unsupervised classification method we extract the primary sand dunes. Finally, the visual comparison of the thematic primary sand dunes maps shows that an effective monitoring system can be implemented easily using free available remote sensing imagery data and open source software (QGIS and Orfeo toolbox).

  17. Ad Hoc Modeling of Root Zone Soil Water with Landsat Imagery and Terrain and Soils Data

    PubMed Central

    Sankey, Joel B.; Lawrence, Rick L.; Wraith, Jon M.

    2008-01-01

    Agricultural producers require knowledge of soil water at plant rooting depths, while many remote sensing studies have focused on surface soil water or mechanistic models that are not easily parameterized. We developed site-specific empirical models to predict spring soil water content for two Montana ranches. Calibration data sample sizes were based on the estimated variability of soil water and the desired level of precision for the soil water estimates. Models used Landsat imagery, a digital elevation model, and a soil survey as predictor variables. Our objectives were to see whether soil water could be predicted accurately with easily obtainable calibration data and predictor variables and to consider the relative influence of the three sources of predictor variables. Independent validation showed that multiple regression models predicted soil water with average error (RMSD) within 0.04 mass water content. This was similar to the accuracy expected based on a statistical power test based on our sample size (n = 41 and n = 50). Improved prediction precision could be achieved with additional calibration samples, and range managers can readily balance the desired level of precision with the amount of effort to collect calibration data. Spring soil water prediction effectively utilized a combination of land surface imagery, terrain data, and subsurface soil characterization data. Ranchers could use accurate spring soil water content predictions to set stocking rates. Such management can help ensure that water, soil, and vegetation resources are used conservatively in irrigated and non-irrigated rangeland systems. PMID:27879710

  18. Ad Hoc Modeling of Root Zone Soil Water with Landsat Imagery and Terrain and Soils Data.

    PubMed

    Sankey, Joel B; Lawrence, Rick L; Wraith, Jon M

    2008-01-21

    Agricultural producers require knowledge of soil water at plant rooting depths,while many remote sensing studies have focused on surface soil water or mechanisticmodels that are not easily parameterized. We developed site-specific empirical models topredict spring soil water content for two Montana ranches. Calibration data sample sizeswere based on the estimated variability of soil water and the desired level of precision forthe soil water estimates. Models used Landsat imagery, a digital elevation model, and asoil survey as predictor variables. Our objectives were to see whether soil water could bepredicted accurately with easily obtainable calibration data and predictor variables and toconsider the relative influence of the three sources of predictor variables. Independentvalidation showed that multiple regression models predicted soil water with average error(RMSD) within 0.04 mass water content. This was similar to the accuracy expected basedon a statistical power test based on our sample size (n = 41 and n = 50). Improvedprediction precision could be achieved with additional calibration samples, and rangemanagers can readily balance the desired level of precision with the amount of effort tocollect calibration data. Spring soil water prediction effectively utilized a combination ofland surface imagery, terrain data, and subsurface soil characterization data. Rancherscould use accurate spring soil water content predictions to set stocking rates. Suchmanagement can help ensure that water, soil, and vegetation resources are usedconservatively in irrigated and non-irrigated rangeland systems.

  19. 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.

  20. Automatic Mosaicking of Satellite Imagery Considering the Clouds

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  1. Using Satellite Imagery to Study Landslides

    NASA Astrophysics Data System (ADS)

    Reif, S. L.; Bluth, G. J.; Rose, W. I.; Matias, O.; Wolf, R.

    2003-04-01

    Much of the world's population currently lives under the threat of volcanic hazards in the secondary form of debris movements such as landslides and lahars. Remote sensing is becoming a useful tool for hazard studies, yet many hazard-prone areas do not utilize this important resource. In this project, we intend to use common remote sensing techniques to study characteristics of landslides and lahars in order to predict hazard zones. Fuego Volcano in Guatemala is a steep sided volcano with a history of large eruptive events, including the well-studied 1974 eruption, that have extruded a large amount of material onto the upper reaches of the Fuego watersheds. Eruption processes have been a primary focus of studies; however, remobilization during the rainy season of the erupted material is hazardous to the local population and agriculture (Vallance et al. 2001, USGS Open-File Report 01-431). A study of the way material moves down Fuego and to the extent that it moves is needed to help properly mitigate the potential hazards. We propose an in-depth remote sensing survey to map the hazard-prone areas. The study will consist of processing 20 years (15 cloud-free images) of Landsat TM and ETM+ data to look at changes in landforms and vegetation. Vegetation indices will be calculated to locate areas devoid of vegetation and a masking process will be used to measure the area of these zones. These area changes will be related to field measurements to create GIS layers denoting geometry changes in the channels around Fuego. These changes will be loaded into a GIS, along with regional climate data, DEMs, hydrologic data, infrastructure, and information about the known volcanic activity recorded in the area by the local volcanologists. Modeling of lahars using LAHARZ and climate data will also be done to determine an estimate of the amount of material moved and to what distances it can be transported. A field survey undertaken in January 2003 acquired GPS ground truth data of

  2. Satellite Imagery Assisted Road-Based Visual Navigation System

    NASA Astrophysics Data System (ADS)

    Volkova, A.; Gibbens, P. W.

    2016-06-01

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

  3. Monitoring large enrichment plants using thermal imagery from commercial satellites: A case study

    SciTech Connect

    Adam Bernstein

    2000-05-01

    Thermal imagery from commercial satellites is an interesting candidate technology for use as a verification tool for the purpose of monitoring certain types of fissile material production sites. Examples of its potential treaty applications include the Fissile Material Cutoff Treaty (FMCT) or a Fissile Material Production Moratorium. To help determine the capabilities and limitations of such imagery as a monitoring tool, the author has examined archived LANDSAT-5 images of the Portsmouth Gaseous Diffusion Plant, a large US uranium-enrichment facility in Ohio. This analysis indicates that large-scale gaseous diffusion plants can very likely be recognized as operational with thermal imagery throughout most of the year in clear weather conditions. It may also be possible to identify certain other large-scale qualitative changes in operations, such as the shut-down of a single process building in a plant, by a comparison of its temperature with the temperatures of neighboring operational process buildings. However, uncertainties in the current data set prevent a definitive conclusion regarding the latter capability. This study identifies intrinsic weaknesses, including vulnerability to countermeasures, that prevent thermal imagery from satellites from being a robust standalone verification tool, even for very large enrichment plants. Nonetheless, the imagery may be useful as a trigger for an on-site inspection, to alert and train inspectors prior to an inspection, and possibly to reduce the frequency of on-site inspections required at a given site. It could have some immediate utility for monitoring the two large gaseous diffusion plants the US and the French plant at Tricastin, and possibly for determining the operational status of two gaseous diffusion plants in China as well--a total of five plants worldwide. The ease of acquisition and modest cost of thermal commercial imagery further increase its attractiveness as a verification tool. In addition to these basic

  4. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and Quantitative mapping of salinity stress in sugarcane fields

    NASA Astrophysics Data System (ADS)

    Hamzeh, Saeid; Naseri, Abd Ali; AlaviPanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

    2016-10-01

    This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image acquired on September 7, 2010 were used as hyperspectral and multispectral satellite imagery. Field data including soil salinity in the sugarcane root zone was collected at 191 locations in 25 fields during September 2010. In the first section of the paper, based on the yield potential of sugarcane as influenced by different soil salinity levels provided by FAO, soil salinity was classified into three classes, low salinity (1.7-3.4 dS/m), moderate salinity (3.5-5.9 dS/m) and high salinity (6-9.5) by applying different classification methods including Support Vector Machine (SVM), Spectral Angle Mapper (SAM), Minimum Distance (MD) and Maximum Likelihood (ML) on Hyperion and Landsat images. In the second part of the paper the performance of nine vegetation indices (eight indices from literature and a new developed index in this study) extracted from Hyperion and Landsat data was evaluated for quantitative mapping of salinity stress. The experimental results indicated that for categorical classification of salinity stress, Landsat data resulted in a higher overall accuracy (OA) and Kappa coefficient (KC) than Hyperion, of which the MD classifier using all bands or PCA (1-5) as an input performed best with an overall accuracy and kappa coefficient of 84.84% and 0.77 respectively. Vice versa for the quantitative estimation of salinity stress, Hyperion outperformed Landsat. In this case, the salinity and water stress index (SWSI) has the best prediction of salinity stress with an R2 of 0.68 and RMSE of 1.15 dS/m for Hyperion followed by Landsat data with an R2 and RMSE of 0.56 and 1.75 dS/m respectively. It was concluded that categorical mapping of salinity stress is the best option

  5. Twenty years of Landsat data accessible through the national satellite land remote sensing data archive

    USGS Publications Warehouse

    Larsen, Dana M.

    1993-01-01

    The EROS Data Center has managed to National Satellite Land Remote Sensing Data Archive's (NSLRSDA) Landsat data since 1972. The NSLRSDA includes Landsat MSS data from 1972 through 1991 and T M data from 1982 through 1993. In response to many requests from multi-disciplined users for an enhanced insight into the availability and volume of Landsat data over specific worldwide land areas, numerous world plots and corresponding statical overviews have been prepared. These presentations include information related to image quality, cloud cover, various types of data overage (i.e. regions, countries, path, rows), acquisition station coverage areas, various archive media formats (i.e. wide band video tapes, computer compatible tapes, high density tapes, etc.) and acquisition time periods (i.e. years, seasons). Plans are to publish this information in a paper sample booklet at the Pecora 12 Symposium, in a USGS circular and on a Landsat CD-ROM; the data will be also be incorporated into GLIS.

  6. Pilot land data system. [for satellite imagery

    NASA Technical Reports Server (NTRS)

    Estes, J. E.; Star, J. L.; Cressy, P. J.; Devirian, M.

    1985-01-01

    The full realization of the potential of satellite remote sensing would require the utilization of information systems which are currently not available. However, technological advances make it now possible to design a data system for meeting the land scientists' most critical information needs. A working group has been assembled to examine the need for a Pilot Data System (PLDS). The pilot program is to establish a limited-scale, distributed information system to explore approaches to satisfy the needs of the land science research community. Aspects and objectives considered by the working group are discussed, taking into account science scenarios, required functions, the characteristics of a land data system, and questions of pilot land data system development.

  7. Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

    NASA Technical Reports Server (NTRS)

    Potter, Christopher S.

    2014-01-01

    A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  9. 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.

  10. 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.

  11. What is the economic value of satellite imagery?

    USGS Publications Warehouse

    Raunikar, Ronald P.; Forney, William M.; Benjamin, Susan P.

    2013-01-01

    Does remote-sensing information, such as that from Landsat and similar Earth-observing satellites, provide economic benefits to society, and can this value be estimated? Using satellite data for northeastern Iowa, U.S. Geological Survey scientists modeled the relations among land uses, agricultural production, and dynamic nitrate (NO3-) contamination of aquifers. They demonstrated that information from such modeling can allow more efficient management of agricultural production without sacrificing groundwater quality. Just for northeastern Iowa, the value of such remote-sensing information was shown to be as much as $858 million ± $197 million per year, which corresponds to a current value of $38.1 billion ± $8.8 billion for that flow of benefits into the foreseeable future.

  12. Research on identification of active volcano features based on Landsat TM/ETM+ imagery

    NASA Astrophysics Data System (ADS)

    Kong, Xiangsheng; Qian, Yonggang

    2009-10-01

    Volcanic activity can present unpredictable disasters to city populations living within regions and for people traveling in plane that intersect with ash-laden eruption clouds. Methods of monitoring volcanic activity include searching for variations in the thermal anomaly, clouds resource and subsidence deformation from active volcano. Over any active volcanoes, low spatial resolution satellite image are used to identify changes in eruptive activity, but are of insufficient spatial resolution to map active volcanic features. The Landsat data can be used to identify the thermal characteristics of a series of lava flows at Fuego volcano and Pacaya volcano, Guatemala. We use Landsat TM/ETM+ 7, 5, 4 (displayed in red, green, and blue, respectively) false-color composite of the research region, acquired on 18 December 1989 and 23 January 2000 to indicate the volcano image features which appear halo structure with blue red and yellow. The interpretation flag is obvious which indicate the difference temperature of volcano crater. Spatially varying haze emitted by volcano activity is identified and removed based on Improved Haze Optimized Transform (HOT) which is a robust haze assessing method. With improved spatial resolution in the thermal IR, we are able to map the bifurcation and braiding of underground lava tubes. With higher spatial resolution panchromatic data, we are able to map lava flow fields, trace very high temperature lava channels, and identify an accurate feature associated with a collapsed crater floor. At both Fuego and Pacaya, we are able to use the thermal data to estimate temperature. We can monitor the dynamic change of the two volcanoes using two difference date Landsat data.

  13. Determination of circulation and turbidity patterns in Kerr Lake from LANDSAT MSS imagery. [Kerr Lake, Virginia, North Carolina

    NASA Technical Reports Server (NTRS)

    Lecroy, S. R. (Principal Investigator)

    1981-01-01

    The LANDSAT imagery was historically analyzed to determine the circulation and turbidity patterns of Kerr Lake, located on the Virginia-North Carolina border. By examining the seasonal and regional turbidity and circulation patterns, a record of sediment transport and possible disposition can be obtained. Sketches were generated, displaying different intensities of brightness observed in bands 5 and 7 of LANDSAT's multispectral scanner data. Differences in and between bands 5 and 7 indicate variances in the levels of surface sediment concentrations. High sediment loads are revealed when distinct patterns appear in the band 7 imagery. The upwelled signal is exponential in nature and saturates in band 5 at low wavelengths for large concentrations of suspended solids.

  14. Korean coastal water depth/sediment and land cover mapping /1:25,000/ by computer analysis of Landsat imagery

    NASA Technical Reports Server (NTRS)

    Park, K. Y.; Miller, L. D.

    1980-01-01

    Computer analysis was applied to single data Landsat MSS imagery of a coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map, and featuring large dynamic sediment transport processes. Supervised image processing yielded a test classification map containing five water depth/sediment classes, two shoreline/tidal classes and five coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%; the training sets were selected by direct examination of the digitally displayed imagery. The unsupervised ISOCLAS (Senkus, 1976) clustering analysis was performed to assess the relative value of this approach to image classification in areas of sparse or nonexistent ground control. Results indicate that it is feasible to produce quantitative maps for detailed study of dynamic coastal processes given a Landsat image data base at sufficiently frequent time intervals.

  15. Korean coastal water depth/sediment and land cover mapping /1:25,000/ by computer analysis of Landsat imagery

    NASA Technical Reports Server (NTRS)

    Park, K. Y.; Miller, L. D.

    1980-01-01

    Computer analysis was applied to single data Landsat MSS imagery of a coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map, and featuring large dynamic sediment transport processes. Supervised image processing yielded a test classification map containing five water depth/sediment classes, two shoreline/tidal classes and five coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%; the training sets were selected by direct examination of the digitally displayed imagery. The unsupervised ISOCLAS (Senkus, 1976) clustering analysis was performed to assess the relative value of this approach to image classification in areas of sparse or nonexistent ground control. Results indicate that it is feasible to produce quantitative maps for detailed study of dynamic coastal processes given a Landsat image data base at sufficiently frequent time intervals.

  16. Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion

    NASA Astrophysics Data System (ADS)

    Yang, Yun; Anderson, Martha C.; Gao, Feng; Hain, Christopher R.; Semmens, Kathryn A.; Kustas, William P.; Noormets, Asko; Wynne, Randolph H.; Thomas, Valerie A.; Sun, Ge

    2017-02-01

    As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes and is directly affected by water and land management, land use change and climate variability. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on the spatial and temporal resolution of satellite data, combined with the effects of cloud contamination, constrain the amount of detail that a single satellite can provide. In this study, we describe an application of a multi-sensor ET data fusion system over a mixed forested/agricultural landscape in North Carolina, USA, during the growing season of 2013. The fusion system ingests ET estimates from the Two-Source Energy Balance Model (TSEB) applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms: hourly geostationary satellite data at 4 km resolution, daily 1 km imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) and biweekly Landsat thermal data sharpened to 30 m. These multiple ET data streams are combined using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to estimate daily ET at 30 m resolution to investigate seasonal water use behavior at the level of individual forest stands and land cover patches. A new method, also exploiting the STARFM algorithm, is used to fill gaps in the Landsat ET retrievals due to cloud cover and/or the scan-line corrector (SLC) failure on Landsat 7. The retrieved daily ET time series agree well with observations at two AmeriFlux eddy covariance flux tower sites in a managed pine plantation within the modeling domain: US-NC2 located in a mid-rotation (20-year-old) loblolly pine stand and US-NC3 located in a recently clear-cut and replanted field site. Root mean square errors (RMSEs) for NC2 and NC3 were 0.99 and 1.02 mm day-1, respectively, with mean absolute errors of approximately 29 % at the

  17. Use of landsat ETM+ SLC-off segment-based gap-filled imagery for crop type mapping

    USGS Publications Warehouse

    Maxwell, S.K.; Craig, M.E.

    2008-01-01

    Failure of the Scan Line Corrector (SLC) on the Landsat ETM+ sensor has had a major impact on many applications that rely on continuous medium resolution imagery to meet their objectives. The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) program uses Landsat imagery as the primary source of data to produce crop-specific maps for 20 states in the USA. A new method has been developed to fill the image gaps resulting from the SLC failure to support the needs of Landsat users who require coincident spectral data, such as for crop type mapping and monitoring. We tested the new gap-filled method for a CDL crop type mapping project in eastern Nebraska. Scan line gaps were simulated on two Landsat 5 images (spring and late summer 2003) and then gap-filled using landscape boundary models, or segment models, that were derived from 1992 and 2002 Landsat images (used in the gap-fill process). Various date combinations of original and gap-filled images were used to derive crop maps using a supervised classification process. Overall kappa values were slightly higher for crop maps derived from SLC-off gap-filled images compared to crop maps derived from the original imagery (0.3–1.3% higher). Although the age of the segment model used to derive the SLC-off gap-filled product did not negatively impact the overall agreement, differences in individual cover type agreement did increase (−0.8%–1.6% using the 2002 segment model to −5.0–5.1% using the 1992 segment model). Classification agreement also decreased for most of the classes as the size of the segment used in the gap-fill process increased.

  18. Processing Satellite Imagery To Detect Waste Tire Piles

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  19. Mapping of West Siberian taiga wetland complexes using Landsat imagery: Implications for methane emissions

    NASA Astrophysics Data System (ADS)

    Terentieva, Irina; Sabrekov, Alexander; Glagolev, Mikhail; Maksyutov, Shamil

    2017-04-01

    Boreal wetlands are important for understanding climate change risks because these environments sink carbon dioxide and emit methane. The West Siberia Lowland (WSL) is the biggest peatland area in Eurasia and is situated in the high latitudes experiencing enhanced rate of climate change. However, fine-scale heterogeneity of wetland landscapes poses a serious challenge when generating regional-scale estimates of greenhouse gas fluxes from point observations. A number of peatland maps of the West Siberia was developed in 1970s, but their accuracy is limited. In order to reduce uncertainties at the regional scale, we mapped wetlands and water bodies in the WSL on a scene-by-scene basis using a supervised classification of Landsat imagery. Training data consisted of high-resolution images and extensive field data collected at 41 test areas. The classification scheme aimed at supporting methane inventory applications and included 7 wetland ecosystem types comprising 9 wetland complexes distinguishable at the Landsat resolution. To merge typologies, mean relative areas of wetland ecosystems within each wetland complex type were estimated using high-resolution images. Accuracy assessment based on 1082 validation polygons of 10×10 pixels indicated an overall map accuracy of 79%. The total area of the WSL wetlands and water bodies was estimated to be 70.78 Mha or 5-17% of the global wetland area. Various oligotrophic environments are dominant among wetland ecosystems, while different fens cover only 14% of the area. Taiga zone contains 75% of WSL's wetlands; their distribution was described in detail by Terentieva et al. (2016). Concerning methane emission, taiga contributes 85% to regional methane flux and tundra only 8%, however ebullition in tundra lakes was not directly measured. Elevated environments as forested bogs and ridges emit at the lowest rates of methane emission. They account for only 2% of the regional total emissions occupying almost 40% of the wetland

  20. Modelling avian biodiversity using raw, unclassified satellite imagery

    PubMed Central

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

    2014-01-01

    Applications of remote sensing for biodiversity conservation typically rely on image classifications that do not capture variability within coarse land cover classes. Here, we compare two measures derived from unclassified remotely sensed data, a measure of habitat heterogeneity and a measure of habitat composition, for explaining bird species richness and the spatial distribution of 10 species in a semi-arid landscape of New Mexico. We surveyed bird abundance from 1996 to 1998 at 42 plots located in the McGregor Range of Fort Bliss Army Reserve. Normalized Difference Vegetation Index values of two May 1997 Landsat scenes were the basis for among-pixel habitat heterogeneity (image texture), and we used the raw imagery to decompose each pixel into different habitat components (spectral mixture analysis). We used model averaging to relate measures of avian biodiversity to measures of image texture and spectral mixture analysis fractions. Measures of habitat heterogeneity, particularly angular second moment and standard deviation, provide higher explanatory power for bird species richness and the abundance of most species than measures of habitat composition. Using image texture, alone or in combination with other classified imagery-based approaches, for monitoring statuses and trends in biological diversity can greatly improve conservation efforts and habitat management. PMID:24733952

  1. Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss

    USGS Publications Warehouse

    Potapov, P.; Hansen, Matthew C.; Stehman, S.V.; Loveland, T.R.; Pittman, K.

    2008-01-01

    Estimation of forest cover change is important for boreal forests, one of the most extensive forested biomes, due to its unique role in global timber stock, carbon sequestration and deposition, and high vulnerability to the effects of global climate change. We used time-series data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to produce annual forest cover loss hotspot maps. These maps were used to assign all blocks (18.5 by 18.5 km) partitioning the boreal biome into strata of high, medium and low likelihood of forest cover loss. A stratified random sample of 118 blocks was interpreted for forest cover and forest cover loss using high spatial resolution Landsat imagery from 2000 and 2005. Area of forest cover gross loss from 2000 to 2005 within the boreal biome is estimated to be 1.63% (standard error 0.10%) of the total biome area, and represents a 4.02% reduction in year 2000 forest cover. The proportion of identified forest cover loss relative to regional forest area is much higher in North America than in Eurasia (5.63% to 3.00%). Of the total forest cover loss identified, 58.9% is attributable to wildfires. The MODIS pan-boreal change hotspot estimates reveal significant increases in forest cover loss due to wildfires in 2002 and 2003, with 2003 being the peak year of loss within the 5-year study period. Overall, the precision of the aggregate forest cover loss estimates derived from the Landsat data and the value of the MODIS-derived map displaying the spatial and temporal patterns of forest loss demonstrate the efficacy of this protocol for operational, cost-effective, and timely biome-wide monitoring of gross forest cover loss.

  2. Monitoring change in the Bering Glacier region, Alaska: Using Landsat TM and ERS-1 imagery

    SciTech Connect

    Payne, J.F.; Coffeen, M.; Macleod, R.D.

    1997-06-01

    The Bering Glacier is the largest (5,180 km{sup 2}) and longest (191 km) glacier in continental North America. This glacier is one of about 200 temperate glaciers in the Alaska/Canada region that are known to surge. Surges at the Bering Glacier typically occur on a 20-30 year cycle. The objective of this project was to extract information regarding the position of the terminus of the glacier from historic aerial photography, early 20{sup th} century ground photography, Landsat Thematic Mapper (TM) satellite data, and European Space Agency, Synthetic Aperture RADAR (ERS-1 SAR) data and integrate it into a single digital database that would lend itself to change detection analysis. ERS-1 SAR data was acquired from six dates between 1992-95 and was terrain corrected and co-registered A single Landsat TM image from June 1991 was used as the base image for classifying land cover types. Historic locations of the glacier terminus were generated using traditional photo interpretation techniques from aerial and ground photography. The result of this platform combination, along with the historical data, is providing land managers with the unique opportunity to generate complete assessments of glacial movement this century and determine land cover changes which may impact wildlife and recreational opportunities.

  3. Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis

    NASA Technical Reports Server (NTRS)

    Potter, Christopher S.

    2015-01-01

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

  4. Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance

    USGS Publications Warehouse

    Huang, C.; Wylie, B.; Yang, L.; Homer, C.; Zylstra, G.

    2002-01-01

    A new tasselled cap transformation based on Landsat 7 at-satellite reflectance was developed. This transformation is most appropriate for regional applications where atmospheric correction is not feasible. The brightness, greenness and wetness of the derived transformation collectively explained over 97% of the spectral variance of the individual scenes used in this study.

  5. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  6. Vegetation cover dynamics of the Mongolian semiarid zone according to multi-temporal LANDSAT imagery (the case of Darkhan test range)

    NASA Astrophysics Data System (ADS)

    Zharnikova, M. A.; Alymbaeva, ZH B.; Ayurzhanaev, A. A.; Garmaev, E. ZH

    2016-11-01

    At present much attention is given to the spatio-temporal dynamics of plant communities of steppes to assess their response to the current climate changes. In this study, a mapping of a selected modeling polygon was carried out on the basis of data decoding and field surveys of vegetation cover in the semi-arid zone. The resulting large-scale map of actual vegetation reflects the current state of the vegetation cover and its horizontal structure. It is a valuable material for monitoring of changes in the chosen area. With multi-temporal satellite Landsat imagery we consider the vegetation cover dynamics of the test range. To analyze the transformation of the environment by the climatic factors, we compared series of NDVI versus the precipitation and of NDVI versus the temperatures. Then we calculated the degree of correlation between them.

  7. Monitoring water quality from LANDSAT. [satellite observation of Virginia

    NASA Technical Reports Server (NTRS)

    Barker, J. L.

    1975-01-01

    Water quality monitoring possibilities from LANDSAT were demonstrated both for direct readings of reflectances from the water and indirect monitoring of changes in use of land surrounding Swift Creek Reservoir in a joint project with the Virginia State Water Control Board and NASA. Film products were shown to have insufficient resolution and all work was done by digitally processing computer compatible tapes. Land cover maps of the 18,000 hectare Swift Creek Reservoir watershed, prepared for two dates in 1974, are shown. A significant decrease in the pine cover was observed in a 740 hectare construction site within the watershed. A measure of the accuracy of classification was obtained by comparing the LANDSAT results with visual classification at five sites on a U-2 photograph. Such changes in land cover can alert personnel to watch for potential changes in water quality.

  8. The use of ERTS/LANDSAT imagery in relation to airborne remote sensing for terrain analysis in Western Queensland, Australia

    NASA Technical Reports Server (NTRS)

    Cole, M. M. (Principal Investigator); Owen-Jones, E. S.

    1976-01-01

    The author has identified the following significant results. LANDSAT 1 and 2 imagery contrast the geology of the Cloncurry-Dobbyn and the Gregory River-Mt. Isa areas very clearly. Known major structural features and lithological units are clearly displayed while, hitherto unknown lineaments were revealed. Throughout this area, similar rock types produce similar spectral signatures, e.g. quartzites produce light signatures, iron rich rocks produce dark signatures. More geological data are discernible at the 1:50,000 scale than on the 1:250,000 scale. Ore horizons may be identified at the 1:50,000 scale, particularly where they are associated with iron rich rocks. On the level plains north of Cloncurry, distinctive spectral signatures produced by the combined reflectances of plant cover, soils, and geology, distinguish different types of superficial deposits. Existing and former channels of the Cloncurry and Williams Rivers are distinguished at the 1:50,000 scale on both the LANDSAT 1 and 2 imagery. On the Cloncurry Plains, fence lines are discernible on the 1:50,000 LANDSAT 2 imagery.

  9. Hydrological applications of Landsat imagery used in the study of the 1973 Indus River flood, Pakistan

    USGS Publications Warehouse

    Deutsch, Morris; Ruggles, F.H.

    1978-01-01

    During August and September 1973, the Indus River Valley of Pakistan experienced one of the largest floods on record, resulting in damages to homes, businesses, public works, and crops amounting to millions of rupees. Tremendous areas of lowlands were inundated along the Indus River and major tributaries. Landsat data made it possible to easily measure the extent of flooding, totaling about 20,000 km2 within an area of about 400,000 km2 south from the Punjab to the Arabian Sea.The Indus River data were used to continue experimentation in the development of rapid, accurate, and inexpensive optical techniques of flood mapping by satellite begun in 1973 for the Mississipi River floods. The research work on the Indus River not resulted in the development of more effective procedures for optical processing of flood data and synoptically depicting flooding, but also provided potentially valuable ancillary information concerning the hydrology of much of the Indus River Basin.

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

    USGS Publications Warehouse

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

    2002-01-01

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

  11. Landsat-8 imagery to estimate clarity in near-shore coastal waters: Feasibility study - Chabahar Bay, Iran

    NASA Astrophysics Data System (ADS)

    Kabiri, Keivan; Moradi, Masoud

    2016-08-01

    This study examined the advantages of incorporating the new band of Landsat-8 OLI imagery (band 1: Coastal/Aerosol, 435-451 nm) to a model for estimation of Secchi disk depth (SDD) values (as an indicator for transparency) in near-shore coastal waters using multispectral bands. In doing so, Chabahar Bay in the southern part of Iran (north of Gulf of Oman) was selected as the study area. Two approximately four-hour in-situ observations (including 48 and 56 field measured SDD values for each date respectively) were performed in the study area using Secchi disk; this was designed to start about two hours before and end about two hours after the time of satellite overpasses. Thereafter, a model was formed for estimation of SDD values based on the terms including all possible linear and mutual ratio values of Coastal/Aerosol (B1), Blue (B2), Green (B3), and Red bands (B4). In the first step, the correlation between reflectance/ratio reflectance values of these bands and Ln(SDD) values were calculated to indicate higher correlated bands/band ratios with the first field measured SDD values. Consequently, 17 combinations of highest correlated bands/band ratios were selected to estimate SDD values. In this regard, 32 points among the 48 field observations were selected to determine unknown coefficients of models using a multiple linear regression, and the rest 16 points were designated for accuracy assessment the results. Eventually, the measured SDD values in second field observations were utilized for validating the results. Final results demonstrated that combination of linear terms including B1, B2 and B3 bands and band ratio terms including ratio reflectance values of B4/B3, B3/B1, and B2/B1 has led to obtain the highest accuracy (R2=0.866 and RMSE=0.919, SVM feature weight=4.294). This was in agreement with the results obtained from the second observations. Finally, by applying the entire 104 field observed SDD values, the model in form of SDD=0.077exp(1.209RB1

  12. Detecting wetland changes in Shanghai, China using FORMOSAT and Landsat TM imagery

    NASA Astrophysics Data System (ADS)

    Tian, Bo; Zhou, Yun-Xuan; Thom, Ronald M.; Diefenderfer, Heida L.; Yuan, Qing

    2015-10-01

    Understanding the state of wetland ecosystems and their changes at the national and local levels is critical for wetland conservation, management, decision-making, and policy development practices. This study analyzed the wetlands in Shanghai, a province-level city, using remote sensing, image processing, and geographic information systems (GIS) techniques based on the Chinese national wetland inventory procedure and standards. FORMOSAT imagery acquired in 2012 and Navy nautical charts of the Yangtze estuarine area were used in conjunction with object-oriented segmentation, expert interpretation, and field validation to determine wetland status. Landsat imagery from 1985, 1995, 2000, 2003 and 2013 as well as social-economic data collected from 1985 to 2013 were used to further assess wetland changes. In 2013, Shanghai contained 376970.6 ha of wetlands, and 78.8% of all wetlands were in marine or estuarine systems. Estuarine waters comprised the single largest wetland category. Between the first national wetland inventory in 2003 and the second national wetland inventory in 2013, Shanghai lost 50519.1 ha of wetlands, amounting to a mean annual loss rate of 1.2% or an 11.8% loss over the decade. Declines were proportionately higher in marine and estuarine wetlands, with an annual loss of 1.8%, while there was a sharp increase of 1882.6% in constructed water storage areas for human uses. Diking, filling, impoundment and reclamation, which are all attributable to the economic development and urbanization associated with population increases, were the major factors that explained the gain and loss of wetlands. Additional factors affecting wetland losses and gains include sediment trapping by the hydropower system, which reduces supply to the estuary and erodes wetlands, and sediment trapping by the jetties, spur dikes, and diversion bulwark associated with a navigation channel deepening project, which has the converse effect, increasing saltmarsh wetland area at

  13. Detecting wetland changes in Shanghai, China using FORMOSAT and Landsat TM imagery

    SciTech Connect

    Tian, Bo; Zhou, Yun-xuan; Thom, Ronald M.; Diefenderfer, Heida L.; Yuan, Qing

    2015-07-14

    Understanding the state of wetland ecosystems and their changes at the national and local levels is critical for wetland conservation, management, decision-making, and policy development practices. This study analyzed the wetlands in Shanghai, a province-level city, using remote sensing, image processing, and geographic information systems (GIS) techniques based on the Chinese national wetland inventory procedure and standards. FORMOSAT imagery acquired in 2012 and Navy nautical charts of the Yangtze estuarine area were used in conjunction with object-oriented segmentation, expert interpretation, and field validation to determine wetland status. Landsat imagery from 1985, 1995, 2000, 2003 and 2013 as well as social-economic data collected from 1985 to 2013 were used to further assess wetland changes. In 2013, Shanghai contained 376,970.6 ha of wetlands, and 78.8% of all wetlands were in marine or estuarine systems. Estuarine waters comprised the single largest wetland category. Between the first national wetland inventory in 2003 and the second national wetland inventory in 2013, Shanghai lost 50,519.13 ha of wetlands, amounting to a mean annual loss rate of 1.2% or an 11.8% loss over the decade. Declines were proportionately higher in marine and estuarine wetlands, with an annual loss of 1.8%, while there was a sharp increase of 1882.6% in constructed water storage areas for human uses. Diking, filling, impoundment and reclamation, which are all attributable to the economic development and urbanization associated with population increases, were the major factors that explained the gain and loss of wetlands. Additional factors affecting wetland losses and gains include sediment trapping by the hydropower system, which reduces supply to the estuary and erodes wetlands, and sediment trapping by the jetties, spur dikes, and diversion bulwark associated with a navigation channel deepening project, which has the converse effect, increasing saltmarsh wetland area at

  14. Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region, New Zealand.

    PubMed

    Hicks, Brendan J; Stichbury, Glen A; Brabyn, Lars K; Allan, Mathew G; Ashraf, Salman

    2013-09-01

    Cost-effective monitoring is necessary for all investigations of lake ecosystem responses to perturbations and long-term change. Satellite imagery offers the opportunity to extend low-cost monitoring and to examine spatial and temporal variability in water clarity data. We have developed automated procedures using Landsat imagery to estimate total suspended sediments (TSS), turbidity (TURB) in nephlometric turbidity units (NTU) and Secchi disc transparency (SDT) in 34 shallow lakes in the Waikato region, New Zealand, over a 10-year time span. Fifty-three Landsat 7 Enhanced Thematic Mapper Plus images captured between January 2000 and March 2009 were used for the analysis, six of which were captured within 24 h of physical in situ measurements for each of 10 shallow lakes. This gave 32-36 usable data points for the regressions between surface reflectance signatures and in situ measurements, which yielded r (2) values ranging from 0.67 to 0.94 for the three water clarity variables. Using these regressions, a series of Arc Macro Language scripts were developed to automate image preparation and water clarity analysis. Minimum and maximum in situ measurements corresponding to the six images were 2 and 344 mg/L for TSS, 75 and 275 NTU for TURB, and 0.05 and 3.04 m for SDT. Remotely sensed water clarity estimates showed good agreement with temporal patterns and trends in monitored lakes and we have extended water clarity datasets to previously unmonitored lakes. High spatial variability of TSS and water clarity within some lakes was apparent, highlighting the importance of localised inputs and processes affecting lake clarity. Moreover, remote sensing can give a whole lake view of water quality, which is very difficult to achieve by in situ point measurements.

  15. Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forests

    Treesearch

    Elizabeth E. Hoy; Nancy H.F. French; Merritt R. Turetsky; Simon N. Trigg; Eric S. Kasischke

    2008-01-01

    Satellite remotely sensed data of fire disturbance offers important information; however, current methods to study fire severity may need modifications for boreal regions. We assessed the potential of the differenced Normalized Burn Ratio (dNBR) and other spectroscopic indices and image transforms derived from Landsat TM/ETM+ data for mapping fire severity in Alaskan...

  16. Assessment of mangrove forests in the Pacific region using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Bhattarai, Bibek; Giri, Chandra

    2011-01-01

    The information on the mangrove forests for the Pacific region is scarce or outdated. A regional assessment based on a consistent methodology and data sources was needed to understand their true extent. Our investigation offers a regionally consistent, high resolution (30 m), and the most comprehensive mapping of mangrove forests on the islands of American Samoa, Fiji, French Polynesia, Guam, Hawaii, Kiribati, Marshall Islands, Micronesia, Nauru, New Caledonia, Northern Mariana Islands, Palau, Papua New Guinea, Samoa, Solomon Islands, Tonga, Tuvalu, Vanuatu, and Wallis and Futuna Islands for the year 2000. We employed a hybrid supervised and unsupervised image classification technique on a total of 128 Landsat scenes gathered between 1999 and 2004, and validated the results using existing geographic information science (GIS) datasets, high resolution imagery, and published literature. We also draw a comparative analysis with the mangrove forests inventory published by the Food and Agriculture Association (FAO) of the United Nations. Our estimate shows a total of 623755 hectares of mangrove forests in the Pacific region; an increase of 18% from FAO's estimates. Although mangrove forests are disproportionately distributed toward a few larger islands on the western Pacific, they are also significant in many smaller islands.

  17. Automatic Extraction of Tide-Coordinated Shoreline Using Open Source Software and Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Goncalves, G.; Duro, N.; Sousa, E.; Figueiredo, I.

    2015-04-01

    Due to both natural and anthropogenic causes, the coastal lines keeps changing dynamically and continuously their shape, position and extend over time. In this paper we propose an approach to derive a tide-coordinate shoreline from two extracted instantaneous shorelines corresponding to a nearly low tide and high tide events. First, all the multispectral images are panshaperned to meet the 15 meters spatial resolution of the panchromatic images. Second, by using the Modification of Normalized Difference Water Index (MNDWI) and the kmeans clustering method we extract the raster shoreline for each image acquisition time. Third, each raster shoreline is smoothed and vectorized using a penalized least square method. Fourth, a 2D constrained Delaunay triangulation is built from the two extracted instantaneous shorelines with their respective heights interpolated from a Tidal gauche station. Finally, the desired tide-coordinate shoreline is interpolated from the previous triangular intertidal surface. The results show that an automatic tide-coordinated extraction method can be efficiently implemented using free available remote sensing imagery data (Landsat 8) and open source software (QGIS and Orfeo toolbox) and python scripting for task automation and software integration.

  18. An operational earth resources satellite system: The LANDSAT follow-on program

    NASA Technical Reports Server (NTRS)

    Stroud, W. G.

    1977-01-01

    The LANDSATS 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The LANDSAT Follow-on Study addressed the economics, technological performance, and design of a system in transition from R and D to operations. Economic benefits were identified; and a complete system from sensors to the ultilization in forecasting crop production, oil and mineral exploration, and water resources management was designed.

  19. Assessment and Prediction of Natural Hazards from Satellite Imagery.

    PubMed

    Gillespie, Thomas W; Chu, Jasmine; Frankenberg, Elizabeth; Thomas, Duncan

    2007-10-01

    Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth's surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake damage comes from high-resolution (0.6 m to 1 m pixel size) passive sensors and moderate resolution active sensors that can quantify the vertical and horizontal movement of the earth's surface. High-resolution passive sensors have been used to successfully assess flood damage while predictive maps of flood vulnerability areas are possible based on physical variables collected from passive and active sensors. Recent moderate resolution sensors are able to provide near real time data on fires and provide quantitative data used in fire behavior models. Limitations currently exist due to atmospheric interference, pixel resolution, and revisit times. However, a number of new microsatellites and constellations of satellites will be launched in the next five years that contain increased resolution (0.5 m to 1 m pixel resolution for active sensors) and revisit times (daily ≤ 2.5 m resolution images from passive sensors) that will significantly improve our ability to assess and predict natural hazards from space.

  20. Spectral discrimination of lithologic facies in the granite of the Pedra Branca Goias using LANDSAT 1 digital imagery

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J.; Almeido, R., Jr.

    1982-01-01

    The applicability of LANDSAT MSS imagery for discriminating geobotanical associations observed in zones of cassiterite-rich metasomatic alterations in the granitic body of Serra da Pedra Branca was investigated. Computer compatible tapes of dry and rainy season imagery were analyzed. Image enlargement, corrections, linear contrast stretch, and ratioing of noncorrelated spectral bands were performed using the Image 100 with a grey scale of 256 levels between zero and 255. Only bands 5 and 7 were considered. Band ratioing of noncorrelated channels (5 and 7) of rainy season imagery permits distinction of areas with different vegetation coverage percentage, which corresponds to geobotanial associations in the area studied. The linear contrast stretch of channel 5, especially of the dry season image is very unsatisfactory in this area.

  1. Specification and preliminary design of the CARTA system for satellite cartography

    NASA Technical Reports Server (NTRS)

    Machadoesilva, A. J. F. (Principal Investigator); Neto, G. C.; Serra, P. R. M.; Souza, R. C. M.; Mitsuo, Fernando Augusta, II

    1984-01-01

    Digital imagery acquired by satellite have inherent geometrical distortion due to sensor characteristics and to platform variations. In INPE a software system for geometric correction of LANDSAT MSS imagery is under development. Such connected imagery will be useful for map generation. Important examples are the generation of LANDSAT image-charts for the Amazon region and the possibility of integrating digital satellite imagery into a Geographic Information System.

  2. Ortophoto and satellite imagery to monitoring biochar in mountain soils (NW of Cantabrian Range, Spain)

    NASA Astrophysics Data System (ADS)

    Fernández, S.; Roces, P.; Recondo, C.; Santin, C.

    2012-04-01

    In the Northwest of the Cantabrian Mountain Range the climate is oceanic and the vegetation cover should be mainly wood forests and heathlands. However, frequent wildfires have led to a progressive degradation of the vegetation cover by enhancing the development of extensive moorlands and pyrophytes species of high combustibility. Previous studies have proved that this intense fire history has altered the rates of carbon (C) transfer from vegetation to soil and carbon accumulation in soils. In this way, C stocks of 32 Mg/ha and 90 Mg/ha were measured in unburned and burned forest soils, respectively. The use of satellite imagery indexes (NDVI; fAPAR and LAI) showed a higher capability of C fixation in the unburned woodland biomass than in the burned one. On the other hand, the burned woodlands presented greater amounts of C stored in soils, mainly due to transfer processes promoted by the fires. Satellite imagery and ortophotography could be useful in order to monitor the C sequestration in soils. Several chemical bonds which represent different forms of soil organic C absorb energy from different wavelengths of the electromagnetic spectrum. The near infrared and visible bands reflectance values could be related to the amounts and types of soil carbon. In this work, we want to test the use of Landsat; Spot and MODIS satellite imageries and orthophotos to monitoring the pool of biochar in soils of wide mountain areas with high rates of C transfer from vegetation to soil, promoted by forest fires. 55 georeferenced soil samples, taken in an area 100 km2 located in the Northwest sector of the Cantabrian Range were crossed with ortophotos and satellite images taken in the winter season. Several spectrometric indexes related to soil properties (NDSI, NDBaI,), color indexes from the visible part of spectrum (SWIR) and values from visible and thermal infrared were calculated for each soil sample. Multivariate statistical analyses will be used to build models to relate the

  3. A model based on satellite altimetry and imagery to evaluate water volume changes in a reservoir in Brazil

    NASA Astrophysics Data System (ADS)

    de C. Abreu, Luiza Gontijo Álvares; Maillard, Philippe

    2014-10-01

    Different satellite missions have instruments to measure the water level variation of oceans and some of these instruments are being used in continental water applications with satisfying results. Altimeters on-board the Envisat and SARAL(Altika) satellites are consistently used to measure the water level in continental water bodies. Recent studies on satellite altimetry combined with satellite imagery have shown the great potential of this technique to estimate the water volume of rivers, lakes, wetlands and reservoirs and its temporal variation in response to climate and other environmental variables. A consistent monitoring of water level variations in reservoirs is crucial to the development policies and implementation of actions regarding the distribution and use of the stored water resource. The Trés Marias reservoir is located within the São Francisco river basin, known as the national integration" river, which provides water flow to the semi-arid region of Brazil. This study presents a method to combine satellite altimetry and imagery of the lake's surface to estimate volume changes and create a model from which volume changes could be computed from either the altimetry or the lake's surface area. Our intention with this study is to evaluate the method and its precision, and the possibility to apply it in other areas, such as wetlands and other lakes where in situ measurements are not available. Moreover, data of monitoring stations usually have an arbitrary altitude reference and are not available for the general public; the data from the satellite altimetry has the advantage of being of global reference (geoid) and compatible with the establishment of a worldwide lake and reservoir database. We combined Envisat and SARAL/Altika altimetry data from 2007-2014 period with Landsat imagery from the same time frame. The data was corrected using a novel processing technique resulting in a relative precision of 0.24 m (RMSE).

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

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

    PubMed

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

    2016-08-19

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

  6. Optical and Physical Methods for Mapping Flooding with Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Fayne, Jessica Fayne; Bolten, John; Lakshmi, Venkat; Ahamed, Aakash

    2016-01-01

    Flood and surface water mapping is becoming increasingly necessary, as extreme flooding events worldwide can damage crop yields and contribute to billions of dollars economic damages as well as social effects including fatalities and destroyed communities (Xaio et al. 2004; Kwak et al. 2015; Mueller et al. 2016).Utilizing earth observing satellite data to map standing water from space is indispensable to flood mapping for disaster response, mitigation, prevention, and warning (McFeeters 1996; Brakenridge and Anderson 2006). Since the early 1970s(Landsat, USGS 2013), researchers have been able to remotely sense surface processes such as extreme flood events to help offset some of these problems. Researchers have demonstrated countless methods and modifications of those methods to help increase knowledge of areas at risk and areas that are flooded using remote sensing data from optical and radar systems, as well as free publically available and costly commercial datasets.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  8. Examining Urban Expansion Using Multi-Temporal Landsat Imagery: a Case Study of the Montreal Census Metropolitan Area from 1975 TO 2015, Canada

    NASA Astrophysics Data System (ADS)

    Ma, Lingfei; Zhao, He; Li, Jonathan

    2016-06-01

    Urban expansion, particularly the movement of residential and commercial land use to sub-urban areas in metropolitan areas, has been considered as a significant signal of regional economic development. In 1970s, the economic centre of Canada moved from Montreal to Toronto. Since some previous research have been focused on the urbanization process in Greater Toronto Area (GTA), it is significant to conduct research in its counterpart. This study evaluates urban expansion process in Montréal census metropolitan area (CMA), Canada, between 1975 and 2015 using satellite images and socio-economic data. Spatial and temporal dynamic information of urbanization process was quantified using Landsat imagery, supervised classification algorithms and the post-classification change detection technique. Accuracy of the Landsat-derived land use classification map ranged from 80% to 97%. The results indicated that continuous growth of built-up areas in the CMA over the study period resulted in a decrease in the area of cultivated land and vegetation. The results showed that urban areas expanded 442 km2 both along major river systems and lakeshores, as well as expanded from urban centres to surrounded areas. The analysis revealed that urban expansion has been largely driven by population growth and economic development. Consequently, the urban expansion maps produced in this research can assist decision-makers to promote sustainable urban development, and forecast potential changes in urbanization growth patterns.

  9. Landsat 6 contract signed

    NASA Astrophysics Data System (ADS)

    Maggs, William Ward

    A new agreement provides $220 million for development and construction of the Landsat 6 remote sensing satellite and its ground systems. The contract, signed on March 31, 1988, by the Department of Commerce (DOC) and the Earth Observation Satellite (EOSAT) Company of Lanham, Md., came just days after approval of DOC's Landsat commercialization plan by subcommittees of the House and Senate appropriations committees.The Landsat 6 spacecraft is due to be launched into orbit on a Titan II rocket in June 1991 from Vandenburg Air Force Base, Calif. The satellite will carry an Enhanced Thematic Mapper (ETM) sensor, an instrument sensitive to electromagnetic radiation in seven ranges or bands of wavelengths. The satellite's payload will also include the Sea Wide Field Sensor (Sea-WiFS), designed to provide information on sea surface temperature and ocean color. The sensor is being developed in a cooperative effort by EOSAT and the National Aeronautics and Space Administration (NASA). A less certain passenger is a proposed 5-m resolution, three-band sensor sensitive to visible light. EOSAT is trying to find both private financing for the device and potential buyers of the high-resolution imagery that it could produce. The company has been actively courting U.S. television networks, which have in the past used imagery from the European Système Probatoire d'Observation de la Terre (SPOT) satellite for news coverage.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  11. INPE LANDSAT-D thematic mapper computer compatible tape format specification

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Desouza, R. C. M.

    1982-01-01

    The format of the computer compatible tapes (CCT) which contain Thematic Mapper (TM) imagery data acquired from the LANDSAT D and D Prime satellites by the INSTITUTO DE PERSQUISAS ESPACIALS (CNPq-INPE/BRAZIL) is defined.

  12. Wildland-Urban Interface evolution mapping using multi-temporal Landsat imagery. The case of forest fires in southern Swiss Alps.

    NASA Astrophysics Data System (ADS)

    Cere, R.; Conedera, M.; Matasci, G.; Kanevski, M.; Tonini, M.; Vega, C.; Volpi, M.

    2012-04-01

    -resolution Landsat imagery is less prone to suffer from high within-class variances, that is naturally smoothed by the spatial resolution of the image accounting for mixed pixels. Then, a second step implementing a post-classification comparison change detection scheme was performed, to detect WUI and related land-cover changes in time. The main result of the present project is a map of the evolution of WUI starting from satellite images and ignition points datasets. This project has been partly supported by the Swiss National Science Foundation under the project "kernelCD" 200021-126505 (www.kernelcd.org)

  13. Determining the dynamics of evapotranspiration from fragmented forests under drought in southwestern Amazonia using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Numata, I.; Khand, K.; Kjaersgaard, J.; Cochrane, M. A.; Silva, S.

    2016-12-01

    Deforestation in the Amazon has resulted in massive amounts of forest biomass loss and also in extensive forest fragmentation across the region. Fragmented tropical forests are exposed to abrupt environmental changes and experience several biological and ecological changes across distances from forest edges. Extreme droughts in 2005 and 2010 have caused extensive tree mortality across this region. These events may exacerbate edge effects, where already water stressed forest fragments dry more rapidly potentially enabling other disturbances such as forest fire. We analyzed the effects of forest fragmentation and drought on forest evapotranspiration (ET) estimated using the energy balance-based model METRIC with Landsat imagery in Rondônia State in the southwestern Amazon. Forest ET estimates were produced for the dry seasons (June-August) of 2009-2011 thus including the 2010 drought event and pre- and post-event periods. METRIC ET data were combined with forest edge data with edge distances of 100m, 300m, 500m, 1000m, 5000m and >5000m (core forest), generated from Landsat land cover maps for spatiotemporal analysis of forest ET. METRIC ET estimates had an agreement with flux tower ET data from the field of R2 = 0.72. Within the study time period, the 2010 drought year showed the lowest average ET from core forest (2.5mm/day), followed by 2011 (3.0mm/day) and 2009 (3.6mm/day) in the month of August, the mid dry season, while no significant differences were noted among three study years earlier in the dry seasons. In terms of edge effects, the major changes in forest ET occur up to 300 m from the forest edges, with ET decreasees of 30 % at 100 m as compared to further distances. The magnitude of edge-related ET changes became even greater during August of the drought year (2010) and the post-drought year (2011). Annual (drought and non-drought) and seasonal (June-August) forest ET variations were highly significant (p<0.001), while the impact of distance from edge on

  14. Advanced snow cover classification by combining terrestrial photography and satellite imagery

    NASA Astrophysics Data System (ADS)

    Härer, S.; Bernhardt, M.; Schulz, K.

    2013-12-01

    Terrestrial photography combined with the recently presented Photo Rectification And ClassificaTIon SoftwarE (PRACTISE V.1.0) has proven to be a valuable source to derive temporal and spatial high-resolution snow cover maps in mountain regions. However, the integrated automatic snow classification algorithm is restricted to images on equally illuminated terrain and the areal coverage of digital photographs is strongly limited. Here, we present PRACTISE V.1.1 which automatically classifies sunny and shaded areas in the photograph separately, eliminating disturbing shadow effects in the classification. The software also calculates the Normalized-Difference Snow Index (NDSI) for a simultaneously captured satellite image. Until now, it was found to be difficult to set the NDSI threshold for snow accurately even though it is critical for a correct classification. Our new method automatically optimizes the threshold value using the camera-derived snow cover map as a cost-effective technique for in-situ ground-truthing. Eventually, the satellite image is classified. The improved software was successfully tested for photographs of a single lens reflex camera and corresponding satellite images of the Landsat series in the Zugspitze massif (Germany). The results have shown that the combination of terrestrial photography and satellite imagery extends the mapping area enormously, keeping the quality of the snow cover maps high. The enlarged areal coverage enhances the potential use of this technique for validating spatially distributed snow hydrological models, even for larger catchments. The presented approach furthermore indicates that it is largely independent of the used sensor systems as well as the investigated surface variable which allows an application in other research disciplines.

  15. 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%.

  16. 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 ...

  17. The relationship between the spectral diversity of satellite imagery, habitat heterogeneity, and plant species richness

    Treesearch

    Steven D. Warren; Martin Alt; Keith D. Olson; Severin D. H. Irl; Manuel J. Steinbauer; Anke Jentsch

    2014-01-01

    Assessment of habitat heterogeneity and plant species richness at the landscape scale is often based on intensive and extensive fieldwork at great cost of time and money. We evaluated the use of satellite imagery as a quantitativemeasure of the relationship between the spectral diversity of satellite imagery, habitat heterogeneity, and plant species richness. A 16 km2...

  18. Thirty Years of Vegetation Change in the Coastal Santa Cruz Mountains of Northern California Detected Using Landsat Satellite Image Analysis

    NASA Technical Reports Server (NTRS)

    Potter, Christopher

    2015-01-01

    Results from Landsat satellite image times series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90% of the (predominantly second-growth) evergreen forest locations sampled.

  19. Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010

    USGS Publications Warehouse

    McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.

    2013-01-01

    Water clarity is a strong indicator of regional water quality. Unlike other common water-quality metrics, such as chlorophyll a, total P, or trophic status, clarity can be accurately and efficiently estimated remotely on a regional scale. Satellite-based remote sensing is useful in regions with many lakes where traditional field-sampling techniques may be prohibitively expensive. Repeated sampling of easily accessed lakes can lead to spatially irregular, nonrandom samples of a region. Remote sensing remedies this problem. We applied a remote monitoring protocol we had previously developed for Maine lakes >8 ha based on Landsat satellite data recorded during 1995–2010 to identify spatial and temporal patterns in Maine lake clarity. We focused on the overlapping region of Landsat paths 11 and 12 to increase availability of cloud-free images in August and early September, a period of relative lake stability and seasonal poor-clarity conditions well suited for annual monitoring. We divided Maine into 3 regions (northeastern, south-central, western) based on morphometric and chemical lake features. We found a general decrease in average statewide lake clarity from 4.94 to 4.38 m during 1995–2010. Water clarity ranged from 4 to 6 m during 1995–2010, but it decreased consistently during 2005–2010. Clarity in both the northeastern and western lake regions has decreased from 5.22 m in 1995 to 4.36 and 4.21 m, respectively, in 2010, whereas lake clarity in the south-central lake region (4.50 m) has not changed since 1995. Climate change, timber harvesting, or watershed morphometry may be responsible for regional water-clarity decline. Remote sensing of regional water clarity provides a more complete spatial perspective of lake water quality than existing, interest-based sampling. However, field sampling done under existing monitoring programs can be used to calibrate accurate models designed to estimate water clarity remotely.

  20. Mapping forest height, foliage height profiles and disturbance characteristics with time series of gap-filled Landsat and ALI imagery

    NASA Astrophysics Data System (ADS)

    Helmer, E.; Ruzycki, T. S.; Wunderle, J. M.; Kwit, C.; Ewert, D. N.; Voggesser, S. M.; Brandeis, T. J.

    2011-12-01

    We mapped tropical dry forest height (RMSE = 0.9 m, R2 = 0.84, range 0.6-7 m) and foliage height profiles with a time series of gap-filled Landsat and Advanced Land Imager (ALI) imagery for the island of Eleuthera, The Bahamas. We also mapped disturbance type and age with decision tree classification of the image time series. Having mapped these variables in the context of studies of wintering habitat of an endangered Nearctic-Neotropical migrant bird, the Kirtland's Warbler (Dendroica kirtlandii), we then illustrated relationships between forest vertical structure, disturbance type and counts of forage species important to the Kirtland's Warbler. The ALI imagery and the Landsat time series were both critical to the result for forest height, which the strong relationship of forest height with disturbance type and age facilitated. Also unique to this study was that seven of the eight image time steps were cloud-gap-filled images: mosaics of the clear parts of several cloudy scenes, in which cloud gaps in a reference scene for each time step are filled with image data from alternate scenes. We created each cloud-cleared image, including a virtually seamless ALI image mosaic, with regression tree normalization of the image data that filled cloud gaps. We also illustrated how viewing time series imagery as red-green-blue composites of tasseled cap wetness (RGB wetness composites) aids reference data collection for classifying tropical forest disturbance type and age.

  1. Large Area Scene Selection Interface (LASSI). Methodology of Selecting Landsat Imagery for the Global Land Survey 2005

    NASA Technical Reports Server (NTRS)

    Franks, Shannon; Masek, Jeffrey G.; Headley, Rachel M.; Gasch, John; Arvidson, Terry

    2009-01-01

    The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004-2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat 7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm's sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

  2. Large area scene selection interface (LASSI): Methodology of selecting landsat imagery for The Global Land Survey 2005

    USGS Publications Warehouse

    Franks, S.; Masek, J.G.; Headley, R.M.K.; Gasch, J.; Arvidson, T.

    2009-01-01

    The Global Land Survey (GLS) 2005 is a cloud-free, orthorec-tified collection of Landsat imagery acquired during the 2004 to 2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat-7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm’s sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

  3. A Two-Step Double Filter Method to Extract Open Water Surfaces from Landsat ETM+ Imagery

    NASA Astrophysics Data System (ADS)

    Wang, Haijing; Kinzelbach, Wolfgang

    2010-05-01

    In arid and semi-arid areas, lakes and temporal ponds play a significant role in agriculture and livelihood of local communities as well as in ecology. Monitoring the changes of these open water bodies allows to draw conclusions on water use as well as climatic impacts and can assist in the formulation of a sustainable resource management strategy. The simultaneous monitoring of larger numbers of water bodies with respect to their stage and area is feasible with the aid of remote sensing. Here the monitoring of lake surface areas is discussed. Landsat TM and ETM+ images provide a medium resolution of 30m, and offer an easily available data source to monitor the long term changes of water surfaces in arid and semi-arid regions. In the past great effort was put into developing simple indices to extract water surfaces from satellite images. However, there is a common problem in achieving accurate results with these indices: How to select a threshold value for water pixels without introducing excessive subjective judgment. The threshold value would also have to vary with location, land features and seasons, allowing for inherent uncertainty. A new method was developed using Landsat ETM+ imaginary (30 meter resolution) to extract open water surfaces. This method uses the Normalized Difference of Vegetation Index (NDVI) as the basis for an objective way of selecting threshold values of Modified Normalized Difference of Water Index (MNDWI) and Stress Degree Days (SDD), which were used as a combined filter to extract open water surfaces. We choose two study areas to verify the method. One study area is in Northeast China, where bigger lakes, smaller muddy ponds and wetlands are interspersed with agricultural land and salt crusts. The other one is Kafue Flats in Zambia, where seasonal floods of the Zambezi River create seasonal wetlands in addition to the more permanent water ponds and river channels. For both sites digital globe images of 0.5 meter resolution are available

  4. Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

    NASA Astrophysics Data System (ADS)

    Khalil, Zahid

    2016-07-01

    Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

  5. Korean coastal water depth/sediment and land cover mapping (1:25,000) by computer analysis of LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Park, K. Y.; Miller, L. D.

    1978-01-01

    Computer analysis was applied to single date LANDSAT MSS imagery of a sample coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map. Supervised image processing yielded a test classification map from this sample image containing 12 classes: 5 water depth/sediment classes, 2 shoreline/tidal classes, and 5 coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%. Unsupervised image classification was applied to a subportion of the site analyzed and produced classification maps comparable in results in a spatial sense. The results of this test indicated that it is feasible to produce such quantitative maps for detailed study of dynamic coastal processes given a LANDSAT image data base at sufficiently frequent time intervals.

  6. Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

    NASA Technical Reports Server (NTRS)

    Fagan, Matthew E.; Defries, Ruth S.; Sesnie, Steven E.; Arroyo-Mora, J. Pablo; Soto, Carlomagno; Singh, Aditya; Townsend, Philip A.; Chazdon, Robin L.

    2015-01-01

    An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  8. Assessment and Prediction of Natural Hazards from Satellite Imagery

    PubMed Central

    Gillespie, Thomas W.; Chu, Jasmine; Frankenberg, Elizabeth; Thomas, Duncan

    2013-01-01

    Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth’s surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake damage comes from high-resolution (0.6 m to 1 m pixel size) passive sensors and moderate resolution active sensors that can quantify the vertical and horizontal movement of the earth’s surface. High-resolution passive sensors have been used to successfully assess flood damage while predictive maps of flood vulnerability areas are possible based on physical variables collected from passive and active sensors. Recent moderate resolution sensors are able to provide near real time data on fires and provide quantitative data used in fire behavior models. Limitations currently exist due to atmospheric interference, pixel resolution, and revisit times. However, a number of new microsatellites and constellations of satellites will be launched in the next five years that contain increased resolution (0.5 m to 1 m pixel resolution for active sensors) and revisit times (daily ≤ 2.5 m resolution images from passive sensors) that will significantly improve our ability to assess and predict natural hazards from space. PMID:25170186

  9. The use of Landsat imagery in structural studies of middle Morocco

    NASA Astrophysics Data System (ADS)

    Bensaid, M.; Mahmood, A.

    Preliminary results of a tectonlinear study of Landsat MSS images in bands, 4, 5 and 7 covering Middle Morocco are presented. The relationships between lineaments and large-scale structural patterns are studied and compared with geological and ore deposits distribution data on the area. Middle Morocco in this article comprises parts of the Moroccan Meseta, Central and Eastern High Atlas and northeastern Anti-Atlas. Rocks of all ages, from Precambrian to Quaternary, are found, and the structural evolution of the area is due to Precambrian, Variscan and Alpine orogenies. Two main lineament sets are recognized on the satellite images. These are NE-SW and NW-SE. The NW-SE set of lineaments is prominent in older Precambrian and Paleozoic terranes, whereas the NE-SW set is observed both in the old inliers and massifs as well as in the younger mountain chains. The NE-SW lineaments therefore represent reactivated fractures that should have played an important role in the tectonics and sedimentary cycles of Middle Morocco. Other lineament trends are seen only in specific regions of the study area. Several major ore deposits follow lineament trends both in the basement and cover rocks. This is particularly true of endogenic deposits in the Anti-Atlas and in the Central Paleozoic massif.

  10. Testing ecoregions in Kentucky and Tennessee with satellite imagery and Forest Inventory data

    Treesearch

    W. Henry McNab; F. Thomas Lloyd

    2009-01-01

    Ecoregions are large mapped areas of hypothesized ecological uniformity that are delineated subjectively based on multiple physical and biological components. Ecoregion maps are seldom evaluated because suitable data sets are often lacking. Landsat imagery is a readily available, low-cost source of archived data that can be used to calculate the normalized difference...

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

    Treesearch

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

    2005-01-01

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

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

    Treesearch

    Ronald E. McRoberts; Greg C. Liknes

    2005-01-01

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

  13. Forest/non-forest mapping using inventory data and satellite imagery

    Treesearch

    Ronald E. McRoberts

    2002-01-01

    For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and two prediction techniques, logistic regression and a k-Nearest Neighbours technique. The maps were used to increase the precision of forest area estimates by...

  14. Mapping disturbances in a mangrove forest using multi-date landsat TM imagery.

    PubMed

    Kovacs, J M; Wang, J; Blanco-Correa, M

    2001-05-01

    To evaluate the accounts of local fishermen, Landsat TM images (1986, 1993, 1999) were examined to assess potential losses in the mangrove forests of the Teacapán-Agua Brava lagoon system, Mexico. A binary change mask derived from image differencing of a band 4/3 ratio was employed to calculate any changes within this forested wetland. The results indicate that by 1986 approximately 18% (or 86 km2) of the mangrove area under study was either dead or in poor condition. The majority of this damage had occurred in the eastern section of the Agua Brava basin, which coincides, with the reports of the elderly fishermen. Examination of aerial photographs from 1970 revealed no adverse impacts in this area and would suggest, as postulated by the fishermen and other scientists, that modifications in environmental conditions following the opening of a canal, Cuautlá canal, in 1972 may have initiated the large-scale mortality. Although these areas of impact are still developing, the results from the satellite data indicate that the majority of the more recent changes are occurring elsewhere in the system. Obvious in the 1999 satellite data, but not so in the 1993, are large areas of mangrove degradation in the northern section of the Teacapán region. In the Agua Brava basin, the more recent transformations are appearing on the western side of the basin. Since long-term records of environmental conditions are absent, it is difficult to determine why these latest changes are occurring or even if the earlier losses were the result of the canal. Potential agents of change that have recently been observed include a hurricane, a second canal, and the uncontrolled expansion of the Cuautlá canal since 1994.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  16. Remote estimation of Kd (PAR) using MODIS and Landsat imagery for turbid inland waters in Northeast China

    NASA Astrophysics Data System (ADS)

    Song, Kaishan; Ma, Jianhang; Wen, Zhidan; Fang, Chong; Shang, Yingxin; Zhao, Ying; Wang, Ming; Du, Jia

    2017-01-01

    Light availability for photosynthetically active radiation (PAR) is one of the major factors governing photosynthesis in aquatic ecosystems. Conventional measurements of light attenuation in the PAR domain (Kd(PAR)) is representative for only small areas of water body. Remotely sensed optical imagery can be utilized to monitor Kd(PAR) in large areas of water bodies, based on the relationship between water leaving radiance and Kd(PAR). In this study, six field surveys were conducted over 20 lakes (or reservoirs) across Northeast China from April to September 2015. In order to derive the Kd(PAR) at regional scale, the Landsat/TM/ETM+/OLI and the MODIS daily surface reflectance data (MOD09GA ∼500 m, Bands 1-7) were used to establish empirical inversion models. Through multiple stepwise regression analysis, the band difference (Red-Blue) and band ratio (NIR/Red) were used in Landsat imagery modeling, and the band difference (Red-Blue) and ratio (Red/Blue) were used in MODIS imagery modeling. The accuracy of the two models was evaluated by 10-fold cross-validation in ten times. The results indicate that the models performed well for both Landsat (R2 = 0.83, RMSE = 0.95, and MRE = 0.33), and MODIS (R2 = 0.86, RMSE = 0.91, and MRE = 0.19) imagery. However, the Kd(PAR) derived by MODIS is slightly higher than that estimated by Landsat (slope = 1.203 and R2 = 0.972). Consistency of model performance between the MODIS daily (MYD09G A) and the 8-Day composite reflectance (MYD09A1) data was verified by Kd(PAR) estimations and regression analysis (slope = 1.044 and R2 = 0.966). Finally, the spatial and temporal distribution of Kd(PAR) in Northeast China indicated that specific geographical characteristics as well as meteorological alterations can influence Kd(PAR) calibrations. Specifically, we have revealed that the wind speed and algal bloom are the major determinants of Kd(PAR) in Lake Hulun (2050 km2) and Xingkai (4412 km2).

  17. Nineteen hundred seventy three significant accomplishments. [Landsat satellite data applications

    NASA Technical Reports Server (NTRS)

    1974-01-01

    Data collected by the Skylab remote sensing satellites was used to develop applications techniques and to combine automatic data classification with statistical clustering methods. Continuing research was concentrated in the correlation and registration of data products and in the definition of the atmospheric effects on remote sensing. The causes of errors encountered in the automated classification of agricultural data are identified. Other applications in forestry, geography, environmental geology, and land use are discussed.

  18. Cloud cover determination in polar regions from satellite imagery

    NASA Technical Reports Server (NTRS)

    Barry, R. G.; Key, J.

    1989-01-01

    The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

  19. Surface Characteristics of Green Island Wakes from Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Campmany, E.; Grainger, R. G.; Dean, S. M.; Sayer, A. M.

    2009-03-01

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

  1. Improved Use of Satellite Imagery to Forecast Hurricanes

    NASA Technical Reports Server (NTRS)

    Louis, Jean-Francois

    2001-01-01

    This project tested a novel method that uses satellite imagery to correct phase errors in the initial state for numerical weather prediction, applied to hurricane forecasts. The system was tested on hurricanes Guillermo (1997), Felicia (1997) and Iniki (1992). We compared the performance of the system with and without phase correction to a procedure that uses bogus data in the initial state, similar to current operational procedures. The phase correction keeps the hurricane on track in the analysis and is far superior to a system without phase correction. Compared to operational procedure, phase correction generates somewhat worse 3-day forecast of the hurricane track, but better forecast of intensity. It is believed that the phase correction module would work best in the context of 4-dimensional variational data assimilation. Very little modification to 4DVar would be required.

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

    USGS Publications Warehouse

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

    2012-01-01

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

  3. Upper atmospheric gravity wave details revealed in nightglow satellite imagery

    PubMed Central

    Miller, Steven D.; Straka, William C.; Yue, Jia; Smith, Steven M.; Alexander, M. Joan; Hoffmann, Lars; Setvák, Martin; Partain, Philip T.

    2015-01-01

    Gravity waves (disturbances to the density structure of the atmosphere whose restoring forces are gravity and buoyancy) comprise the principal form of energy exchange between the lower and upper atmosphere. Wave breaking drives the mean upper atmospheric circulation, determining boundary conditions to stratospheric processes, which in turn influence tropospheric weather and climate patterns on various spatial and temporal scales. Despite their recognized importance, very little is known about upper-level gravity wave characteristics. The knowledge gap is mainly due to lack of global, high-resolution observations from currently available satellite observing systems. Consequently, representations of wave-related processes in global models are crude, highly parameterized, and poorly constrained, limiting the description of various processes influenced by them. Here we highlight, through a series of examples, the unanticipated ability of the Day/Night Band (DNB) on the NOAA/NASA Suomi National Polar-orbiting Partnership environmental satellite to resolve gravity structures near the mesopause via nightglow emissions at unprecedented subkilometric detail. On moonless nights, the Day/Night Band observations provide all-weather viewing of waves as they modulate the nightglow layer located near the mesopause (∼90 km above mean sea level). These waves are launched by a variety of physical mechanisms, ranging from orography to convection, intensifying fronts, and even seismic and volcanic events. Cross-referencing the Day/Night Band imagery with conventional thermal infrared imagery also available helps to discern nightglow structures and in some cases to attribute their sources. The capability stands to advance our basic understanding of a critical yet poorly constrained driver of the atmospheric circulation. PMID:26630004

  4. Upper atmospheric gravity wave details revealed in nightglow satellite imagery.

    PubMed

    Miller, Steven D; Straka, William C; Yue, Jia; Smith, Steven M; Alexander, M Joan; Hoffmann, Lars; Setvák, Martin; Partain, Philip T

    2015-12-08

    Gravity waves (disturbances to the density structure of the atmosphere whose restoring forces are gravity and buoyancy) comprise the principal form of energy exchange between the lower and upper atmosphere. Wave breaking drives the mean upper atmospheric circulation, determining boundary conditions to stratospheric processes, which in turn influence tropospheric weather and climate patterns on various spatial and temporal scales. Despite their recognized importance, very little is known about upper-level gravity wave characteristics. The knowledge gap is mainly due to lack of global, high-resolution observations from currently available satellite observing systems. Consequently, representations of wave-related processes in global models are crude, highly parameterized, and poorly constrained, limiting the description of various processes influenced by them. Here we highlight, through a series of examples, the unanticipated ability of the Day/Night Band (DNB) on the NOAA/NASA Suomi National Polar-orbiting Partnership environmental satellite to resolve gravity structures near the mesopause via nightglow emissions at unprecedented subkilometric detail. On moonless nights, the Day/Night Band observations provide all-weather viewing of waves as they modulate the nightglow layer located near the mesopause (∼ 90 km above mean sea level). These waves are launched by a variety of physical mechanisms, ranging from orography to convection, intensifying fronts, and even seismic and volcanic events. Cross-referencing the Day/Night Band imagery with conventional thermal infrared imagery also available helps to discern nightglow structures and in some cases to attribute their sources. The capability stands to advance our basic understanding of a critical yet poorly constrained driver of the atmospheric circulation.

  5. A web-based tool that combines satellite and weather station observations to support irrigation scheduling

    USDA-ARS?s Scientific Manuscript database

    Abstract: The Satellite Irrigation Management Support (SIMS) project combines NASA's Terrestrial Observation and Prediction System (TOPS), Landsat and MODIS satellite imagery, and reference evapotranspiration from surface weather station networks to map daily crop irrigation demand in California in ...

  6. Tracking surface and subsurface lakes on the Greenland Ice Sheet using Sentinel-1 SAR and Landsat-8 OLI imagery

    NASA Astrophysics Data System (ADS)

    Miles, Katie; Willis, Ian; Benedek, Corinne; Williamson, Andrew; Tedesco, Marco

    2017-04-01

    Supraglacial lakes (SGLs) on the Greenland Ice Sheet (GrIS) are an important component of the ice sheet's mass balance and hydrology, with their drainage affecting ice dynamics. This study uses imagery from the recently launched Sentinel-1A Synthetic Aperture Radar (SAR) to investigate SGLs in West Greenland. SAR can image through cloud and in darkness, overcoming some of the limitations of commonly used optical sensors. A semi automated algorithm is developed to detect surface lakes from Sentinel images during the 2015 summer. It generally detects water in all locations where a Landsat-8 NDWI classification (with a relatively high threshold value) detects water. A combined set of images from Landsat-8 and Sentinel-1 is used to track lake behaviour at a comparable temporal resolution to that which is possible with MODIS, but at a higher spatial resolution. A fully automated lake drainage detection algorithm is used to investigate both rapid and slow drainages for both small and large lakes through the summer. Our combined Landsat-Sentinel dataset, with a temporal resolution of three days, could track smaller lakes (mean 0.089 km2) than are resolvable in MODIS (minimum 0.125 km2). Small lake drainage events (lakes smaller than can be detected using MODIS) were found to occur at lower elevations ( 200 m) and slightly earlier in the melt season than larger events, as were slow lake drainage events compared to rapid events. The Sentinel imagery allows the analysis to be extended manually into the early winter to calculate the dates and elevations of lake freeze-through more precisely than is possible with optical imagery (mean 30 August, 1270 m mean elevation). Finally, the Sentinel imagery allows subsurface lakes (which are invisible to optical sensors) to be detected, and, for the first time, their dates of appearance and freeze-through to be calculated (mean 9 August and 7 October, respectively). These subsurface lakes occur at higher elevations than the surface

  7. Determining surface meltwater pond volume using satellite imagery

    NASA Astrophysics Data System (ADS)

    Sneed, W. A.; Hamilton, G. S.

    2006-12-01

    Ponded surface meltwater on Arctic ice caps and ice sheets is an important glaciological and climatological characteristic. Changes in the distribution and amount of ponds with time represent changes in the surface climate conditions controlling melting. The availability of large volumes of ponded surface water raises the possibility of sudden drainage to the bed, a change in basal lubrication, and a rapid increase in ice velocity. While the problem of calculating the areal extent of meltwater ponds using satellite imagery is fairly straightforward, determining the depth and thus the volume is not. We describe a method for deriving the depth of meltwater ponds using 15 m resolution ASTER imagery. We apply the technique to sequences of satellite imagery acquired over Austfonna, Svalbard and the western margin of the Greenland Ice Sheet, to derive changes in melt pond extent and volume during the period 2000-2005. These changes are probably related to accumulation and summer melt conditions. The method is well-suited to the near-optically-clear melt ponds of ice sheets and ice caps, but not to the turbid ponds of alpine glaciers. The method involves making some reasonable assumptions about the albedo of the bottom surface of the ponds and the optical attenuation characteristics of ASTER bands VNIR1 and VNIR3 through the ponded meltwater. Preliminary laboratory analysis of ponded meltwater from Greenland supports our assumption that such water contains little or no chlorophyll A with minimal levels of suspended organic and inorganic solids and, to a first approximation, can be consider laboratory-pure fresh water. For an ~78 km2 test area in northeastern Austfonna we have calculated a threefold increase in meltwater volume during one six-day period in July 2004. In northwestern Greenland, an ~171 km2 area near Melville Bay in July 2002 had a volume of surface meltwater of nearly 2x10^7 m3; in August 2005 the same area had a volume of 3.7x10^7 m3 of surface meltwater.

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

    NASA Astrophysics Data System (ADS)

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

    2013-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  10. 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.

  11. Aboveground Live Forest Biomass Map for the US From Satellite Imagery and Inventory Data

    NASA Astrophysics Data System (ADS)

    Helmer, E.; Blackard, J.; Finco, M.; Holden, G.; Hoppus, M.; Jacobs, D.; Lister, A.; Moisen, G.; Nelson, M.; Riemann, R.; Ruefenacht, B.; Salajanu, D.; Weyermann, D.; Winterberger, K.; Czaplewski, R.; Tymcio, R.; Brandeis, T.

    2004-12-01

    A gridded map of aboveground live forest biomass for the conterminous U.S., Alaska and Puerto Rico with a 250-m cell size resulted from integrating plot-level biomass estimates, from USDA Forest Service (USFS) nation-wide forest inventory data, with satellite imagery and ancillary geospatial data. The image and other predictor layers included MOD09 8-Day surface reflectance imagery (1) from the Moderate Resolution Imaging Spectroradiometer, MODIS-derived proportional tree cover (2), Landsat image-derived proportional land cover (3-4), climate averages (5-6) and topographic variables (7). By state or mapping zone (8), plot-based aboveground live forest biomass estimates generally fell within 5 percent of map-based estimates, and the map provided previously unavailable spatial detail. Here we describe the inventory data, the modeling approach, and the error maps. We secondly compare estimates of U.S. forest carbon storage in live woody biomass from this map with other estimates. We also critically evaluate the modeling process and spatial scaling issues. (1)Vermote EF, Vermueulen A. 1999. MOD09 ATBD, Univ. of Maryland, College Park, 107 pp. (2) Hansen M, DeFries R, et al. 2003. GLCF, Univ. of Maryland, College Park (3) Vogelmann JE, Howard S, et al. 2001. Photogramm Eng Rem S 67:650 (4) Helmer E, Ramos O, et al. 2002. Caribbean J Sci 38:165 (5) Daly C, Kittel T, et al. 2000. 12th AMS Conf on Applied Climatology, Amer Meteorol Soc, Asheville (6) Daly C, Helmer E, et al. 2003. Intl J Climatology 23:1359 (7) Gesch D, Oimoen M, et al. 2002. Photogramm Eng Rem S 68:5 (8) Homer C, Huang C, et al. 2004. Photogramm Eng Rem S 70:829

  12. Structural and stratigraphic mapping from satellite imagery, Kalpin uplift, northwestern Tarim basin, northwest China

    SciTech Connect

    McKnight, C.L.; Carroll, A.R.; Chu, J.; Hendrix, M.S.; Graham, S.A.; Lyon, R.J.P. )

    1990-05-01

    The Kalpin uplift, located on the northwestern margin of the Tarim craton, northwest China, exposes a complete Paleozoic cratonal stratigraphic sequence. The lack of vegetative cover and the visible color contrasts between stratigraphic units afford an optimal situation for detailed geologic mapping from Landsat Multispectral Scanner imagery at a scale of 1:250,000. Field work in the eastern Kalpin uplift constrains the geologic interpretation of the satellite imagery. Exposed basement rock in the Kalpin uplift consists of deformed and metamorphosed upper Proterozoic strata cut by unmetamorphosed mafic dikes. The overlying sedimentary section was deposited primarily in shallow marine to nonmarine environments and includes Sinian (latest Proterozoic to early Cambrian) siliciclastics and carbonates; Cambrian and Ordovician carbonates; Silurian green shales; Devonian red beds; Carboniferous siliciclastics and carbonates; and Permian carbonates, siliciclastics, and subaerial basalt flows. Paleozoic strata are exposed in a series of low, parallel, curvilinear ranges located at the leading edges of low-angle, southeast-vergent thrust sheets. The regular thrust repetition of the entire Paleozoic section suggests the presence of a detachment horizon within the Cambrian section. These southeast-vergent thrust sheets override an older structural trend on the craton, the Bachu uplift, at right angles, folding as they do so. Strike-slip faults cutting the thrust sheets along the same trend as the Bachu uplift suggest the location of buried lateral ramps associated with the Bachu uplift. The young deformation in the Kalpin uplift is a response to compressive stresses produced by the northward movement of the Indian plate. Major faults in the Tian Shan mountain range to the north have been reactivated, resulting in southward-directed thrusting over the Tarim craton.

  13. A comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in lower Chesapeake Bay

    NASA Technical Reports Server (NTRS)

    Ackleson, S. G.; Klemas, V.

    1985-01-01

    LANDSAT Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery generated simultaneously over Guinea Marsh, Virginia, are assessed in the ability to detect submerged aquatic, bottom-adhering plant canopies (SAV). An unsupervised clustering algorithm is applied to both image types and the resulting classifications compared to SAV distributions derived from color aerial photography. Class confidence and accuracy are first computed for all water areas and then only shallow areas where water depth is less than 6 feet. In both the TM and MSS imagery, masking water areas deeper than 6 ft. resulted in greater classification accuracy at confidence levels greater than 50%. Both systems perform poorly in detecting SAV with crown cover densities less than 70%. On the basis of the spectral resolution, radiometric sensitivity, and location of visible bands, TM imagery does not offer a significant advantage over MSS data for detecting SAV in Lower Chesapeake Bay. However, because the TM imagery represents a higher spatial resolution, smaller SAV canopies may be detected than is possible with MSS data.

  14. Flooded area cartography with kernel-based classifiers and Landsat TM imagery

    NASA Astrophysics Data System (ADS)

    Volpi, M.; Petropoulos, G. P.; Kanevski, M.

    2012-04-01

    Timely and accurate flooding extent maps for both emergency and recovery phases are required by scientists, local authorities and decision makers. In particular, the issue of reducing exposure by quantifying vulnerability to inundation has recently began to be considered by European policies. Remote sensing can provide valuable information to this task, particularly over inaccessible regions. Provided that cloud-free conditions exist, multi-temporal optical images can be exploited for automatic cartography of the inundation. Image processing techniques based on kernels are promising tools in many remote sensing problems, ranging from biophysical parameter estimation to multi-temporal classification and change detection. The success of such methods is largely due to the explicit non-linear nature of the discriminant function and to their robustness to high-dimensional input spaces, such as those generated from remote sensing spectral bands. In our study, we examined the application of two supervised kernel-based classifiers for flooded area extraction from Landsat TM imagery. As a case study, we analyzed a region of the Missouri River in South Dakota, United States, in which images before and after a flood that took place in 2011 were available. In our approach, the mapping issue is recast as a change detection problem, whereby only the amount of water in excess to the permanent standing one was considered. Support Vector Machine (SVM) and Fisher's Linear Discriminant Analysis (LDA) classifications were applied successfully. Both classifiers were utilized in their linear and non-linear (kernel) versions. Evaluation of the ability of the two methods in delineating the flooding extent was conducted on the basis of classification accuracy assessment metrics as well as the McNemar statistical significance testing. Our findings showed the suitability of the non-linear kernel extensions to accurately map the flood extent. Possible future developments of the methodology

  15. Detection of ship tracks in ATSR2 satellite imagery

    NASA Astrophysics Data System (ADS)

    Campmany, E.; Grainger, R. G.; Dean, S. M.

    2008-08-01

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

  16. Land cover classification with an expert system approach using Landsat ETM imagery: a case study of Trabzon.

    PubMed

    Kahya, Oguzhan; Bayram, Bulent; Reis, Selcuk

    2010-01-01

    The main objective of this study is to generate a knowledge base which is composed of user-defined variables and included raster imagery, vector coverage, spatial models, external programs, and simple scalars and to develop an expert classification using Landsat 7 (ETM+) imagery for land cover classification in a part of Trabzon city. Expert systems allow for the integration of remote-sensed data with other sources of geo-referenced information such as land use data, spatial texture, and digital elevation model to obtain greater classification accuracy. Logical decision rules are used with the various datasets to assign class values for each pixel. Expert system is very suitable for the work of image interpretation as a powerful means of information integration. Landsat ETM data acquired in the year 2000 were initially classified into seven classes for land cover using a maximum likelihood decision rule. An expert system was constructed to perform post-classification sorting of the initial land cover classification using additional spatial datasets such as land use data. The overall accuracy of expert classification was 95.80%. Individual class accuracy ranged from 75% to 100% for each class.

  17. Multitemporal Analysis of Coastal Built-up Development: Use of SPOT and Landsat TM Imagery

    NASA Astrophysics Data System (ADS)

    Alphan, Hakan

    2014-05-01

    Mediterranean coastal landscape is subject to increasingly complex land use/land cover (LU/LC) changes. Majority of these changes occur as a result of urbanization, tourism, agriculture and transportation activities. Diversity and extent of human activities on the coast results with complex changes in short term. Therefore, high temporal and spatial resolution of change detection may facilitate analyzing above mentioned changes more accurately. In this context, SPOT (Satellite Pour l'Observation de la Terre) dataset have advantages in terms of both high spatial resolution (10 m) and frequent temporal coverage for landscape monitoring and modeling. The coastal zone of Erdemli district, located in the west of the central district of Mersin (SE Mediterranean Coast of Turkey) is currently experiencing problems due to development of multistory buildings as summer apartments near the coastline and expansion of rural settlements in close proximity to the coast. This development on the coast threatens both agriculture areas and natural vegetation and causes landscape fragmentation. The aim of this paper is to monitor qualitative and quantitative aspects of built-up development in the coast of Erdemli (Mersin/Turkey) and analyze its negative impacts on the coastal landscape. Panchromatic SPOT datasets with a ground resolution of 10 m acquired in 1989, 1995, 2001 and 2007 were combined with multispectral Landsat images prior to classification. Urbanization on the coastal zone was mapped at finer spatial (i.e. 10m) and time (i.e. 6 years) scales and current change trends were determined understand dynamics of built-up development on the coast.

  18. Extracting dune mobility time series from sequences of optical satellite imagery

    NASA Astrophysics Data System (ADS)

    Vermeesch, P.; Leprince, S.

    2012-12-01

    distribution, and divide their stepwise displacements by the time elapsed between the satellite exposures. This algorithm was applied to a sequence of seven Landsat, SPOT and ASTER images from the Bodélé Depression in northern Chad spanning the past 26 years, and was extended using declassified Corona imagery from 1965. The resulting time series indicates less than ten percent change in windiness of the area over the past 45 years.

  19. An operational earth resources satellite system - The Landsat follow-on program

    NASA Technical Reports Server (NTRS)

    Stroud, W. G.

    1977-01-01

    The Landsats 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The Landsat follow-on study addressed the economics, technological performance, and design of a system in transition from R&D to operations. Economic benefits were identified; and a complete system from sensors to the utilization in forecasting crop production, oil and mineral exploration, water resources management was designed. Benefits-to-costs ratio in present-worth dollars is at least 4:1.

  20. An operational earth resources satellite system - The Landsat follow-on program

    NASA Technical Reports Server (NTRS)

    Stroud, W. G.

    1977-01-01

    The Landsats 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The Landsat follow-on study addressed the economics, technological performance, and design of a system in transition from R&D to operations. Economic benefits were identified; and a complete system from sensors to the utilization in forecasting crop production, oil and mineral exploration, water resources management was designed. Benefits-to-costs ratio in present-worth dollars is at least 4:1.

  1. Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

    NASA Astrophysics Data System (ADS)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

    2016-06-01

    The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

  2. Detecting Chlorophyll and Phycocyanin in Lake Texoma Using in Situ Photo from GPS Digital Camera and Landsat 8 OLI Imagery

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Hambright, K.; Xiao, X.

    2013-12-01

    Characterizing the temporal and spatial change of algae blooms across lake systems is difficult through conventional sampling methodologies. The application of remote sensing to lake water quality has improved significantly over recent years. However there are seldom reports about in situ photos from GPS digital camera and the new satellite Landsat 8 OLI monitoring algae blooms in freshwater lakes. A pilot study was carried out in Lake Texoma in Oklahoma on April 25th 2013. At each site (12 sites in total), pigments (chlorophyll a and phycocyanin concentration), in situ spectral data and digital photos had been acquired using Hydrolab DS5X sonde (calibrated routinely against laboratory standards), ASD FieldSpec and GPS camera, respectively. The field spectral data sets were transformed to blue, green and red ranges which match the spectral resolution of Landsat 8 OLI images by average spectral reflectance signature to the first four Landsat 8 OLI bands. Comparing with other ratio indices, red/ blue was the best ratio index which can be employed in predicting phycocyanin and chlorophyll a concentration; and pigments (phycocyanin and chlorophyll a) concentration in whole depth should be selected to be detected using remote sensing method in Lake Texoam in the followed analysis. An image based darkest pixel subtraction method was used to process atmospheric correction of Landsat 8 OLI images. After atmospheric correction, the DN values were extracted and used to compute ratio of band4 (Red)/ band1(Blue). Higher correlation coefficients existed in both between resampled spectral reflectance and ratio of red/ blue of photo DN values (R2=0.9425 n=12) and between resampled spectral reflectance and ratio of red/ blue of Landsat 8 OLI images DN values (R2=0.8476 n=12). Finally, we analyzed the correlation between pigments concentrations in whole depth and DN values ratio red/ blue of both Landsat 8 OLI images and digital photos. There were higher correlation coefficients

  3. Age discrimination among eruptives of Menengai Caldera, Kenya, using vegetation parameters from satellite imagery

    NASA Technical Reports Server (NTRS)

    Blodget, Herbert W.; Heirtzler, James R.

    1993-01-01

    Results are presented of an investigation to determine the degree to which digitally processed Landsat TM imagery can be used to discriminate among vegetated lava flows of different ages in the Menengai Caldera, Kenya. A selective series of five images, consisting of a color-coded Landsat 5 classification and four color composites, are compared with geologic maps. The most recent of more than 70 postcaldera flows within the caldera are trachytes, which are variably covered by shrubs and subsidiary grasses. Soil development evolves as a function of time, and as such supports a changing plant community. Progressively older flows exhibit the increasing dominance of grasses over bushes. The Landsat images correlated well with geologic maps, but the two mapped age classes could be further subdivided on the basis of different vegetation communities. It is concluded that field maps can be modified, and in some cases corrected by use of such imagery, and that digitally enhanced Landsat imagery can be a useful aid to field mapping in similar terrains.

  4. Age discrimination among eruptives of Menengai Caldera, Kenya, using vegetation parameters from satellite imagery

    NASA Technical Reports Server (NTRS)

    Blodget, Herbert W.; Heirtzler, James R.

    1993-01-01

    Results are presented of an investigation to determine the degree to which digitally processed Landsat TM imagery can be used to discriminate among vegetated lava flows of different ages in the Menengai Caldera, Kenya. A selective series of five images, consisting of a color-coded Landsat 5 classification and four color composites, are compared with geologic maps. The most recent of more than 70 postcaldera flows within the caldera are trachytes, which are variably covered by shrubs and subsidiary grasses. Soil development evolves as a function of time, and as such supports a changing plant community. Progressively older flows exhibit the increasing dominance of grasses over bushes. The Landsat images correlated well with geologic maps, but the two mapped age classes could be further subdivided on the basis of different vegetation communities. It is concluded that field maps can be modified, and in some cases corrected by use of such imagery, and that digitally enhanced Landsat imagery can be a useful aid to field mapping in similar terrains.

  5. 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

  6. Analysis of the Possibility of Military Applications of Civilian Remote Sensing Satellite Imagery,

    DTIC Science & Technology

    1996-06-12

    With the end of the Cold War and the changing of the world order, the market for civilian remote sensing satellite imagery is taking shape and...expanding. More and more civilian remote sensing reconnaissance-grade satellite systems are going into service one after the other. Exchanges of satellite

  7. Crop growth dynamics modeling using time-series satellite imagery

    NASA Astrophysics Data System (ADS)

    Zhao, Yu

    2014-11-01

    In modern agriculture, remote sensing technology plays an essential role in monitoring crop growth and crop yield prediction. To monitor crop growth and predict crop yield, accurate and timely crop growth information is significant, in particularly for large scale farming. As the high cost and low data availability of high-resolution satellite images such as RapidEye, we focus on the time-series low resolution satellite imagery. In this research, NDVI curve, which was retrieved from satellite images of MODIS 8-days 250m surface reflectance, was applied to monitor soybean's yield. Conventional model and vegetation index for yield prediction has problems on describing the growth basic processes affecting yield component formation. In our research, a novel method is developed to well model the Crop Growth Dynamics (CGD) and generate CGD index to describe the soybean's yield component formation. We analyze the standard growth stage of soybean and to model the growth process, we have two key calculate process. The first is normalization of the NDVI-curve coordinate and division of the crop growth based on the standard development stages using EAT (Effective accumulated temperature).The second is modeling the biological growth on each development stage through analyzing the factors of yield component formation. The evaluation was performed through the soybean yield prediction using the CGD Index in the growth stage when the whole dataset for modeling is available and we got precision of 88.5% which is about 10% higher than the conventional method. The validation results showed that prediction accuracy using our CGD modeling is satisfied and can be applied in practice of large scale soybean yield monitoring.

  8. Detailed maps of tropical forest types are within reach: forest tree communities for Trinidad and Tobago mapped with multiseason Landsat and multiseason fine-resolution imagery

    Treesearch

    Eileen H. Helmer; Thomas S. Ruzycki; Jay Benner; Shannon M. Voggesser; Barbara P. Scobie; Courtenay Park; David W. Fanning; Seepersad. Ramnarine

    2012-01-01

    Tropical forest managers need detailed maps of forest types for REDD+, but spectral similarity among forest types; cloud and scan-line gaps; and scarce vegetation ground plots make producing such maps with satellite imagery difficult. How can managers map tropical forest tree communities with satellite imagery given these challenges? Here we describe a case study of...

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  10. Utilization of LANDSAT images in cartography

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Alburquerque, P. C. G.

    1981-01-01

    The use of multispectral imagery obtained from LANDSAT for mapping purposes is discussed with emphasis on geometric rectification, image resolution, and systematic topographic mapping. A method is given for constructing 1:250,000 scale maps. The limitations for satellite cartography are examined.

  11. Overall evaluation of LANDSAT (ERTS) follow-on imagery for cartographic application

    NASA Technical Reports Server (NTRS)

    Colvocoresses, A. P. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. The NASA/Cousteau experiment showed that under suitable conditions and with calibration data, the bottom of clear tropical seas can be mapped with LANDSAT to a depth of 22 meters with a root-mean-square error of about 10 percent. This application required the high gain setting of band 4 of the MSS. The experiment also confirmed that a somewhat lower waveband than band 4 would increase the water penetration capability of future LANDSATS. Other experiments illustrated by the reprinting of upper Chesapeake Bay indicate that the original LANDSAT signals must be modulated and optimized for the photographic and lithographic processes. Work by the Canadian mapping agency indicates significant improvements in the control identification and geometric accuracy of LANDSAT cartographic applications.

  12. BOREAS Level-3p Landsat TM Imagery: Geocoded and Scaled At-sensor Radiance

    NASA Technical Reports Server (NTRS)

    Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Hall, Forrest G. (Editor); Cihlar, Josef

    2000-01-01

    For BOReal Ecosystem-Atmosphere Study (BOREAS), the level-3p Landsat Thematic Mapper (TM) data were used to supplement the level-3s Landsat TM products. Along with the other remotely sensed images, the Landsat TM images were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation (FPAR) and Leaf Area Index (LAI). Although very similar to the level-3s Landsat TM products, the level-3p images were processed with ground control information, which improved the accuracy of the geographic coordinates provided. Geographically, the level-3p images cover the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA). Temporally, the four images cover the period of 20-Aug-1988 to 07-Jun-1994. Except for the 07-Jun-1994 image, which contains seven bands, the other three contain only three bands.

  13. Nearest neighbor, bilinear interpolation and bicubic interpolation geographic correction effects on LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Jayroe, R. R., Jr.

    1976-01-01

    Geographical correction effects on LANDSAT image data are identified, using the nearest neighbor, bilinear interpolation and bicubic interpolation techniques. Potential impacts of registration on image compression and classification are explored.

  14. Mission to Earth: LANDSAT Views the World. [Color imagery of the earth's surface

    NASA Technical Reports Server (NTRS)

    Short, N. M.; Lowman, P. D., Jr.; Freden, S. C.; Finch, W. A., Jr.

    1976-01-01

    The LANDSAT program and system is described. The entire global land surface of Earth is visualized in 400 color plates at a scale and resolution that specify natural land cultural features in man's familiar environments. A glossary is included.

  15. Use of Landsat imagery to estimate ground-water pumpage for irrigation on the Columbia Plateau in eastern Washington, 1985

    USGS Publications Warehouse

    Van Metre, P.C.; Seevers, Paul

    1991-01-01

    A method for estimating ground-water pumpage for irrigation was developed for the Columbia Plateau in eastern Washington. The method combines water-application rates estimated from pumpage data with acreage of irrigated crops that was mapped by using Landsat imagery. The study area consisted of Grant, Lincoln, Adams, and Franklin Counties, an area of approximately 8,900 square miles, and accounts for approximately three-fourths of the ground-water pumpage in the Columbia Plateau in eastern Washington. Data from two passes of Landsat's multispectral scanner were analyzed by using a spectral band ratioing procedure to map irrigated crops for the study area. Data from one pass of Landsat's thematic mapper, covering approximately two-thirds of the study area, also were analyzed for determining irrigated crops in the area resulting in a 6-percent improvement in accuracy over the multispectral scanner analysis. A total of 576 annual water-application rates associated with particular crops, for the 1982 through 1985 seasons, were calculated. A regression equation was developed for estimating annual water-application rates as a function of crop type, annual precipitation, irrigation system type, and available water capacity of the soil. Crops were grouped into three water-use categories: (1) small grains, primarily wheat and barley; (2) high water-use crops consisting of corn, alfalfa, and potatoes; and (3) miscellaneous vegetable and row crops. Annual water-application rates, expressed as a depth of water, then were multiplied by irrigated area determined by Landsat to estimate a volume of water pumped for irrigation for 1985-620,000 acre-feet. An assessment of accuracy for estimating pumpage for 28 of the sites showed that total predicted pumpage was within 4 percent of the total observed pumpage.

  16. Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery

    USGS Publications Warehouse

    Hatten, James R.

    2014-01-01

    The Mount Graham red squirrel (Tamiasciurus hudsonicus grahamensis) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.

  17. Improving classification of crop residues using digital land ownership data and Landsat TM imagery

    NASA Technical Reports Server (NTRS)

    Zhuang, Xin; Engel, Bernard A.; Baumgardner, Marion F.; Swain, Philip H.

    1991-01-01

    Plant residue on the surface of cultivated soils in Miami County, Indiana is analyzed in terms of quantity and type with Landsat TM data to generate information for a conservation program for agricultural soil. The Landsat data are enhanced with land-ownership data in a geographic information system to facilitate classification with maximum-likelihood, minimum-distance, and neural-network classifiers. The most effective classifications resulted from the use of the neural network on the enhanced TM data.

  18. Improving classification of crop residues using digital land ownership data and Landsat TM imagery

    NASA Technical Reports Server (NTRS)

    Zhuang, Xin; Engel, Bernard A.; Baumgardner, Marion F.; Swain, Philip H.

    1991-01-01

    Plant residue on the surface of cultivated soils in Miami County, Indiana is analyzed in terms of quantity and type with Landsat TM data to generate information for a conservation program for agricultural soil. The Landsat data are enhanced with land-ownership data in a geographic information system to facilitate classification with maximum-likelihood, minimum-distance, and neural-network classifiers. The most effective classifications resulted from the use of the neural network on the enhanced TM data.

  19. Investigation of LANDSAT imagery on correlations between ore deposits and major shield structures in Finland

    NASA Technical Reports Server (NTRS)

    Tuominen, H. V. (Principal Investigator); Kuosmanen, V.

    1977-01-01

    The author has identified the following significant results. Several regional lineaments appear to correlate with the distribution of ore deposits and showings. Combined study of LANDSAT summer and winter mosaics and color composites of geological, geomorphological, and geophysical maps makes the correlation more perceptible. The revealed pattern of significant lineaments in northern Finland is fairly regular. The most significant lineaments seen in LANDSAT mosaics are not detectable in single images.

  20. LULC Classification and Topographic Correction of Landsat-7 ETM+ Imagery in the Yangjia River Watershed: the Influence of DEM Resolution.

    PubMed

    Gao, Yongnian; Zhang, Wanchang

    2009-01-01

    DEM-based topographic corrections on Landsat-7 ETM+ imagery from rugged terrain, as an effective processing techniques to improve the accuracy of Land Use/Land Cover (LULC) classification as well as land surface parameter retrievals with remotely sensed data, has been frequently reported in the literature. However, few studies have investigated the exact effects of DEM with different resolutions on the correction of imagery. Taking the topographic corrections on the Landsat-7 ETM+ images acquired from the rugged terrain of the Yangjiahe river basin (P.R. China) as an example, the present work systematically investigates such issues by means of two commonly used topographic correction algorithms with the support of different spatial resolution DEMs. After the pre-processing procedures, i.e. atmospheric correction and geo-registration, were applied to the ETM+ images, two topographic correction algorithms, namely SCS correction and Minnaert correction, were applied to assess the effects of different spatial resolution DEMs obtained from two sources in the removal of topographic effects and LULC classifications. The results suggested that the topographic effects were tremendously reduced with these two algorithms under the support of different spatial resolution DEMs, and the performance of the topographic correction with the 1:50,000-topographic-map DEM was similar to that achieved using SRTM DEM. Moreover, when the same topographic correction algorithm was applied the accuracy of LULC classification after topographic correction based on 1:50,000-topographic-map DEM was similar as that based on SRTM DEM, which implies that the 90 m SRTM DEM can be used as an alternative for the topographic correction of ETM+ imagery when high resolution DEM is unavailable.