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. 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.

  3. 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.

  4. 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.

  5. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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).

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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).

  7. 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

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  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. 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).

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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)

  9. 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

  10. 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.

  11. 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.

  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. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  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. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.   

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  11. 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.

  12. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  14. 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.

  15. 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... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image...

  16. 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... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image...

  17. 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... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image...

  18. 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... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image...

  19. 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... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image...

  20. 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.

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  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. 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.

  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. 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.

  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. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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)

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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).

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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).

  14. 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).

  15. 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.

  16. 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…

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. An evaluation of Landsat 3 RBV imagery for an area of complex terrain in Southern Italy

    NASA Technical Reports Server (NTRS)

    Townshend, J. R. G.; Williams, D. F.; Justice, C. D.

    1979-01-01

    Return Beam Videcon imagery from Landsat 3 was obtained in August, 1978 for part of Southern Italy in the regions of Basilicata and Apulia. The resolution of this imagery for medium contrast objects is approximately 40 meters and is shown to provide significant information concerning land cover and fluvial morphometry. Because of the wide spectral band width which is sensed (0.505-0.750 microns) by the RBV cameras, discrimination is only possible for spectrally distinct cover types, especially oak woodland. Fluvial morphometry can be readily described using the imagery. Because of the intense dissection of the area, the lowest order streams cannot be consistently mapped, but the rank order of the measured values of properties such as drainage density and link frequency for different lithologies corresponds closely to the actual ranking.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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.

  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. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  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. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  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. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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).

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

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

    USGS Publications Warehouse

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

    2008-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss

    USGS Publications Warehouse

    Potapov, P.; Hansen, M.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. ?? 2008 Elsevier Inc.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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).

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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)

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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%.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  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, orthorectified 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. ?? 2009 American Society for Photogrammetry and Remote Sensing.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  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. 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.

  11. 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

  12. 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).

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. A web-based tool that combines satellite and weather station observations to support irrigation scheduling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

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

    NASA Astrophysics Data System (ADS)

    Tang, Shengjun; Wu, Bo; Zhu, Qing

    2016-04-01

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

  9. Estuarine and Tidal Freshwater Habitat Cover Types Along the Lower Columbia River Estuary Determined from Landsat 7 Enhanced Thematic Mapper (ETM+) Imagery, Technical Report 2003.

    SciTech Connect

    Garono, Ralph; Robinson, Rob

    2003-10-01

    Developing an understanding of the distribution and changes in estuarine and tidal floodplain ecosystems is critical to the management of biological resources in the lower Columbia River. Columbia River plants, fish, and wildlife require specific physicochemical and ecological conditions to sustain their populations. As habitats are degraded or lost, this capability is altered, often irretrievably; those species that cannot adapt are lost from the ecosystem. The Lower Columbia River Estuary Partnership (Estuary Partnership) completed a comprehensive ecosystem protection and enhancement plan for the lower Columbia River and estuary in 1999 (Jerrick, 1999). The plan identified habitat loss and modification as a critical threat to the integrity of the lower Columbia River ecosystem and called for a habitat inventory as a key first step in its long term restoration efforts. In 2000, the Estuary Partnership initiated a multiphase project to produce a spatial data set describing the current location and distribution of estuarine and tidal freshwater habitat cover types along the lower Columbia River from the river mouth to the Bonneville Dam using a consistent methodology and data sources (Fig. 1). The first phase of the project was the development of a broadbrush description of the estuarine and tidal freshwater habitat cover classes for the entire study area ({approx}146 river miles) using Landsat 7 ETM+ satellite imagery. Phase II of the project entailed analysis of the classified satellite imagery from Phase I. Analysis of change in landcover and a summary of the spatial relationships between cover types are part of Phase II. Phase III of the project included the classification of the high resolution hyperspectral imagery collected in 2000 and 2001 for key focal areas within the larger study area. Finally, Phase IV consists of this final report that presents results from refining the Landsat ETM+ classification and provides recommendations for future actions

  10. Examining Phenology-based Classification Approaches for Irrigated Crop Type Mapping Using Landsat Time-series Imagery

    NASA Astrophysics Data System (ADS)

    Zheng, B.; Myint, S. W.

    2013-12-01

    Mapping irrigated crop types is crucial for assessment and monitoring of agriculture water use, food production, land use planning, investment targeting, and policy simulation, especially in a semi-arid environment with high risks of prolonged and intense droughts. Despite the availability of advanced image classification techniques and a variety of remotely sensed imagery, accurate crop type mapping remains a challenge because of the complexity of agricultural land use systems. We evaluated several classifiers to identify different crop types in Phoenix Active Management Area (PHX AMA) in central Arizona. All available cloud-free Landat imagery for two years (i.e., 2002, 2005) were utilized to generate time-series normalized difference vegetation index (NDVI) over the entire growing period to produce accurate crop type maps. A total of 42 endmembers were identified from Landsat NDVI time-series imagery. We not only attempted to identify crop types but also to determine the complex cropping patterns in the study area. Three different classifiers, namely spectral angle mapper, random forest, and support vector machine, were evaluated and compared to determine the best suitable classification method to identify crop types and cropping patterns of irrigated crops.

  11. Verification of Aerosol Optical Depth Retrievals using Cloud Shadows Retrieved from Satellite Imagery

    DTIC Science & Technology

    2008-03-01

    reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching ...ASTER imagery used in this investigation were obtained through the National Geospatial- Intelligence Agency via the Commercial Satellite Imagery...Naval Postgraduate School, CA, 5-10, 143-152. Wehrli, C., 1985: Extraterrestrial Solar Spectrum – Publ. 615. Physical Meteorological

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  13. Application of standard photogeologic techniques to LANDSAT imagery for mineral exploration in the basin and range province of Utah and Nevada

    NASA Technical Reports Server (NTRS)

    Lattman, L. H. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. Standard photogeologic techniques were applied to LANDSAT imagery of the basin and range province of Utah and Nevada to relate linear, tonal, textural, drainage, and geomorphic features to known mineralized areas in an attempt to develop criteria for the location of mineral deposits. No consistent correlation was found between lineaments, mapped according to specified criteria, and locations of mines, mining districts, or intrusive outcrops. Tonal and textural patterns were more closely related to geologic outcrop patterns than to mineralization. A statistical study of drainage azimuths of various length classes as measured on LANDSAT showed significant correlation with mineralized districts in the length class of 3-6 km. Alignments of outcrops of basalt, a rock type highly visible on LANDSAT imagery, appear to be colinear with acidic and intermediate intrusive centers in some areas and may assist on the recognition of regional fracture systems for mineral exploration.

  14. Modeling vertebrate diversity in Oregon using satellite imagery

    NASA Astrophysics Data System (ADS)

    Cablk, Mary Elizabeth

    Vertebrate diversity was modeled for the state of Oregon using a parametric approach to regression tree analysis. This exploratory data analysis effectively modeled the non-linear relationships between vertebrate richness and phenology, terrain, and climate. Phenology was derived from time-series NOAA-AVHRR satellite imagery for the year 1992 using two methods: principal component analysis and derivation of EROS data center greenness metrics. These two measures of spatial and temporal vegetation condition incorporated the critical temporal element in this analysis. The first three principal components were shown to contain spatial and temporal information about the landscape and discriminated phenologically distinct regions in Oregon. Principal components 2 and 3, 6 greenness metrics, elevation, slope, aspect, annual precipitation, and annual seasonal temperature difference were investigated as correlates to amphibians, birds, all vertebrates, reptiles, and mammals. Variation explained for each regression tree by taxa were: amphibians (91%), birds (67%), all vertebrates (66%), reptiles (57%), and mammals (55%). Spatial statistics were used to quantify the pattern of each taxa and assess validity of resulting predictions from regression tree models. Regression tree analysis was relatively robust against spatial autocorrelation in the response data and graphical results indicated models were well fit to the data.

  15. Tuna aggregation and feeding near fronts observed in satellite imagery

    NASA Astrophysics Data System (ADS)

    Fiedler, Paul C.; Bernard, Hannah J.

    1987-08-01

    Stomach contents of albacore ( Thunnus alalunga) and skipjack ( Katsuwonus pelamis) caught off California in August 1983 showed they were feeding on juvenile northern anchovy ( Engraulis mordax), other fishes, and planktonic crustaceans. The distribution and diet of these predators were related to mesoscale frontal features visible in satellite sea surface temperature and phytoplankton pigment imagery. Albacore were caught in the vicinity of a filament of cold, pigment-rich surface water that varied with the intensity of coastal upwelling on time scales of several days. Stomachs of albacore caught closer to the filament contained relatively more juvenile anchovy and fewer pelagic red crabs ( Pleuroncodes planipes). Skipjack were caught in warm water in the Southern California Bight, north of their normal range due to El Nin˜o warming. They appeared to be feeding most successfully near the strong frontal boundary of a productive, cold water mass south of Pt. Conception, where dense patches of euphausiids were available. Both species were feeding near variable, mesoscale centers of high productivity where prey abundance may be enhanced.

  16. Automatic interface measurement and analysis. [shoreline length of Alabama using LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Faller, K. H.

    1975-01-01

    A technique for detecting and measuring the interface between two categories in classified scanner data is described together with two application demonstrations. Measurements were found to be accurate to 1.5% root mean square error on features of known length while comparison of measurements made using the technique on LANDSAT data to opisometer measurements on 1:24,000 scale maps shows excellent agreement. Application of the technique to two frames of LANDSAT data classified using a two channel, two class classifier resulted in a computation of 64 km annual decrease in shoreline length. The tidal shoreline of a portion of Alabama was measured using LANDSAT data. Based on the measurement of this portion, the total tidal shoreline length of Alabama is estimated to be 1313 kilometers.

  17. Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

    NASA Technical Reports Server (NTRS)

    Williams, D. L.; Stauffer, M. L.

    1978-01-01

    The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

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

    NASA Technical Reports Server (NTRS)

    Potter, Christopher

    2016-01-01

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

  19. Comparison of sampling designs for estimating deforestation from landsat TM and MODIS imagery: a case study in Mato Grosso, Brazil.

    PubMed

    Zhu, Shanyou; Zhang, Hailong; Liu, Ronggao; Cao, Yun; Zhang, Guixin

    2014-01-01

    Sampling designs are commonly used to estimate deforestation over large areas, but comparisons between different sampling strategies are required. Using PRODES deforestation data as a reference, deforestation in the state of Mato Grosso in Brazil from 2005 to 2006 is evaluated using Landsat imagery and a nearly synchronous MODIS dataset. The MODIS-derived deforestation is used to assist in sampling and extrapolation. Three sampling designs are compared according to the estimated deforestation of the entire study area based on simple extrapolation and linear regression models. The results show that stratified sampling for strata construction and sample allocation using the MODIS-derived deforestation hotspots provided more precise estimations than simple random and systematic sampling. Moreover, the relationship between the MODIS-derived and TM-derived deforestation provides a precise estimate of the total deforestation area as well as the distribution of deforestation in each block.

  20. 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, S.

    1976-01-01

    The author has identified the following significant results. Distinctive spectral signatures were found associated with areas of near surface bedrock with covered ground east of Dugald River and along the Thorntonia River valley west of Lady Annie. Linears identified in the Dugald River area on LANDSAT 2 imagery taken in March and July 1975 over the Cloncurry-Dobbyn area, displayed preferred orientation. A linear group with NE-SW orientation was identified in the Lady Annie area. In this area, the copper mineralization in the Mt. Kelly area occurs along a well marked linear with NNW/SSE direction apparent on images for March, September, and November 1975. Geobotanical anomalies provided surface expression of the copper deposits in Mt. Kelley.

  1. An application of LANDSAT multispectral imagery for the classification of hydrobiological systems, Shark River Slough, Everglades National Park, Florida

    NASA Technical Reports Server (NTRS)

    Rose, P. W.; Rosendahl, P. C. (Principal Investigator)

    1979-01-01

    Multivariant hydrologic parameters over the Shark River Slough were investigated. Ground truth was established utilizing U-2 infrared photography and comprehensive field data to define a control network which represented all hydrobiological systems in the slough. These data were then applied to LANDSAT imagery utilizing an interactive multispectral processor which generated hydrographic maps through classification of the slough and defined the multispectral surface radiance characteristics of the wetlands areas in the park. The spectral response of each hydrobiological zone was determined and plotted to formulate multispectral relationships between the emittent energy from the slough in order to determine the best possible multispectral wavelength combinations to enhance classification results. The extent of each hydrobiological zone in slough was determined and flow vectors for water movement throughout the slough established.

  2. Comparison of Sampling Designs for Estimating Deforestation from Landsat TM and MODIS Imagery: A Case Study in Mato Grosso, Brazil

    PubMed Central

    Zhu, Shanyou; Zhang, Hailong; Liu, Ronggao; Cao, Yun; Zhang, Guixin

    2014-01-01

    Sampling designs are commonly used to estimate deforestation over large areas, but comparisons between different sampling strategies are required. Using PRODES deforestation data as a reference, deforestation in the state of Mato Grosso in Brazil from 2005 to 2006 is evaluated using Landsat imagery and a nearly synchronous MODIS dataset. The MODIS-derived deforestation is used to assist in sampling and extrapolation. Three sampling designs are compared according to the estimated deforestation of the entire study area based on simple extrapolation and linear regression models. The results show that stratified sampling for strata construction and sample allocation using the MODIS-derived deforestation hotspots provided more precise estimations than simple random and systematic sampling. Moreover, the relationship between the MODIS-derived and TM-derived deforestation provides a precise estimate of the total deforestation area as well as the distribution of deforestation in each block. PMID:25258742

  3. Monitoring Forest Degradation for a Case Study in Cambodia: Comparison of Landsat 8 and Sentinel-2 Imagery

    NASA Astrophysics Data System (ADS)

    Langner, Andreas; Miettinen, Jukka; Stibig, Hans-Jurgen

    2016-08-01

    We use a Normalized Burned Ratio (NBR) differential approach for detecting forest canopy disturbance caused by selective logging in evergreen tropical moist forests of central Cambodia. The general disturbance pattern obtained from Landsat 8 (30 m) imagery is largely compatible to Sentinel-2 (10 m), showing good conformity to high resolution RapidEye reference data. However, the 10 m spatial resolution of Sentinel-2 provides notably higher spatial detail and purer pixel values, increasing the potential for detecting fine and subtle forest canopy changes as indicators for potential forest degradation. We can expect further improvement for detecting short-lived disturbance signals in tropical forest canopies due to an increased revisit frequency (5 days) after the Sentinel-2B launch.

  4. Atmospheric Correction of Satellite GF-1/WFV Imagery and Quantitative Estimation of Suspended Particulate Matter in the Yangtze Estuary

    PubMed Central

    Shang, Pei; Shen, Fang

    2016-01-01

    The Multispectral Wide Field of View (WFV) camera on the Chinese GF-1 satellite, launched in 2013, has advantages of high spatial resolution (16 m), short revisit period (4 days) and wide scene swath (800 km) compared to the Landsat-8/OLI, which make it an ideal means of monitoring spatial-temporal changes of Suspended Particulate Matter (SPM) in large estuaries like the Yangtze Estuary. However, a lack of proper atmospheric correction methods has limited its application in water quality assessment. We propose an atmospheric correction method based on a look up table coupled by the atmosphere radiative transfer model (6S) and the water semi-empirical radiative transfer (SERT) model for inversion of water-leaving reflectance from GF-1 top-of-atmosphere radiance, and then retrieving SPM concentration from water-leaving radiance reflectance of the Yangtze Estuary and its adjacent sea. Results are validated by the Landsat-8/OLI imagery together with autonomous fixed station data, and influences of human activities (e.g., waterway construction and shipping) on SPM distribution are analyzed. PMID:27897987

  5. Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

    USGS Publications Warehouse

    Krizanich, Gary; Finn, Michael P.

    2009-01-01

    Water quality of Table Rock Lake in southwestern Missouri is assessed using Landsat Thematic Mapper satellite data. A pilot study uses multidate satellite image scenes in conjunction with physical measurements of secchi disk transparency collected by the Lakes of Missouri Volunteer Program to construct a regression model used to estimate water clarity. The natural log of secchi disk transparency is the dependent variable in the regression and the independent variables are Thematic Mapper band 1 (blue) reflectance and a ratio of the band 1 and band 3 (red) reflectance. The regression model can be used to reliably predict water clarity anywhere within the lake. A pixel-level lake map of predicted water clarity or computed trophic state can be produced from the model output. Information derived from this model can be used by water-resource managers to assess water quality and evaluate effects of changes in the watershed on water quality.

  6. Earthshots: Satellite images of environmental change – Shanghai, China

    USGS Publications Warehouse

    Adamson, Thomas

    2015-01-01

    Much of Shanghai’s growth has been in satellite developments. The Landsat imagery makes this clear as the smaller populated areas outside of Shanghai expand and then are absorbed by the urban expansion.

  7. Linking multi-temporal satellite imagery to coastal wetland dynamics and bird distribution

    USGS Publications Warehouse

    Pickens, Bradley A.; King, Sammy L.

    2014-01-01

    Ecosystems are characterized by dynamic ecological processes, such as flooding and fires, but spatial models are often limited to a single measurement in time. The characterization of direct, fine-scale processes affecting animals is potentially valuable for management applications, but these are difficult to quantify over broad extents. Direct predictors are also expected to improve transferability of models beyond the area of study. Here, we investigated the ability of non-static and multi-temporal habitat characteristics to predict marsh bird distributions, while testing model generality and transferability between two coastal habitats. Distribution models were developed for king rail (Rallus elegans), common gallinule (Gallinula galeata), least bittern (Ixobrychus exilis), and purple gallinule (Porphyrio martinica) in fresh and intermediate marsh types in the northern Gulf Coast of Louisiana and Texas, USA. For model development, repeated point count surveys of marsh birds were conducted from 2009 to 2011. Landsat satellite imagery was used to quantify both annual conditions and cumulative, multi-temporal habitat characteristics. We used multivariate adaptive regression splines to quantify bird-habitat relationships for fresh, intermediate, and combined marsh habitats. Multi-temporal habitat characteristics ranked as more important than single-date characteristics, as temporary water was most influential in six of eight models. Predictive power was greater for marsh type-specific models compared to general models and model transferability was poor. Birds in fresh marsh selected for annual habitat characterizations, while birds in intermediate marsh selected for cumulative wetness and heterogeneity. Our findings emphasize that dynamic ecological processes can affect species distribution and species-habitat relationships may differ with dominant landscape characteristics.

  8. Mapping tropical dry forest habitats integrating landsat NDVI, Ikonos imagery, and topographic information in the Caribbean island of Mona.

    PubMed

    Martinuzzi, Sebastiáin; Gould, William A; Ramos Gonzalez, Olga M; Martinez Robles, Alma; Calle Maldonado, Paulina; Pérez-Buitrago, Néstor; Fumero Caban, José J

    2008-06-01

    Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference Vegetation Index (NDVI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDVI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5500 ha area, with a kappa coefficient of accuracy equal to 79%. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island.

  9. USGS Releases Landsat Orthorectified State Mosaics

    USGS Publications Warehouse

    ,

    2005-01-01

    The U.S. Geological Survey (USGS) National Remote Sensing Data Archive, located at the USGS Center for Earth Resources Observation and Science (EROS) in Sioux Falls, South Dakota, maintains the Landsat orthorectified data archive. Within the archive are Landsat Enhanced Thematic Mapper Plus (ETM+) data that have been pansharpened and orthorectified by the Earth Satellite Corporation. This imagery has acquisition dates ranging from 1999 to 2001 and was created to provide users with access to quality-screened, high-resolution satellite images with global coverage over the Earth's landmasses.

  10. Integrated Use of Multi-temporal SAR and Optical Satellite Imagery for Crop Mapping in Ukraine

    NASA Astrophysics Data System (ADS)

    Lavreniuk, M. S.; Kussul, N.; Skakun, S.

    2014-12-01

    Information on location and spatial distribution of crops is extremely important within many applications such as crop area estimation, crop yield forecasting and environmental impact analysis [1-2]. Synthetic-aperture radar (SAR) instruments on board remote sensing satellites offer unique features to imaging crops due to their all weather capabilities and ability to capture crop characteristics not available by optical instruments. This abstract aims to explore feasibility and the use of multi-temporal multi-polarization SAR images along with multi-temporal optical images to crop classification in Ukraine using a neural network ensemble. The study area included a JECAM test site in Ukraine which is a part of the Global Agriculture Monitoring (GEOGLAM) initiative. Six optical images were acquired by Landsat-8, and twelve SAR images were acquired by Radarsat-2 (six in FQ8W mode with angle 28 deg., and FQ20W with angle 40 deg.) over the study region. Optical images were atmospherically corrected. SAR images were filtered for speckle, and converted to backscatter coefficients. Ground truth data on crop type (274 polygons) were collected during the summer of 2013. In order to perform supervised classification of multi-temporal satellite imagery, an ensemble of neural networks, in particular multi-layer perceptrons (MLPs), was used. The use of the ensemble allowed us to improve overall (OA) classification accuracy from +0.1% to +2% comparing to an individual network. Adding multi-temporal SAR images to multi-temporal optical images improved both OA and individual class accuracies, in particular for sunflower (gains up to +25.9%), soybeans (+16.2%), and maize (+6.2%). It was also found that better OA can be obtained using shallow angle (FQ20W, 40°) OA=77% over steeper angle (FQ8W, 28°) OA=71.78%. 1. F. Kogan et al., "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," Int. J. Appl. Earth Observ. Geoinform

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  12. BOREAS Level-3b Landsat TM Imagery: At-sensor Radiances in BSQ Format

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef

    2000-01-01

    For BOREAS, the level-3b Landsat TM data, along with the other remotely sensed 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 FPAR and LAI. Although very similar in content to the level-3a Landsat TM products, the level-3b images were created to provide users with a directly usable at-sensor radiance image. Geographically, the level-3b images cover the BOREAS NSA and SSA. Temporally, the images cover the period of 22-Jun-1984 to 09-Jul-1996. The images are available in binary, image format files.

  13. Evaluation of solar angle variation over digital processing of LANDSAT imagery. [Brazil

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Novo, E. M. L. M.

    1984-01-01

    The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Original images are transformed by means of digital filtering to enhance their spatial features. The resulting images are used to obtain an unsupervised classification of relief units. After defining relief classes, which are supposed to be spectrally different, topographic variables (declivity, altitude, relief range and slope length) are used to identify the true relief units existing on the ground. The samples are also clustered by means of an unsupervised classification option. The results obtained for each LANDSAT overpass are compared. Digital processing is highly affected by illumination geometry. There is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

  14. On the Effectiveness of Sentinel-2 Data for Land-Cover Mapping: Comparison with Landsat and SPOT Imagery

    NASA Astrophysics Data System (ADS)

    Buchholz, Tim; Marconcini, Mattia; Fernandez-Prieto, Diego

    2012-04-01

    The objective of this work is twofold. On the one hand, we aim at assessing the effectiveness of Sentinel-2 data for land-cover mapping, and evaluating the improved discrimination capabilities offered by new features of the Multi-Spectral Imager (MSI) sensor. On the other hand, we compare the performances with those obtained using both Landsat-5 TM and SPOT-5 HRG imagery. Simulated Sentinel-2 data are derived from hyperspectral airborne images acquired in the framework of four different ESA campaigns, namely SPARC 2003 (Barrax, Castilla-La Mancha, Spain), AGRISAR 2006 (Demmin, Pomerania, Germany) and CEFLES2 2007 (Marmande, Aquitaine, France). In each case, we discard the three spectral bands at 60 meter resolution (i.e., band 1, band 9 and band 10) and resample all the 20 meter-resolution bands to 10 meter resolution using nearest neighbour interpolation. Available prior knowledge is used for defining a complete ground truth for all the land-cover classes characterizing each investigated site. In each case, besides considering the whole available 10 spectral bands, we also run the branch & bound feature selection algorithm for identifying the subset of n features (varying n from 1 to 9) maximizing the (expected) separability between the investigated land-cover classes (for which training samples are available). Furthermore we run experiments by adding the new features of Sentinel-2 successive to the corresponding Landsat-5 Thematic Mapper (TM) bands. Then, in order to assess the discrimination capabilities offered by different features, for each subset we run two supervised classifiers, namely, the Maximum Likelihood (ML) classifier and Support Vector Machines (SVM). ML is a simple yet generally rather effective statistical classifier, which does not require the user to set any free parameter. SVM are advanced state-of-art classifiers, which proved capable of outperforming other traditional approaches. For the selection of the two free parameters (i.e., a

  15. Environmental Analysis of the Upper Susitna River Basin using Landsat Imagery

    DTIC Science & Technology

    1980-01-01

    themselves before be- phic detail of topographic features is more ob- coming involved in more advanced , automated vious. Features with small topographic...3) Also, the bars (1) and islands mentary rocks or massive igneous rocks, or with (2) apparent on the Landsat scene andf the NASA folded or...A033500 petrology and structure of the Maclaren, Ruby Range McKim, H L, L W Gatto, C I Merry, and R K Haugen (1976b) and Coast Range Belts implications

  16. 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.

    1976-01-01

    The author has identified the following significant results. Based on tests, it is obvious that practically all major LANDSAT winter linears found are geologically significant features. Most of them are chains of bogs, lakes, rivers, and cultivated areas covered by ice and/or snow, i.e., unforested linear topographic lows. They need no explanation other than that they are extensive fracture zones of the basement.

  17. Preliminary statistical studies concerning the Campos RJ sugar cane area, using LANDSAT imagery and aerial photographs

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Costa, S. R. X.; Paiao, L. B. F.; Mendonca, F. J.; Shimabukuro, Y. E.; Duarte, V.

    1983-01-01

    The two phase sampling technique was applied to estimate the area cultivated with sugar cane in an approximately 984 sq km pilot region of Campos. Correlation between existing aerial photography and LANDSAT data was used. The two phase sampling technique corresponded to 99.6% of the results obtained by aerial photography, taken as ground truth. This estimate has a standard deviation of 225 ha, which constitutes a coefficient of variation of 0.6%.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  19. A Project to Map and Monitor Baldcypress Forests in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

    NASA Technical Reports Server (NTRS)

    Spruce, Joseph; Sader, Steven; Smoot, James

    2012-01-01

    Cypress swamp forests of Louisiana offer many important ecological and economic benefits: wildlife habitat, forest products, storm buffers, water quality, and recreation. Such forests are also threatened by multiple factors: subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, hurricanes, insect and nutria damage, timber harvesting, and land use conversion. Unfortunately, there are many information gaps regarding the type, location, extent, and condition of these forests. Better more up to date swamp forest mapping products are needed to aid coastal forest conservation and restoration work (e.g., through the Coastal Forest Conservation Initiative or CFCI). In response, a collaborative project was initiated to develop, test and demonstrate cypress swamp forest mapping products, using NASA supported Landsat, ASTER, and MODIS satellite data. Research Objectives are: Develop, test, and demonstrate use of Landsat and ASTER data for computing new cypress forest classification products and Landsat, ASTER, and MODIS satellite data for detecting and monitoring swamp forest change

  20. Skylab imagery: Application to reservoir management in New England

    NASA Technical Reports Server (NTRS)

    Cooper, S.; Anderson, D. (Principal Investigator); Mckim, H. L.; Gatto, L. W.; Merry, C. J.; Haugen, R. K.

    1975-01-01

    The author has identified the following significant results. S190B imagery is superior to the LANDSAT imagery for land use mapping and is as useful for level 1 and 2 land use mapping as the RB-57/RC8 high altitude imagery. Detailed land use mapping at levels 3 and finer from satellite imagery requires better resolution. For evaluating factors that are required to determine volume runoff potentials in a watershed, the S190B imagery was found to be as useful as the RB-57/RC8 high altitude aircraft imagery.

  1. Remote sensing: Physical principles, sensors and products, and the LANDSAT

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Steffen, C. A.; Lorenzzetti, J. A.; Stech, J. L.; Desouza, R. C. M.

    1981-01-01

    Techniques of data acquisition by remote sensing are introduced in this teaching aid. The properties of the elements involved (radiant energy, topograph, atmospheric attenuation, surfaces, and sensors) are covered. Radiometers, photography, scanners, and radar are described as well as their products. Aspects of the LANDSAT system examined include the characteristics of the satellite and its orbit, the multispectral band scanner, and the return beam vidicon. Pixels (picture elements), pattern registration, and the characteristics, reception, and processing of LANDSAT imagery are also considered.

  2. APPLYING SATELLITE IMAGERY TO TRIAGE ASSESSMENT OF ECOSYSTEM HEALTH

    EPA Science Inventory

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

  3. Application of NASA ERTS-1 satellite imagery in coastal studies

    NASA Technical Reports Server (NTRS)

    Magoon, O. T.; Berg, D. W. (Principal Investigator); Hallermeier, R. J.

    1973-01-01

    There are no author-identified significant results in this report. Review of ERTS-1 imagery indicates that it contains information of great value in coastal engineering studies. A brief introduction is given to the methods by which imagery is generated, and examples of its application to coastal engineering. Specific applications discussed include study of the movement of coastal and nearshore sediment-laden water masses and information for planning and construction in remote areas of the world.

  4. Identifying woody vegetation on coal surface mines using phenological indicators with multitemporal Landsat imagery

    NASA Astrophysics Data System (ADS)

    Oliphant, A. J.; Li, J.; Wynne, R. H.; Donovan, P. F.; Zipper, C. E.

    2014-11-01

    Surface mining for coal has disturbed large land areas in the Appalachian Mountains. Better information on mined lands' ecosystem recovery status is necessary for effective environmental management in mining-impacted regions. Because record quality varies between state mining agencies and much mining occurred prior to widespread use of geospatial technologies, accurate maps of mining extents, durations, and land cover effects are often not available. Landsat data are well suited to mapping and characterizing land cover and forest recovery on former coal surface mines. Past mine reclamation techniques have often failed to restore premining forest vegetation but natural processes may enable native forests to re-establish on mined areas with time. However, the invasive species autumn olive (Elaeagnus umbellate) is proliferating widely on former coal surface mines, often inhibiting reestablishment of native forests. Autumn olive outcompetes native vegetation because it fixes atmospheric nitrogen and benefits from a longer growing season than native deciduous trees. This longer growing season, along with Landsat 8's high signal to noise ratio, has enabled species-level classification of autumn olive using multitemporal Landsat 8 data at accuracy levels usually only obtainable using higher spatial or spectral resolution sensors. We have used classification and regression tree (CART®) and support vector machine (SVM) to classify five counties in the coal mining region of Virginia for presence and absence of autumn olive. The best model found was a CART® model with 36 nodes which had an overall accuracy of 84% and kappa of 0.68. Autumn olive had conditional kappa of 0.65 and a producers and users accuracy of 86% and 83% respectively. The best SVM model used a second order polynomial kernel and had an overall accuracy of 77%, an overall kappa of 0.54 and a producers and users accuracy of 60% and 90% respectively.

  5. Age discrimination among basalt flows using digitally enhanced LANDSAT imagery. [Saudi Arabia

    NASA Technical Reports Server (NTRS)

    Blodget, H. W.; Brown, G. F.

    1984-01-01

    Digitally enhanced LANDSAT MSS data were used to discriminate among basalt flows of historical to Tertiary age, at a test site in Northwestern Saudi Arabia. Spectral signatures compared favorably with a field-defined classification that permits discrimination among five groups of basalt flows on the basis of geomorphic criteria. Characteristics that contributed to age definition include: surface texture, weathering, color, drainage evolution, and khabrah development. The inherent gradation in the evolution of geomorphic parameters, however, makes visual extrapolation between areas subjective. Therefore, incorporation of spectrally-derived volcanic units into the mapping process should produce more quantitatively consistent age groupings.

  6. Color enhancement of landsat agricultural imagery: JPL LACIE image processing support task

    NASA Technical Reports Server (NTRS)

    Madura, D. P.; Soha, J. M.; Green, W. B.; Wherry, D. B.; Lewis, S. D.

    1978-01-01

    Color enhancement techniques were applied to LACIE LANDSAT segments to determine if such enhancement can assist analysis in crop identification. The procedure involved increasing the color range by removing correlation between components. First, a principal component transformation was performed, followed by contrast enhancement to equalize component variances, followed by an inverse transformation to restore familiar color relationships. Filtering was applied to lower order components to reduce color speckle in the enhanced products. Use of single acquisition and multiple acquisition statistics to control the enhancement were compared, and the effects of normalization investigated. Evaluation is left to LACIE personnel.

  7. Comparison of Wyoming land cover types derived from the Landsat Thematic Mapper satellite with climate variables

    SciTech Connect

    Driese, K.L.; Reiners, W.A.

    1995-06-01

    As part of the Gap Analysis Program (National Biological survey) the land cover of Wyoming was mapped into 46 classes using the Landsat Thematic Mapper Satellite. This map was subsequently analyzed using a geographic information system (GIS) to calculate the amount of each type present in the state and to characterize each of the 46 types in terms of annual precipitation, minimum and maximum mean monthly temperature, growing degree days and elevation. Simple GCM-based climate change scenarios (changes in temperature and precipitation) were examined in relation to these characterizations. Results indicate that Wyoming types occupy overlapping climatic {open_quotes}envelopes{close_quotes} and possible climate change resulting from increased greenhouse gasses could result in significant changes in the Wyoming landscape.

  8. Geological Mapping Uses Landsat 4-5TM Satellite Data in Manlai Soum of Omnogovi Aimag

    NASA Astrophysics Data System (ADS)

    Norovsuren, B.

    2014-12-01

    Author: Bayanmonkh N1, Undram.G1, Tsolmon.R2, Ariunzul.Ya1, Bayartungalag B31 Environmental Research Information and Study Center 2NUM-ITC-UNESCO Space Science and Remote Sensing International Laboratory, National University of Mongolia 3Geology and Hydrology School, Korea University KEY WORDS: geology, mineral resources, fracture, structure, lithologyABSTRACTGeologic map is the most important map for mining when it does exploration job. In Mongolia geological map completed by Russian geologists which is done by earlier technology. Those maps doesn't satisfy for present requirements. Thus we want to study improve geological map which includes fracture, structural map and lithology use Landsat TM4-5 satellite data. If we can produce a geological map from satellite data with more specification then geologist can explain or read mineralogy very easily. We searched all methodology and researches of every single element of geological mapping. Then we used 3 different remote sensing methodologies to produce structural and lithology and fracture map based on geographic information system's softwares. There can be found a visible lithology border improvement and understandable structural map and we found fracture of the Russian geological map has a lot of distortion. The result of research geologist can read mineralogy elements very easy and discovered 3 unfound important elements from satellite image.

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

    PubMed

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

    2014-11-01

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

  10. Precipitation effects on the selection of suitable non-variant targets intended for atmospheric correction of satellite remotely sensed imagery

    NASA Astrophysics Data System (ADS)

    Themistocleous, Kyriacos; Hadjimitsis, Diofantos G.; Retalis, Adrianos; Chrysoulakis, Nektarios; Michaelides, Silas

    2013-09-01

    One of the most well-established atmospheric correction methods of satellite imagery is the use of the empirical line method using non-variant targets. Non-variant targets serve as pseudo-invariant targets since their reflectance values are stable across time. A recent adaptation of the empirical line method incorporates the use of ground reflectance measurements of selected non-variant targets. Most of the users are not aware of the existing conditions of the pseudo-invariant targets; i.e., whether they are dry or wet. Any omission of such effects may cause erroneous results; therefore, remote sensing users must be aware of such effects. This study assessed the effects of precipitation on five types of commonly located surfaces, including asphalt, concrete and sand, intended as pseudo-invariant targets for atmospheric correction. Spectroradiometric measurements were taken in wet and dry conditions to obtain the spectral signatures of the targets, from January 2010 to May 2011 (46 campaigns). An atmospheric correction of eleven Landsat TM/ETM + satellite images using the empirical line method was conducted. To identify the effects of precipitation, a comparison was conducted of the atmospheric path radiance component for wet and dry conditions. It was found that precipitation conditions such as rainfall affected the reflectance values of the surfaces, especially sand. Therefore, precipitation conditions need to be considered when using non-variant targets in atmospheric correction methods.

  11. BOREAS Level-3a Landsat TM Imagery: Scaled At-sensor Radiance in BSQ Format

    NASA Technical Reports Server (NTRS)

    Nickerson, Jaime; Hall, Forrest G. (Editor); Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef

    2000-01-01

    For BOREAS, the level-3a Landsat TM data, along with the other remotely sensed 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 FPAR and LAI. Although very similar in content to the level-3s Landsat TM products, the level-3a images were created to provide users with a more usable BSQ format and to provide information that permitted direct determination of per-pixel latitude and longitude coordinates. Geographically, the level-3a images cover the BOREAS NSA and SSA. Temporally, the images cover the period of 22-Jun-1984 to 30-Jul-1996. The images are available in binary, image-format files. With permission from CCRS and RSI, several of the full-resolution images are included on the BOREAS CD-ROM series. Due to copyright issues, the images not included on the CD-ROM may not be publicly available. See Sections 15 and 16 for information about how to acquire the data. Information about the images not on the CD-ROMs is provided in an inventory listing on the CD-ROMs.

  12. Retrieving leaf chlorophyll content in wheat and corn using Landsat-8 imagery

    NASA Astrophysics Data System (ADS)

    Arabian, Joyce

    The purpose of this study is to develop a method of modeling crop leaf chlorophyll content (Chlab) using remote sensing data with a physically-based modelling approach. During the 2013 growing season, ground data were collected at 28 corn and wheat sites near Stratford, Ontario. Effective leaf area index, hyperspectral leaf reflectance and transmittance, and chemically extracted Chlab were acquired at each site. A two-step inversion process was developed to model crop Chlab using Landsat-8. In this process, a look-up-table (LUT) was developed using SAIL, a bidirectional radiative-transfer model, to simulate canopy reflectance. The LUT was then utilized to calculate leaf-level reflectance and input into PROSPECT, a leaf-level radiative transfer model, to estimate Chlab. Validation of PROSPECT with ground-based Chlab using simulated Landsat-8 bands shows an R2= 0.83 and RMSE=8.48 mug/cm 2. Validation using the LUT shows an R2=0.64 at the leaf level and R2= 0.87 at the canopy level.

  13. Assessing Change in Agricultural Productivity Caused by Drought and Conflict in Northern Syria using Landsat Imagery.

    NASA Astrophysics Data System (ADS)

    Girgin, T.; Ozdogan, M.

    2015-12-01

    Until recently, agricultural production in Syria has been an important source of revenue and food security for the country. At its peak, agriculture in Syria accounted for 25 percent of the country's GDP. In 2014, Syrian agriculture accounted for less than 5 percent of the GDP. This decline in agricultural productivity is the cause of a 3-year long drought that started in 2007, followed by a still-ongoing conflict that started in mid-2011. Using remote sensing tools, this paper focuses on the impact that the 2007-2010 drought had on agricultural production, as well as the impact that the ongoing conflict had on the agricultural production in northern Syria. Remote sensing is a powerful and great solution to study regions of the world that are hard-to-reach due to conflict and/or other limitations. It is particularly useful when studying a region that inaccessible due to an ongoing conflict, such as in northern Syria. Using multi-temporal Landsat 5 and Landsat 8 images from August 2006, 2010 and 2014 and utilizing the neural networks algorithm, we assessed for agricultural output change in northern Syria. We conclude that the ongoing Syrian conflict has had a bigger impact on the agricultural output in northern Syria than the 3-year long drought.

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

    PubMed

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

    2011-06-01

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

  15. Correlation of chlorophyll, suspended matter, and related parameters of waters in the lower Chesapeake Bay area to LANDSAT-1 imagery

    NASA Technical Reports Server (NTRS)

    Fleischer, P. (Principal Investigator); Bowker, D. E.; Witte, W. G.; Gosink, T. A.; Hanna, W. J.; Ludwick, J. C.

    1976-01-01

    The author has identified the following significant results. An effort to relate water parameters of the lower Chesapeake Bay area to multispectral scanner images of LANDSAT 1 has shown that some spectral bands can be correlated to water parameters, and has demonstrated the feasibility of synoptic mapping of estuaries by satellite. Bands 5 and 6 were shown to be useful for monitoring total particles. Band 5 showed high correlation with suspended sediment concentration. Attenuation coefficients monitored continuously by ship along three baselines were cross correlated with radiance values on three days. Improved correlations resulted when tidal conditions were taken into consideration. A contouring program was developed to display sediment variation in the lower Chesapeake Bay from the MSS bands.

  16. Use of Landsat imagery to detect land cover changes for monitoring soil sealing; case study: Bologna province (Italy)

    NASA Astrophysics Data System (ADS)

    Casciere, Rossella; Franci, Francesca; Bitelli, Gabriele

    2014-08-01

    Landsat archives (made accessible by USGS at no charge since 2011) have made available to the scientific community a large amount of satellite multispectral images, providing new opportunities for environmental information, such as the analysis of land use/cover changes, which represent important tools for planning and sustainable land management. Processing a time series images, the creation of land cover maps has been improved in order to analyze phenomena such as the soil sealing. The main topic of this work is in fact the detection of roads and buildings construction or everything that involve soil removing. This subject is highly relevant, given the impact of the phenomenon on land use planning, environmental sustainability, agricultural policies and urban runoff. The analysis, still in progress, has been applied to Bologna Province (Emilia-Romagna Region, Italy) that covers 3703 Km2. This area is strongly urbanized: 8,9% of the total surface is sealed against a national value of 6,7%, with the soil sealing rate which has been defined from recent studies as the fourth Italian value in the 2001/2011 period. Other information available for this territory derive from CORINE Land Cover and Copernicus Projects. In the first one, the minimum mapping unit is 25 ha and the one for change is 5 ha; these values are too large for an accurate detection of the soil sealing dynamics. On the other hand, the Copernicus Project provides an imperviousness layer with a better resolution (20x20 m2), but its maps start from 2006. Therefore, the potential of multispectral remote sensing analysis over large areas and the multitemporal Landsat availability have been combined for a better knowledge about land cover changes. For this work, Landsat 5 and Landsat 8 images have been acquired between 1987 and 2013, according to basic requirements as low cloud cover and a common acquisition season (summer). A supervised pixel-based classification has been performed, with maximum likelihood

  17. Integrated Mapping of Drought-Impacted Areas in the Sierra-Nevada Foothills Region of California Using Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Rao, M.

    2014-12-01

    Drought is a natural disaster with serious implications to environmental, social and economic well-being at local, regional and global scales. In its third year, California's drought condition has seriously impacted not just the agricultural sector, but also the natural resources sector including forestry, wildlife, and fisheries. As of July 15, 2014, the National Weather Service drought monitor shows 81% of California in the category of extreme drought. As future predictions of drought and fire severity become more real in California, there is an increased awareness to pursue innovative and cost-effective solutions that are based on silvicultural treatments and controlled burns to improve forest health and reduce the risk of high-severity wildfires. The main goal of this study is to develop a GIS map of the drought-impacted region of northern and central California using remote sensing data. Specifically, based on a geospatial database for the study region, Landsat imagery in conjunction with field and ancillary data will be analyzed using a combination of supervised and unsupervised classification techniques in addition to spectral indices such as the Modified Perpendicular Drought Index (MPDI). This spectral index basically scales the line perpendicular to the soil line defined in the Red-NIR feature space in conjunction with added information about vegetative fraction derived using NDVI. The image processing will be conducted for two time periods (2001 and 2014) to characterize the severity of the drought. In addition to field data, data collected by state agencies including calforests.org will be used in the classification and accuracy assessment procedures. Visual assessment using high-resolution imagery such as NAIP will be used to further refine the spatial maps. The drought severity maps produced will greatly facilitate site-specific planning efforts aimed at implementing resource management decisions.

  18. Using multitemporal Landsat imagery to monitor and model the influences of landscape pattern on urban expansion in a metropolitan region

    NASA Astrophysics Data System (ADS)

    Yang, Yetao; Wong, Louis Ngai Yuen; Chen, Chao; Chen, Tao

    2014-01-01

    Studying the interaction between landscape patterns and temporal land-use changes in a metropolitan area can improve understanding of the urbanization process. Multitemporal remote sensing imagery is widely used to map the urbanization-caused temporal land-use dynamics, which mainly appear as built-up growth. Remote sensing integrated with landscape metrics is also used to quantitatively describe the landscape pattern of the urban area in recent literature. However, few studies have focused on the interaction between the pattern and the process of urbanization in a metropolitan area. We propose a grid-based framework to analyze the influence of the landscape pattern on the built-up growth by using the multitemporal Landsat imagery. Remote sensing classification method is used to obtain thematic land-use maps. Built-up growth is then extracted from the multitemporal classification results by a postclassification change detection. Landscape pattern, which is quantitatively described by landscape metrics, is derived from the thematic land-use maps. A grid-based method is used to analyze the spatial variation of landscape pattern and its related built-up growth. Finally, the spatial relationship between the landscape pattern and the built-up growth characters is assessed and modeled by using the mathematical regression method. The present study shows that an apparent correlation between landscape pattern and built-up growth exists. The correlation reflects the inherent influences of landscape pattern on urban expansion. The landscape pattern indicates the land development stage, while the urbanization stage determines the speed and style of the following built-up growth. Scales, including temporal scale and spatial scale, are important to modeling the landscape pattern effects on the built-up growth. The proposed analysis framework is efficient in detecting and modeling the landscape pattern effects on the built-up growth.

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

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

    A technique is developed to eliminate the atmosphere and surface noise effects on Landsat signals of water bodies by manipulating the total signal from Landsat in such a way that only the volume reflectance is left as a residual. With the Landsat signal from a lake and the known volume reflectance for its clear water it is possible to eliminate the surface and atmospheric effects and have residual signals that are indicative only of the type and concentration of the material in other lakes. Laboratory values are more precise than field values because in the field one must contend with indirect skylight and wave action which can be removed in the laboratory. The volume reflectance of distilled water or a very clear lake approaching distilled water was determined in the laboratory by the use of the Bendix radiant power measuring instrument. The Bendix multispectral data analysis system provided a color categorized image of several hundred lakes in a Wisconsin area. These lakes were categorized for tannin and nontannin waters and for the degrees of algae, silt, weeds, and bottom effects present.

  20. Application of satellite photographic and MSS data to selected geologic and natural resource problems in Pennsylvania. 1: Lineaments and mineral occurrences in Pennsylvania. 2: Relation of lineaments to sulfide deposits: Bald Eagle Mountain, Centre County, Pennsylvania. 3: Comparison of Skylab and LANDSAT lineaments with joint orientations in north central Pennsylvania

    NASA Technical Reports Server (NTRS)

    Kowalik, W. S.; Gold, D. P.; Krohn, M. D.

    1975-01-01

    Those metallic mineral occurrences in Pennsylvania are reported which lie near lineaments mapped from LANDSAT-1 satellite imagery and verified from Skylab photography where available. The lineaments were categorized by degree of expression and type of expression; the mineral occurrences were classified by host rock age, mineralization type, and value. The accompanying tables and figure document the mineral occurrences geographically associated with lineaments and serve as a base for a mineral exploration model.

  1. The use of LANDSAT-1 imagery for water quality studies in southern Scandinavia

    NASA Technical Reports Server (NTRS)

    Hellden, U.

    1975-01-01

    The possibilities of using LANDSAT-1 images for environmental studies, with special references to water quality studies, were investigated by selecting test areas in southern Scandinavia. The MSS images of different bands are compared under the magnification of an Interpretoscope and densitometric analyses are performed in a Schnell-photometer. The possibility of tracing pollution plumes is studied in the Oresund outside Copenhagen. The effect of different sewers and the circulation of the polluted water is analyzed in various situations. The variation in reflectivity of a great number of lakes in South and Middle Sweden is studied by means of densitometric analyses and significant regional differences are found. The correlation with in situ measurements of water quality (turbidity and secchi disc transparency) of the sampled lakes (made by the National Swedish Environment Protection Board) is fairly good.

  2. BOREAS Level-3s Landsat TM Imagery Scaled At-sensor Radiance in LGSOWG Format

    NASA Technical Reports Server (NTRS)

    Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef; Hall, Forrest G. (Editor)

    2000-01-01

    For BOReal Ecosystem-Atmosphere Study (BOREAS),the level-3s Landsat Thematic Mapper (TM) data, along with the other remotely sensed 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). CCRS collected and supplied the level-3s images to BOREAS for use in the remote sensing research activities. Geographically,the bulk of the level-3s images cover the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA) with a few images covering the area between the NSA and SSA. Temporally,the images cover the period of 22-Jun-1984 to 30-Jul-1996. The images are available in binary,image-format files.

  3. Application LANDSAT imagery to geologic mapping in the ice-free valleys of Antarctica

    NASA Technical Reports Server (NTRS)

    Houston, R. S. (Principal Investigator); Marrs, R. W.; Smithson, S. B.

    1976-01-01

    The author has identified the following significant results. Studies in the Ice-Free Valleys are resulted in the compilation of a sizeable library of maps and publications. Rock reflectance measurements were taken during the Antarctic summer of 1973. Spectral reflectance of rocks (mostly mafic lava flows) in the McMurdo and Ice-Free Valleys areas were measured using a filter wheel photometer equipped to measure reflectances in the four Landsat bands. A series of samples were collected at regular intervals across a large differentiated, mafic sill near Lake Vida. Chemical analyses of the sample suggest that the tonal variations in this sill are controlled by changes in the iron content of the rock. False color images were prepared for a number of areas by the diazo method and with an optical multispectral biviewer. These images were useful in defining boundaries of sea ice, snow cover, and in the study of ablating glaciers, but were not very useful for rock discrimination.

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

    PubMed

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

    2016-12-16

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

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

    PubMed Central

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

    2016-01-01

    Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

  6. The employment of weather satellite imagery in an effort to identify and locate the forest-tundra ecotone in Canada

    NASA Technical Reports Server (NTRS)

    Aldrich, S. A.; Aldrich, F. T.; Rudd, R. D.

    1969-01-01

    Weather satellite imagery provides the only routinely available orbital imagery depicting the high latitudes. Although resolution is low on this imagery, it is believed that a major natural feature, notably linear in expression, should be mappable on it. The transition zone from forest to tundra, the ecotone, is such a feature. Locational correlation is herein established between a linear signature on the imagery and several ground truth positions of the ecotone in Canada.

  7. An evaluation of the first four LANDSAT-D thematic mapper reflective sensors for monitoring vegetation: A comparison with other satellite sensor systems

    NASA Technical Reports Server (NTRS)

    Tucker, C. J.

    1978-01-01

    The first four LANDSAT-D thematic mapper sensors were evaluated and compared to: the return beam vidicon (RBV) and multispectral scanners (MSS) sensors from LANDSATS 1, 2, and 3; Colvocoresses' proposed 'operational LANDSAT' three band system; and the French SPOT three band system using simulation/intergration techniques and in situ collected spectral reflectance data. Sensors were evaluated by their ability to discriminate vegetation biomass, chlorophyll concentration, and leaf water content. The thematic mapper and SPOT bands were found to be superior in a spectral resolution context to the other three sensor systems for vegetational applications. Significant improvements are expected for most vegetational analyses from LANDSAT-D thematic mapper and SPOT imagery over MSS and RBV imagery.

  8. Change in Land Cover along the Lower Columbia River Estuary as Determined from Landsat Thematic Mapper (TM) Imagery, Technical Report 2003.

    SciTech Connect

    Garono, Ralph; Anderson, Becci; Robinson, Rob

    2003-10-01

    Thematic Mapper (TM) satellite imagery, making it feasible to assess land cover changes between 1992 and 2000.

  9. Landsat Data Continuity Mission

    USGS Publications Warehouse

    ,

    2007-01-01

    The Landsat Data Continuity Mission (LDCM) is a partnership between the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) to place the next Landsat satellite in orbit by late 2012. The Landsat era that began in 1972 will become a nearly 45-year global land record with the successful launch and operation of the LDCM. The LDCM will continue the acquisition, archival, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The mission objectives of the LDCM are to (1) collect and archive medium resolution (circa 30-m spatial resolution) multispectral image data affording seasonal coverage of the global landmasses for a period of no less than 5 years; (2) ensure that LDCM data are sufficiently consistent with data from the earlier Landsat missions, in terms of acquisition geometry, calibration, coverage characteristics, spectral characteristics, output product quality, and data availability to permit studies of land-cover and land-use change over time; and (3) distribute LDCM data products to the general public on a nondiscriminatory basis and at a price no greater than the incremental cost of fulfilling a user request. Distribution of LDCM data over the Internet at no cost to the user is currently planned.

  10. Landsat Data Continuity Mission

    USGS Publications Warehouse

    ,

    2012-01-01

    The Landsat Data Continuity Mission (LDCM) is a partnership formed between the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) to place the next Landsat satellite in orbit in January 2013. The Landsat era that began in 1972 will become a nearly 41-year global land record with the successful launch and operation of the LDCM. The LDCM will continue the acquisition, archiving, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The mission objectives of the LDCM are to (1) collect and archive medium resolution (30-meter spatial resolution) multispectral image data affording seasonal coverage of the global landmasses for a period of no less than 5 years; (2) ensure that LDCM data are sufficiently consistent with data from the earlier Landsat missions in terms of acquisition geometry, calibration, coverage characteristics, spectral characteristics, output product quality, and data availability to permit studies of landcover and land-use change over time; and (3) distribute LDCM data products to the general public on a nondiscriminatory basis at no cost to the user.

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

    SciTech Connect

    Vannoni, M.G.

    1999-06-08

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

  12. Spectral discrimination of ignimbritic rocks of southern Argentina in Landsat Thematic Mapper imagery using GER SIRIS laboratory data

    NASA Astrophysics Data System (ADS)

    Mehl, Harald; Reimer, Wolfgang; Miller, Hubert

    1994-12-01

    The article shows some basic approaches to discriminate ignimbrite type pyroclastic flow deposits in Landsat Thematic Mapper imagery of semi-arid areas. Beside certain topographical and tectonical fea- tures which already describe ignimbrites and associated pyroclastic flows in those environments, our interest is focused on the influence of specific mineralogical and depositional characteristics on the spectral reflectance response. Spectral signatures in the visible and near infrared region of various fresh and weathered samples as well as desert varnish and soil samples were recorded using a GER SIRIS laboratory spectroscope to determine the factors controlling their proper response in all Thematic Mapper bands. Whole rock geochemistry data, X-ray powder diffraction analysis and microscopical studies as well as surface interpretations of the samples documented certain properties which might cause different spectral signatures also of geochemically mostly equivalent rocks. According to the semi-arid conditions of the South Patagonian Massif which are the most important constituents with respect to rock weathering and mineral alteration a more effective discrimination of the mostly leucocratic rocks was obtained using TM bands 7-4-1 and 7-5-2 as RGB false colour com- posites. Three image processing techniques, contrast stretched ratio composites, decorrelation stretched false colour composites and relative channel colour composites were examined to distinguish the variable ignimbrite outcrops in the chosen test site.

  13. Accurate and efficient correction of adjacency effects for high resolution imagery: comparison to the Lambertian correction for Landsat

    NASA Astrophysics Data System (ADS)

    Sei, Alain

    2016-10-01

    The state of the art of atmospheric correction for moderate resolution and high resolution sensors is based on assuming that the surface reflectance at the bottom of the atmosphere is uniform. This assumption accounts for multiple scattering but ignores the contribution of neighboring pixels, that is it ignores adjacency effects. Its great advantage however is to substantially reduce the computational cost of performing atmospheric correction and make the problem computationally tractable. In a recent paper, (Sei, 2015) a computationally efficient method was introduced for the correction of adjacency effects through the use of fast FFT-based evaluations of singular integrals and the use of analytic continuation. It was shown that divergent Neumann series can be avoided and accurate results be obtained for clear and turbid atmospheres. We analyze in this paper the error of the standard state of the art Lambertian atmospheric correction method on Landsat imagery and compare it to our newly introduced method. We show that for high contrast scenes the state of the art atmospheric correction yields much larger errors than our method.

  14. Remote sensing of submerged aquatic vegetation in lower Chesapeake Bay - A comparison of Landsat MSS to TM imagery

    NASA Technical Reports Server (NTRS)

    Ackleson, S. G.; Klemas, V.

    1987-01-01

    Landsat MSS and TM imagery, obtained simultaneously over Guinea Marsh, VA, as analyzed and compares for its ability to detect submerged aquatic vegetation (SAV). An unsupervised clustering algorithm was applied to each image, where the input classification parameters are defined as functions of apparent sensor noise. Class confidence and accuracy were computed for all water areas by comparing the classified images, pixel-by-pixel, to rasterized SAV distributions derived from color aerial photography. To illustrate the effect of water depth on classification error, areas of depth greater than 1.9 m were masked, and class confidence and accuracy recalculated. A single-scattering radiative-transfer model is used to illustrate how percent canopy cover and water depth affect the volume reflectance from a water column containing SAV. For a submerged canopy that is morphologically and optically similar to Zostera marina inhabiting Lower Chesapeake Bay, dense canopies may be isolated by masking optically deep water. For less dense canopies, the effect of increasing water depth is to increase the apparent percent crown cover, which may result in classification error.

  15. Computer analysis of Landsat, Thematic Mapper imagery and existing road locations for elk habitat mapping in northern California

    SciTech Connect

    Fox, L. III; Burton, T.S.

    1996-03-01

    We analyzed Landsat, Thermatic Mapper imagery and previously mapped, road locations to identify vegetation classes and measure elk habitat quality throughout a 350,810 hectare study area in north-central California. Computerized image classification procedures were used to identify and map 26 classes of vegetation cover and ten classes of non-vegetated land. A geographic information system was used to integrate road locations, quantify forage and cover quality ratings for vegetation types, and calculate an elk habitat quality index. Vegetation classes were aggregated into three forage quality and three cover quality ratings. Road locations were used to define corridors of low habitat quality, representing hunting pressure. Mountainous regions were dominated by conifer forest types and foothill regions were dominated by Juniper-Pine-Grass types. The valley region contained large amounts of the sage and rabbit brush types. Thirty-four percent of the western third of the study area, dominated by foothills and mountains, was classed as good habitat. By contrast the central and eastern portions of the study area, dominated by the valley region and mountains, contained a small proportion (12 percent) of the better habitats. {copyright} {ital 1996 American Institute of Physics.}

  16. Assessment of EOS Aqua AMSR-E Arctic Sea Ice Concentrations using Landsat-7 and Airborne Microwave Imagery

    NASA Technical Reports Server (NTRS)

    Cavalieri, Donald J.; Markus, Thorsten; Hall, Dorothy K.; Gasiewski, Albin J.; Klein, Marian; Ivanoff, Alvaro

    2006-01-01

    An assessment of Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) sea ice concentrations under winter conditions using ice concentrations derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery obtained during the March 2003 Arctic sea ice validation field campaign is presented. The National Oceanic and Atmospheric Administration Environmental Technology Laboratory's Airborne Polarimetric Scanning Radiometer Measurements, which were made from the National Aeronautics and Space Administration P 3B aircraft during the campaign, were used primarily as a diagnostic tool to understand the comparative results and to suggest improvements to the AMSR-E ice concentration algorithm. Based on the AMSR-E/ETM+ comparisons, a good overall agreement with little bias (approx. 1%) for areas of first year and young sea ice was found. Areas of new ice production result in a negative bias of about 5% in the AMSR-E ice concentration retrievals, with a root mean square error of 8%. Some areas of deep snow also resulted in an underestimate of the ice concentration (approx. 10%). For all ice types combined and for the full range of ice concentrations, the bias ranged from 0% to 3%, and the rms errors ranged from 1% to 7%, depending on the region. The new-ice and deep-snow biases are expected to be reduced through an adjustment of the new-ice and ice-type C algorithm tie points.

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

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

  19. Land use change detection based on multi-date imagery from different satellite sensor systems

    NASA Technical Reports Server (NTRS)

    Stow, Douglas A.; Collins, Doretta; Mckinsey, David

    1990-01-01

    An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

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

    USGS Publications Warehouse

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

    2002-01-01

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

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

    NASA Astrophysics Data System (ADS)

    AlShamsi, Meera R.

    2016-10-01

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

  2. Quantitative Interpretation of Arctic Tundra Attributes Using Remote Sensing: Leveraging Field Data, Modern- and Legacy Landsat Data, and Commercial Imagery in Northern Alaska

    NASA Astrophysics Data System (ADS)

    Frost, G. V., Jr.; Macander, M. J.; Nelson, P. R.

    2014-12-01

    Integrated analysis of ground-based vegetation data and remote sensing supports vegetation mapping, landscape-change detection, wildlife habitat assessment, and tracking of phenological events such as green-up and senescence. The life-cycles of tundra plants occur within a highly compressed seasonal window, making the quantitative assessment of vegetation and landscape attributes from ≤30m resolution remotely-sensed imagery, such as above-ground biomass, % shrub cover, and % surface water, a difficult task when applied across large study domains. To support mapping of vegetation and landscape attributes across ~100,000 km2 of Alaska's North Slope, we obtained ground data for tundra vegetation using a point-intercept sampling approach across a network of 107 field plots spanning gradients of bioclimate, landscape position (upland, lowland, riverine), and geomorphic setting (foothills, coastal plain). At each plot, vegetation data were collected along three 50-m linear transects, compatible with 30-m Landsat imagery. We summarized live vegetation, litter, and non-vegetated surfaces using three terms: top cover (uppermost "hit"), percent cover (total areal cover along transect), and hit density (all "hits" at a point). We then evaluated a suite of data models (e.g., General Additive Models, classification tree, clustering) and data-mining approaches (e.g., neural networks, random forest) using midsummer Landsat TM/ETM+ acquisitions since 1985, and OLI acquisitions for 2013-2014. The large size, frequent cloudiness, and interannual variability of the study area necessitated the compositing of a multitude of Landsat scenes. A median NDVI compositing technique was used to select Landsat observations from cloud- and shadow-free pixels that met day-of-year and year constraints. This technique produced seamless, phenologically consistent composites that are largely free of artifacts and suitable for regional-scale analysis. Ground-based training data and an archive of

  3. A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery.

    PubMed

    Tan, Kok Chooi; Lim, Hwee San; Matjafri, Mohd Zubir; Abdullah, Khiruddin

    2012-06-01

    Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.

  4. Agricultural policy effects on land cover and land use over 30 years in Tartous, Syria, as seen in Landsat imagery

    NASA Astrophysics Data System (ADS)

    Ibrahim, Waad Youssef; Batzli, Sam; Menzel, W. Paul

    2014-01-01

    This study pursues a connection between agricultural policy and the changes in land use and land cover detected with remote sensing satellite data. One part of the study analyzes the Syrian agricultural policy, wherein, certain regional targets have been selected for annual citrus or greenhouse development along with tools of enforcement, support, and monitoring. The second part of the study investigates the utility of remote sensing (RS) and geographical information systems (GIS) to map land use land cover changes (LULC-Cs) in a time series of images from Landsat Thematic Mapper (TM) from 1987, 1998, 2006, and 2010 and Enhanced Thematic Mapper plus (ETM+) from 1999 to 2002. Several multispectral band analyses have been performed to determine the most suitable band combinations for isolating greenhouses and citrus farms. Supervised classification with maximum likelihood classifier has been used to produce precise land use land cover map. This research demonstrates that spatial relationship between LULC-Cs and agricultural policies can be determined through a science-based GIS/RS application to a time series of satellite images taken at the same time of the implemented policy.

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

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  6. Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites.

    PubMed

    Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed

    2014-12-01

    This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring.

  7. Satellite imagery for assessing range fire damage in the Sandhills of Nebraska

    NASA Technical Reports Server (NTRS)

    Drew, J. V. (Principal Investigator); Seevers, P. M.; Jensen, P. N.

    1973-01-01

    The author has identified the following significant results. Initial imagery from the first ERTS indicates that satellite-acquired data is of value in determining the location and extent of range fire in the Sand Hills region of Nebraska. Preliminary results suggest that it can also provide a tool for monitoring soil erosion by wind and evaluating the recovery of vegetation in burned areas.

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

    EPA Science Inventory

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Flood Inundation Mapping in the Logone Floodplain from Multi Temporal Landsat ETM+Imagery

    NASA Technical Reports Server (NTRS)

    Jung, Hahn Chul; Alsdorf, Douglas E.; Moritz, Mark; Lee, Hyongki; Vassolo, Sara

    2011-01-01

    Yearly flooding in the Logone floodplain makes an impact on agricultural, pastoral, and fishery systems in the Lake Chad Basin. Since the flooding extent and depth are highly variable, flood inundation mapping helps us make better use of water resources and prevent flood hazards in the Logone floodplain. The flood maps are generated from 33 multi temporal Landsat Enhanced Thematic Mapper Plus (ETM+) during three years 2006 to 2008. Flooded area is classified using a short-wave infrared band whereas open water is classified by Iterative Self-organizing Data Analysis (ISODATA) clustering. The maximum flooding extent in the study area increases up to approximately 5.8K km2 in late October 2008. The study also provides strong correlation of the flooding extents with water height variations in both the floodplain and the river based on a second polynomial regression model. The water heights are from ENIVSAT altimetry in the floodplain and gauge measurements in the river. Coefficients of determination between flooding extents and water height variations are greater than 0.91 with 4 to 36 days in phase lag. Floodwater drains back to the river and to the northeast during the recession period in December and January. The study supports understanding of the Logone floodplain dynamics in detail of spatial pattern and size of the flooding extent and assists the flood monitoring and prediction systems in the catchment.

  12. Monitoring the plague of oriental migratory locust using multi-temporal Landsat TM imagery

    NASA Astrophysics Data System (ADS)

    Liu, Zhenbo; Ni, Shaoxiang; Zha, Yong; Shi, Xuezheng

    2006-03-01

    Locust plague is a kind of the world-wide biological calamity to agriculture. In China's history, more than 90% of locust plagues were caused by the oriental migratory locust, Locusta migratoria manilensis (Meyen). At the present time, it is difficult for monitoring and forecasting systems in this country to provide real time information of locust plague outbreak in large area. In order to adopt timely measures for prevention and control of locust outbreak, it is necessary to apply advanced remote sensing technology for monitoring and forecasting locust outbreak This paper introduces a case study on monitoring oriental migratory locust plague with remote sensing technology in 3 pilot sites, namely, Huangzao, Yangguangzhuang, and Tengnan, which were the 3 major locust damaged areas in Huanghua City, Hebei Province, China during the period of large scale oriental migratory locust breakout in 2002. In this study, locust damage intensity, areas with various damage intensities and their distribution in pilot sites are determined by means of comparison between Landsat ETM+ image of locust damaged vegetation on 31st May, 2002 and TM image of healthy vegetation before damage on 23rd May, 2002. Then, information of various locust distribution density in pilot sites is extracted by establishing the Locust Density Index (LDI).

  13. Geological applications of LANDSAT-1 imagery to the Great Salt Lake area

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

    The ERTS program has been designed as a research and development tool to demonstrate that remote sensing from orbital altitudes is a feasible and practical approach to efficient management of earth resources. From this synoptic view and repetitive coverage provided by ERTS imagery of the Great Salt Lake area, large geological and structural features, trends, and patterns have been identified and mapped. A comparative analysis of lineaments observed in September and December data was conducted, existing mineral locations were plotted, and areas considered prospective for mineralization based on apparent structure-mineralization relationships were defined. The additional information obtained using ERTS data provides an added source of information to aid in the development of more effective mineral exploration programs.

  14. Enumeration of prairie wetlands with Landsat and aircraft data

    USGS Publications Warehouse

    Gilmer, D.S.; Work, E.A.; Colwell, J.E.; Rebel, D.L.

    1980-01-01

    A method is described for making an estimate of wetland numbers in the glaciated prairie region. A double-phase sampling approach is used which consists of first making a total census of wetlands using Landsat data, and then adjusting the Landsat results on the basis of samples derived from high resolution aircraft data. The method is relatively simple to use and has general applicability for estimating habitat features not consistently detectable or resolvable on Landsat imagery because their size range includes features less than the resolution capability of the satellite's sensor.

  15. Analysis of lake level changes in Nam Co in central Tibet utilizing synergistic satellite altimetry and optical imagery

    NASA Astrophysics Data System (ADS)

    Kropáček, Jan; Braun, Andreas; Kang, Shichang; Feng, Chen; Ye, Qinghua; Hochschild, Volker

    2012-07-01

    The fluctuations of closed basin lakes on the Tibetan Plateau are a valuable record of climate change induced water balance alterations within the catchments. Since these basins are remote and hard to access, multisensoral remote sensing is a valuable method to gather the necessary water budget components with appropriate spatial coverage and with high temporal resolutions. Thus the lake level elevation changes of the central Tibetan lake Nam Co were examined in example by a comparison of satellite altimetry (RA-2/ENVISAT, GFO radar altimeters and GLAS/ICESat laser altimeter for the period 2000-2009) and the evaluation of a time series of optical satellite data dating back to 1976 (Landsat) and 1965 (Corona) in order to validate hydrological water budget modelling results. The combination of all three altimeters revealed a rising trend of lake level on average by 0.31 m/year in the period 2000-2009 which corresponds to a total volume change of 6.2 km3. This is in a good agreement with simulated average lake level rise of 0.35 m/year obtained from distributed hydrological modelling (Krause et al., 2010). The movements of lakeshore measured on the satellite imagery confirm the trend revealed by the altimetry data and they also indicate the rising trend since 1965. While GFO provides a dense time series of data the more accurate ENVISAT/RA-2 data unfortunately feature large data gaps over Tibet. The measurements from time limited campaigns of ICESat validate the results of radar altimetry and they provide unlike radar altimeters a valid height over lake ice during winter and spring period. The results show that the presented approach is a valuable contribution to understand the impact of changing climate on the hydrology of Tibetan lakes.

  16. Remote sensing of Damavand volcano (Iran) using Landsat imagery: Implications for the volcano dynamics

    NASA Astrophysics Data System (ADS)

    Eskandari, Amir; De Rosa, Rosanna; Amini, Sadraddin

    2015-11-01

    Remote sensing techniques are applied to retrieve land surface temperature (LST), radiative heat flux (RHF), geothermal heat flux (GHF), and to map hydrothermal alteration zones around the Damavand stratovolcano (Iran). Landsat Enhanced Thematic Mapper Plus (ETM +) day and nighttime images are used and merged to available geological data to identify thermal anomaly areas. RHF is determined using the Stefan-Boltzmann equation after preprocessing (geometric, radiometric and atmospheric correction) and processing (emissivity calculation and LST retrieval) of thermal infrared bands. In order to estimate GHF from daytime image, solar radiation and albedo maps are generated to minimize these effects. The GHF values are derived from nighttime image using the background subtraction technique. Using Boolean operation, only those pixels with the GHF values greater than 30 W/m2 obtained from daytime image and the GHF values greater than 10 W/m2 estimated from nighttime image are identified as thermal anomalies. The geothermal areas are identified by combining the thermal anomaly map and other geological information. Thermal anomalies have close spatial correlation to faults, thermal springs, and high heat flow measurements from subsurface data and lithology. Some of the thermal anomalies and hydrothermal alteration areas also overlap active deformation areas. This suggests role of heat and hydrothermal alteration on flank instability processes. The thermal anomaly areas show an arc-shaped pattern. This pattern and the concentration of higher GHF areas in the eastern sector of the volcano are consistent with a release of fluids in a transition zone between a transpressional and a transtensional tectonic regime. The combination of thermal infrared data with other geological information layers can be used to detect geothermal areas as well as to analyze the complex relationships among geothermal activity, active tectonics, and gravity instability processes on volcanoes.

  17. Elliptical morphotectonic features on Landsat imagery in southwestern New York, northwestern Pennsylvania, and northeastern Ohio

    SciTech Connect

    Pees, S.T.; Palmquist, J.C.

    1984-12-01

    Circular to elliptical patterns are expressed in many diverse ways and scales on earth's surface. Some are clearly of endogenic origin, whereas others are proved to be astroblemes. Many are still of indeterminate origin, but hypotheses have been offered to explain some of them. The Lake Chautauqua-Kinzua composite feature in New York and Pennsylvania is expressed by an inner ring of 29 km (18 mi) (long axis) and fragmented concentric bands extending up to 48 km (30 mi) from its center to include a curved part of the Allegheny River in the Kinzua reservoir area (Pennsylvania). It is bisected by the northeast-southwest Chautauqua anticline and fault zone (decollement), locus of the Bass Islands-Akron dolomite oil and gas play. The Pymatuning reservoir, inverted teardrop feature of 34 km (21 mi) north-south length in Pennsylvania, is defined by impounded water and drainage courses bounding a topographically positive area. A slight anticlinal flexure is coaxial with the ellipse. A deep well found gas in the upper Gatesburg Formation. A nearly circular ring of 9.75 km (6 mi) diameter near New Lyme, Ashtabula County, Ohio, is seen as a tonal design on a specially enhanced composite false-color Landsat image. Elliptical patters may reflect deep deformation, differential compaction over buried basement hills, salt tectonics, filled negative areas, impact phenomena, or various other conditions that cause differences in surface configurations, surficial material, and moisture content. Investigation of such features, especially by seismic surveys and basement drill tests, is suggested for oil and gas exploration in this area.

  18. Determining relative contributions of vegetation and topography to burn severity from LANDSAT imagery.

    PubMed

    Wu, Zhiwei; He, Hong S; Liang, Yu; Cai, Longyan; Lewis, Bernard J

    2013-10-01

    Fire is a dominant process in boreal forest landscapes and creates a spatial patch mosaic with different burn severities and age classes. Quantifying effects of vegetation and topography on burn severity provides a scientific basis on which forest fire management plans are developed to reduce catastrophic fires. However, the relative contribution of vegetation and topography to burn severity is highly debated especially under extreme weather conditions. In this study, we hypothesized that relationships of vegetation and topography to burn severity vary with fire size. We examined this hypothesis in a boreal forest landscape of northeastern China by computing the burn severity of 24 fire patches as the difference between the pre- and post-fire Normalized Difference Vegetation Index obtained from two Landsat TM images. The vegetation and topography to burn severity relationships were evaluated at three fire-size levels of small (<100 ha, n = 12), moderate (100-1,000 ha, n = 9), and large (>1,000 ha, n = 3). Our results showed that vegetation and topography to burn severity relationships were fire-size-dependent. The burn severity of small fires was primary controlled by vegetation conditions (e.g., understory cover), and the burn severity of large fires was strongly influenced by topographic conditions (e.g., elevation). For moderate fires, the relationships were complex and indistinguishable. Our results also indicated that the pattern trends of relative importance for both vegetation and topography factors were not dependent on fire size. Our study can help managers to design fire management plans according to vegetation characteristics that are found important in controlling burn severity and prioritize management locations based on the relative importance of vegetation and topography.

  19. Mapping and Change Analysis in Mangrove Forest by Using Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Dan, T. T.; Chen, C. F.; Chiang, S. H.; Ogawa, S.

    2016-06-01

    Mangrove is located in the tropical and subtropical regions and brings good services for native people. Mangrove in the world has been lost with a rapid rate. Therefore, monitoring a spatiotemporal distribution of mangrove is thus critical for natural resource management. This research objectives were: (i) to map the current extent of mangrove in the West and Central Africa and in the Sundarbans delta, and (ii) to identify change of mangrove using Landsat data. The data were processed through four main steps: (1) data pre-processing including atmospheric correction and image normalization, (2) image classification using supervised classification approach, (3) accuracy assessment for the classification results, and (4) change detection analysis. Validation was made by comparing the classification results with the ground reference data, which yielded satisfactory agreement with overall accuracy 84.1% and Kappa coefficient of 0.74 in the West and Central Africa and 83.0% and 0.73 in the Sundarbans, respectively. The result shows that mangrove areas have changed significantly. In the West and Central Africa, mangrove loss from 1988 to 2014 was approximately 16.9%, and only 2.5% was recovered or newly planted at the same time, while the overall change of mangrove in the Sundarbans increased approximately by 900 km2 of total mangrove area. Mangrove declined due to deforestation, natural catastrophes deforestation and mangrove rehabilitation programs. The overall efforts in this study demonstrated the effectiveness of the proposed method used for investigating spatiotemporal changes of mangrove and the results could provide planners with invaluable quantitative information for sustainable management of mangrove ecosystems in these regions.

  20. Determining the effect of artificial grasslands on climate change using satellite imagery

    NASA Astrophysics Data System (ADS)

    Song, Y.; Lee, W.; Kwak, D.; Yoo, S.; Kwak, H.; Nam, K.; Lee, S.

    2012-12-01

    Recently, climate change has been started for several reasons. the most reason is the human activity such as using fossil fuel release the carbon to the atmosphere causing greenhouse effect. It changed tendency of the climate all over the world and the change is making the difficulty for mankind to have normal activity. However, it can be mitigated by ecosystem services such as mitigating temperature change of grasslands function. As ecosystem services started to be important for understanding the value of nature, It needs to be quantitatively calculated for conservation. In this study, the relationship artificial grasslands; agricultural land and the change of the surface was defined. First, It was compared past LANDSAT imagery(1970's) on agriculture area with present LANDSAT Imagery(2000's) to determine land cover which was changed from rice paddy area to impervious surface. Next, It was extracted on past climate data on the applicable study area by ArcMap 10. Finally, we could determine relationship temperature change and ground coverage were changed with rice paddy to impermeable area. This study will be helpful to prove quantitative value of the paddy farming.

  1. Remote sensing of effects of land-use practices on water quality. [environmental surveys using Landsat satellites

    NASA Technical Reports Server (NTRS)

    Graves, D. H.

    1975-01-01

    Research efforts are presented for the use of remote sensing in environmental surveys in Kentucky. Ground truth parameters were established that represent the vegetative cover of disturbed and undisturbed watersheds in the Cumberland Plateau of eastern Kentucky. Several water quality parameters were monitored of the watersheds utilized in the establishment of ground truth data. The capabilities of multistage-multispectral aerial photography and satellite imagery were evaluated in detecting various land use practices. The use of photographic signatures of known land use areas utilizing manually-operated spot densitometers was studied. The correlation of imagery signature data to water quality data was examined. Potential water quality predictions were developed from forested and nonforested watersheds based upon the above correlations. The cost effectiveness of predicting water quality values was evaluated using multistage and satellite imagery sampling techniques.

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  3. Landsat 8

    USGS Publications Warehouse

    ,

    2013-01-01

    The Landsat era that began in 1972 will continue into the future, since the February 2013 launch of the Landsat Data Continuity Mission (renamed Landsat 8 on May 30, 2013). The Landsat 8 satellite provides 16-bit high-quality land-surface data, with instruments advancing future measurement capabilities while ensuring compatibility with historical Landsat data. The Operational Land Imager sensor collects data in the visible, near infrared, and shortwave infrared wavelength regions as well as a panchromatic band. Two new spectral bands have been added: a deep-blue band for coastal water and aerosol studies (band 1), and a band for cirrus cloud detection (band 9). A Quality Assurance band is also included to indicate the presence of terrain shadowing, data artifacts, and clouds. The Thermal Infrared Sensor collects data in two long wavelength thermal infrared bands and has a 3-year design life.

  4. An evaluation of the use of ERTS-1 satellite imagery for grizzly bear habitat analysis

    NASA Technical Reports Server (NTRS)

    Varney, J. R.; Craighead, J. J.; Sumner, J.

    1973-01-01

    Multispectral scanner images taken by the ERTS-1 satellite in August and October, 1972, were examined to determine if they would be useful in identifying and mapping favorable habitat for grizzly bears. It was possible to identify areas having a suitable mixture of alpine meadow and timber, and to eliminate those which did not meet the isolation requirements of grizzlies because of farming or grazing activity. High altitude timbered areas mapped from satellite imagery agreed reasonably well with the distribution of whitebark pine, an important food species. Analysis of satellite imagery appears to be a valuable supplement to present ground observation methods, since it allows the most important areas to be identified for intensive study and many others to be eliminated from consideration. A sampling plan can be developed from such data which will minimize field effort and overall program cost.

  5. Using Landsat imagery and GIS to constrain late Miocene paleorelief and rates of erosion in the Hangay Dome, Mongolia

    NASA Astrophysics Data System (ADS)

    Smith, S. G.; Wegmann, K. W.; Bayasgalan, G.; Ancuta, L. D.; Gosse, J. C.

    2013-12-01

    Existing hypotheses maintain that the Hangay Dome of central Mongolia, situated significantly above continental freeboard and flanked by large strike-slip faults, is the result of relatively recent uplift, but ongoing geomorphological investigations of erosion rates, river incision, and paleotopography yield evidence to the contrary. For instance, Landsat Thematic Mapper (TM) imagery provides a unique opportunity to establish a 1st order approximation of local topographic relief at ~10 Ma. This age corresponds to the lowest layer in a thick (>600m) sequence of lava flows capping a 525 km2 area of high topography in the Hangay Dome (47.15°N, 100.05°E). The lava flows filled in and now preserve paleovalleys with ~700 m of local relief that are cut into basement. These paleovalleys exhibit similar relief to modern day, and are exposed along valley walls carved by Quaternary alpine glaciers. We quantify paleorelief in this remote mountain range by mapping the contact between basalt flows and granitic basement with ArcGIS and Landsat TM imagery. Spectral contrast between basalt and granite is maximized in a 1-5-6 band combination, and field mapping served to ground-truth the contact in certain areas. From this contact, a basal surface was interpolated and inferred to represent local topography at the time of the lowermost basalt flow (~10 Ma). Hypsometry, zonal statistics and topographic profile analysis indicate that relief of the relict surface is analogous to that of the present day. A similar GIS technique was applied to calculate the volume of rock removed since 6.13 Ma, which is the age for the uppermost, ridge-top basalt flow. In this experiment, a post-eruptive landscape was constructed by ';filling in' the post-lava flow valleys that are now incised into the upper lava flow surface. Subtracting the modern landscape from the post-eruptive surface yields the removal of 118 km3 of rock. Normalized for the study area, this results in a late Miocene to present net

  6. Inexpensive land-use maps extracted from satellite data

    NASA Technical Reports Server (NTRS)

    Barney, T. W.; Barr, D. J.; Elifrits, C. D.; Johannsen, C. J.

    1979-01-01

    Satellite images are interpretable with minimal skill and equipment by employing method which uses false color composite print of image of area transmitted from Landsat satellite. Method is effective for those who have little experience with satellite imagery, little time, and little money available.

  7. Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

    NASA Astrophysics Data System (ADS)

    Zhang, Min; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Liu, Ke

    2016-01-01

    Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.

  8. Using Satellite Imagery from the International Charter to Support Disaster Response Management

    NASA Astrophysics Data System (ADS)

    Bawden, G. W.; Jones, B. K.; Lamb, R.

    2014-12-01

    The International Charter provides satellite remote sensing imagery to emergency response and decision-making communities during major natural and anthropogenic disasters to help mitigate the effects of disasters on human life and property. The International Charter (http://www.disasterscharter.org) is a commitment by 15 of the world's space agencies to provide data from over 31 satellite systems and series to provide remote sensing imagery at no cost during a major disaster. The Internal Charter has been activated over 400 times since it was established in 1999 supporting the emergency response efforts for earthquakes, floods, ocean storms, volcanic unrest, landslides, oil spills, fires and others. The US Geological Survey Hazards Data Distribution System (HDDS: http://hddsexplorer.usgs.gov) delivers satellite imagery from the InternationalCharter and other data sources to support global disaster response. We will provide an overview of the remote sensing imagery from the International Charter with examples from the 2010 Haiti Earthquake and 2011 Tōhoku earthquake and tsunami.

  9. Monitoring of environmental effects of coal strip mining from satellite imagery

    NASA Technical Reports Server (NTRS)

    Brooks, R. L.; Parra, C. G.

    1976-01-01

    This paper evaluates satellite imagery as a means of monitoring coal strip mines and their environmental effects. The satellite imagery employed is Skylab EREP S-190A and S-190B from SL-2, SL-3 and SL-4 missions; a large variety of camera/film/filter combinations has been reviewed. The investigation includes determining the applicability of satellite imagery for detection of disturbed acreage in areas of coal surface mining as well as the much more detailed monitoring of specific surface-mining operations, including: active mines, inactive mines, highwalls, ramp roads, pits, water impoundments and their associated acidity, graded areas and types of grading, and reclamed areas. Techniques have been developed to enable mining personnel to utilize this imagery in a practical and economic manner, requiring no previous photo-interpretation background and no purchases of expensive viewing or data-analysis equipment. To corroborate the photo-interpretation results, on-site observations were made in the very active mining area near Madisonville, Kentucky.

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

    PubMed Central

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

    2017-01-01

    Epipolar resampling aims to eliminate the vertical parallax of stereo images. Due to the dynamic nature of the exterior orientation parameters of linear pushbroom satellite imagery and the complexity of reconstructing the epipolar geometry using rigorous sensor models, so far, no epipolar resampling approach has been proposed based on these models. In this paper for the first time it is shown that the orientation of the instantaneous baseline (IB) of conjugate image points (CIPs) in the linear pushbroom satellite imagery can be modeled with high precision in terms of the rows- and the columns-number of CIPs. Taking advantage of this feature, a novel approach is then presented for epipolar resampling of cross-track linear pushbroom satellite imagery. The proposed method is based on the rigorous sensor model. As the instantaneous position of sensors remains fixed, the digital elevation model of the area of interest is not required in the resampling process. Experimental results obtained from two pairs of SPOT and one pair of RapidEye stereo imagery with different terrain conditions shows that the proposed epipolar resampling approach benefits from a superior accuracy, as the remained vertical parallaxes of all CIPs in the normalized images are close to zero. PMID:28085044

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

    PubMed

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

    2017-01-11

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

  12. Detection of tamarisk defoliation by the northern tamarisk beetle based on multitemporal Landsat 5 thematic mapper imagery

    USGS Publications Warehouse

    Meng, Ran; Dennison, Philip E.; Jamison, Levi R.; van Riper, Charles; Nager, Pamela; Hultine, Kevin R.; Bean, Dan W.; Dudley, Tom

    2012-01-01

    The spread of tamarisk (Tamarix spp., also known as saltcedar) is a significant ecological disturbance in western North America and has long been targeted for control, leading to the importation of the northern tamarisk beetle (Diorhabda carinulata) as a biological control agent. Following its initial release along the Colorado River near Moab, Utah in 2004, the beetle has successfully established and defoliated tamarisk across much of the upper Colorado River Basin. However, the spatial distribution and seasonal timing of defoliation are complex and difficult to quantify over large areas. To address this challenge, we tested and compared two remote sensing approaches to mapping tamarisk defoliation: Disturbance Index (DI) and a decision tree method called Random Forest (RF). Based on multitemporal Landsat 5 TM imagery for 2006-2010, changes in DI and defoliation probability from RF were calculated to detect tamarisk defoliation along the banks of Green, Colorado, Dolores and San Juan rivers within the Colorado Plateau area. Defoliation mapping accuracy was assessed based on field surveys partitioned into 10 km sections of river and on regions of interest created for continuous riparian vegetation. The DI method detected 3711 ha of defoliated area in 2007, 7350 ha in 2008, 10,457 ha in 2009 and 5898 ha in 2010. The RF method detected much smaller areas of defoliation but proved to have higher accuracy, as demonstrated by accuracy assessment and sensitivity analysis, with 784 ha in 2007, 960 ha in 2008, 934 ha in 2009, and 1008 ha in 2010. Results indicate that remote sensing approaches are likely to be useful for studying spatiotemporal patterns of tamarisk defoliation as the tamarisk leaf beetle spreads throughout the western United States.

  13. Estimating urban impervious surfaces from Landsat-5 TM imagery using multilayer perceptron neural network and support vector machine

    NASA Astrophysics Data System (ADS)

    Sun, Zhongchang; Guo, Huadong; Li, Xinwu; Lu, Linlin; Du, Xiaoping

    2011-01-01

    In recent years, the urban impervious surface has been recognized as a key quantifiable indicator in assessing urbanization impacts on environmental and ecological conditions. A surge of research interests has resulted in the estimation of urban impervious surface using remote sensing studies. The objective of this paper is to examine and compare the effectiveness of two algorithms for extracting impervious surfaces from Landsat TM imagery; the multilayer perceptron neural network (MLPNN) and the support vector machine (SVM). An accuracy assessment was performed using the high-resolution WorldView images. The root mean square error (RMSE), the mean absolute error (MAE), and the coefficient of determination (R2) were calculated to validate the classification performance and accuracies of MLPNN and SVM. For the MLPNN model, the RMSE, MAE, and R2 were 17.18%, 11.10%, and 0.8474, respectively. The SVM yielded a result with an RMSE of 13.75%, an MAE of 8.92%, and an R2 of 0.9032. The results indicated that SVM performance was superior to that of MLPNN in impervious surface classification. To further evaluate the performance of MLPNN and SVM in handling the mixed-pixels, an accuracy assessment was also conducted for the selected test areas, including commercial, residential, and rural areas. Our results suggested that SVM had better capability in handling the mixed-pixel problem than MLPNN. The superior performance of SVM over MLPNN is mainly attributed to the SVM's capability of deriving the global optimum and handling the over-fitting problem by suitable parameter selection. Overall, SVM provides an efficient and useful method for estimating the impervious surface.

  14. Retrieving sea-wave spectra using satellite-imagery spectra in a wide range of frequencies

    NASA Astrophysics Data System (ADS)

    Bondur, V. G.; Dulov, V. A.; Murynin, A. B.; Ignatiev, V. Yu.

    2016-11-01

    A method to register sea-wave spectra using optical aerospace imagery has been developed. The method is based on the use of retrieval operators both in areas of high and low spatial frequencies, including the areas of spectral maximum. The approach to adjust and validate the method developed using sea truth data obtained by string wave recorders has been suggested. This paper presents the results of using the suggested method to study sea-wave spectra using high-resolution satellite imagery for various water areas under different conditions of wave generation.

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

    NASA Astrophysics Data System (ADS)

    Kit, Oleksandr; Lüdeke, Matthias

    2013-09-01

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

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

    DTIC Science & Technology

    2013-09-01

    in ICAPS, 2004, pp. 142–149. [24] J. E. Fowler, S. Mun, and E. W. Tramel, “Block- based compressed sensing of images and video,” Foundations and...Imagery Compression algorithm (OASIC) aims to conserve satellite channel capacity when transmitting oceanic imagery to Earth. OASIC conserves chan...losses, respectively. C N0 = AtPt(LpLd)Ar KTe (1.1) 2 Channel capacity, is the rate at which bits can be propagated through the range of frequencies

  17. Landsat continuity: Issues and opportunities for land cover monitoring

    USGS Publications Warehouse

    Wulder, M.A.; White, Joanne C.; Goward, S.N.; Masek, J.G.; Irons, J.R.; Herold, M.; Cohen, W.B.; Loveland, T.R.; Woodcock, C.E.

    2008-01-01

    Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures

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

    NASA Astrophysics Data System (ADS)

    Kingfield, D.; de Beurs, K.

    2014-12-01

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

  19. The use of LANDSAT DCS and imagery in reservoir management and operation. [Maine, New Hampshire, Vermont, and Canada

    NASA Technical Reports Server (NTRS)

    Cooper, S. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. A graph that shows the snow water equivalent data during the 1975-76 winter season for the Ninemile and Michaud Farms snow pillows located in northern Maine is shown. The Bournes transducers used in the snow pillow interface were tested after field use under controlled laboratory conditions of temperature and pressure. It was found that the temperature calibration curve for the Bournes transducers became erratic below 0 C. On 8-10 August 1976, the remainder of hurricane, Belle, travelled through Vermont, New Hampshire, northern Maine, and on into Canada's Maritime Provinces dumping three inches of rain in many areas. In Canada and Maine, local storms dropped up to two inches during the following week. The Saint John River reached near flood stages at Fort Kent, Maine. During this storm, DCP data were received from Fort Kent, Ninemile Bridge, and Saint Francis River in New Brunswick. Resulting high runoff after these storms was studied in connection with the proposed Dickey-Lincoln School dams to be built in that area, and significantly, it was found that creditable flood hydrographs could be generated from LANDSAT DCP data in spite of the voids caused by the satellite being below the horizon.

  20. Retrieval of lake water temperature based on LandSat TM imagery: A case study in East Lake of Wuhan

    NASA Astrophysics Data System (ADS)

    Cao, Bo; Kang, Ling; Yang, Shengmei

    2013-10-01

    Lake water temperature is one of the most important parameters determining ecological conditions in lake water. With the recent development of satellite remote sensing, remotely sensed data instead of traditional sampling measurement can be used to retrieve the lake surface temperature. The East Lake located in the Wuhan city was selected as research region in this paper. The mono window algorithm has been applied to retrieve the lake water temperature of East lake basin with Landsat TM data. Through three groups of field survey data, the outcome shows that the retrieval results using the mono window model are quite approximate to the same period of the experimental region historical temperature data. So, it is feasible to utilize the remote sensing method to obtain the lake temperature. Meanwhile, the retrieval results also demonstrate that the East Lake surface temperatures from different years have the similar distribution regularity. Generally speaking, the temperature of the lake center is higher than the surrounding area. The west of lake is mostly higher than the east mainly due to the vegetation density and urbanization distribution condition. This conclusion is important to the further study on monitoring the East Lake temperature particularly in large scale.

  1. Coastline change assessment on water reservoirs located in the Konya Basin Area, Turkey, using multitemporal landsat imagery.

    PubMed

    Durduran, S Savas

    2010-05-01

    This paper focuses mainly on the coastline change assessment on water reservoirs located in the Konya Basin Area, Turkey. The Konya Closed Basin exists at the Central Anatolia Region and covers a region of 50,000 km(2) area corresponding to the 7% cumulative area of Turkey in which three million people live, 45% in rural areas and 55% in urban areas. The basin is surrounded with the city centers of Konya, Aksaray, Karaman, Isparta, Niğde, Ankara, Nevşehir, and Antalya cities. In this study, these changes were examined using Landsat TM and ETM+ 1987-2006 and 1990-2000. In the image processing step, image and vectorization of the satellite images were carried out to monitor coastline changes over the lakes located in the Konya Closed Basin Area. At the end of the study, significant coastline movements were detected for a 19-year period due to drought effects, agricultural watering, and planning mistakes experienced in the basin.

  2. Use of Argon, Corona, and Landsat imagery to assess 30 years of land resource changes in west-central Senegal

    USGS Publications Warehouse

    Tappan, G. Gray; Hadj, Amadou; Wood, Eric C.; Lietzow, Ronald W.

    2000-01-01

    Over the past 35 years, an agricultural area of west-central Senegal has experienced rapid population growth, fast expansion of agricultural lands, a decline in rainfall, and degradation of vegetative and soil resources. Although such changes have not escaped the attention of Senegal's people, its government, and the scientific community the ability to monitor and quantify land resource trends of recent decades has been difficult. Recently available high-resolution satellite photographs from the American Argon and Corona Programs provide coverage of Senegal back to 1963. The photographs make it possible to study and map land resources at the beginning of the Space Age. In this study, we characterize the changes that have occurred in the region from the early 1960s to the mid-1 990s. Early Argon and Corona photographs are used to reconstruct the historical land use and land cover; comparisons are made with assessments from recent Landsat images. Field studies and aerial surveys provide additional insight. The forces of change, driven primarily by population growth and unsustainable agricultural practices, are examined

  3. Assessing and monitoring the risk of land degradation in Baragan Plain, Romania, using spectral mixture analysis and Landsat imagery.

    PubMed

    Vorovencii, Iosif

    2016-07-01

    The fall of the communist regime in Romania at the end of 1989 and the ensuing transition to the market economy brought about many changes in the use of agricultural land. These changes combined with the action of climatic factors led, in most cases, to negative effects increasing the risk of degradation of agricultural land. This study aims to assess and monitor the risk of land degradation in Baragan Plain, Romania, for the period 1988-2011 using Landsat Thematic Mapper (TM) and Spectral Mixture Analysis (SMA). Each satellite image was classified through the Decision Tree Classifier (DTC) method; then, on the basis of certain threshold values, we obtained maps of land degradation and maps showing the passage from various classes of land use/land cover (LULC) to land degradation. The results indicate that during the intermediary periods there was an ascending and descending trend in the risk of land degradation determined by the interaction of climatic factors with the social-economic ones. For the entire period, the overall trend was ascending, the risk of land degradation increasing by around 4.60 % of the studied surface. Out of the climatic factors, high temperatures and, implicitly, drought were the most significant. The social-economic factors are the result of the changes which occurred after the fall of the communist regime, the most important being the fragmentation of agricultural land and the destruction of the irrigation system.

  4. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

    NASA Astrophysics Data System (ADS)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

    2016-04-01

    Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

  5. Watershed-scale land-use mapping with satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Satellite remote sensing data has many advantages compared with other data sources, such as field methods and aerial photography, for land cover classification. In particular,it is useful in evaluating temporal and spatial effects. In addition, remote sensing can offer a cost-effective means of prov...

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

    NASA Astrophysics Data System (ADS)

    Gong, K.; Fritsch, D.

    2016-06-01

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

  7. Cloud cover determination in polar regions from satellite imagery

    NASA Technical Reports Server (NTRS)

    Barry, R. G.; Maslanik, J. A.; Key, J. R.

    1987-01-01

    A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.

  8. Verification of LANDSAT imagery for morphametric and topological studies of drainage basins in a section of the western plateau of Sao Paulo State: Tiete-Aguapei watershed. M.S. Thesis; [Brazil

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Camargo, J. C. G.

    1982-01-01

    The potential of using LANDSAT MSS imagery for morphometric and topological studies of drainage basins was verified. Using Tiete and Aguapei watershed (Western Plateau) as the test site because of its homogeneous landscape. Morphometric variables collected for ten drainage basins include: circularity index; river density; drainage density; topographic texture; areal and index length; basin parameter; and main river length 1st order and 2nd order channel length. The topographical variables determined were: order; magnitude; bifuraction ratio; weighted bifuraction ratio; number of segments; number of linking; trajectory length; and topological diameter. Data were collected on topographical maps at the scale of 1:250,000 and 1:59,000 and on LANDSAT imagery at the scale of 1:250,000. The results which were summarized on tables for further analysis, show that LANDSAT imagery can supply the lack of topographic charts for drainage studies.

  9. Landsat Data

    USGS Publications Warehouse

    ,

    1997-01-01

    In the mid-1960's, the National Aeronautics and Space Administration (NASA) embarked on an initiative to develop and launch the first Earth monitoring satellite to meet the needs of resource managers and earth scientists. The U.S. Geological Survey (USGS) entered into a partnership with NASA in the early 1970?s to assume responsibility for archiving data and distributing data products. On July 23, 1972, NASA launched the first in a series of satellites designed to provide repetitive global coverage of the Earth?s land masses. Designated initially as the "Earth Resources Technology Satellite-A" ("ERTS-A"), it used a Nimbus-type platform that was modified to carry sensor systems and data relay equipment. When operational orbit was achieved, it was designated "ERTS-1." The satellite continued to function beyond its designed life expectancy of 1 year and finally ceased to operate on January 6, 1978, more than 5 years after its launch date. The second in this series of Earth resources satellites (designated ?ERTS-B?) was launched January 22, 1975. It was renamed "Landsat 2" by NASA, which also renamed "ERTS-1" as "Landsat 1." Three additional Landsats were launched in 1978, 1982, and 1984 (Landsats 3, 4, and 5 ). (See table 1). NASA was responsible for operating the program through the early 1980?s. In January 1983, operation of the Landsat system was transferred to the National Oceanic and Atmospheric Administration (NOAA). In October 1985, the Landsat system was commercialized and the Earth Observation Satellite Company, now Space Imaging EOSAT, assumed responsibility for its operation under contract to NOAA. Throughout these changes, the USGS EROS Data Center (EDC) retained primary responsibility as the Government archive of Landsat data. The Land Remote Sensing Policy Act of 1992 (Public Law 102-5555) officially authorized the National Satellite Land Remote Sensing Data Archive and assigned responsibility to the Department of the Interior. In addition to its Landsat

  10. Satellite Imagery Analysis for Nighttime Temperature Inversion Clouds

    NASA Technical Reports Server (NTRS)

    Kawamoto, K.; Minnis, P.; Arduini, R.; Smith, W., Jr.

    2001-01-01

    Clouds play important roles in the climate system. Their optical and microphysical properties, which largely determine their radiative property, need to be investigated. Among several measurement means, satellite remote sensing seems to be the most promising. Since most of the cloud algorithms proposed so far are daytime use which utilizes solar radiation, Minnis et al. (1998) developed a nighttime use one using 3.7-, 11 - and 12-microns channels. Their algorithm, however, has a drawback that is not able to treat temperature inversion cases. We update their algorithm, incorporating new parameterization by Arduini et al. (1999) which is valid for temperature inversion cases. This updated algorithm has been applied to GOES satellite data and reasonable retrieval results were obtained.

  11. General pattern of the turbid water in the Seto-inland sea extracted from multispectral imageries by the LANDSAT-1 and 2

    NASA Technical Reports Server (NTRS)

    Maruyasu, T. (Principal Investigator); Watanabe, K.

    1976-01-01

    The author has identified the following significant results. Each distribution pattern of turbid water changes with the time in accordance with daily tides, seasonal variation of tides, and occasional rainfall. Two cases of successfully repeated LANDSAT observations for the same sea regions suggested a general pattern of turbid water could be extracted for each region. Photographic and digital processes were used to extract patterns of turbid water separately from the cloud and smog-layer in MSS 4, 5, and 7 imageries. A mosaic of image-masked imageries displays a general pattern of turbid water for almost the entire Seto Inland Sea. No such pattern was extracted for the Aki-Nada south of Hiroshima City where the water is fairly polluted, nor for the Iyo-Nada where the water is generally clearer than in other regions of the Seto Inland Sea.

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

    NASA Astrophysics Data System (ADS)

    Keys-Mathews, Lisa D.

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

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

    PubMed

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

    2017-02-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  15. Options for using Landsat and RapidEye satellite images aiming the water productivity assessments in mixed agro-ecosystems

    NASA Astrophysics Data System (ADS)

    de C. Teixeira, Antônio H.; Leivas, Janice F.; Bayma-Silva, Gustavo

    2016-10-01

    For water productivity (WP) assessments, the SAFER (Surface Algorithm for Evapotranspiration Retrieving) algorithm for evapotranspiration (ET) and the Monteith's light use efficiency (LUE) model for biomass production (BIO), were applied to Landsat and RapidEye satellite images, in the Brazilian semiarid region, inside the dry season of 2011, in a mixture of irrigated and rainfed agro-ecosystems. Firstly, with the Landsat image, the methodology from which the surface temperature (T0) is derived as a residue in the radiation balance was tested. Low differences were detected, being Landsat ET with the thermal band averaged 0.9 +/- 1.5 mm d-1, while without it the mean value was 0.8 +/- 1.5 mm d-1. The corresponding Landsat BIO values were respectively 28 +/- 59 and 28 +/- 58 kg ha-1 d-1, resulting in mean WP of 1.3 +/- 1.3 kg m-3, in both cases. After having confidence on the residual methodology for retrieving T0 it was applied to the RapidEye image, resulting in average pixel values for ET, BIO and WP of 0.6 +/- 1.5 mm d-1, 26 +/- 58 kg ha-1 d-1 and 0.9 +/- 1.3 kg m-3, representing 75%, 93% and 69% of the Landsat ones obtained without the thermal band. In addition, the Surface Resistance Algorithm (SUREAL) was used to classify the agro-ecosystems into irrigated crops and natural vegetation by using the RapidEye image. The incremental values for ET, BIO and WP in 2011 were 2.0 +/- 1.3 mm d-1, 88 +/- 87 kg ha d-1 and 2.5 +/- 0.6 kg m-3, respectively, as a result of the replacement of the natural species by crops.

  16. Landsat-7 Mission and Early Results

    NASA Technical Reports Server (NTRS)

    Dolan, S. Kenneth; Sabelhaus, Phillip A.; Williams, Darrel L.; Irons, James R.; Barker, John L.; Markham, Brian L.; Bolek, Joseph T.; Scott, Steven S.; Thompson, R. J.; Rapp, Jeffrey J.

    1999-01-01

    The Landsat-7 mission has the goal of acquiring annual data sets of reflective band digital imagery of the landmass of the Earth at a spatial resolution of 30 meters for a period of five years using the Enhanced Thematic Mapper Plus (ETM+) imager on the Landsat-7 satellite. The satellite was launched on April 15, 1999. The mission builds on the 27-year continuous archive of thematic images of the Earth from previous Landsat satellites. This paper will describe the ETM+ instrument, the spacecraft, and the ground processing system in place to accomplish the mission. Results from the first few months in orbit will be given, with emphasis on performance parameters that affect image quality, quantity, and availability. There will also be a discussion of the Landsat Data Policy and the user interface designed to make contents of the archive readily available, expedite ordering, and distribute the data quickly. Landsat-7, established by a Presidential Directive and a Public Law, is a joint program of the National Aeronautics and Space Administration (NASA) Earth Science Enterprise and the United States Geological Survey (USGS) Earth Resources Observing System (EROS) Data Center.

  17. Water productivity mapping using Landsat 8 satellite together with weather stations

    NASA Astrophysics Data System (ADS)

    Franco, Renato A. M.; Hernandez, Fernando B. T.; de C. Teixeira, Antônio H.; Leivas, Janice Freitas; Coaguila, Daniel Noe; Neale, Christopher M.

    2016-10-01

    The use of remote sensing satellite in conjunction with models and meteorological data enable the mapping of biophysical properties of agroecosystems with satisfactory accuracy. The main goal of this research was to determine the spatial-temporal agro-ecological indicators of water productivity in watersheds with different types of land use and occupation, using Landsat 8 images, agro-meteorological stations and application of Monteith and SAFER (Simple Algorithm for Retrieving Evapotranspiration) models to estimate the production biomass (BIO) and the actual evapotranspiration (ET), respectively. Incident global solar radiation (RS ↓) is observed seasonality of radiation during the year. Higher RS ↓levels happen during the first and the last four months, when the Sun is around its zenith positions in the study region. During the natural dry period in the region, the RS↓ is lower because winter solstice time for the Southern Hemisphere, this condition it is verified the reducing in the values of ET and BIO. Average values of biophysical properties for the study period were 0.54, 0.16 and 301 K for Normalized Difference Vegetation Index, albedo and surface temperature, respectively. The highest value of BIO was 105 kg ha-1d-1 and occurred in July 2013. The lowest value was 15.9 kg ha-1d-1 and occurred in October 2014. ET showed a value of 1.65 mm d-1 in the rainy period and 0.64 during the dry period in the study area. The highest average ET occurred in the irrigated area (June 2014), with a value of 1.89 mm d-1 and a maximum of 2.46 mm d-1. WP average for the evaluated period was 3.06 Kg m-3, with the largest value of 4.91 Kg m-3 in June 2013 and a minimum value of 2.45 Kg m-3 in September 2013.

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

    NASA Technical Reports Server (NTRS)

    Anderson, Charles E.

    1988-01-01

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

  19. Interpretation of snowcover from satellite imagery for use in water supply forecasts in the Sierra Nevada

    NASA Technical Reports Server (NTRS)

    Brown, A. J.; Hannaford, J. F.

    1975-01-01

    The California ASVT test area is composed of two study areas; one in Northern California covering the Upper Sacramento and Feather River Basins, and the other covering the Southern Sierra Basins of the San Joaquin, Kings, Kaweah, Tule, and Kern Rivers. Experiences of reducing snowcover from satellite imagery; the accuracy of present water supply forecast schemes; and the potential advantages of introducing snowcover into the forecast procedures are described.

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

    NASA Astrophysics Data System (ADS)

    Mohan, M.

    2016-06-01

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

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

    DTIC Science & Technology

    2006-05-31

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

  2. Spatial and Temporal Varying Thresholds for Cloud Detection in Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary; Haines, Stephanie

    2007-01-01

    A new cloud detection technique has been developed and applied to both geostationary and polar orbiting satellite imagery having channels in the thermal infrared and short wave infrared spectral regions. The bispectral composite threshold (BCT) technique uses only the 11 micron and 3.9 micron channels, and composite imagery generated from these channels, in a four-step cloud detection procedure to produce a binary cloud mask at single pixel resolution. A unique aspect of this algorithm is the use of 20-day composites of the 11 micron and the 11 - 3.9 micron channel difference imagery to represent spatially and temporally varying clear-sky thresholds for the bispectral cloud tests. The BCT cloud detection algorithm has been applied to GOES and MODIS data over the continental United States over the last three years with good success. The resulting products have been validated against "truth" datasets (generated by the manual determination of the sky conditions from available satellite imagery) for various seasons from the 2003-2005 periods. The day and night algorithm has been shown to determine the correct sky conditions 80-90% of the time (on average) over land and ocean areas. Only a small variation in algorithm performance occurs between day-night, land-ocean, and between seasons. The algorithm performs least well. during he winter season with only 80% of the sky conditions determined correctly. The algorithm was found to under-determine clouds at night and during times of low sun angle (in geostationary satellite data) and tends to over-determine the presence of clouds during the day, particularly in the summertime. Since the spectral tests use only the short- and long-wave channels common to most multispectral scanners; the application of the BCT technique to a variety of satellite sensors including SEVERI should be straightforward and produce similar performance results.

  3. Investigation of Panchromatic Satellite Imagery Sensor Low Bias in Shadow Method Aerosol Optical Depth Retrieval

    DTIC Science & Technology

    2009-03-01

    the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the...Joint Publication 3-59, environmental data is considered intelligence information and is deemed critically important to successful military...matching AERONET stations were used to start the search for matching satellite imagery. The DigitalGlobe ImageFinder web application was used to

  4. An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

    NASA Technical Reports Server (NTRS)

    Spruce, Joseph P.; Sader, Steve; Smoot, James

    2012-01-01

    This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

  5. Use of Commercial Satellite Imagery for Surveillance of the Canadian North by the Canadian Armed Forces

    DTIC Science & Technology

    1988-12-01

    other m . m . I - i i P " ° . . . nations plan to build, fly, and market their own systems. Among them are Japan, Canada, India , and a consortium of...The United States, Europe (ESA), India , Japan, Canada, the Soviet Union, and France plan to sell satellite acquired imagery in the iSOs. Additional...70)C25:537)C32:37S) 155 Indian Remote Sensing Satellite (IRS) Country Launch Or-bit Lifetime oF Origin Date Parameters India ? i - 996 3 Years H a S0I

  6. Distortion-free mapping of VISSR imagery data from geosynchronous satellites

    NASA Technical Reports Server (NTRS)

    Chan, F. K.

    1981-01-01

    The formulation is rigorous and includes all misalignment angles of the VISSR, the sun sensor and the instantaneous spin axis with the satellite's body axis. It also includes the effects due to the motion of the satellite's suborbital point. All the mapping equations for distortion removal were reduced to simplest forms, and all the algorithms were optimized as much as possible. An approach was then formulated for implementing these algorithms for in-line operational use. It is concluded that in-line distortion removal is possible in real-time processing of infra-red but not visible VISSR imagery data.

  7. Cloud cover determination in polar regions from satellite imagery

    NASA Technical Reports Server (NTRS)

    Barry, R. G.; Key, J. R.; Maslanik, J. A.

    1988-01-01

    The principal objectives of this project are: (1) to develop suitable validation data sets to evaluate the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; (2) to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers; and (3) to compare synoptic cloud data from a control run experiment of the GISS climate model II with typical observed synoptic cloud patterns.

  8. Evaluation of Future Internet Technologies for Processing and Distribution of Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Becedas, J.; Perez, R.; Gonzalez, G.; Alvarez, J.; Garcia, F.; Maldonado, F.; Sucari, A.; Garcia, J.

    2015-04-01

    Satellite imagery data centres are designed to operate a defined number of satellites. For instance, difficulties when new satellites have to be incorporated in the system appear. This occurs because traditional infrastructures are neither flexible nor scalable. With the appearance of Future Internet technologies new solutions can be provided to manage large and variable amounts of data on demand. These technologies optimize resources and facilitate the appearance of new applications and services in the traditional Earth Observation (EO) market. The use of Future Internet technologies for the EO sector were validated with the GEO-Cloud experiment, part of the Fed4FIRE FP7 European project. This work presents the final results of the project, in which a constellation of satellites records the whole Earth surface on a daily basis. The satellite imagery is downloaded into a distributed network of ground stations and ingested in a cloud infrastructure, where the data is processed, stored, archived and distributed to the end users. The processing and transfer times inside the cloud, workload of the processors, automatic cataloguing and accessibility through the Internet are evaluated to validate if Future Internet technologies present advantages over traditional methods. Applicability of these technologies is evaluated to provide high added value services. Finally, the advantages of using federated testbeds to carry out large scale, industry driven experiments are analysed evaluating the feasibility of an experiment developed in the European infrastructure Fed4FIRE and its migration to a commercial cloud: SoftLayer, an IBM Company.

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

    PubMed

    Ma, Zhenling; Wu, Xiaoliang; Yan, Li; Xu, Zhenliang

    2017-01-26

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

  10. Analysis of terrain data based on satellite imagery for aviation purposes

    NASA Astrophysics Data System (ADS)

    Eilmus, B.; Heidelmeyer, G.; Klingauf, U.

    2007-10-01

    Due to the regulation of the ICAO (International Civil Aviation Organization), which requires the provision of electronic terrain data with a certain quality by each contracting state for its territory, the demand for terrain data for aviation purposes increases. This regulation poses a problem particularly for developing and newly industrialising countries, which have not the financial resources for the generation of terrain data meeting the required specifications. Studies performed at the Institute of Flight Systems and Automatic Control at the Technische Universitaet Darmstadt show that a promising and cost-effective method to encounter this challenge is the use of high resolution optical satellite imagery with a stereoscopic coverage. This method can be performed without the acquisition of ground control points and leads by this to cost reductions. To validate this method, the accuracy of terrain data generated from satellite imagery is analysed. Due to the various available very high resolution satellites, the accuracy is not limited by the spatial resolution of the imagery, but principally by the accuracy of the geolocation. This is why furthermore methods are proposed that may help to increase the accuracy, to eliminate blunders as well as systematic errors and thus to enhance the reliability of the acquired terrain information in order to achieve applicability in aviation.

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

    PubMed

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

    2014-01-01

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

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

    USGS Publications Warehouse

    Stapleton, Seth P.; LaRue, Michelle A.; Lecomte, Nicolas; Atkinson, Stephen N.; Garshelis, David L.; Porter, Claire; Atwood, Todd C.

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed Central

    Ma, Zhenling; Wu, Xiaoliang; Yan, Li; Xu, Zhenliang

    2017-01-01

    With the development of space technology and the performance of remote sensors, high-resolution satellites are continuously launched by countries around the world. Due to high efficiency, large coverage and not being limited by the spatial regulation, satellite imagery becomes one of the important means to acquire geospatial information. This paper explores geometric processing using satellite imagery without ground control points (GCPs). The outcome of spatial triangulation is introduced for geo-positioning as repeated observation. Results from combining block adjustment with non-oriented new images indicate the feasibility of geometric positioning with the repeated observation. GCPs are a must when high accuracy is demanded in conventional block adjustment; the accuracy of direct georeferencing with repeated observation without GCPs is superior to conventional forward intersection and even approximate to conventional block adjustment with GCPs. The conclusion is drawn that taking the existing oriented imagery as repeated observation enhances the effective utilization of previous spatial triangulation achievement, which makes the breakthrough for repeated observation to improve accuracy by increasing the base-height ratio and redundant observation. Georeferencing tests using data from multiple sensors and platforms with the repeated observation will be carried out in the follow-up research. PMID:28134779

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  16. Large-area rice yield forecasting using satellite imageries

    NASA Astrophysics Data System (ADS)

    Wang, Yi-Ping; Chang, Kuo-Wei; Chen, Rong-Kuen; Lo, Jeng-Chung; Shen, Yuan

    2010-02-01

    Ability to make large-area yield prediction before harvest is important in many aspects of agricultural decision-making. In this study, canopy reflectance band ratios (NIR/RED, NIR/GRN) of paddy rice ( Oryza sativa L.) at booting stage, from field measurements conducted from 1999 to 2005, were correlated with the corresponding yield data to derive regression-type yield prediction models for the first and second season crop, respectively. These yield models were then validated with ground truth measurements conducted in 2007 and 2008 at eight sites, of different soil properties, climatic conditions, and various treatments in cultivars planted and N application rates, using surface reflectance retrieved from atmospherically corrected SPOT imageries. These validation tests indicated that root mean square error of predicting grain yields per unit area by the proposed models were less than 0.7 T ha -1 for both cropping seasons. Since village is the basic unit for national rice yield census statistics in Taiwan, the yield models were further used to forecast average regional yields for 14 selected villages and compared with officially reported data. Results indicate that the average yield per unit area at village scale can be forecasted with a root mean square error of 1.1 T ha -1 provided no damaging weather occurred during the final month before actual harvest. The methodology can be applied to other optical sensors with similar spectral bands in the visible/near-infrared and to different geographical regions provided that the relation between yield and spectral index is established.

  17. Detection of Neolithic Settlements in Thessaly (Greece) Through Multispectral and Hyperspectral Satellite Imagery

    PubMed Central

    Alexakis, Dimitrios; Sarris, Apostolos; Astaras, Theodoros; Albanakis, Konstantinos

    2009-01-01

    Thessaly is a low relief region in Greece where hundreds of Neolithic settlements/tells called magoules were established from the Early Neolithic period until the Bronze Age (6,000 – 3,000 BC). Multi-sensor remote sensing was applied to the study area in order to evaluate its potential to detect Neolithic settlements. Hundreds of sites were geo-referenced through systematic GPS surveying throughout the region. Data from four primary sensors were used, namely Landsat ETM, ASTER, EO1 - HYPERION and IKONOS. A range of image processing techniques were originally applied to the hyperspectral imagery in order to detect the settlements and validate the results of GPS surveying. Although specific difficulties were encountered in the automatic classification of archaeological features composed by a similar parent material with the surrounding landscape, the results of the research suggested a different response of each sensor to the detection of the Neolithic settlements, according to their spectral and spatial resolution. PMID:22399961

  18. Landsat: a global land-imaging mission

    USGS Publications Warehouse

    ,

    2012-01-01

    Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.

  19. Landsat: A Global Land-Imaging Project

    USGS Publications Warehouse

    Headley, Rachel

    2010-01-01

    Across nearly four decades since 1972, Landsat satellites continuously have acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space; consequently, NASA develops remote-sensing instruments and spacecraft, then launches and validates the satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground-data reception, archiving, product generation, and distribution. The result of this program is a visible, long-term record of natural and human-induced changes on the global landscape.

  20. Landsat: A global land-imaging mission

    USGS Publications Warehouse

    ,

    2012-01-01

    Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.