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. Study of the Nevada Test Site using Landsat satellite imagery

    SciTech Connect

    Zimmerman, P.D.

    1993-07-01

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

  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. 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

    ... Landsat Satellite Imagery AGENCY: United States Geological Survey (USGS), Interior. ACTION: Notice.... Geological Survey, 2150-C Centre Avenue, Fort Collins, CO 80526 (mail); (970) 226- 9230 (fax); or pponds@usgs... telephone at (970) 226-9133. ] SUPPLEMENTARY INFORMATION: I. Abstract In 2008, the USGS's Land...

  7. 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...

  8. 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.

  9. Landsat imagery: a unique resource

    USGS Publications Warehouse

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

    2011-01-01

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

  10. 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.

  11. 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.

  12. 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

  13. A new method to determine eroded areas in arid environment using Landsat satellite imagery

    NASA Astrophysics Data System (ADS)

    A, Aydda; Ah, Algouti; Ab, Algouti; M, Essemani; Y, Taghya

    2014-06-01

    Erosion (by water or wind) is an increasing problem for many local authorities and government agencies throughout the world. The identification of eroded areas in arid and humid regions can be very useful for environmental planning and can help reduce soil and sediment degradation in these regions. In this work we present a new method to determine eroded areas in arid environment. In this method were explored lithological data to determine eroded areas. These data were collected in the field using GPS (Global Positioning System) checkpoints and geological maps. For that, two lithological maps of the study areas were analysed to determine lithological data change. Those two maps were obtained from the classification algorithm by applying the maximum likelihood on two Landsat satellite images. After images classification and validation a change detection technique was adopted to determine eroded areas. This method was applied in northern part of Atlantic Sahara desert to confirm their potentiality.

  14. 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).

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. High spatial resolution mapping of malaria transmission risk in the Gambia, west Africa, using LANDSAT TM satellite imagery.

    PubMed

    Bøgh, Claus; Lindsay, Steven W; Clarke, Siân E; Dean, Andy; Jawara, Musa; Pinder, Margaret; Thomas, Christopher J

    2007-05-01

    Understanding local variability in malaria transmission risk is critically important when designing intervention or vaccine trials. Using a combination of field data, satellite image analysis, and GIS modeling, we developed a high-resolution map of malaria entomological inoculation rates (EIR) in The Gambia, West Africa. The analyses are based on the variation in exposure to malaria parasites experienced in 48 villages in 1996 and 21 villages in 1997. The entomological inoculation rate (EIR) varied from 0 to 166 infective bites per person per rainy season. Detailed field surveys identified the major Anopheles gambiae s.l. breeding habitats. These habitats were mapped by classification of a LANDSAT TM satellite image with an overall accuracy of 85%. Village EIRs decreased as a power function based on the breeding areas size and proximity. We use this relationship and the breeding habitats to map the variation in EIR over the entire 2500-km(2) study area.

  2. Water quality mapping using Landsat TM imagery

    NASA Astrophysics Data System (ADS)

    Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Alias, A. N.; Wong, C. J.; Mustapha-Rosli, M. R.; Mohd Saleh, N.

    2009-05-01

    Environmental monitoring through the method of traditional ship sampling is time consuming and requires a high survey cost. The objective of this study is to evaluate the feasibility of Landsat TM imagery for total suspended solids (TSS) mapping using a newly developed algorithm over Penang Island. The study area is the seawater region around Penang Island, Malaysia. Water samples were collected during a 3-hour period simultaneously with the satellite image acquisition and later analyzed in the laboratory above the study area. The samples locations were determined using a handheld GPS. The satellite image was geometrically corrected using the second order polynomial transformation. The satellite image also was atmospheric corrected by using ATCOR2 image processing software. The digital numbers for each band corresponding to the sea-truth locations were extracted and then converted into reflectance values for calibration of the water quality algorithm. The proposed algorithm is based on the reflectance model that is a function of the inherent optical properties of water, which can be related to its constituent's concentrations. The generated algorithm was developed for three visible wavelenghts, red, green and blue for this study. Results indicate that the proposed developed algorithm was superior based on the correlation coefficient (R) and root-mean-square deviation (RMS) values. Finally the proposed algorithm was used for TSS mapping at Penang Island, Malaysia. The generated TSS map was colour-coded for visual interpretation and image smoothing was performed on the map to remove random noise. This preliminary study has produced a promising result. This study indicates that the empirical algorithm is suitable for TSS mapping around Penang Island by using satellite Landsat TM data.

  3. 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.

  4. 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.

  5. 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).

  6. 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.

  7. 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

  8. 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) satellite-data 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

  9. Eliminating Topographic Illumination Effects from Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Gale, J.; Small, C.

    2013-12-01

    The solar illumination across a single satellite image is variable due to tree cover, slope, aspect and flux density. This makes it difficult to discern differences in land cover. In order to extract different land cover types from multispectral moderate resolution imagery, many techniques (mainly supervised and unsupervised classifications) have been used. These methods often perform adequately, but often must ignore finer resolution phenomena. Supervised classification suffers from this flaw, while unsupervised classification also often detects large differences in solar illumination as different classes. This makes lower flux density vegetation classify differently than illuminated vegetation, even of the same species. Existing topographic correction methods may overcorrect, rely on site-specific empirical terms or require data often unavailable in areas of interest (Kane et al. 2008). We present a new technique to remove topographic illumination effects with available global data and spectral unmixing. It uses a three endmember mixing model of substrate, vegetation, and dark (SVD) on Landsat imagery (Small 2004). The dark fraction is then plotted against a simulated incidence angle image derived from ASTER GDEM data to see the incidence angle-dark fraction space. This technique minimizes the trend between solar illumination values calculated from ASTER GDEM and the SVD dark fraction. This trend is then minimized to the nominal flux density of a level surface. With this minimization, the fraction estimates are reduced on sun-facing slopes and increased on sun-backing slopes. The resulting image can then be used to study variations in land cover without the overprinting of topographic shadow or variations in solar flux.

  10. 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

  11. 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

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

    USGS Publications Warehouse

    Miller, Holly M.

    2016-04-18

    Users were asked how often they needed Landsat imagery to meet various requirements for their primary application. The survey question specifically asked how often users needed usable imagery, which differs from how often they would like the Landsat satellites to acquire an image. Users were asked to identify their needed frequency

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  14. 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.

  15. 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. PMID:27510986

  16. 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

  17. 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.

  18. 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.

  19. Barrier Island Shorelines Extracted from Landsat Imagery

    USGS Publications Warehouse

    Guy, Kristy K.

    2015-01-01

    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.

  20. 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. ?? 2003 Elsevier B.V. All rights reserved.

  1. Digital techniques for processing Landsat imagery

    NASA Technical Reports Server (NTRS)

    Green, W. B.

    1978-01-01

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

  2. 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

  3. 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.

  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 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.

  6. 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).

  7. 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.

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

    NASA Technical Reports Server (NTRS)

    1975-01-01

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

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

    NASA Technical Reports Server (NTRS)

    1976-01-01

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

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

    NASA Technical Reports Server (NTRS)

    1976-01-01

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

  11. FINDINGS ON THE USE OF LANDSAT-3 RETURN BEAM VIDICON IMAGERY FOR DETECTING LAND USE AND LAND COVER CHANGES.

    USGS Publications Warehouse

    Milazzo, Valerie A.

    1983-01-01

    The spatial resolution of imagery from the return beam vidicon (RBV) camera aboard the Landsat-3 satellite suggested that such data might prove useful in inspecting land use and land cover maps. In this study, a 1972 land use and land cover map derived from aerial photographs is compared with a 1978 Landsat RBV image to delineate areas of change. Findings indicate RBV imagery useful in establishing the fact of change and in identifying gross category changes.

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

    USGS Publications Warehouse

    Serbina, Larisa O.; Miller, Holly M.

    2014-01-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

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

    NASA Technical Reports Server (NTRS)

    1977-01-01

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

  19. 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...

  20. Calibration, Compositing, and Classification of Landsat Datasets and High-Resolution Imagery in Arctic Alaska

    NASA Astrophysics Data System (ADS)

    Macander, M. J.; Frost, G. V., Jr.

    2014-12-01

    Providing calibrated, cloud-free, and phenologically consistent satellite basemaps at moderate (~30 m) and high resolution (≤2 m) is critical to the mapping of arctic tundra vegetation and landscape attributes across large study areas. We obtained ground cover (n = 107) and field spectra (n = 28) data for tundra vegetation across a network of field plots in a ~100,000 km2 study area spanning the foothills and coastal plain ecoregions of Alaska's North Slope. Calibration and atmospheric correction of Landsat TM, ETM+ and OLI, WorldView-2, and GeoEye-1 imagery were performed and we compared results across sensors and with ground spectra. For the Landsat imagery, we produced consistent basemaps using compositing approaches that focused on capturing central tendencies from multiple years of imagery within narrow phenological windows (e.g., green-up, peak growth, fall senescence). We leveraged information from the full 1985-2014 time series to optimize compositing year ranges to prevent bias due to directional changes (e.g., shrubification), and "step-changes" (e.g., tundra fire, lake drainage, ice-wedge degradation) in vegetation and landscape characteristics over the Landsat era. Finally, we explored automated classification of the calibrated Landsat and high-resolution imagery using the spectral rule-based classifier Satellite Image Automatic Mapper (SIAM).

  1. Feasibility of sea ice typing with synthetic aperture radar (SAR): Merging of Landsat thematic mapper and ERS 1 SAR satellite imagery

    NASA Technical Reports Server (NTRS)

    Steffen, Konrad; Heinrichs, John

    1994-01-01

    Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and Landsat thematic mapper (TM) images were acquired for the same area in the Beaufort Sea, April 16 and 18, 1992. The two image pairs were colocated to the same grid (25-m resolution), and a supervised ice type classification was performed on the TM images in order to classify ice free, nilas, gray ice, gray-white ice, thin first-year ice, medium and thick first-year ice, and old ice. Comparison of the collocated SAR pixels showed that ice-free areas can only be classified under calm wind conditions (less than 3 m/s) and for surface winds greater than 10 m/s based on the backscattering coefficient alone. This is true for pack ice regions during the cold months of the year where ice-free areas are spatially limited and where the capillary waves that cause SAR backscatter are dampened by entrained ice crystals. For nilas, two distinct backscatter classes were found at -17 dB and at -10 dB. The higher backscattering coefficient is attributed to the presence of frost flowers on light nilas. Gray and gray-white ice have a backscatter signature similar to first-year ice and therefore cannot be distinguished by SAR alone. First-year and old ice can be clearly separated based on their backscattering coefficient. The performance of the Geophysical Processor System ice classifier was tested against the Landsat derived ice products. It was found that smooth first-year ice and rough first-year ice were not significantly different in the backscatter domain. Ice concentration estimates based on ERS 1 C band SAR showed an error range of 5 to 8% for high ice concentration regions, mainly due to misclassified ice-free and smooth first-year ice areas. This error is expected to increase for areas of lower ice concentration. The combination of C band SAR and TM channels 2, 4, and 6 resulted in ice typing performance with an estimated accuracy of 90% for all seven ice classes.

  2. Applications of Landsat imagery to a coastal inlet stability study

    NASA Technical Reports Server (NTRS)

    Wang, Y.-H.

    1981-01-01

    Polcyn and Lyzenga (1975) and Middleton and Barber (1976) have demonstrated that it is possible to correlate the radiance values of a multispectral imagery, such as Landsat imagery, with the depth related information. The present study is one more example of such an effort. Two sets of Landsat magnetic tape were obtained and displayed on the screen of an Image-100 computer. Spectral analysis was performed to produce various signatures, their extent, and location. Subsequent ground truth observations and measurements were gathered by means of hydrographic surveys and low altitude aerial photographs for interpretation and calibration of the Landsat data. Finally, a coastal engineering assessment based on the Landsat data was made. Recommendations regarding the navigational canal alignment and dredging practice are presented in the light of inlet stability.

  3. 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...

  4. 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)

  5. 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.

  6. Satellite imagery of the earth

    USGS Publications Warehouse

    Merifield, P.M.; Cronin, J.; Foshee, L.L.; Gawarecki, S.J.; Neal, J.T.; Stevenson, R.E.; Stone, R.O.; Williams, R.S., Jr.

    1969-01-01

    Photography of the Earth from spacecraft has application to both atmospheric and Earth sciences. Gemini and Apollo photographs have furnished information on sea surface roughness, areas of potential upwelling and oceanic current systems. Regional geologic structures and geomorphologic features are also recorded in orbital photographs. Infrared satellite imagery provides meteorological and hydrological data and is potentially useful for locating fresh water springs along coastal areas, sources of geothermal power and volcanic activity. Ground and airborne surveys are being undertaken to create a basis for the interpretation of data obtained from future satellite systems.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Satellite imagery and discourses of transparency

    NASA Astrophysics Data System (ADS)

    Harris, Chad Vincent

    In the last decade there has been a dramatic increase in satellite imagery available in the commercial marketplace and to the public in general. Satellite imagery systems and imagery archives, a knowledge domain formally monopolized by nation states, have become available to the public, both from declassified intelligence data and from fully integrated commercial vendors who create and market imagery data. Some of these firms have recently launched their own satellite imagery systems and created rather large imagery "architectures" that threaten to rival military reconnaissance systems. The increasing resolution of the imagery and the growing expertise of software and imagery interpretation developers has engendered a public discourse about the potentials for increased transparency in national and global affairs. However, transparency is an attribute of satellite remote sensing and imagery production that is taken for granted in the debate surrounding the growing public availability of high-resolution satellite imagery. This paper examines remote sensing and military photo reconnaissance imagery technology and the production of satellite imagery in the interests of contemplating the complex connections between imagery satellites, historically situated discourses about democratic and global transparency, and the formation and maintenance of nation state systems. Broader historical connections will also be explored between satellite imagery and the history of the use of cartographic and geospatial technologies in the formation and administrative control of nation states and in the discursive formulation of national identity. Attention will be on the technology itself as a powerful social actor through its connection to both national sovereignty and transcendent notions of scientific objectivity. The issues of the paper will be explored through a close look at aerial photography and satellite imagery both as communicative tools of power and as culturally relevant

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Spatial reasoning to determine stream network from LANDSAT imagery

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  4. Integration of radar and Landsat imagery for structural analysis

    SciTech Connect

    Dodge, R.L.

    1986-05-01

    Radar imagery contains information on texture, structural orientation, and topography that augments data interpretable from Landsat Multispectral Scanner and Thematic Mapper data. Integrating data available from these two remote-sensing systems results in a more complete interpretation of surface features related to subsurface structures. Examples of improved interpretation emphasize the importance of radar's variable illumination azimuth for recognizing structural trends in addition to those seen on Landsat data. Also, textural detail and increased resolution from radar imagery improve the interpretability of fracture patterns and fracture density, and high resolution and variable illumination angle enhance topographic detail and recognition of structurally controlled topography. Tonal variations in the visible-near infrared, seen on Landsat data, can be related to fracture density, structurally controlled soil moisture conditions, and structurally controlled topography. Integrating the surface expression of structural features on the two types of data results in better maps of the surface expression of subsurface structures. Examples presented illustrate applications of such integrated analysis. Data from Landsat and radar sensors can be integrated visually, during the interpretation process, or digitally. Both approaches have advantages; visual integration is more practical for regional analysis, and digital integration can be applied in high-graded areas.

  5. 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.

  6. Open quarry monitoring using gap-filled LANDSAT 7 ETM SLC-OFF imagery

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.; Raptis, Ilias

    2014-10-01

    Open quarries are at the same time a necessity but also a source of pollution. Necessity as they supply the necessary fuel for energy production and source of pollution as they affect biodiversity, vegetation cover and threaten water resources. The objective of this work is to indicate a monitoring methodology using Landsat ETM SLC off imagery. On May 31, 2003, the Scan Line Corrector (SLC), which compensates for the forward motion of Landsat 7, failed. Without an operating SLC, the Enhanced Thematic Mapper Plus (ETM+) line of sight now traces a zig-zag pattern along the satellite ground track. As a result, imaged area is duplicated, with width that increases towards the scene edge. An estimated twenty-two percent of any given scene is lost because of the SLC failure. The maximum width of the data gaps along the edge of the image would be equivalent to one full scan line, or approximately 390 to 450 meters. The precise location of the missing scan lines will vary from scene to scene. In this study a gap filling technique for Landsat ETM SLC off imagery is evaluated. Different Landsat 7 ETM+ images SLC off were restored and then compared to historical data and data from other sensors. The restored images have been used in order to monitor the expansion of an open quarry in western Peloponnese and the results are presented.

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  10. Development of Bayesian-based transformation method of Landsat imagery into pseudo-hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Hoang, Nguyen Tien; Koike, Katsuaki

    2015-10-01

    It has been generally accepted that hyperspectral remote sensing is more effective and provides greater accuracy than multispectral remote sensing in many application fields. EO-1 Hyperion, a representative hyperspectral sensor, has much more spectral bands, while Landsat data has much wider image scene and longer continuous space-based record of Earth's land. This study aims to develop a new method, Pseudo-Hyperspectral Image Synthesis Algorithm (PHISA), to transform Landsat imagery into pseudo hyperspectral imagery using the correlation between Landsat and EO-1 Hyperion data. At first Hyperion scene was precisely pre-processed and co-registered to Landsat scene, and both data were corrected for atmospheric effects. Bayesian model averaging method (BMA) was applied to select the best model from a class of several possible models. Subsequently, this best model is utilized to calculate pseudo-hyperspectral data by R programming. Based on the selection results by BMA, we transform Landsat imagery into 155 bands of pseudo-hyperspectral imagery. Most models have multiple R-squared values higher than 90%, which assures high accuracy of the models. There are no significant differences visually between the pseudo- and original data. Most bands have Pearson's coefficients < 0.95, and only a small fraction has the coefficients < 0.93 like outliers in the data sets. In a similar manner, most Root Mean Square Error values are considerably low, smaller than 0.014. These observations strongly support that the proposed PHISA is valid for transforming Landsat data into pseudo-hyperspectral data from the outlook of statistics.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  12. 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.

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

    PubMed

    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.

  14. 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

  15. Estimation of urban surface emissivity based on sub-pixel classification of Landsat8 imagery

    NASA Astrophysics Data System (ADS)

    Orolmaa, E.; Tuya, S.; Tugjsuren, N.; Batbayar, J.

    2015-09-01

    Information about the spatial distribution of urban surface emissivity is essential for surface temperature estimation. The latter is critical in many applications, such as estimation of surface sensible and latent heat fluxes, energy budget, urban canopy modeling, bio-climatic studies and urban planning. This study proposes an estimation of urban surface emissivity, which is primarily based on spectral mixture analysis. The urban surface is assumed to consist of three fundamental land cover components, namely vegetation, impervious and soil that refer to the urban environment. Due to the complexity of the urban environment, the impervious component is further divided into two land cover components: high-albedo and low-albedo impervious. Emissivity values are assigned to each component based on emissivity distributions derived from the Landsat8. Following the proposed method, by combining the fraction of each cover component with a respective emissivity value, an overall emissivity for a given pixel is estimated. The methodology is applicable to visible and near infrared satellite imagery. Therefore it could be used to derive emissivity maps from most multispectral satellite sensors. The proposed approach was applied to Landsat8 multispectral data for the city of Darkhan-Uul, Mongolia. Emissivity, as well as land surface temperature maps in the spectral region of 10.6 - 11.2 μm (Landsat8 band 10) and 11.5-12.5 (Landsat8 band 11) were derived.

  16. Pollution solution. From the Landsat -- a satellite for all seasons

    SciTech Connect

    1994-12-31

    The video shows how Landsat`s remote sensing capabilities can aid in resolving environmental quality problems. The satellite can locate and monitor strip mining operations to facilitate land reclamation programs. The satellite helps solve some meteorological mysteries by taking the path of airborne pollution. It can also monitor the course of industrial wastes and garbage dumped into lakes, rivers, and coastal areas.

  17. 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.

  18. 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.

  19. Techniques for land use change detection using Landsat imagery

    NASA Technical Reports Server (NTRS)

    Angelici, G. L.; Bryant, N. A.; Friedman, S. Z.

    1977-01-01

    A variety of procedures were developed for the delineation of areas of land use change using Landsat Multispectral Scanner data and the generation of statistics revealing the nature of the changes involved (i.e., number of acres changed from rural to urban). Techniques of the Image Based Information System were utilized in all stages of the procedure, from logging the Landsat data and registering two frames of imagery, to extracting the changed areas and printing tabulations of land use change in acres. Two alternative methods of delineating land use change are presented while enumerating the steps of the entire process. The Houston, Texas urban area, and the Orlando, Florida urban area, are used as illustrative examples of various procedures.

  20. Quick-look satellite imagery for Alaska: A tool for environmental monitoring

    SciTech Connect

    George, T.; Reynolds, G.; Dean, K.; Miller, J.

    1992-03-01

    Satellite imagery is a valuable tool for environmental monitoring of natural and man-made events. Analysis of imagery within a few hours is vital if these data are to be used to respond to rapidly changing conditions. Since April of 1982 Landsat imagery from the Quick-Look Project at the Geophysical Institute has been available for real-time applications. The system provides near real-time Landsat MSS imagery for applications including monitoring flood hazards, sea ice motion, forest fires and agricultural development. In the 1990s additional satellites with new sensors are being launched which will provide more opportunities for near real-time use. To take advantage of the sensors, additional facilities are needed to receive, process and deliver the data in a timely fashion. Candidate sensors and spacecraft include Enhanced Thematic Mapper (ETM) on Landsat-6; Advanced Very High Resolution Radiometer (AVHRR) on the NOAA polar orbiting satellites; SPOT; Japan's Meteorological Observation Satellite (MOS); OPS (Optical Sensor) on the Japanese Earth Resources Satellite-1 (JERS-1) and the Advanced Earth Observing Satellite (ADEOS). Ongoing projects, such as the Alaska SAR Facility, can provide some components of a multiple satellite receiving system. Such a capability will provide a valuable source of data to study global change in the Arctic. The authors will describe the capabilities required to use satellite data for environmental monitoring

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Estimating alluvial fan surface ages using Landsat 8 multispectral imagery

    NASA Astrophysics Data System (ADS)

    D'Arcy, Mitch; Mason, Philippa J.; Whittaker, Alexander C.; Roda Boluda, Duna C.

    2015-04-01

    Accurate exposure age models are now essential for geomorphological and stratigraphic field research, and generally depend on laboratory analyses such as radiocarbon, cosmogenic nuclide or luminescence approaches. However, these techniques cannot be deployed in situ in the field, meaning other methods are needed to produce a preliminary age model, map depositional surfaces of different ages, and select sampling sites for the types of laboratory analyses outlined above. With the widespread availability of high-resolution multispectral imagery, a promising approach is to use remotely sensed data to discriminate depositional surfaces with different ages. Here, we use new Landsat 8 Operational Land Imager (OLI) multispectral imagery to characterise the reflectance of 35 alluvial fan surfaces in the semi-arid Owens Valley, California. These surfaces have been mapped in detail in the field, have similar granitic compositions, and have well-constrained exposure ages ranging from modern to ~ 125 ka, measured using a high density of 10-Be cosmogenic nuclide samples. We identify a clear age signal recorded in the spectral properties of these surfaces. With increasing exposure age, there is a predictable redshift effect in the reflectance of the surfaces across the visible and short-wave infrared spectrum. Simple calculations, such as the brightness ratio of red/blue wavelengths, produce sensitive power law relationships with exposure age for at least 125 ka, meaning Landsat 8 imagery can be used to estimate surface exposure age remotely, at least in this calibrated dryland location. The ability to remotely sense exposure age has useful implications for field mapping, selecting suitable sampling sites for laboratory-based exposure age techniques, and correlating existing age constraints to previously un-sampled surfaces. We present the uncertainties associated with this spectral approach to exposure dating, evaluate its likely physical origins, and discuss its applicability

  6. Long-term Landsat 5 and 7 Reflectance Inconsistencies Caused by Landsat Satellite Orbit Drifts

    NASA Astrophysics Data System (ADS)

    Zhang, H.; Roy, D. P.

    2015-12-01

    Keywords: Landsat, long term data record, orbit drift The Landsat satellite series provide the longest temporal record of space-based earth observations and, with their free data availability, the systematic generation of consistent Landsat time series products has been advocated. The Landsat 5 and 7 satellites were launched into nominally the same orbits but temporally sparse station keeping maneuvers meant that their orbits drifted over the satellite mission lives with local crossing times varying differently between sensors and by up to 0.92 hours (Landsat 5 1982 to 2012) and 0.21 hours (Landsat 7 1999 to 2012). Consequently, their images were acquired with temporally variable solar zenith angles. Long-term Landsat 5 and 7 reflectance inconsistencies may be introduced by orbit drift induced solar zenith variations combined with surface reflectance anisotropy. The majority of terrestrial surfaces reflect optical wavelength radiation anisotropically with a directional dependence that varies as a function of the sun-target-sensor geometry, commonly described by the Bi-directional Reflectance Distribution Function (BRDF). This study quantifies the overpass time and observed solar zenith angles for all the Landsat 5 and 7 images available in the Landsat archive along an approximately north-south Landsat path over the Conterminous United States. The impact of observed solar zenith angle variations on red and near-infrared nadir view reflectance and on the derived normalized difference vegetation index (NDVI) with respect to different Moderate-Resolution Imaging Spectroradiometer (MODIS) BRDF land cover types is modelled. Results show that the 31 year Landsat 5 solar zenith variations and the 14 year relative Landsat 5 and 7 solar zenith differences vary latitudinally (up to 10º and 4º respectively) and impose small but significant reflectance and NDVI variations that should be minimized before long-term time series application.

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

    NASA Technical Reports Server (NTRS)

    Anderson, J. H. (Principal Investigator)

    1976-01-01

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

  8. Study of atmospheric diffusion from the LANDSAT imagery

    SciTech Connect

    Viswanadham, Y.; Torsani, J.A.

    1982-11-20

    Detailed analyses of the LANDSAT multispectral scanner (MSS) data of the smoke plumes that originated in eastern Cabo Frio (22/sup 0/ 59'S; 42/sup 0/ 02'W) and crossed over into the Atlantic ocean are presented 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. Conventional interpretation techniques are applied to analyze the images with a view to arrive at certain plume characteristics. The analysis of the visible smoke plumes revealed that the plume was 130 km long and attained a maximum width of 937 m, 10 km away from the chimney emitting the effluent. 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 two empirical methods for determining the horizontal eddy diffusivity coefficient (K/sub y/) in the Gaussian plume formula was evaluated with the estimated standard deviation of the crosswind distribution of material in the plume (sigma/sub y/) from the LANDSAT imagery. Most consistent estimates for K/sub y/ are obtained from the formula based on Taylor's theory of 'diffusion by continuous moment.' K/sub y/ values of about 158 m/sup 2/ ..sigma..)/sup 1/ in quasi-neutral conditions and 49 m/sup 2/ s/sup -1/ in stable conditions are obtained from a plot of sigma/sup 2//sub y/ as a function of distance from the source. The rate of kinetic energy dissipation (epsilon) is evaluated from the diffusion parameters sigma/sub y/ and K/sub y/. The epsilon value ranges from 0.1 x 10/sup -5/ m/sup 2/ s/sup -3/ to 80.2 x 10/sup -5/ m/sup 2/ s/sup -3/ in quasi-neutral and stable stratifications.

  9. 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.

  10. 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.

  11. 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.   

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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.

  7. 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.

  8. Land cover data from Landsat single-date archive imagery: an integrated classification approach

    NASA Astrophysics Data System (ADS)

    Bajocco, Sofia; Ceccarelli, Tomaso; Rinaldo, Simone; De Angelis, Antonella; Salvati, Luca; Perini, Luigi

    2012-10-01

    The analysis of land cover dynamics provides insight into many environmental problems. However, there are few data sources which can be used to derive consistent time series, remote sensing being one of the most valuable ones. Due to their multi-temporal and spatial coverage needs, such analysis is usually based on large land cover datasets, which requires automated, objective and repeatable procedures. The USGS Landsat archives provide free access to multispectral, high-resolution remotely sensed data starting from the mid-eighties; in many cases, however, only single date images are available. This paper suggests an objective approach for generating land cover information from 30m resolution and single date Landsat archive satellite imagery. A procedure was developed integrating pixel-based and object-oriented classifiers, which consists of the following basic steps: i) pre-processing of the satellite image, including radiance and reflectance calibration, texture analysis and derivation of vegetation indices, ii) segmentation of the pre-processed image, iii) its classification integrating both radiometric and textural properties. The integrated procedure was tested for an area in Sardinia Region, Italy, and compared with a purely pixel-based one. Results demonstrated that a better overall accuracy, evaluated against the available land cover cartography, was obtained with the integrated (86%) compared to the pixel-based classification (68%) at the first CORINE Land Cover level. The proposed methodology needs to be further tested for evaluating its trasferability in time (constructing comparable land cover time series) and space (for covering larger areas).

  9. 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 ...

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

    NASA Technical Reports Server (NTRS)

    Blair, R. W., Jr.

    1981-01-01

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

  11. Geological interpretation of Landsat TM imagery and aeromagnetic survey data, northern Precordillera region, Argentina

    NASA Astrophysics Data System (ADS)

    Chernicoff, C. J.; Nash, C. R.

    2002-03-01

    This case study demonstrates a methodology for obtaining maximum geoscientific value from reconnaissance (1000 m line spacing) aeromagnetic data through integration with high-resolution satellite imagery. In this study, lithostratigraphic interpretation of optimally processed Landsat TM data at reconnaissance mapping scale (1:100,000) has been carried out as a precursor to geophysical interpretation, providing the basic 'framework' in which to view the imaged geophysical data. The Landsat-derived framework shows the correct positions and vergences of major structures, which characterize this part of the Andean foreland thrust-and-fold belt. Within the structural framework derived from satellite imagery, the locations of major shallow-source aeromagnetic anomalies related to intermediate/mafic extrusive and subvolcanic rocks and the controlling structures of these economically important magmatic events can be correctly interpreted. Results of the study indicate a significant, coherent, and previously unrecognized post-Permian, pre-Miocene volcanic/subvolcanic center, which is probably associated with regional sinistral strike-slip along a reactivated N-S accretionary suture and a pre-existing Precambrian/Paleozoic basement structure. Subsequent west-vergent thick-skinned thrusting associated with uplift of Sierra Valle Fertil Precambrian block has developed a set of distinctive NW-oriented strike-slip faults at the site of the volcanic center. The NW structures cut and rotate late Miocene thin-skinned structures associated with the Precordillera fold-and-thrust belt. Intrusive rocks associated with the inferred Oligocene volcanic center form easily recognizable, partially remanent dipole anomalies, are associated with alteration and Au mineralization (Cerro Guachi, El Pescado, Gnrl. Belgrano mines), and are located along NW-oriented sinistral splay faults. The strike-slip related tectonic/magmatic event is currently regarded as Oligocene in age and may correlate

  12. 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.

  13. 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.

  14. 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...

  15. Lineament extraction and analysis, comparison of LANDSAT ETM and ASTER imagery. Case study: Suoimuoi tropical karst catchment, Vietnam

    NASA Astrophysics Data System (ADS)

    Hung, L. Q.; Batelaan, O.; De Smedt, F.

    2005-10-01

    Vast areas of the world consist of hard rocks (basement complexes), where water is restricted to secondary permeability, and thus to the fractures and the weathered zones. As the success ratio of drilling in hard rock terrain may be low, and the use of geophysics is often judged as too expensive, the study of lineaments from remote sensed imagery offers an attractive alternative analysis technique. High production areas in hard-rock aquifers are generally associated with conductive fracture zones. An effective approach for delineation of fracture zones is based on lineament indices extracted from satellite imagery. Together with a detailed structural analysis and understanding of the tectonic evolution of a given area it provides useful information for geological mapping and understanding of groundwater flow and occurrence in fractured rocks. The accuracy of extracted lineaments depends strongly on the spatial resolution of the imagery, higher resolution imagery result in a higher quality of lineament map. The ASTER sensor provides imagery with a higher resolution (15m) than the LANDSAT sensor (30m). It is tested and shown here that extracted lineaments from the VNIR ASTER imagery are considerably less noisy and show a higher accuracy than lineaments extracted from other imagery.

  16. Assessing ground water development potential using landsat imagery.

    PubMed

    Mutiti, Samuel; Levy, Jonathan; Mutiti, Christine; Gaturu, Ndung'u S

    2010-01-01

    Seven villages in southeastern Kenya surround Mt. Kasigau and depend on the mountain's cloud forest for their water supply. Five of these villages have regularly experienced water shortages, and all village water supplies were contaminated with Escherichia coli bacteria. There is a need to economically find new sources of fresh ground water. Remote sensing offers a relatively quick and cost-effective way of identifying areas with high potential for ground water development. This study used spectral properties of features on Landsat remote sensing imagery to map linear features, soil types, surface moisture, and vegetation. Linear features represented geologic or geomorphologic features indicating either shallow ground water or areas of increased subsurface hydraulic conductivity. Regarding soil type, black soils were identified as potential indicators of shallow aquifers based on their relatively lower elevation and association with river valleys. A vegetation map was created using unsupervised classification, and three of the resulting vegetation classes were observed to be commonly associated with wet areas and/or ground water discharge. A wetness map, created using tasseled cap analysis, was used to identify all areas of high ground moisture, including those that corresponded to vegetated areas. The linear features, soil type, vegetation, and wetness maps were overlaid to produce a composite that highlighted areas with the highest potential for ground water development. Electrical resistivity surveys confirmed that areas highlighted by the composite image had relatively shallow depths to the water table. Some figures in this paper are available in color in the online version of the paper. PMID:19210559

  17. 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.

  18. 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.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Bayat, F.; Hasanlou, M.

    2016-06-01

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

  1. 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.

  2. 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.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Li, J.; Sheng, Y.

    2009-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  6. 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.

  7. 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

  8. 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.

  9. 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.

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

    PubMed

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

    2002-10-01

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

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

    NASA Technical Reports Server (NTRS)

    Lusch, D. P.

    1981-01-01

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

  12. The use of LANDSAT DCS and imagery in reservoir management and operation

    NASA Technical Reports Server (NTRS)

    Cooper, S.; Bock, P.; Horowitz, J.; Foran, D.

    1975-01-01

    Experiments by the New England Division (NED), Corps of Engineers with LANDSAT-1 data collection and imaging systems are reported. Data cover the future usefulness of data products received from satellites such as LANDSAT in the day to day operation of NED water resources systems used to control floods.

  13. 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

  14. 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.

  15. 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.

  16. Peatland classification of West Siberia based on Landsat imagery

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  17. 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.

  18. 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

  19. 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

  20. Annual dynamics of impervious surface in the Pearl River Delta, China, from 1988 to 2013, using time series Landsat imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Lei; Weng, Qihao

    2016-03-01

    Information on impervious surface distribution and dynamics is useful for understanding urbanization and its impacts on hydrological cycle, water management, surface energy balances, urban heat island, and biodiversity. Numerous methods have been developed and successfully applied to estimate impervious surfaces. Previous methods of impervious surface estimation mainly focused on the spectral differences between impervious surfaces and other land covers. Moreover, the accuracy of estimation from single or multi-temporal images was often limited by the mixed pixel problem in coarse- or medium-resolution imagery or by the intra-class spectral variability problem in high resolution imagery. Time series satellite imagery provides potential to resolve the above problems as well as the spectral confusion with similar surface characteristics due to phenological change, inter-annual climatic variability, and long-term changes of vegetation. Since Landsat time series has a long record with an effective spatial resolution, this study aimed at estimating and mapping impervious surfaces by analyzing temporal spectral differences between impervious and pervious surfaces that were extracted from dense time series Landsat imagery. Specifically, this study developed an efficient method to extract annual impervious surfaces from time series Landsat data and applied it to the Pearl River Delta, southern China, from 1988 to 2013. The annual classification accuracy yielded from 71% to 91% for all classes, while the mapping accuracy of impervious surfaces ranged from 80.5% to 94.5%. Furthermore, it is found that the use of more than 50% of Scan Line Corrector (SLC)-off images after 2003 did not substantially reduced annual classification accuracy, which ranged from 78% to 91%. It is also worthy to note that more than 80% of classification accuracies were achieved in both 2002 and 2010 despite of more than 40% of cloud cover detected in these two years. These results suggested that the

  1. Accuracy Comparison of Vhr Systematic-Ortho Satellite Imageries against Vhr Orthorectified Imageries Using Gcp

    NASA Astrophysics Data System (ADS)

    Widyaningrum, E.; Fajari, M.; Octariady, J.

    2016-06-01

    The Very High Resolution (VHR) satellite imageries such us Pleiades, WorldView-2, GeoEye-1 used for precise mapping purpose must be corrected from any distortion to achieve the expected accuracy. Orthorectification is performed to eliminate geometric errors of the VHR satellite imageries. Orthorectification requires main input data such as Digital Elevation Model (DEM) and Ground Control Point (GCP). The VHR systematic-ortho imageries were generated using SRTM 30m DEM without using any GCP data. The accuracy value differences of VHR systematic-ortho imageries and VHR orthorectified imageries using GCP currently is not exactly defined. This study aimed to identified the accuracy comparison of VHR systematic-ortho imageries against orthorectified imageries using GCP. Orthorectified imageries using GCP created by using Rigorous model. Accuracy evaluation is calculated by using several independent check points.

  2. Operational use of LANDSAT imagery for the estimation of snow areal extent

    NASA Technical Reports Server (NTRS)

    Katibah, E. F.

    1975-01-01

    Quantification of the surface area of snow covering watersheds can be a useful parameter in estimating snow water content for inclusion in water runoff prediction equations. An operational manual interpretation technique is described, which allows fast and accurate estimates to be made of the areal extent of snow parameter using LANDSAT-1 imagery. The analysis procedures and the statistical results are presented.

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

    ERIC Educational Resources Information Center

    Harnapp, Vern

    1978-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. 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.

  6. Space based topographic mapping experiment using Seasat synthetic aperture radar and LANDSAT 3 return beam vidicon imagery

    NASA Technical Reports Server (NTRS)

    Mader, G. L.

    1981-01-01

    A technique for producing topographic information is described which is based on same side/same time viewing using a dissimilar combination of radar imagery and photographic images. Common geographic areas viewed from similar space reference locations produce scene elevation displacements in opposite direction and proper use of this characteristic can yield the perspective information necessary for determination of base to height ratios. These base to height ratios can in turn be used to produce a topographic map. A test area covering the Harrisburg, Pennsylvania region was observed by synthetic aperture radar on the Seasat satellite and by return beam vidicon on by the LANDSAT - 3 satellite. The techniques developed for the scaling re-orientation and common registration of the two images are presented along with the topographic determination data. Topographic determination based exclusively on the images content is compared to the map information which is used as a performance calibration base.

  7. Automated Detection of Clouds in Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary

    2010-01-01

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

  8. 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.

  9. 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.

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

    NASA Technical Reports Server (NTRS)

    Lecroy, S. R.

    1982-01-01

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

  11. Objective indicators of pasture degradation from spectral mixture analysis of Landsat imagery

    NASA Astrophysics Data System (ADS)

    Davidson, Eric A.; Asner, Gregory P.; Stone, Thomas A.; Neill, Christopher; Figueiredo, Ricardo O.

    2008-03-01

    Degradation of cattle pastures is a management concern that influences future land use in Amazonia. However, "degradation" is poorly defined and has different meanings for ranchers, ecologists, and policy makers. Here we analyze pasture degradation using objective scalars of photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and exposed soil (S) derived from Landsat imagery. A general, probabilistic spectral mixture model decomposed satellite spectral reflectance measurements into subpixel estimates of PV, NPV, and S covers at ranches in western and eastern Amazonia. Most pasture management units at all ranches fell along a single line of decreasing PV with increasing NPV and S, which could be considered a degradation continuum. The ranch with the highest stocking densities and most intensive management had greater NPV and S than a less intensively managed ranch. The number of liming, herbiciding, and disking treatments applied to each pasture management unit was positively correlated with NPV and negatively correlated with PV. Although these objective scalars revealed signs of degradation, intensive management kept exposed soil to <40% cover and maintained economically viable cattle production over several decades. In ranches with few management inputs, the high PV cover in young pastures declined with increasing pasture age, while NPV and S increased, even where grazing intensity was low. Both highly productive pastures and vigorous regrowth of native vegetation cause high PV values. Analysis of spectral properties holds promise for identifying areas where grazing intensity has exceeded management inputs, thus increasing coverage of senescent foliage and exposed soil.

  12. Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery.

    PubMed

    Li, Jing; Zipper, Carl E; Donovan, Patricia F; Wynne, Randolph H; Oliphant, Adam J

    2015-09-01

    Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA's central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia's >4000-km(2) coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features.

  13. Identifying and inventorying cypress domes in the Florida panhandle using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Calaminus, Andre Kyle

    Cypress domes are swamp ecosystems dominated by pond cypress (Taxodium ascendens), a conifer native to North America. Cypress domes can be found in flatland depressions throughout the southeast United States, hydrologically separated from other water bodies. Threatened by urbanization and land use change, these unique ecosystems have experienced degradation, destruction, and habitat loss over the past few decades. While many domes have been identified in central and southern Florida, literature is lacking on cypress domes found in the Florida panhandle. Cypress domes within the Florida panhandle were located, inventoried, and analyzed for landscape patterns, including size and shape. Additionally, the cypress dome areas were subject to pixel change detection for temporal comparison of dome size from 2000 to 2013. Using satellite imagery from the Landsat 8 spacecraft, support vector machine classification, and publicly available data, a total of 1,568 cypress domes were found to exist in the Florida panhandle, with a mean area of 1.28 hectares, ranging from a minimum of 0.13 ha to a maximum of 4.95 ha, occupying 19.79 km2, or 0.078% of the panhandle study area. A change detection analysis over the 13 year period show a net gain of 284.63 ha in cypress dome growth.

  14. Application of Landsat 8 imagery to regional-scale assessment of lake water quality

    NASA Astrophysics Data System (ADS)

    Andrzej Urbanski, Jacek; Wochna, Agnieszka; Bubak, Iwona; Grzybowski, Waldemar; Lukawska-Matuszewska, Katarzyna; Łącka, Magda; Śliwińska, Sylwia; Wojtasiewicz, Bożena; Zajączkowski, Marek

    2016-09-01

    The aim of the project was to create a tool with which to support regional lake quality assessment using Landsat 8 imagery data. The model of assigning the ecological status was implemented in GIS for the northern part of Poland and classifies lake quality for several classes according to classification of WFD using two basic assumptions. The first is that there exists a combination of OLI bands (OLI2/OLI4 was used) which correlates well with the trophic state of the lakes; the second assumption is that the reference trophic state depends on the mean depth of the lake. The model uses a lake geodatabase which contains lakes outlines, raster masks of lakes and attribute information about their mean depth. There is no need to provide any field data when using this tool, as calibration of the model is done using subsets of lakes which were classified using legally defined methods. The tool allows fast classification of 2800 lakes from the area of interest. The results show good agreement between satellite and expert based methods.

  15. 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.

  16. Using satellite imagery to asses trends in soil and crop productivity across landscapes

    NASA Astrophysics Data System (ADS)

    Sheffield, K.; Morse-McNabb, E.

    2015-07-01

    Measuring different indicators of production and soil health over the long term will help build a picture of soil health and productivity across the landscape. This paper examines the potential contribution of satellite imagery to this area. This investigation undertook a very long time series analysis of Landsat imagery (approximately 40 years) and MODIS imagery (approximately 10 years). Novel datasets and approaches were used to assess areas based on land use history and land cover condition. Spring Normalised Difference Vegetation Index (NDVI), land cover maps based on NDVI thresholds, annual cumulative NDVI and fractional ground cover (FGC) were used to identify trends in vegetation cover change at a landscape scale, and their relationship with factors such as land use intensification history, geomorphology, rainfall, and land use. This work has improved the broad, baseline understanding of production variation across the landscape, while also providing a practical demonstration of the integration of a range of disparate data sources.

  17. Quantifying River Widths of North America from Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  18. Classifying environmentally significant urban land uses with satellite imagery.

    PubMed

    Park, Mi-Hyun; Stenstrom, Michael K

    2008-01-01

    We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads. PMID:17291679

  19. 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.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  2. 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. 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.

  4. 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. PMID:27070424

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  6. 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.

  7. 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.

  8. Reconciling Satellite-Derived Atmospheric Properties with Fine-Resolution Land Imagery: Insights for Atmospheric Correction

    NASA Technical Reports Server (NTRS)

    Zelazowski, Przemyslaw; Sayer, Andrew M.; Thomas, Gareth E; Grainger, Roy G.

    2011-01-01

    This paper investigates to what extent satellite measurements of atmospheric properties can be reconciled with fine-resolution land imagery, in order to improve the estimates of surface reflectance through physically based atmospheric correction. The analysis deals with mountainous area (Landsat scene of Peruvian Amazon/Andes, 72 E and 13 S), where the atmosphere is highly variable. Data from satellite sensors were used for characterization of the key atmospheric constituents: total water vapor (TWV), aerosol optical depth (AOD), and total ozone. Constituent time series revealed the season-dependent mean state of the atmosphere and its variability. Discrepancies between AOD from the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS) highlighted substantial uncertainty of atmospheric aerosol properties. The distribution of TWV and AOD over a Landsat scene was found to be exponentially related to ground elevation (mean R(sup 2) of 0.82 and 0.29, respectively). In consequence, the atmosphere-induced and seasonally varying bias of the top-of-atmosphere signal was also elevation dependent (e.g., mean Normalized Difference Vegetation Index bias at 500 m was 0.06 and at 4000 m was 0.01). We demonstrate that satellite measurements of key atmospheric constituents can be downscaled and gap filled with the proposed "background + anomalies" approach, to allow for a better compatibility with fine-resolution land surface imagery. Older images (i.e., predating the MODIS/ATSR era), without coincident atmospheric data, can be corrected using climatologies derived from time series of satellite retrievals. Averaging such climatologies over space compromises the quality of correction result to a much greater degree than averaging them over time. We conclude that the quality of both recent and older fine-resolution land surface imagery can be improved with satellite-based atmospheric data acquired to date.

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  10. 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.

  11. Mapping the Philippines’ Mangrove Forests Using Landsat Imagery

    PubMed Central

    Long, Jordan B.; 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. PMID:22163779

  12. Mapping the Philippines' mangrove forests using Landsat imagery.

    PubMed

    Long, Jordan B; 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. PMID:22163779

  13. Mapping the Philippines' mangrove forests using Landsat imagery

    USGS Publications Warehouse

    Long, J.B.; Giri, C.

    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. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

  14. 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.

  15. A simple and effective method for detecting and quantifying forest disturbances and regeneration using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Jin, S.; Yang, L.; Danielson, P.; Homer, C.; Fry, J.

    2012-12-01

    Disturbances of any size and magnitude of intensity, whether natural or human-caused, change existing forest conditions and initiate succession to create dynamic and new ecological communities. Effective management of these forest resources, both public and private, requires reliable and timely information about their status and trends. As part of the National Land Cover Database, we have developed a focused change detection method using Landsat imagery to improve the efficiency and effectiveness of existing forest change monitoring capabilities. The Normalized Burn Ratio (NBR) derived from Landsat imagery has been widely used for monitoring fire disturbance, and the Normalized Difference Vegetation Index (NDVI) has been extensively used for indicating the vegetation biomass, or health and vitality status. By integrating these two indices derived from imagery acquired from two-date Landsat images within a growing season, a model was developed to intelligently map the location and quantify the magnitude of forest disturbance and regeneration processes. The model has been tested on four image pairs from different forest regions (Northeast, Southeast, Northwest, and Southwest) of the United States. Initial results showed that the method can map high intensity forest disturbance such as forest harvest and forest fire with high accuracy; it is also sensitive to subtle changes such as forest regeneration, forest commercial thinning, and forest degradation caused by insect damage. The model is simple, effective, and applicable to other regions with forest cover. The approach can provide critical and objective change information on status and trends on forested land for management planning purposes.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  17. 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.

  18. 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).

  19. 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).

  20. 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.

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  8. 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.

  9. Photogrammetric Processing Using ZY-3 Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.

    2015-03-01

    This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are

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

    NASA Astrophysics Data System (ADS)

    Fernandez, Sim Joseph; Milano, Alan

    2016-07-01

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

  11. Exploration applications of satellite imagery in mature basins - A summation

    SciTech Connect

    Berger, Z. )

    1991-08-01

    A series of examples supported by surface and subsurface controls illustrates procedures used to integrate satellite imagery interpretation into a conventional exploration program, and the potential contribution of such an approach to the recognition of new hydrocarbon plays in mature basins. Integrated analysis of satellite imagery data consists of four major steps. The first step focuses on the recognition of style, trend, and timing of deformation of exposed structures located at the basin interior or around its margins. This information is obtained through an integrated analysis of satellite imagery data, stereo aerial photography, surface geological mapping, and field observations. The second step consists of integrating the satellite imagery with gravity and magnetic data to recognize obscured and/or buried structures. The third step involves the analysis of available seismic data which is specifically processes to enhance subtle basement topography in order to determine influences on reservoir quality. In the fourth step, subsurface structure, isopach, show, and pool maps derived from available well information are integrated into the structural interpretation. These four analytical steps are demonstrated with examples form the Powder River basin, Western Canada basin, Paris basin, and Central basin platform of west Texas. In all of these highly mature basins, it is easy to demonstrate that (1) hydrocarbon migration and accumulation was largely controlled by subtle basement structures, and (2) these structures can be detected through the integrated analysis of satellite imagery.

  12. Evaluating lake phytoplanton response to human disturbance and climate change using satellite imagery

    NASA Astrophysics Data System (ADS)

    Novitski, Linda Nicole

    Accurate and cost-effective assessment of water quality is necessary for proper management and restoration of inland water bodies susceptible to algal bloom conditions. Landsat and MODIS satellite images were used to create chlorophyll and Secchi depth predictive models for algal assessment of Great Lakes and other lakes of the United States. Boosted regression tree (BRT) models using satellite imagery are both easy to use and can have high predictive performance. BRT models inferred chlorophyll and Secchi depth more accurately than linear regression models for all study locations. Inferred chlorophyll of inner Saginaw Bay was subsequently used in ecological models to help understand the ecological drivers of algal blooms in this ecosystem. For small lakes (non-Great Lakes), the best national Landsat model for ln-transformed chlorophyll was the BRT model and had a cross-validation R 2 of 0.44 and a 0.76 ln-transformed mug/L RMSE. The best national Landsat model for Secchi depth was also a BRT model that had an adjusted R 2 of 0.52 and a 0.80 m RMSE. We assessed the applicability of the national chlorophyll model for ecological analysis by comparing the total phosphorus- chlorophyll relationship with chlorophyll determined from sampling or remote sensing, which showed the total phosphorus- chlorophyll relationship had an adjusted R2 = 0.58 and 1.02 ln-transformed microg/L RMSE with sampled chlorophyll versus an adjusted R2 = 0.56 and 1.04 ln-transformed mug/L RMSE with chlorophyll determined by the boosted regression tree remote sensing model. For Great Lakes models, the MODIS BRT model predicted chlorophyll most accurately of the three BRT models and compared well to other models in the literature. BRT models for Landsat ETM+ and TM more accurately predicted chlorophyll than the MSS model and all Landsat models had favorable results when compared to the literature. BRT chlorophyll predictive models are useful in helping to understand historical, long

  13. 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.

  14. 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.

  15. 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.

  16. Analysis of the Shoreline Position Extracted from Landsat TM and ETM+ Imagery

    NASA Astrophysics Data System (ADS)

    Sanchez-Garcia, E.; Pardo-Pascual, J. E.; Balaguer-Beser, A.; Almonacid-Caballer, J.

    2015-04-01

    A statistical analysis of the results obtained by the tool SELI (Shoreline Extraction from Landsat Imagery) is made in order to characterise the medium and long term period changes occurring on beaches. The analysis is based on the hypothesis that intraannual shifts of coastline positions hover around an average position, which would be significant when trying to set these medium and long term trends. Fluctuations around this average are understood as the effect of short-term changes -variations related to sea level, wave run-up, and the immediate morphological beach profile settings of the incident waves- whilst the alterations of the average position will obey changes relating to the global sedimentary harmony of the analysed beach segment. The goal of this study is to assess the validity of extracted Landsat shorelines knowing whether the intrinsic error could alter the position of the computed mean annual shoreline or if it is balanced out between the successive averaged images. Two periods are stablished for the temporal analysis in the area according to the availability of other data taken from high precision sources. Statistical tests performed to compare samples (Landsat versus high accuracy) indicate that the two sources of data provide similar information regarding annual means; coastal behaviour and dynamics, thereby verifying Landsat shorelines as useful data for evolutionary studies.

  17. 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.

  18. 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

  19. 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.

  20. Utilizing LANDSAT imagery to monitor land-use change - A case study in Ohio

    NASA Technical Reports Server (NTRS)

    Gordon, S. I.

    1980-01-01

    A study, performed in Ohio, of the nature and extent of interpretation errors in the application of Landsat imagery to land-use planning and modeling is reported. Potential errors associated with the misalignment of pixels after geometric correction and with misclassification of land cover or land use due to spectral similarities were identified on interpreted computer-compatible tapes of a portion of Franklin County for two adjacent days of 1975 and one day of 1973, and the extents of these errors were quantified by comparison with a ground-checked set of aerial-photograph interpretations. The open-space and agricultural categories are found to be the most consistently classified, while the more urban areas were classified correctly only from about 43 to 8% of the time. It is thus recommended that the direct application of Landsat data to land-use planning must await improvements in classification techniques and accuracy.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    PubMed

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

    2010-01-01

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

  3. 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

  4. 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

  5. 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.

  6. 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.

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

    PubMed

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

    2010-09-01

    Up to present, no study has been published with respect to the cross-comparison between ASTER and Landsat-7 ETM+ imagery. Therefore, the present paper has implemented the complementary study on the images between these two sensors. The study firstly conducted the sensors characteristics comparison, including orbit characteristic, sensor scanning mode and imagery spectral characteristic. Further comparison was implemented to get the relation equations between corresponding VNIR and SWIR bands of these two sensors based on the apparent reflectance of the three pairs of synchronization images and large common ground regions. The validation has been done to verify the effectiveness of the proposed corresponding bands relation equations and matching coefficients. The result shows that the provided relation equations have high accuracy. PMID:21105431

  8. Comparison and analysis of linear alignments from Landsat imagery of diverse geologic terrane

    SciTech Connect

    Frederking, R.L.; Allenbach, R.T.; Jackson, R.B.; Keefer, W.D.; Motamedi, A.R.; Von Der Heyde, W.S.; Wingo, R.D.

    1985-01-01

    Geometric alignments referred to as linears, linear features or lineaments are routinely observed on Landsat imagery. Alignments that cannot be accounted for by cultural, known geologic or other recognized sources are classed as speculative and of dubious geologic significance. These features may in fact be imaginary. Speculative alignments are however, important to exploration because of their frequent association with known hydrocarbon accumulations and/or areas of mineralization. Data pertaining to speculative linear alignments in diverse geologic terrane have been obtained. Alignment frequency rose diagrams are prepared for each area and statistical profiles are developed. Replication of linear alignments suggest that these features are real elements of the imagery and not imaginary lines. Observed orientation modal frequencies are consistent with alignment trends of known structural features in the different areas. Variation in spatial density of alignments appears to be related to lithologic factors.

  9. Remote sensing models using Landsat satellite data to monitor algal blooms in Lake Champlain.

    PubMed

    Trescott, A; Park, M-H

    2013-01-01

    Lake Champlain is significantly impaired by excess phosphorus loading, requiring frequent lake-wide monitoring for eutrophic conditions and algal blooms. Satellite remote sensing provides regular, synoptic coverage of algal production over large areas with better spatial and temporal resolution compared with in situ monitoring. This study developed two algal production models using Landsat Enhanced Thematic Mapper Plus (ETM(+)) satellite imagery: a single band model and a band ratio model. The models predicted chlorophyll a concentrations to estimate algal cell densities throughout Lake Champlain. Each model was calibrated with in situ data compiled from summer 2006 (July 24 to September 10), and then validated with data for individual days in August 2007 and 2008. Validation results for the final single band and band ratio models produced Nash-Sutcliffe efficiency (NSE) coefficients of 0.65 and 0.66, respectively, confirming satisfactory model performance for both models. Because these models have been validated over multiple days and years, they can be applied for continuous monitoring of the lake.

  10. 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.

  11. 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.

  12. 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.

  13. Determination of stack plume properties from satellite imagery

    NASA Technical Reports Server (NTRS)

    Staylor, W. F.

    1977-01-01

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

  14. Weakly stationary noise filtering of satellite-acquired imagery

    NASA Technical Reports Server (NTRS)

    Palgen, J. J. O.; Tamches, I.; Deutsch, E. S.

    1971-01-01

    A type of weakly stationary noise called herringbone noise was observed in satellite imagery. The characteristics of this noise are described; a model for its simulation was developed. The model is used to degrade pictorial data for comparison with similar noise degraded Nimbus data. Two filtering methods are defined and evaluated. A user's application demonstration is discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  16. 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.

  17. What Can We Learn About Glaciers and Ice Sheets From 30 Years of Landsat Imagery?

    NASA Astrophysics Data System (ADS)

    Gardner, A. S.; Scambos, T.; Fahnestock, M. A.; Moholdt, G.; Nilsson, J.

    2015-12-01

    Glacier and ice sheets are known to be rapidly changing and currently account for two thirds of observed sea level rise. Attributing the causes of the rapid decline in land ice requires separation of mass change processes, i.e. accumulation of precipitation, meltwater runoff, and solid ice discharge. Here we examine a 30 year record of Landsat imagery to determine trends in glacier velocity at a global scale in an attempt to identify anomalies in glacier flow that are contributing to changes in land ice mass. The Landsat archive represents a treasure trove of information with hundreds of thousands of images acquired over glaciers and ice sheets during the past 30 years. Gleaning useful and consistent surface displacement information from a multiple sensor archive that is heavily contaminated by cloud, saturated images, poorly resolved sensor geometry, and data gaps has proved challenging. Temporal stacking of displacement fields (Dehecq et al., 2015) and correcting for unresolved topography (Roseanau et al., 2012) have been shown to greatly improve derived velocities. Here we present results from a global processing of the complete Landsat archive for information on glacier surface displacements. We highlight patterns of coherent regional change as well as well as rapid basin-scale changes in glacier flow.

  18. Mapping Tillage Practices Using Landsat Imagery: What's Next Before Operational Implementation?

    NASA Astrophysics Data System (ADS)

    Zheng, B.; Campbell, J. B.

    2012-12-01

    Conservation tillage practices can benefit the environment in various ways, including reduction of soil erosion, improvement of water quality, and reduced consumption of fossil fuels. Monitoring tillage practices in space and time will permit better evaluation of their impacts on our environment and assist evaluation of effective agricultural management practices and policies. With the open access and continuity of Landsat data, it is possible to trace the history of tillage management back to the 1980s and to monitor future management events. We have improved mapping accuracies of tillage practices using a multi-temporal approach which requires both Landsat 5 TM (Thematic Mapper) and 7 ETM+ (Enhanced Thematic Mapper plus) data to maximize classification accuracy. To facilitate a broader application of this approach in tillage mapping, we tested a multi-scale segmentation approach to fill the missing data of Landsat 7 scan-line corrector (SLC)-off images, and designed a set of procedures to generate field-level tillage maps with three tillage categories. However, several issues require our attention before it can be implemented operationally, such as effects of soil variation and insufficient satellite observations for certain areas. This study provides insights about uses of remote sensing for current tillage mapping, and the capabilities that may be open for future tillage mapping as Landsat 8 Operational Land Imager (OLI) and European Space Agency Sentinel-2 are scheduled to be launched in 2013.

  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. 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

  1. Development of Water Quality Parameter Retrieval Algorithms for Estimating Total Suspended Solids and Chlorophyll-A Concentration Using LANDSAT-8 Imagery at Poteran Island Water

    NASA Astrophysics Data System (ADS)

    Laili, N.; Arafah, F.; Jaelani, L. M.; Subehi, L.; Pamungkas, A.; Koenhardono, E. S.; Sulisetyono, A.

    2015-10-01

    The Landsat-8 satellite imagery is now highly developed compares to the former of Landsat projects. Both land and water area are possibly mapped using this satellite sensor. Considerable approaches have been made to obtain a more accurate method for extracting the information of water area from the images. It is difficult to generate an accurate water quality information from Landsat images by using some existing algorithm provided by researchers. Even though, those algorithms have been validated in some water area, but the dynamic changes and the specific characteristics of each area make it necessary to get them evaluated and validated over another water area. This paper aims to make a new algorithm by correlating the measured and estimated TSS and Chla concentration. We collected in-situ remote sensing reflectance, TSS and Chl-a concentration in 9 stations surrounding the Poteran islands as well as Landsat 8 data on the same acquisition time of April 22, 2015. The regression model for estimating TSS produced high accuracy with determination coefficient (R2), NMAE and RMSE of 0.709; 9.67 % and 1.705 g/m3 respectively. Whereas, Chla retrieval algorithm produced R2 of 0.579; NMAE of 10.40% and RMSE of 51.946 mg/m3. By implementing these algorithms to Landsat 8 image, the estimated water quality parameters over Poteran island water ranged from 9.480 to 15.801 g/m3 and 238.546 to 346.627 mg/m3 for TSS and Chl-a respectively.

  2. 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.

  3. 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.

  4. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-03-19

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

  7. 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...

  8. 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

  9. Comparison of physically and image based atmospheric correction methods for Sentinel-2 satellite imagery

    NASA Astrophysics Data System (ADS)

    Lantzanakis, Giannis; Mitraka, Zina; Chrysoulakis, Nektarios

    2016-08-01

    Atmospheric correction is the process to retrieve the surface reflectance from remotely sensed imagery by removing the atmospheric effects (Scattering and Absorption). The process determines the optical characteristics of the atmosphere and then applies it in order to correct the atmospheric effects on satellite images. Two main categories of atmospheric correction methods can be identified, the ones that rely on radiative transfer modeling and the image-based ones. In this study, four methods are compared, three physically-based (6S, FLAASH, Sen2Cor) and one image-based (DOS) for their effectiveness on atmospheric correction of Sentinel-2 high resolution optical imagery. A Sentinel-2 image, acquired on a clear day over Heraklion, Greece was used. Ancillary information on the aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used for the physically based methods. In line with similar studies using Landsat images, the physically based methods perform better than the image-based ones also for the Sentinel-2 imagery. Nevertheless, their high computational demand and the need for ancillary atmospheric information makes them difficult to apply. Different atmospheric correction methods showed different results for specific land cover types, suggesting that the selection of the suitable method is also application dependent.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Mapping Hazardous River Ice from High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  3. 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.

  4. Landsat 4 thematic mapper imagery: improved tool for geologic mapping in eastern overthrust

    SciTech Connect

    Miller, J.E.

    1984-04-01

    The central Appalachians were studied using Landsat 4 thematic mapper (TM) data to evaluate the improved spatial resolution (30 x 30 m, 100 x 100 ft) of TM for mapping capabilities. The TM bands 2, 3, and 4 were contrast stretched and edge enhanced using digital processing techniques. Photogeologic analysis of the 1:125,000-scale TM image examined drainage, landform, lineament, and structural features. The study area comprises the junction of the central and southern Appalachians where fold axes change from N30/sup 0/E to N60/sup 0/E. Southeast-dipping thrust faults trend northeastward across the area. Cambrian through Devonian rocks are involved in and exposed by the thrust faults. Recognition of drainage relationships (density and pattern) are important in identifying lithologies. Landforms reflect structure and lithology through characteristic topographic expression. Improved identification and delineation of drainage and landform characteristics on TM imagery support structural and lithologic interpretations. Lineaments were identified by drainage, tonal, and topographic characteristics. Two major lineaments trending N83/sup 0/E and N56/sup 0/W, at the junction of the southern and central Appalachians, were identified. Identified structural features include fold axes, thrust faults, strike-slip faults, and thrust-faulted folds. Detailed lineament and structural mapping on TM imagery aids in unraveling complex surface geologic patterns in this critical area of the eastern overthrust. Digitally enhanced Landsat 4 TM data proved advantageous for accurate mapping of drainage, landform, lineament, and structural features. Improved accuracy on a regional scale allows reliable geologic mapping and therefore subsurface interpretations, benefiting hydrocarbon exploration.

  5. Landsat 4 thematic mapper imagery: improved tool for geologic mapping in eastern overthrust

    SciTech Connect

    Miller, J.E.

    1984-04-01

    The central Appalachians were studied using Landsat 4 thematic mapper (TM) data to evaluate the improved spatial resolution (30 x 30 m, 100 x 100 ft) of TM for mapping capabilities. The TM bands 2, 3, and 4 were contrast stretched and edge enhanced using digital processing techniques. Photogeologic analysis of the 1:125,000-scale TM image examined drainage, landform, lineament, and structural features. The study area comprises the junction of the central and southern Appalachians where fold axes change from N30/sup 0/E to N60/sup 0/E. Southeast-dipping thrust faults trend northeastward across the area. Cambrian through Devonian rocks are involved in and exposed by the thrust faults. Recognition of drainage relationships (density and pattern) are important in identifying lithologies. Landforms reflect structure and lithology through characteristic topographic expression. Improved identification and delineation of drainage and landform characteristics on TM imagery support structural and lithologic interpretations. Lineaments were identified by drainage, tonal, and topographic characteristics. Two major lineaments trending N83/sup 0/E and N56/sup 0/W, at the junction of the southern and central Appalachians, were identified. Identified structural features include fold axes, thrust faults, strike-slip faults, and thrust-faulted folds. Detailed lineament and structural mapping on TM imagery aids in unraveling complex surface geologic patterns in this critical area of the eastern overthrust. Digitally enhanced Landsat 4 TM data proved advantageous for accurate mapping of drainage, landform, lineament, and structural features. Improved accuracy on a regional scale allows reliable geologic mapping and therefore subsurface interpretations, benefitting hydrocarbon exploration.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Surface reflectance correction and stereo enhancement of Landsat thematic mapper imagery for structural geologic exploration

    SciTech Connect

    Thiessen, R.L.; Johnson, L.K.; Foote, H.P.; Eliason, J.R.

    1986-11-01

    Structural remote sensing analysis techniques for exploration have focussed on mapping of crustal fracture zones which can provide pathways for mineralization as well as permeability for movement and/or accumulation of oil, gas, and geothermal fluids. These analyses have relied heavily on manual lineament analysis of enhanced imagery. These image products contain shadow effects that preferentially enhance or suppress lineaments. This study was conducted to evaluate a digital technique for surface reflectance correction for shadows and subsequent stereo enhancement to provide shadow corrected stereo models for structural geologic exploration. Image products were produced from digital Landsat Thematic Mapper (TM) data and a digital elevation model (DEM). The Paiute Ridge quadrangle, Nevada, was selected as a test area for the analysis. Landsat TM data were registered to the DEM and processed to reduce topographic shadowing effects. A Minnaert reflectance model was used to approximate the topographic lighting effects. This reflectance model provided quantitative evaluation of each pixel in the image and was directly used to create a shadow image. These reflectance values were utilized to remove shadow effects from the TM data to produce the corrected surface reflectance. The DEM was used to stereo enhance the shadow corrected TM image. Fracture orientations determined from the original TM and shadow images show similar bias resulting from solar illumination. This bias was not present in the results from the shadow corrected and the corrected stereopair images, with the best correlation to the trends observed in the field data given by the latter.

  13. 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.

  14. 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.

  15. Chernobyl doses. Volume 2. Conifer stress near chernobyl derived from landsat imagery. Technical report, 29 September 1987-28 February 1992

    SciTech Connect

    McClellan, G.E.; Hemmer, T.H.; DeWitt, R.N.

    1992-12-01

    This volume presents Landsat Thematic Mapper imagery of the area surrounding the Chernobyl Nuclear Reactor Station and derives quantitative estimates of the spatial extent and time progression of stress on coniferous forests resulting from the 26 April 1986 reactor explosion and release of radioactive material. Change detection between pre- and postaccident images demonstrates convincingly that remote sensing of the spectral reflectance of coniferous forests in visible and infrared wavelengths at moderate spatial resolution (30 meters) will detect the effects of large radiation doses to the forest canopy. This work was initiated at a time when the expectation for direct data from the Soviet Union on local, accident-induced radiation levels was limited and the satellite data provided an alternative source. Although information exchange with the former Soviet Union has improved dramatically, the results of this report are important, since they prove the feasibility of large-scale, spectral response measurements on radiation-exposed pine trees in a natural environment. Volume 1 presents the derivation of radiation doses from the imagery reviewed in this volume, describes changes in spectral reflectivity of the affected trees as a function of dose and time, and discusses the military operational implications of these results....Chernobyl, Forest damage, Landsat, Change detection, Conifer stress.

  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. 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).

  18. Ad Hoc Modeling of Root Zone Soil Water with Landsat Imagery and Terrain and Soils Data

    PubMed Central

    Sankey, Joel B.; Lawrence, Rick L.; Wraith, Jon M.

    2008-01-01

    Agricultural producers require knowledge of soil water at plant rooting depths, while many remote sensing studies have focused on surface soil water or mechanistic models that are not easily parameterized. We developed site-specific empirical models to predict spring soil water content for two Montana ranches. Calibration data sample sizes were based on the estimated variability of soil water and the desired level of precision for the soil water estimates. Models used Landsat imagery, a digital elevation model, and a soil survey as predictor variables. Our objectives were to see whether soil water could be predicted accurately with easily obtainable calibration data and predictor variables and to consider the relative influence of the three sources of predictor variables. Independent validation showed that multiple regression models predicted soil water with average error (RMSD) within 0.04 mass water content. This was similar to the accuracy expected based on a statistical power test based on our sample size (n = 41 and n = 50). Improved prediction precision could be achieved with additional calibration samples, and range managers can readily balance the desired level of precision with the amount of effort to collect calibration data. Spring soil water prediction effectively utilized a combination of land surface imagery, terrain data, and subsurface soil characterization data. Ranchers could use accurate spring soil water content predictions to set stocking rates. Such management can help ensure that water, soil, and vegetation resources are used conservatively in irrigated and non-irrigated rangeland systems.

  19. 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.

  20. 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

  1. 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

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

    USGS Publications Warehouse

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-07-01

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

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

    PubMed

    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.

  5. 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

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

    PubMed

    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

  7. 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

  8. Snowline and Glacier Assessment in the Central Hindu Kush, Afghanistan, Utilizing Multi- Temporal Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Haritashya, U. K.; Bishop, M. P.; Shroder, J. F.; Bulley, H. N.; Olsenholler, J. A.; Sartan, J. N.

    2006-12-01

    Snow- and glacier-covered massifs in Afghanistan represent the main source of fresh water for the country. Although it is widely recognized that these high altitude cryospheric components are highly sensitive to climatic fluctuation, very little information on changing conditions in Afghanistan have been reported. Climate simulations representing a carbon-dioxide-loading scenario suggest Afghanistan, and the Hindu Kush and Karakoram of Pakistan, could exhibit greater rates of change than in the eastern Himalaya. Consequently, our objective was to assess changes in snowline altitude and glacier areas over a thirty year period. Specifically, we used multi-temporal satellite imagery from different optical sensors from 1973 2002 to assess snowline altitude variations and glacier retreat in the Central Hindu Kush, Afghanistan. Landsat MSS, Landsat TM and ASTER imagery were orthorectified and radiometrically calibrated, and a digital elevation model was generated using ASTER data. We developed a semi-automatic pixel-based, multi-spectral, classification method that incorporates spectral and topographic information. The ASTER-derived DEM represented the baseline elevation reference. Our results are based upon analysis of 12 mountain massifs and 80 glaciers, and indicate that the snowline altitude has increased by approximately 200 m in the last three decades. Results also show glacier retreat and the disconnection of tributary glaciers to their main trunk glacier. In addition, the increase in meltwater production is evident on some glaciers, as revealed by variation in the frequency and size of supraglacial and proglacial lakes. These cryospheric changes can be linked to regional-scale climate change that is affecting the water resource supply in this chronically arid Hindu Kush area. There is an urgent need to conduct fieldwork to obtain direct measurements to further document rapid change due to climate forcing.

  9. Multi-Temporal Satellite Imagery for Urban Expansion Assessment at Sharjah City /UAE

    NASA Astrophysics Data System (ADS)

    Al-Ruzouq, R.; Shanableh, A.

    2014-06-01

    Change detection is the process of identifying differences in land cover over time. As human and natural forces continue to alter the landscape, it is important to develop monitoring methods to assess and quantify these changes. Recent advances in satellite imagery, in terms of improved spatial and temporal resolutions, are allowing for efficient identification of change patterns and the prediction of areas of growth. Sharjah is the third largest and most populous city in the United Arab Emirates (UAE). It is located along the northern coast of the Persian Gulf on the Arabian Peninsula. After the discovery of oil and its export in the last four decades at UAE, it has experienced very rapid growth in industry, economy and population. The main purpose of this study is to detect urban development in Sharjah city by detecting and registering linear features in multi-temporal Landsat images. This paper used linear features for image registration that were chosen since they can be reliably extracted from imagery with significantly different geometric and radiometric properties. Derived edges from the registered images are used as the basis for change detection. Image registration and pixel-pixel subtraction has been implement using multi- temporal Landsat images for Sharjah City. Straight-line segments have been used for accurate co-registration as well as main element for a reliable change detection procedure. Results illustrate that highest range of growth that represented by linear features (building and roads) have been accrued during 1976 - 1987 and stand for 36.24% of the total urban features inside Sharjah city. Moreover, result shows that since 1976 to 2010, the cumulative urban expansion inside Sharjah city is 71.9%.

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

    USGS Publications Warehouse

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

    2002-01-01

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

  11. Global-scale object detection using satellite imagery

    NASA Astrophysics Data System (ADS)

    Hamid, R.; O'Hara, S.; Tabb, M.

    2014-08-01

    In recent years, there has been a substantial increase in the availability of high-resolution commercial satellite imagery, enabling a variety of new remote-sensing applications. One of the main challenges for these applications is the accurate and efficient extraction of semantic information from satellite imagery. In this work, we investigate an important instance of this class of challenges which involves automatic detection of multiple objects in satellite images. We present a system for large-scale object training and detection, leveraging recent advances in feature representation and aggregation within the bag-of-words paradigm. Given the scale of the problem, one of the key challenges in learning object detectors is the acquisition and curation of labeled training data. We present a crowd-sourcing based framework that allows efficient acquisition of labeled training data, along with an iterative mechanism to overcome the label noise introduced by the crowd during the labeling process. To show the competence of the presented scheme, we show detection results over several object-classes using training data captured from close to 200 cities and tested over multiple geographic locations.

  12. 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.

  13. Determination of circulation and turbidity patterns in Kerr Lake from LANDSAT MSS imagery. [Kerr Lake, Virginia, North Carolina

    NASA Technical Reports Server (NTRS)

    Lecroy, S. R. (Principal Investigator)

    1981-01-01

    The LANDSAT imagery was historically analyzed to determine the circulation and turbidity patterns of Kerr Lake, located on the Virginia-North Carolina border. By examining the seasonal and regional turbidity and circulation patterns, a record of sediment transport and possible disposition can be obtained. Sketches were generated, displaying different intensities of brightness observed in bands 5 and 7 of LANDSAT's multispectral scanner data. Differences in and between bands 5 and 7 indicate variances in the levels of surface sediment concentrations. High sediment loads are revealed when distinct patterns appear in the band 7 imagery. The upwelled signal is exponential in nature and saturates in band 5 at low wavelengths for large concentrations of suspended solids.

  14. 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.

  15. Evapotranspiration Retrieval through Optical/Thermal Satellite Imagery and Ground Measurements in the Green River Basin, Wyoming

    NASA Astrophysics Data System (ADS)

    Pradhan, N.; Hendrickx, J. M.; Ogden, F. L.; Wollf, S. W.

    2010-12-01

    Remote sensing methods are increasingly employed in combination with modeling for evapotranspiration estimation because they can provide multi-temporal, spatially-distributed estimates of key variables based on spatially distributed measurements. The approach for estimating evapotranspiration with remotely sensed data couples thermal and optical remote sensing with energy balance models such as: SEBAL, Surface Energy Balance Algorithms for Land, and METRICtm, Mapping Evapotranspiration at high Resolution using Internalized Calibration. The objective of this study is to investigate how ground measurements and satellite imagery at different scales can be combined to retrieve actual evapotranspiration over large watersheds. Scales of ground measurements are: (1) point scale that is typical for regular meteorological measurements such as air temperature, relative humidity, solar radiation, and wind speed; (2) footprint scale that varies from about 5,000 m2 for eddy-covariance measurements of sensible and latent heat fluxes to about 5,000,000 m2 for scintillometer sensible heat flux measurements when optical/thermal Landsat and MODIS satellites pass over around 10 am. In our analysis, we focused on evapotranspiration or consumptive use associated with irrigated agriculture in the Green River Basin in Wyoming that is the main headwater tributary of the entire Colorado River Basin. Ground-based meteorological stations, eddy-covariance and large-aperture scintillometers were set up in Pinedale, Green River basin, Wyoming to conduct the research. METRIC is used to retrieve evapotranspiration estimates from Landsat5 (30-120 m resolution) and MODIS (250-1000 m resolution) imagery.

  16. 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.

  17. DTM generation in forest regions from satellite stereo imagery

    NASA Astrophysics Data System (ADS)

    Tian, J.; Krauss, T.; Reinartz, P.

    2014-11-01

    Satellite stereo imagery is becoming a popular data source for derivation of height information. Many new Digital Surface Model (DSM) generation and evaluation methods have been proposed based on these data. A novel Digital Terrain Model (DTM) extraction method based on the DSM from satellite stereo imagery is proposed in this paper. Instead of directly filtering the DSM, firstly a single channel based classification method is proposed. In this step, no multi-spectral information is used, because for some stereo sensors, like Cartosat-1, only panchromatic channels are available. The proposed classification method adopts the random forests method to get initial probability maps of the four main classes in forest regions (high-forest, low-forest, ground, and buildings). To cover the pepper and salt effect of this pixel based classification method, the probability maps are further filtered based on the adaptive Wiener filtering. Then a cube-based greedy strategy is applied in generating the final classification map from these refined probability maps. Secondly, the height distances between neighboring regions are calculated along the boundary regions. These height distances can be used to estimate the relative region heights. Thirdly, the DTM is extracted by subtracting these relative region heights from the DSM in the order of: buildings - low forest - high forest. In the end, the extracted DTM is further smoothed using median filter. The proposed DTM extraction method is finally tested on satellite stereo imagery captured by Cartosat-1. Quality evaluation is performed by comparing the extracted DTMs to a reference DTM, which is generated from the last return airborne laser scanning point cloud.

  18. 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.

  19. Hydrological applications of Landsat imagery used in the study of the 1973 Indues River floor, Pakistand

    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 Mississippi 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.

  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, 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.

  1. Mapping grass communities based on multi-temporal Landsat TM imagery and environmental variables

    NASA Astrophysics Data System (ADS)

    Zeng, Yuandi; Liu, Yanfang; Liu, Yaolin; de Leeuw, Jan

    2007-06-01

    Information on the spatial distribution of grass communities in wetland is increasingly recognized as important for effective wetland management and biological conservation. Remote sensing techniques has been proved to be an effective alternative to intensive and costly ground surveys for mapping grass community. However, the mapping accuracy of grass communities in wetland is still not preferable. The aim of this paper is to develop an effective method to map grass communities in Poyang Lake Natural Reserve. Through statistic analysis, elevation is selected as an environmental variable for its high relationship with the distribution of grass communities; NDVI stacked from images of different months was used to generate Carex community map; the image in October was used to discriminate Miscanthus and Cynodon communities. Classifications were firstly performed with maximum likelihood classifier using single date satellite image with and without elevation; then layered classifications were performed using multi-temporal satellite imagery and elevation with maximum likelihood classifier, decision tree and artificial neural network separately. The results show that environmental variables can improve the mapping accuracy; and the classification with multitemporal imagery and elevation is significantly better than that with single date image and elevation (p=0.001). Besides, maximum likelihood (a=92.71%, k=0.90) and artificial neural network (a=94.79%, k=0.93) perform significantly better than decision tree (a=86.46%, k=0.83).

  2. 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

  3. 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

  4. Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance

    USGS Publications Warehouse

    Huang, C.; Wylie, B.; Yang, L.; Homer, C.; Zylstra, G.

    2002-01-01

    A new tasselled cap transformation based on Landsat 7 at-satellite reflectance was developed. This transformation is most appropriate for regional applications where atmospheric correction is not feasible. The brightness, greenness and wetness of the derived transformation collectively explained over 97% of the spectral variance of the individual scenes used in this study.

  5. 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).

  6. 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.

  7. 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

  8. Commercial feasibility of traffic data collection using satellite imagery

    NASA Astrophysics Data System (ADS)

    Merry, Carolyn J.; McCord, Mark R.; Bossler, John D.

    1995-01-01

    Requests to market remote sensing data at fine spatial resolutions have been proposed. We evaluated the potential of complementing traffic data collection programs with such data. One of the most fundamental issues is the imaging resolution required to identify vehicles on a highway. We simulated the performance of three spatial resolutions (1.0 m, 2.1 m and 4.2 m) by processing aerial photography (0.4-0.7 μm) of the Columbus, Ohio, area. The imagery was used to count and classify two groups of vehicles—large trucks and smaller vehicles—on several highway segments. We found that the 1.0 m resolution performed significantly better than the coarser resolutions for correctly identifying vehicles. We also investigated the coverage of an orbiting satellite for imaging highways. We find that a 1-m resolution satellite would cover approximately 1% of the highways in the continental U.S. per day.

  9. 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.

  10. 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. PMID:27540167

  11. The preprocessing of multispectral data. II. [of Landsat satellite

    NASA Technical Reports Server (NTRS)

    Quiel, F.

    1976-01-01

    It is pointed out that a correction of atmospheric effects is an important requirement for a full utilization of the possibilities provided by preprocessing techniques. The most significant characteristics of original and preprocessed data are considered, taking into account the solution of classification problems by means of the preprocessing procedure. Improvements obtainable with different preprocessing techniques are illustrated with the aid of examples involving Landsat data regarding an area in Colorado.

  12. Use of satellite imagery for wildland resource evaluation

    NASA Technical Reports Server (NTRS)

    Tueller, P. T. (Principal Investigator)

    1972-01-01

    The author has identified the following significant results. Accurate identification and delineation of crested wheatgrass seedlings has enabled a broad inventory of this resource. The entire state of Nevada is being inventoried for crested wheatgrass seedlings. Irrigated fields and pastures are easily visible from ERTS-1 imagery and were quantified in total acres on 12,500 square miles of the state. Recent fire scars may be monitored and inventoried from satellite-borne imagery. Inventory and quantification of large native meadows of Nevada have been accomplished on one frame of ERTS-1 data. This inventory would not have been economically feasible with any known ground inventory method. The U-2 sequential data taken in the spring revealed several resource management oriented phenological changes in the vegetation. The green-up of grasses and shrubs was detected on the imagery and supplied a good indicator for livestock turn-out dates. Water level manipulations in the Ruby Marsh were readily detected by noting changes in vegetation growth and reflectance.

  13. A model based on satellite altimetry and imagery to evaluate water volume changes in a reservoir in Brazil

    NASA Astrophysics Data System (ADS)

    de C. Abreu, Luiza Gontijo Álvares; Maillard, Philippe

    2014-10-01

    Different satellite missions have instruments to measure the water level variation of oceans and some of these instruments are being used in continental water applications with satisfying results. Altimeters on-board the Envisat and SARAL(Altika) satellites are consistently used to measure the water level in continental water bodies. Recent studies on satellite altimetry combined with satellite imagery have shown the great potential of this technique to estimate the water volume of rivers, lakes, wetlands and reservoirs and its temporal variation in response to climate and other environmental variables. A consistent monitoring of water level variations in reservoirs is crucial to the development policies and implementation of actions regarding the distribution and use of the stored water resource. The Trés Marias reservoir is located within the São Francisco river basin, known as the national integration" river, which provides water flow to the semi-arid region of Brazil. This study presents a method to combine satellite altimetry and imagery of the lake's surface to estimate volume changes and create a model from which volume changes could be computed from either the altimetry or the lake's surface area. Our intention with this study is to evaluate the method and its precision, and the possibility to apply it in other areas, such as wetlands and other lakes where in situ measurements are not available. Moreover, data of monitoring stations usually have an arbitrary altitude reference and are not available for the general public; the data from the satellite altimetry has the advantage of being of global reference (geoid) and compatible with the establishment of a worldwide lake and reservoir database. We combined Envisat and SARAL/Altika altimetry data from 2007-2014 period with Landsat imagery from the same time frame. The data was corrected using a novel processing technique resulting in a relative precision of 0.24 m (RMSE).

  14. Post-classification comparison of land cover using multitemporal Landsat and ASTER imagery: the case of Kahramanmaraş, Turkey.

    PubMed

    Alphan, Hakan; Doygun, Hakan; Unlukaplan, Yüksel I

    2009-04-01

    This study assessed land cover (LC) changes in Kahramanmaraş (K.Maraş) and its environs by using multitemporal Landsat and ASTER imagery, respectively belong to 1989, 2000 and 2004. A priori defined nine land cover classes in the classification scheme were urban and built-up, forest, sparsely vegetated areas, grassland, vegetated stream beds, unvegetated stream beds, bare areas, crop fields, and water bodies. Individual classifications were employed using the combination of both unsupervised and supervised classification methods. Iterative Self Organizing Data Analysis (ISODATA) was used to reduce spectral variation in the scenes arising from complex pattern of crop fields. Maximum Likelihood classifier was used in the LC classification of the individual images. Image pairs of consecutive dates were compared by overlaying the thematic LC maps and cross-tabulating the LC statistics. Urbanization and expansion of agriculture were the major reasons for the dramatic LC conversions. The amount of conversion from crop fields to water occurred as large as 927.67 ha, accounting for 73% of the total land-to-water conversion. Conversions to agriculture have mainly been occurred from grasslands and sparsely vegetated areas as large as 1,314.95 and 1,325.84 ha, respectively. Urban coverage doubled in this period as a result of 1,443.45 ha of increase. Urban area increased in the second period from 2,920 to 3,526 ha. Conversions to agriculture occurred at high amounts. A total of 1,075.79 ha area changed from sparsely vegetated areas to crop fields. A landscape-level environmental monitoring scheme based on satellite remote sensing was proposed for effective environmental resource management.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Application of structures mapped from Landsat imagery to exploration for stratigraphic traps in Paradox basin

    SciTech Connect

    Merin, I.S.; Michael, R.C.

    1985-02-01

    Significant quantities of petroleum occur in algal buildups of Pennsylvanian age in the Paradox basin. Isopach and lithofacies mapping by others suggest that low-relief paleostructures appear to have controlled Pennsylvanian sea-floor topography and thus the distribution of the buildups. Several workers have reported that these paleostructures trend northwest and northeast. Therefore, the basin can be visualized as a mosaic of fault blocks that were differentially active through geologic time. The buildups are elongate northwest, and their distribution and overall shape appear to be controlled by northwest-trending paleostructures. Some larger buildups (i.e., Ismay) show local northeast-trending thicks within an overall northwest-trending buildup. Examination of Landsat imagery revealed an extensive network of northwest-and northeast-trending lineaments that parallel linear patterns apparent from aeromagnetic, gravity, and subsurface isopach data. Additionally, outcrops along selected lineaments contain fractures that parallel these lineaments, suggesting that the lineaments are related to fundamental (i.e., basement) fracture zones along which algal buildups may have developed. Comparison of the fracture network to the distribution of algal thickening reveals these buildups occur predominantly along northwest-trending lineaments. Local disruptions within and apparent terminations of the buildups correspond to cross-cutting northeast-trending lineaments. This relationship provides guidance to locating prospective algal buildups. Integration of these data with detailed subsurface mapping can refine some leads into prospects. Several of these features have been successfully drilled.

  20. 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.

  1. 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. PMID:23430067

  2. 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.

  3. 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 ...

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Application of knowledge-based classification techniques and geographic information systems (GIS) on satellite imagery for stormwater management

    NASA Astrophysics Data System (ADS)

    Abellera, Lourdes Villanueva

    Stormwater management is concerned with runoff control and water quality optimization. A stormwater model is a tool applied to reach this goal. Hydrologic variables required to run this model are usually obtained from field surveys and aerial photo-interpretation. However, these procedures are slow and difficult. An alternative is the automated processing of satellite imagery. We examined various studies that utilized satellite data to provide inputs to stormwater models. The overall results of the modeling effort are acceptable even if the outputs of satellite data processing are used instead of those obtained from standard techniques. One important model input parameter is land use because it is associated with the amounts of runoff and pollutants generated in a parcel of land. Hence, we also explored new ways that land use can be identified from satellite imagery. Next, we demonstrated how the combined technologies of satellite remote sensing, knowledge-based systems, and geographic information systems (GIS) are used to delineate impervious surfaces from a Landsat ETM+ data. Imperviousness is a critical model input parameter because it is proportional to runoff rates and volumes. We found that raw satellite image, normalized difference vegetation image, and ancillary data can provide rules to distinguish impervious surfaces satisfactorily. We also identified different levels of pollutant loadings (high, medium, low) from the same satellite imagery using similar techniques. It is useful to identify areas with high stormwater pollutant emissions so that they can be prioritized for the implementation of best management practices. The contaminants studied were total suspended solids, biochemical oxygen demand, total phosphorus, total Kjeldahl nitrogen, copper, and oil and grease. We observed that raw data, tasseled cap transformed images, and ancillary data can be utilized to make rules for mapping pollution levels. Finally, we devised a method to compute weights

  10. 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.

  11. Flood damage assessment performed based on Support Vector Machines combined with Landsat TM imagery and GIS

    NASA Astrophysics Data System (ADS)

    Alouene, Y.; Petropoulos, G. P.; Kalogrias, A.; Papanikolaou, F.

    2012-04-01

    Floods are a water-related natural disaster affecting and often threatening different aspects of human life, such as property damage, economic degradation, and in some instances even loss of precious human lives. Being able to provide accurately and cost-effectively assessment of damage from floods is essential to both scientists and policy makers in many aspects ranging from mitigating to assessing damage extent as well as in rehabilitation of affected areas. Remote Sensing often combined with Geographical Information Systems (GIS) has generally shown a very promising potential in performing rapidly and cost-effectively flooding damage assessment, particularly so in remote, otherwise inaccessible locations. The progress in remote sensing during the last twenty years or so has resulted to the development of a large number of image processing techniques suitable for use with a range of remote sensing data in performing flooding damage assessment. Supervised image classification is regarded as one of the most widely used approaches employed for this purpose. Yet, the use of recently developed image classification algorithms such as of machine learning-based Support Vector Machines (SVMs) classifier has not been adequately investigated for this purpose. The objective of our work had been to quantitatively evaluate the ability of SVMs combined with Landsat TM multispectral imagery in performing a damage assessment of a flood occurred in a Mediterranean region. A further objective has been to examine if the inclusion of additional spectral information apart from the original TM bands in SVMs can improve flooded area extraction accuracy. As a case study is used the case of a river Evros flooding of 2010 located in the north of Greece, in which TM imagery before and shortly after the flooding was available. Assessment of the flooded area is performed in a GIS environment on the basis of classification accuracy assessment metrics as well as comparisons versus a vector

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Landsat 6 contract signed

    NASA Astrophysics Data System (ADS)

    Maggs, William Ward

    A new agreement provides $220 million for development and construction of the Landsat 6 remote sensing satellite and its ground systems. The contract, signed on March 31, 1988, by the Department of Commerce (DOC) and the Earth Observation Satellite (EOSAT) Company of Lanham, Md., came just days after approval of DOC's Landsat commercialization plan by subcommittees of the House and Senate appropriations committees.The Landsat 6 spacecraft is due to be launched into orbit on a Titan II rocket in June 1991 from Vandenburg Air Force Base, Calif. The satellite will carry an Enhanced Thematic Mapper (ETM) sensor, an instrument sensitive to electromagnetic radiation in seven ranges or bands of wavelengths. The satellite's payload will also include the Sea Wide Field Sensor (Sea-WiFS), designed to provide information on sea surface temperature and ocean color. The sensor is being developed in a cooperative effort by EOSAT and the National Aeronautics and Space Administration (NASA). A less certain passenger is a proposed 5-m resolution, three-band sensor sensitive to visible light. EOSAT is trying to find both private financing for the device and potential buyers of the high-resolution imagery that it could produce. The company has been actively courting U.S. television networks, which have in the past used imagery from the European Système Probatoire d'Observation de la Terre (SPOT) satellite for news coverage.

  18. 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.

  19. Application of Landsat imagery to hydrocarbon exploration in Niobrara Formation, Denver basin

    SciTech Connect

    Merin, I.S.; Moore, W.R.

    1985-02-01

    The Niobrara Formation produces commercial quantities of oil from fractures in several places in the Denver basin. The Niobrara in this basin is an oil-prone, mature source rock having as much as 3.4% TOC, and has been in the generating window since early Eocene. This implies that hydrocarbon generation from the Niobrara is partly contemporaneous with the Laramide orogeny. The Laramide was a multiple-phase orogenic event that began with compression directed to the east-northeast during the Late Cretaceous to Paleocene and ended with compression directed to the northeast during the Eocene. The authors believe the Eocene phase activated northeast-trending extension fractures that may have acted as loci for storage and migration of hydrocarbons, locally generated in the Niobrara. The auto-fracing pressures related to hydrocarbon generation in the Niobrara theoretically would preferentially open and fill this northeast-trending fracture system. Examination of Landsat imagery shows that zones of northeast-trending lineaments are present throughout the basin. Numerous northeast-trending faults are present in the basin, and many overlie older zones that were reactivated during the Laramide. This suggests that these lineaments are previously unrecognized fracture zones. The authors have defined an exploration fairway within the basin based on subsurface isopach and resistivity mapping. The authors believe that mapping of northeast-trending fractures can help identify leads (within this fairway) prospective for Niobrara production. Support of this concept is the location of several apparently productive Niobrara wells along a zone of northeast-trending lineaments.

  20. 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

  1. 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

    2015-12-01

    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

  2. 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

    2015-12-01

    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.

  3. Upper atmospheric gravity wave details revealed in nightglow satellite imagery

    PubMed Central

    Miller, Steven D.; Straka, William C.; Yue, Jia; Smith, Steven M.; Alexander, M. Joan; Hoffmann, Lars; Setvák, Martin; Partain, Philip T.

    2015-01-01

    Gravity waves (disturbances to the density structure of the atmosphere whose restoring forces are gravity and buoyancy) comprise the principal form of energy exchange between the lower and upper atmosphere. Wave breaking drives the mean upper atmospheric circulation, determining boundary conditions to stratospheric processes, which in turn influence tropospheric weather and climate patterns on various spatial and temporal scales. Despite their recognized importance, very little is known about upper-level gravity wave characteristics. The knowledge gap is mainly due to lack of global, high-resolution observations from currently available satellite observing systems. Consequently, representations of wave-related processes in global models are crude, highly parameterized, and poorly constrained, limiting the description of various processes influenced by them. Here we highlight, through a series of examples, the unanticipated ability of the Day/Night Band (DNB) on the NOAA/NASA Suomi National Polar-orbiting Partnership environmental satellite to resolve gravity structures near the mesopause via nightglow emissions at unprecedented subkilometric detail. On moonless nights, the Day/Night Band observations provide all-weather viewing of waves as they modulate the nightglow layer located near the mesopause (∼90 km above mean sea level). These waves are launched by a variety of physical mechanisms, ranging from orography to convection, intensifying fronts, and even seismic and volcanic events. Cross-referencing the Day/Night Band imagery with conventional thermal infrared imagery also available helps to discern nightglow structures and in some cases to attribute their sources. The capability stands to advance our basic understanding of a critical yet poorly constrained driver of the atmospheric circulation. PMID:26630004

  4. 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.

  5. Korean coastal water depth/sediment and land cover mapping (1:25,000) by computer analysis of LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Park, K. Y.; Miller, L. D.

    1978-01-01

    Computer analysis was applied to single date LANDSAT MSS imagery of a sample coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map. Supervised image processing yielded a test classification map from this sample image containing 12 classes: 5 water depth/sediment classes, 2 shoreline/tidal classes, and 5 coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%. Unsupervised image classification was applied to a subportion of the site analyzed and produced classification maps comparable in results in a spatial sense. The results of this test indicated that it is feasible to produce such quantitative maps for detailed study of dynamic coastal processes given a LANDSAT image data base at sufficiently frequent time intervals.

  6. Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

    NASA Technical Reports Server (NTRS)

    Fagan, Matthew E.; Defries, Ruth S.; Sesnie, Steven E.; Arroyo-Mora, J. Pablo; Soto, Carlomagno; Singh, Aditya; Townsend, Philip A.; Chazdon, Robin L.

    2015-01-01

    An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

  7. 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.

  8. Green leaf phenology at Landsat resolution: scaling from the plot to satellite

    NASA Astrophysics Data System (ADS)

    Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

    2005-12-01

    Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (<500 m). These dramatic gradients, of a similar magnitude to differences in leaf-onset from MD to MA, occur in of low-relief (<40 m) upland regions. The patterns suggest that microclimates resulting from springtime cold-air drainage may be influential in governing the start of leaf growth. These microclimates may be of crucial importance in interpreting in situ records and interpolating phenology from satellite data. Regional patterns from the Landsat analyses suggest topographic, coastal, and land-use controls on phenology. For example, our results indicate that deciduous forests

  9. 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.

  10. 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.

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

    SciTech Connect

    Newsam, S D; Kamath, C

    2004-01-22

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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 ...

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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...

  3. Warm core ring dynamics derived from satellite imagery

    NASA Technical Reports Server (NTRS)

    Hooker, Stanford B.; Brown, James W.

    1994-01-01

    A reinterpretation of the life history of warm core ring 82-b is constructed from drifter trajectories, hydrographic profiles, and satellite-derived sea surface temperature fields. An analysis of the observations strongly suggests this ring is fundamentally a dipole structure for much of its existence. The dipole has unequal strength vortices, with the cyclone being the weaker component. Quantification of the dipole indicates the anticyclonic is oval shaped and rotates at approximately 7.7 deg per day, while the cyclone revolves around the anticyclone at about 14.5 deg per day, yielding an orbit period of approximately 25 days for the cyclone. The elusive part of the dipole explanation is in interpreting its surface signature as a function of time, as the cyclone appears to disappear when in proximity to the steep continental slope. Vortex modeling suggests that when the weaker cyclonic eddy is placed close to a boundary, the cyclone is drawn into a filament as it is advected through the gap between the anticyclone and the boundary. This means the cyclone is either in a filamentation state or undergoing the straining associated with filamentation approximately three fourths of this time, which is in complete agreement with the satellite imagery. In addition, the 82-B dipole configuration is sufficiently robust to survive continuous interaction with the continental slope and the onset of a Gulf Stream interaction. Although only warm core ring 82-B is analyzed in detail (and found to be a vortex pair), dipole configurations are found in the warm core ring 81-F time series as well.

  4. 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.

  5. Nearest neighbor, bilinear interpolation and bicubic interpolation geographic correction effects on LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Jayroe, R. R., Jr.

    1976-01-01

    Geographical correction effects on LANDSAT image data are identified, using the nearest neighbor, bilinear interpolation and bicubic interpolation techniques. Potential impacts of registration on image compression and classification are explored.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Applicability Evaluation of Object Detection Method to Satellite and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Kamiya, K.; Fuse, T.; Takahashi, M.

    2016-06-01

    Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING) method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Identifying and locating land irrigated by center-pivot irrigation systems using satellite imagery

    NASA Technical Reports Server (NTRS)

    Hoffman, R. O.

    1980-01-01

    A methodology for using Landsat imagery for the identification and location of land irrigated by center-pivot irrigation systems is presented. The procedure involves the use of sets of Landsat band 5 imagery taken separated in time by about three weeks during the irrigation season, a zoom transfer scope and mylar base maps to record the locations of center pivots. Further computer processing of the data has been used to obtain plots of center-pivot irrigation systems and tables indicating the distribution and growth of systems by county for the state of Nebraska, and has been found to be in 95% agreement with current high-altitude IR photography. The information obtainable can be used for models of ground-water aquifers or resource planning.

  16. 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.

  17. 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.

  18. 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.

  19. Validation of the morphological compositing method for ZY-3 satellite imagery

    NASA Astrophysics Data System (ADS)

    Feng, Shuna; Zhao, Yindi

    2014-11-01

    Each scene of image generated from earth observation satellites can only cover a certain area. When one scene cannot cover a user's area of interest, two or more scenes are needed to be registered and combined into a single image, and this composition process is referred to as image mosaicking. The key issue in image composition is to decide where to place the seam line in overlapping region. The optimal seam line which joins several scenes of images covered the entire study area, is usually determined by texture and other characteristics of the overlap region for seamless quality. Recently, a morphological image compositing algorithm was proposed which is able to automatically delineate seam lines along salient image structures. And this algorithm uses the ideas of marker-controlled segmentation for image mosaicking and divides the overlap region into a determined number of areas. The resulting seam lines of the morphological image compositing algorithm cut along high gradient regions which are object edges in initial images. However, the morphological compositing method only applied to delineate the invisible seam line to the human eyes based on Landsat ETM+ data which is the representation of medium resolution data. In this paper, we test the validation of the morphological compositing method to generate visually pleasing seam line for image mosaic without changing the image radiometry and feasibility to handle two adjacent scenes simultaneously on high spatial resolution imagery by using ZY-3 multispectral image data. The focus of this paper is developing a quantitative evaluation measure which is usually formulated as the sum of morphological gradient of the image mosaic along the seam line divided by the length of the seam to quantitatively estimate the `quality' of the automatically delineate seam line.

  20. 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.

  1. 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.

  2. The RISCO RapidIce Viewer: An application for monitoring the polar ice sheets with multi-resolution, multi-temporal, multi-sensor satellite imagery

    NASA Astrophysics Data System (ADS)

    Herried, B.; Porter, C. C.; Morin, P. J.; Howat, I. M.

    2013-12-01

    The Rapid Ice Sheet Change Observatory (RISCO) is a NASA-funded, inter-organizational collaboration created to provide a systematic framework for gathering, processing, analyzing, and distributing consistent satellite imagery of polar ice sheet change for Antarctica and Greenland. RISCO gathers observations over areas of rapid change and makes them easily accessible to investigators, media, and the general public. As opposed to existing data centers, which are structured to archive and distribute diverse types of raw data to end users with the specialized software and skills to analyze them, RISCO distributes processed georeferenced raster image data products in JPEG and GeoTIFF formats, making them immediately viewable in a browser-based application. Currently, the archive includes 16 sensors including: MODIS Terra, MODIS Aqua, MODIS Terra Bands 3-6-7, Landsat MSS, Landsat TM, Landsat ETM+, Landsat 8 OLI, EO-1, SPOT, ASTER VNIR, Operation IceBridge ATM and LVIS, and commercial satellites such as WorldView-1, WorldView-2, QuickBird-2, GeoEye-1 and IKONOS. The RISCO RapidIce Viewer is a lightweight JavaScript application that provides an interface to viewing and downloading the satellite imagery from predefined areas-of-interest (or 'subsets'), which are normally between 10,000 and 20,000 sq km. Users select a subset (from a map or drop-down) and the archive of individual granules is loaded in a thumbnail grid, sorted chronologically (newest first). For each thumbnail, users can choose to view a larger preview JPG, download a GeoTIFF, or be redirected back to the original data center to see the original imagery or view metadata. There are several options for filtering displayed including by sensor, by date range, by month, or by cloud cover. Last, users can select multiple images to play back as an animation. The RapidIce Viewer is an easy-to-use, software independent application for researchers to quickly monitor daily changes in ice sheets or download historical

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. Lineaments perceived on landsat imagery of central Texas: applications to geothermal resource assessment

    SciTech Connect

    Woodruff, C.M. Jr.; Caran, S.C.; Ruscetta, C.A.; Foley, D.

    1981-05-01

    Lineaments perceived on Landsat images were evaluated to provide evidence for buried structures, which, in turn, apparently control the location of geothermal anomalies. Additional well data were obtained and a new map showing faults displacing the Buda Limestone was constructed. (MHR)

  10. 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.

  11. 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.

  12. Himalayan glaciers: understanding contrasting patterns of glacier behavior using multi-temporal satellite imagery

    NASA Astrophysics Data System (ADS)

    Racoviteanu, A.

    2014-12-01

    High rates of glacier retreat for the last decades are often reported, and believed to be induced by 20th century climate changes. However, regional glacier fluctuations are complex, and depend on a combination of climate and local topography. Furthermore, in ares such as the Hindu-Kush Himalaya, there are concerns about warming, decreasing monsoon precipitation and their impact on local glacier regimes. Currently, the challenge is in understanding the magnitude of feedbacks between large-scale climate forcing and small-scale glacier behavior. Spatio-temporal patterns of glacier distribution are still llimited in some areas of the high Hindu-Kush Himalaya, but multi-temporal satellite imagery has helped fill spatial and temporal gaps in regional glacier parameters in the last decade. Here I present a synopsis of the behavior of glaciers across the Himalaya, following a west to east gradient. In particular, I focus on spatial patterns of glacier parameters in the eastern Himalaya, which I investigate at multi-spatial scales using remote sensing data from declassified Corona, ASTER, Landsat ETM+, Quickbird and Worldview2 sensors. I also present the use of high-resolution imagery, including texture and thermal analysis for mapping glacier features at small scale, which are particularly useful in understanding surface trends of debris-covered glaciers, which are prevalent in the Himalaya. I compare and contrast spatial patterns of glacier area and élévation changes in the monsoon-influenced eastern Himalaya (the Everest region in the Nepal Himalaya and Sikkim in the Indian Himalaya) with other observations from the dry western Indian Himalaya (Ladakh and Lahul-Spiti), both field measurements and remote sensing-based. In the eastern Himalaya, results point to glacier area change of -0.24 % ± 0.08% per year from the 1960's to the 2006's, with a higher rate of retreat in the last decade (-0.43% /yr). Debris-covered glacier tongues show thinning trends of -30.8 m± 39 m

  13. Atmospheric Correction of High-Spatial-Resolution Commercial Satellite Imagery Products Using MODIS Atmospheric Products

    NASA Technical Reports Server (NTRS)

    Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronand; Russell, Jeff; Prados, Don; Stanley, Thomas

    2005-01-01

    Remotely sensed ground reflectance is the foundation of any interoperability or change detection technique. Satellite intercomparisons and accurate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), require the generation of accurate reflectance maps (NDVI is used to describe or infer a wide variety of biophysical parameters and is defined in terms of near-infrared (NIR) and red band reflectances). Accurate reflectance-map generation from satellite imagery relies on the removal of solar and satellite geometry and of atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance has been widely applied to a few systems only. The ability to obtain atmospherically corrected imagery and products from various satellites is essential to enable widescale use of remotely sensed, multitemporal imagery for a variety of applications. An atmospheric correction approach derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that can be applied to high-spatial-resolution satellite imagery under many conditions was evaluated to demonstrate a reliable, effective reflectance map generation method. Additional information is included in the original extended abstract.

  14. 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...

  15. 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.

  16. 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.

  17. 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

  18. 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%.

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

    NASA Technical Reports Server (NTRS)

    Tuominen, H. V. (Principal Investigator); Kuosmanen, V.

    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.

  20. Regional scale net radiation estimation by means of Landsat and TERRA/AQUA imagery and GIS modeling

    NASA Astrophysics Data System (ADS)

    Cristóbal, J.; Ninyerola, M.; Pons, X.; Llorens, P.; Poyatos, R.

    2009-04-01

    balance among the net shortwave radiation Rn and the net longwave radiation. In addition, two types of approaches have been carried out for its determination: the estimation of the variables implied in the calculation of Rn at daily level (Rndl); and the calculation of the Rn at the time of satellite pass (Rni) and its subsequent conversion to daily Rn by means of the Rn ratio. Net shortwave radiation has been computed by means of albedo and a solar radiation model obtained through a DEM following the methodology of Pons and Ninyerola (2008).This methodology takes into account the position of the Sun, the angles of incidence, the projected shadows and the distance from the Earth to the Sun at one hour intervals. The diffuse radiation is estimated from the direct radiaton and the exoatmospheric direct solar irradiance is estimated with the Page equation (1986) and fitted by Baldasano et al. (1994). Net longwave radiation has been calculated through land surface temperature and emissivity, atmospheric water vapour and air temperature. Air temperature has been modeled by means of multiple regression analysis and GIS interpolation using ground meteorological stations. Finally, air emissivity has been computed using air temperature models and atmospheric water vapour following the methodology developed by Dilley and O'Brien (1998). Finally, models have been validated through a set of 13 ground meteorological standard stations and an experimental station placed in a Mediterranean mountain area over a Pinus sylvestris stand. Obtained results show a mean RMSE of 20 W m-2 in the case of Landsat and a mean RMSE of 22 W m-2 in the case of TERRA/AQUA MODIS, being these results in agreement with other published results, but also offering better RMSE in some cases. Keywords: Net radiation, Landsat, TERRA/AQUA MODIS, GIS modeling, regional scale.

  1. 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.

  2. Phenologically informed re-ordering of Landsat to account for inter-annual variability: a method to map Ash trees (Fraxinus spp.) using remotely sensed imagery

    NASA Astrophysics Data System (ADS)

    Isaacson, B. N.; Singh, A.; Serbin, S. P.; Townsend, P. A.

    2009-12-01

    Rapid ecosystem invasion by the emerald ash borer (Agrilus planipennis Fairemaire) is forcing resource managers to make decisions regarding how best to manage the pest, but a detailed map of abundance of the host, ash trees of the genus Fraxinus, does not exist, frustrating fully informed management decisions. We have developed methods to map ash tree abundance across a broad spatial extent in Wisconsin using their unique phenology (late leaf-out, early leaf-fall) and the rich dataset of Landsat imagery that can be used to characterize ash senescence with respect to other deciduous species. However, across environmental gradients in Wisconsin, senescence can vary by days or even weeks such that leaf-drop within one species can temporally vary even within a single Landsat footprint. To address this issue, we used phenology products from NASA’s MODIS for North American Carbon Program (NACP) coupled with vegetation indices derived from a time series of Landsat imagery across multiple years to determine the phenological position of each Landsat pixel within a single idealized growing season. Pixels within Landsat images collected in different years were re-arranged in a phenologically-informed time series that described autumn senescence. This characterization of leaf-drop was then related to the abundance of ash trees, producing a spatially-generalizable model of moderate resolution capable of predicting ash abundance across the state using multiple Landsat scenes. Empirical models predicting ash abundance for two Landsat footprints in Wisconsin indicate model fits for ash abundance of R^2=0.65 in north-central WI, and R^2>0.70 in southeastern WI.

  3. 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. PMID:24338007

  4. Simulation of LANDSAT multispectral scanner spatial resolution with airborne scanner data

    NASA Technical Reports Server (NTRS)

    Hlavka, C. A.

    1986-01-01

    A technique for simulation of low spatial resolution satellite imagery by using high resolution scanner data is described. The scanner data is convolved with the approximate point spread function of the low resolution data and then resampled to emulate low resolution imagery. The technique was successfully applied to Daedalus airborne scanner data to simulate a portion of a LANDSAT multispectra scanner scene.

  5. 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

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

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  7. 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.

  8. Modeling spatial-temporal change of Poyang Lake using multi-temporal Landsat imagery

    NASA Astrophysics Data System (ADS)

    Hui, Fengming; Xu, Bing; Huang, Huabing; Gong, Peng

    2007-06-01

    Exchanging water with the lower branch of Yangtze River, Poyang Lake is a seasonal lake. During the spring and summer flooding season it inundates a large area while in the winter it shrinks considerably creating a large tract of marshland for wild migratory birds. A better knowledge on the water coverage duration and the beginning and ending dates for the vast range of marshlands surrounding the lake is important for the measurement, modeling and management of marshland ecosystems. In addition, the abundance of a special type of snail (Oncomelania hupensis) (the intermediate host of parasite schistosome (Schistosoma japonicum) in this region) is also heavily dependent on the water coverage information. However, there is no accurate DEM for the lake bottom and the inundated marshland, nor is there sufficient water level information over this area. In this study, we assess the feasibility on the use of multitemporal Landsat images in mapping the spatial-temporal change of Poyang Lake water body and the temporal process of water inundating of marshlands. All eight Landsat Thematic Mapper images that are cloud free during a period of one year were used in this study. We used NDWI and MNDWI methods to map water bodies. We then examine the annual spatial-temporal change of the Poyang Lake water body. Finally we attempt to obtain the duration of water inundation of marshlands based on the temporal sequence of water extent determined from the Landsat images. The results showed although the images can be used to capture the snapshots of water coverage in this area, they are insufficient to provide accurate estimation on the spatial-temporal process of water inundating over the marshlands through linear interpolation.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. EROS Main Image File: A Picture Perfect Database for Landsat Imagery and Aerial Photography.

    ERIC Educational Resources Information Center

    Jack, Robert F.

    1984-01-01

    Describes Earth Resources Observation System online database, which provides access to computerized images of Earth obtained via satellite. Highlights include retrieval system and commands, types of images, search strategies, other online functions, and interpretation of accessions. Satellite information, sources and samples of accessions, and…

  14. 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.

  15. Coastal applications of the ERTS-1 satellite imagery

    NASA Technical Reports Server (NTRS)

    Magoon, O. T. (Principal Investigator)

    1972-01-01

    There are no author-identified significant results in this report. Samples are given of the possible applications of ERTS-1 imagery to coastal and nearshore studies. Briefly discussed are: (1) obtaining regional views of extended coastal areas; (2) distribution of sediments; (3) coastal configurations and changes; (4) barrier islands; (5) underwater penetration, and (6) coastal waves.

  16. 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.

  17. 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.

  18. 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.

  19. Spatial heterogeneity in geothermally-influenced lakes derived from atmospherically corrected Landsat thermal imagery and three-dimensional hydrodynamic modelling

    NASA Astrophysics Data System (ADS)

    Allan, Mathew G.; Hamilton, David P.; Trolle, Dennis; Muraoka, Kohji; McBride, Christopher

    2016-08-01

    Atmospheric correction of Landsat 7 thermal data was carried out for the purpose of retrieval of lake skin water temperature in Rotorua lakes, and Lake Taupo, North Island, New Zealand. The effect of the atmosphere was modelled using four sources of atmospheric profile data as input to the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer model. The retrieved skin water temperatures were validated using a high-frequency temperature sensor deployed from a monitoring buoy at the water surface of Lake Rotorua. The most accurate atmospheric correction method was with Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric profile data (root-mean-square-error, RMSE, 0.48 K), followed by radiosonde (0.52 K), Atmospheric Infrared Sounder (AIRS) Level 3 (0.54 K), and the NASA atmospheric correction parameter calculator (0.94 K). Retrieved water temperature was used for assessing spatial heterogeneity and accuracy of surface water temperature simulated with a three-dimensional (3-D) hydrodynamic model of Lake Rotoehu, located approximately 20 km east of Lake Rotorua. This comparison indicated that the model was suitable for reproducing the dominant horizontal variations in surface water temperature in the lake. This study demonstrated the potential of accurate satellite-based thermal monitoring to validate temperature outputs from 3-D hydrodynamic model simulations. It also provided atmospheric correction options for local and global applications of Landsat thermal data.

  20. Mapping impervious surface area in the Brazilian Amazon using Landsat Imagery

    PubMed Central

    Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

    2013-01-01

    Impervious surface area (ISA) is an important parameter related to environmental change and socioeconomic conditions, and has been given increasing attention in the past two decades. However, mapping ISA using remote sensing data is still a challenge due to the variety and complexity of materials comprising ISA and the limitations of remote sensing data spectral and spatial resolution. This paper examines ISA mapping with Landsat Thematic Mapper (TM) images in urban and urban–rural landscapes in the Brazilian Amazon. A fractional-based method and a per-pixel based method were used to map ISA distribution, and their results were evaluated with QuickBird images based on the 2010 Brazilian census at the sector scale of analysis for examining the mapping performance. This research showed that the fraction-based method improved the ISA estimation, especially in urban–rural frontiers and in a landscape with a small urban extent. Large errors were mainly located at the sites having ISA proportions of 0.2–0.4 in a census sector. Calibration with high spatial resolution data is valuable for improving Landsat-based ISA estimates. PMID:24151451

  1. Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery.

    PubMed

    Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

    2011-01-01

    This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms - maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes.

  2. 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.

  3. 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.

  4. Extending a field-based Sonoran desert vegetation classification to a regional scale using optical and microwave satellite imagery

    NASA Astrophysics Data System (ADS)

    Shupe, Scott Marshall

    2000-10-01

    Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers

  5. 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.

  6. 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.

  7. 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.

  8. Uses of Terra, Landsat 7, and Other Satellite Data Sets for Disaster Management

    NASA Astrophysics Data System (ADS)

    Mouginis-Mark, P. J.; Owensby, P.; Chellis, C.; Lo, J.

    2001-05-01

    One of the basic requirements of those who provide information products in support of disaster managers is to have rapid access to current image data at a uniform spatial resolution over the entire geographic region of interest. This is particularly true for the Pacific Disaster Center (PDC), which is focused generating information products for many different types of natural disaster (e.g., hurricanes, floods, fires, volcanic eruptions, tsunamis and earthquakes), and a wide range of users in many countries. The PDC provides support to emergency managers via the timely distribution of information products and services for all natural events in and around the Pacific and Indian Oceans. All phases of emergency management (mitigation, preparedness, response, and recovery) fall under the objective. The PDC fuses science (physics-based numerical models), new data sources (e.g., satellite images), and advanced information and communication technologies (e.g., on-line interactive GIS map production) to provide operational support to a diverse range of disaster managers. We have been working to demonstrate the value to disaster managers of Landsat 7 mosaics derived from multiple scenes of the same area, and to make the generation of browse versions of new mosaics available over the web in real-time. We are using full-resolution Landsat mosaics in the analysis of population growth in areas of the Big Island, Hawaii, at greatest risk from new volcanic eruptions, and the production of baseline images for parts of the Western Pacific where few high resolution maps are available. However, greater utility is believed to lie in combining Landsat data with other types of satellite data sets in order to meet a broader range of disaster manager needs. Observations from the Terra spacecraft (ASTER), as well as commercial data (Ikonos), allow new aspects of disaster management to be addressed. Much of our current work is focused on cities that are at great risk from earthquakes

  9. 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.

  10. 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

  11. The Use of LANDSAT DCS and Imagery in Reservoir Management and Operation. [Maine

    NASA Technical Reports Server (NTRS)

    Cooper, S. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. The demonstration, local user terminal, has proven the hypothesis that a relatively inexpensive, automatic, and easily maintained ground receiving station for satellite relayed data is practical for an operational use.

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

    SciTech Connect

    Vatsavai, Raju; Graesser, Jordan B

    2012-01-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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...

  19. 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.

  20. 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.

  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. Remote sensing monitoring of coastal change in Tangshan with Landsat imagery

    NASA Astrophysics Data System (ADS)

    Shi, Aiqin; Zhang, Huaguo; Wang, Xiaozhen; Lou, Xiulin

    2015-12-01

    Coastal zone is the interaction area between the ocean and the land, and it is one of the most important residential areas of human. Coastal area management and planning is necessary in utilizing coastal space and resources. Coastal zone changed rapidly in recent decades in Tangshan, China. In this research, a total of 11 Landsat images were selected for studying the coastal change in Tangshan during the last 35 years. Results showed that the coastline length increased by 114.05 km, while land area increased by 449.76km2 from 1975 to 2010. The main period of coastal increasing in Tangshan occurred during 2005-2010, and the primary area changes happened in Caofeidian District and Jingtang Port. The main reason of the rapid coastal changes in Tangshan was the human activities of industrial and commercial district construction and harbor construction.

  3. 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.

  4. Fully automated procedure for ship detection using optical satellite imagery

    NASA Astrophysics Data System (ADS)

    Corbane, C.; Pecoul, E.; Demagistri, L.; Petit, M.

    2009-01-01

    Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the framework of a European integrated project GMES-Security/LIMES, we developed an operational ship detection algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing control system. The automatic detection model is based on statistical methods, mathematical morphology and other signal processing techniques such as the wavelet analysis and Radon transform. This paper presents current progress made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on panchromatic SPOT 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship detection strategies.

  5. An ensemble pansharpening approach for finer-scale mapping of sugarcane with Landsat 8 imagery

    NASA Astrophysics Data System (ADS)

    Johnson, Brian A.; Scheyvens, Henry; Shivakoti, Binaya R.

    2014-12-01

    We tested the effects of three fast pansharpening methods - Intensity-Hue-Saturation (IHS), Brovey Transform (BT), and Additive Wavelet Transform (AWT) - on sugarcane classification in a Landsat 8 image (bands 1-7), and proposed two ensemble pansharpening approaches (band stacking and band averaging) which combine the pixel-level information of multiple pansharpened images for classification. To test the proposed ensemble pansharpening approaches, we classified “sugarcane” and “other” land cover in the unsharpened Landsat multispectral image, the individual pansharpened images, and the band-stacked and band-averaged ensemble images using Support Vector Machines (SVM), and assessed the classification accuracy of each image. Of the individual pansharpened images, the AWT image achieved higher classification accuracy than the unsharpened image, while the IHS and BT images did not. The band-stacked ensemble images achieved higher classification accuracies than the unsharpened and individual pansharpened images, with the IHS-BT-AWT band-stacked image producing the most accurate classification result, followed by the IHS-BT band-stacked image. The ensemble images containing averaged pixel values from multiple pansharpened images achieved lower classification accuracies than the band-stacked ensemble images, but most still had higher accuracies than the unsharpened and individual pansharpened results. Our results indicate that ensemble pansharpening approaches have the potential to increase classification accuracy, at least for relatively simple classification tasks. Based on the results of the study, we recommend further investigation of ensemble pansharpening for image analysis (e.g. classification and regression tasks) in agricultural and non-agricultural environments.

  6. 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.

  7. 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.}

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. The use of LANDSAT DCS and imagery in reservoir management and operation. [New England and Alaska

    NASA Technical Reports Server (NTRS)

    Cooper, S. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. The local user terminal has proven the hypothesis that a relatively inexpensive, automatic, and easily maintained ground receive station for satellite relayed data is practical for operational use. Data acquisition activities were expanded to include both the teletype-relayed information as well as that received directly from local user terminals.

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

    SciTech Connect

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

    2007-01-01

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

  14. 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

  15. LANDSAT 1 cumulative non-US standard catalog. Observation ID listing. Coordinate listing. [for 1974 and 1975

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The catalog includes data pertaining to imagery acquired by LANDSAT 1 from July 23, 1974 through July 23, 1975. Two listings of imagery are included: (1) an observation identification listing, and (2) a listing based on geographic location (coordinate listing). World maps of satellite coverage are given.

  16. 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.

  17. 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.

  18. 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.

  19. NCSL task force findings on feasible state uses of LANDSAT

    NASA Technical Reports Server (NTRS)

    Bay, S. M.

    1978-01-01

    Data needs for state natural resources programs, state capabilities for using satellite technology, and the existing remote sensing technology are reviewed. State programs in land use planning, wetlands management, coastal zone management, transportation planning, and forestry management are summarized. Emphasis is placed on the use of LANDSAT imagery.

  20. 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.

  1. 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.

  2. 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.

  3. Flood inundation mapping in the Logone floodplain from multi temporal Landsat ETM+ imagery

    NASA Astrophysics Data System (ADS)

    Jung, H.; Alsdorf, D. E.; Moritz, M.; Lee, H.; Vassolo, S.

    2011-12-01

    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 ~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.

  4. 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.

  5. Tectonic framework of Powder River Basin, Wyoming and Montana, interpreted from Landsat imagery

    SciTech Connect

    Marrs, R.W.; Raines, G.L.

    1984-11-01

    Linear features in the Powder River basin, Wyoming and Montana, were interpreted from Landsat images and analyzed to define major lineaments. Lineaments identified include several that trend northwest and a prominent set that trends northeast. These lineaments represent broad (5-10 km or 3-6 mi) linear zones where smaller, parallel and subparallel linear features are concentrated at the surface. The smaller linear features are interpreted as possible expressions of joints, fractures, folds, or lithologic boundaries produced by periodic readjustment along basement-block boundaries. The lineaments discussed in this report were visually interpreted from maps of linear features and contour maps showing concentrations of linear features. Lineaments were subsequently compared to mapped structures, outcrop patterns, geophysical data, and isopach maps to assess their geologic significance. Correlations of these lineaments with mapped structures, geophysical gradients, or facies changes strongly support the interpretation that they represent the surface expression of boundaries of crustal blocks that have been periodically reactivated through time. The northeast and northwest patterns provide evidence that a systematic, rectilinear pattern of crustal blocks formed early in the earth's history and has largely controlled subsequent adjustments of the earth's crust. These findings suggest the potential for depositional control of sedimentary units by structural adjustments between basement blocks and, thus, lead to the conclusion that lineaments may be used as guides in petroleum and mineral exploration if favorable source and host rocks are present.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  7. 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.

  8. 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.

  9. 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...

  10. Teaching High-School Physics Using Satellite Imagery.

    ERIC Educational Resources Information Center

    Dimock, Crandall W.; Cornillon, Peter

    1994-01-01

    Presents a small sample of the lesson plans developed as a result of a summer workshop that allowed a high school physics teacher to explore the uses of satellite-derived sea surface temperature fields in the physical science classroom. (ZWH)

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  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. 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.

  20. Progress in operational estimation of regional evapotranspiration using satellite imagery

    NASA Astrophysics Data System (ADS)

    Tasumi, Masahiro

    This dissertation presents a developed remote sensing model named SEBAL-ID, which estimates evapotranspiration (ET) from satellite images. The operationally usable remote sensing model was developed for Idaho and western United States conditions by refining the SEBAL (Surface Energy Balance Algorithm for Land) algorithm developed by Bastiaanssen in 1995. The original algorithm has been successfully applied in the world especially in developing countries. In the SEBAL Algorithm, ET from land surfaces is estimated by solving the land surface energy balance for each pixel of a satellite image. The instantaneous (satellite image time) ET is estimated as a residual of the energy balance at the land surface, and the estimated instantaneous value is extrapolated to 24-hour and seasonal ET, which are the final products of SEBAL. The refinements in SEBAL-ID include the application to mountainous regions, an increase in the reliability of estimates by adopting an internal calibration procedure using public weather data, and modifying empirical equations. The proposed model was applied in southern Idaho, and agreed well with lysimeter measured ET data. This dissertation presents results of many analyses with SEBAL-ID, which are valuable not only to SEBAL-ID users but also to SEBAL users around the world. The analyses cover the following topics: surface albedo estimation, estimated LAI by satellite image analyses, effect of atmospheric correction in surface temperature estimation, effect of elevation on surface temperature, ground heat flux estimation method and accuracy, impact of surface roughness for momentum transport, the sensible heat estimation method, windspeed and surface temperature relation, use of a soil water balance model in SEBAL-ID and the behavior of the ETr fraction. The developed model, SEBAL-ID, has already been applied for actual water resources management in Idaho State by the state agency Idaho Department of Water Resources.

  1. 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.

  2. 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.

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

    PubMed Central

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

    2012-01-01

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

  4. Prelaunch Photogrammetric Calibration of Russian Satellite Elektro-L Imagery Instruments

    NASA Astrophysics Data System (ADS)

    Gektin, U. M.; Egoshkin, N. A.; Eremeev, V. V.; Kuznetcov, A. E.; Kochergin, A. M.

    2016-06-01

    Technology of prelaunch geometric calibration of multispectral imagery instruments of Russian geostationary satellites "Elektro-L" No.1 and No.2 is considered. Circular control points are used as a test field. Its geometrical model is developed to take distortions in the collimator optical system into account. Multiple observations of a test field at different angles is used to cover the full visual field of a geostationary sensor. New algorithm of circular control point detection is developed and adapted to complex geometry of geostationary imagery. It is capable of processing images formed as a set of separate scans. Under calibration, sensor design parameters and also the law of scanning mirror motion are specified. The paper contains results of the technology approval under prelaunch calibration of MSU-GS sensors for geostationary operational meteorological satellites (GOMS) "Elektro-L" No.1 and No.2.

  5. 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.

  6. 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.

  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. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Needs for registration and rectification of satellite imagery for land use and land cover and hydrologic applications

    NASA Technical Reports Server (NTRS)

    Gaydos, L.

    1982-01-01

    The use of satellite imagery and data for registration of land use, land cover and hydrology was discussed. Maps and aggregations are made from existing the data in concert with other data in a geographic information system. Basic needs for registration and rectification of satellite imagery related to specifying, reformatting, and overlaying the data are noted. It is found that the data are sufficient for users who must expand much effort in registering data.

  13. 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.

  14. 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.

  15. 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.

  16. 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. PMID:27351187

  17. 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.

  18. Landsat and TRMM imagery potentiality for assessing water superficial variation and bottom depth of shallow lake: case study of Lake Poopó.

    NASA Astrophysics Data System (ADS)

    Satgé, F.; Espinoza, R.; Pillco, R.; Roig, H.; Timouk, F.; Garnier, J.; Bonnet, M. P.

    2015-12-01

    In flat regions, lake extent fluctuations may be used as an indicator of climate variability and/or pressures on water resources at the basin scale. In this context, an accurate delineation through remote sensing is a valuable tool. Here we focused on Lake Poopó located in the Bolivian Andean plateau at an elevation of about 3686 m. With an extent from 500 to 3000 km2 and a mean depth ranging from few cm to 2 m between dry and wet season, respectively, this lake is very sensitive to water use and climatic change. Field spectral-radiometric measurements were collected on both Lake shore and shallow regions in 2014. A total of 84 measurements matching with a Landsat-OLI 8 overpass were made available for our study. The database was used to test FLASSH atmospheric correction module of ENVI software under different parametrization. It shows the usefulness and necessity of such correction before using Landsat imagery. Then, five commonly used indexes for separating inland water (NDWI, MNDWI, WRI, NDVI and AWEI) were computed from Atmospheric corrected Landsat image and compared with field spectral-radiometric measurement. WRI was found the most suitable indexes to delineate Lake Poopó extent according to spectral-radiometric measurements. Using FLAASH atmospheric correction and WRI index, Landsat imagery was used to estimate Lake Poopó extent for a 17 years period from 1998 to 2015. Fluctuations are compared with rainfall measurement from TRMM TMPA-3B42 v7 and In Situ evaporation to highlights climatic or water use changes during this period. Finally, 130 water depth measurements collected in 2005 were used to establish a logarithmic correlation between WRI and water depth. The relation was applied for 2014 and computed water depths are in agreement with In Situ measurement with an overall RMSE value of 5 cm.

  19. Landsat electron beam recorder

    NASA Astrophysics Data System (ADS)

    Grosso, P. F.; Whitley, J. P.

    A minicomputer-controlled electron beam recorder (EBR) presently in use at the Brazilian Government's Institute De Pesquisas Espaclais (INPE) satellite ground station is described. This 5-in.-film-size EBR is used to record both Landsat and SPOT satellite imagery in South America. A brief electron beam recorder technology review is presented. The EBR is capable of recording both vector and text data from computer-aided design, publishing, and line art systems and raster data from image scanners, raster image processors (RIPS), halftone/screen generators, and remote image sensors. A variety of image formats may be recorded on numerous film sizes (16 mm, 35 mm, 70 mm, 105 mm, 5-in, 5.5-in., and 9.5-in.). These recordings are used directly or optically enlarged depending on the final product.

  20. Satellite imagery time series for the detection of looting activities at archaeological sites

    NASA Astrophysics Data System (ADS)

    Coluzzi, Rosa; Lasaponara, Rosa; Masini, Nicola

    2010-05-01

    Clandestine excavations is one of the biggest man-made risks which affect the archaeological heritage, especially in some countries of Southern America, Asia and Middle East. To contrast and limit this phenomenon a systematic monitoring is required. The protection of archaeological heritage from clandestine excavations is generally based on a direct surveillance, but it is time consuming and expensive for remote archaeological sites and non practicable in several countries due to military or political restrictions. In such conditions, Very high resolution (VHR) satellite imagery offer a suitable chance thanks to their global coverage and frequent revisitation times. This paper is focused on the results we obtained from ongoing research focused on the use of VHR satellite images for the identification and monitoring of looting. A time series of satellite images (QuickBird-2 and World-View-1) has been exploited to analyze and monitor archaeological looting in the Nasca Ceremonial Centre of Cahuachi (Peru) dating back between the 4th centurt B.C. and the 4th century A.D. The Cahuachi study case herein presented put in evidence the limits of VHR satellite imagery in detecting features linked to looting activity. This suggested to experience local spatial autocorrelation statistics which allowed us to improve the reliability of satellite in mapping looted area.