Science.gov

Sample records for landsat satellite imagery

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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).

  11. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  13. 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.

  14. 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.

  15. Vector statistics of LANDSAT imagery

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  16. 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.

  17. 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.

  18. 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.

    2015-01-01

    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.

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

    NASA Technical Reports Server (NTRS)

    Steffen, Konrad; Schweiger, Axel

    1991-01-01

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

  20. 75 FR 39701 - Revision of a Currently Approved Collection: Users, Uses, and Benefits of Landsat Satellite Imagery

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-12

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

  1. Remote possibilities. From the Landsat -- a satellite for all seasons

    SciTech Connect

    1994-12-31

    This report presents Landsat and its big picture from outer space. It explains the concept of remote sensing. The satellite can provide visual imagery of resource problems in the fields of environmental quality, geology water, land use, and agriculture. The data acquired by the satellite is available to everyone to help resolve resource problems.

  2. 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.

  3. 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).

  4. 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

  5. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed

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

    2016-09-01

    Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m(2) in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500 °C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVInov) and 10 December 2014 (NDVIdec) because the potential AB was highly associated with NDVInov and NDVIdec (r (2)  = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVInov and NDVIdec, respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass. PMID:27510986

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  9. Glacier change over the last century, Caucasus Mountains, Georgia, observed from old topographical maps, Landsat and ASTER satellite imagery

    NASA Astrophysics Data System (ADS)

    Tielidze, Levan G.

    2016-03-01

    Changes in the area and number of glaciers in the Georgian Caucasus Mountains were examined over the last century, by comparing recent Landsat and ASTER images (2014) with older topographical maps (1911, 1960) along with middle and high mountain meteorological stations data. Total glacier area decreased by 8.1 ± 1.8 % (0.2 ± 0.04 % yr-1) or by 49.9 ± 10.6 km2 from 613.6 ± 9.8 km2 to 563.7 ± 11.3 km2 during 1911-1960, while the number of glaciers increased from 515 to 786. During 1960-2014, the total ice area decreased by 36.9 ± 2.2 % (0.7 ± 0.04 % yr-1) or by 207.9 ± 9.8 km2 from 563.7 ± 11.3 km2 to 355.8 ± 8.3 km2, while glacier numbers decreased from 786 to 637. In total, the area of Georgia glaciers reduced by 42.0 ± 2.0 % (0.4 ± 0.02 % yr-1) between 1911 and 2014. The eastern Caucasus section had the highest retreat rate of 67.3 ± 2.0 % (0.7 ± 0.02 % yr-1) over this period, while the central part of Georgian Caucasus had the lowest, 34.6 ± 1.8 % (0.3 ± 0.01 % yr-1), with the western Caucasus intermediate at 42.8 ± 2.7 % (0.4 ± 0.03 % yr-1).

  10. 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.

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

    NASA Technical Reports Server (NTRS)

    Baker, R. N.

    1977-01-01

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

  12. 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.

  13. 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.

  14. Plume dispersion investigated by landsat imagery

    NASA Astrophysics Data System (ADS)

    Desiato, F.; Ciminelli, M. G.

    Suspended particulate in the atmosphere may be detected by satellite sensors due to scattered radiation. A number of LANDSAT TM images presenting the evidence of the pollutant plumes emitted at the stack of the electric power plants located at two Italian coastal sites, dispersing mainly over the sea surface, have been selected. The satellite data of Band 1 of the visible channel have been elaborated to estimate the lateral dispersion as a function of the travel time. The results show the presence of an accelerated diffusion regime at a rate slower than the one predicted by the relative diffusion theory.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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).

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Mapping shorelines to subpixel accuracy using Landsat imagery

    NASA Astrophysics Data System (ADS)

    Abileah, Ron; Vignudelli, Stefano; Scozzari, Andrea

    2013-04-01

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

  6. 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.

  7. 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.

  8. 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.

  9. Monitoring Playa Hydrology using LANDSAT Imagery

    NASA Astrophysics Data System (ADS)

    Young, C. B.; Pradhananga, A.

    2004-12-01

    Playa lakes are wetland basins found across the Great Plains. These ephemeral lakes serve as habitat for migrating waterfowl and act as concentrated recharge points for groundwater aquifers. Playas are generally small but number in the tens of thousands, making them a significant component of the ecology and hydrology of the Great Plains. The shear number of playas makes this system difficult to study. Satellite remote sensing, however, can be used to monitor playa hydrology over broad space and time scales. This study demonstrates the use of a four-image LANDSAT sequence to study a cluster of playas in Beaver County, Oklahoma. A simple water budget model is developed to predict aggregate playa water surface area for the study area.

  10. 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.

  11. 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.

  12. 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.

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

    NASA Technical Reports Server (NTRS)

    1977-01-01

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

  14. 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).

  15. 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...

  16. 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.

  17. 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.

  18. 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...

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

  1. 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)

  2. 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.

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

    NASA Technical Reports Server (NTRS)

    1976-01-01

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

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

    NASA Technical Reports Server (NTRS)

    1975-01-01

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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Seong, Jeong C.

    2015-12-01

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

  11. LANDSAT 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.

  12. 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.

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

    NASA Technical Reports Server (NTRS)

    1977-01-01

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

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

    NASA Technical Reports Server (NTRS)

    1977-01-01

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

  15. 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.

  16. 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.

  17. Applications of Landsat imagery to geological research in Minnesota

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  18. LANDSAT imagery of the Central Andes

    NASA Technical Reports Server (NTRS)

    Komer, C. A.; Morgan, P.

    1986-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Dillard, J. P.

    1975-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  1. 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.

  2. Operational applications of satellite snowcover observations and LANDSAT data collection systems operations in central Arizona

    NASA Technical Reports Server (NTRS)

    Schumann, H. H.

    1975-01-01

    Repetitive LANDSAT and NOAA-4 satellite imagery together with aerial surveys are being evaluated to develop an operational capability for mapping snowcover distributions on the Salt-Verde watershed of central Arizona. Satellite telemetry is also being used for near-real time relay of hydrologic data to aid in the management and operation of reservoirs on the Salt and Verde Rivers. Aerial reconnaissance flights were conducted to collect information on the depth and distribution of snowcover to provide ground truth for use in the analysis of the satellite imagery. A technique for rapid and economical determination of snow depths, using oblique aerial photography of snow markers, was developed.

  3. Linear features determined from Landsat imagery in western Kansas

    USGS Publications Warehouse

    Cooley, M.E.

    1984-01-01

    A map (scale 1:500,000) shows the linear features determined from Landsat imagery in western Kansas. The linear features, sometimes called linear trends or lineaments, are not identified as to type or origin. Most probably represent fractures or fracture zones, which may affect the movement of water or other fluids through the rocks. The linear features are classified as to length--less than 30 miles and more than 30 miles. (USGS)

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  5. 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.

  6. 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.

  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. 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.

  9. 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. PMID:26393607

  10. 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

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

    NASA Technical Reports Server (NTRS)

    Lee, Y. J.

    1975-01-01

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

  14. 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.

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

    SciTech Connect

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

    1983-09-01

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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  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. Linear features determined from Landsat imagery in North Dakota

    USGS Publications Warehouse

    Cooley, M.E.

    1983-01-01

    The report consists of a map (scale 1:500,000) that shows the linear features determined from Landsat imagery in North Dakota. The linear features, sometimes called linear trends or lineaments, are not identified as to type or origin. Most probably represent fractures or fracture zones, which may affect the movement of water or other fluids through the rocks. The linear features are classified as to length--less than 30 miles, 30 to 200 miles, 200 to 500 miles, and more than 500 miles. (USGS)

  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. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Measuring Streamwood Accumulations In A Reservoir Using Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Gonzalez, R. L.; Senter, A. E.; Pasternack, G. B.; Ustin, S.

    2011-12-01

    Streamwood (woody materials greater than 10 cm in diameter and 1 m in length) is important to river networks, providing structure, hydraulic variability, and organic carbon to river ecosystems. In reservoirs where recreational activities take place, streamwood is moved into holding areas to minimize human health hazards. A common disposal method in California is to burn the wood soon after the first rains; streamwood is often insufficiently quantified by managers before disposal. As a result of active management and the loss of longitudinal connectivity caused by dams, streamwood's potential as a geomorphic agent and its biological constituents are lost to downstream ecosystems. To measure how much streamwood can accumulate in a mountain reservoir, Landsat 5 multispectral 30-m resolution imagery was used to aerially quantify streamwood floating on the surface of New Bullard's Bar Reservoir on the North Yuba River, Sierra Nevada, California, in a time-series from 1984 to present. The scientific questions answered by this study were: 1) how much streamwood was transported into the reservoir on a yearly basis? And, 2) what discharge-area relationships exist between gaged discharge and streamwood measures? Landsat images representative of the highest water surface elevation of each year were acquired from the publically available USGS online database, then atmospherically corrected, empirical-line calibrated, and georeferenced using ENVI software. ROIs and spectral library files were developed for four endmembers: forest, water, streamwood, and shoreline, and used in supervised maximum likelihood classifications. An unsupervised isodata classification was also performed, and results were linked to understand areas of confusion and to create a more robust streamwood identification model. A 1-m USGS DOQ image from 1998 and field surveys in 2006 and 2010 were used to ground-truth Landsat results.

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

    NASA Astrophysics Data System (ADS)

    Ledoux, Lindsay

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

  12. 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.

  13. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  15. 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.

  16. 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...

  17. 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.

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

    NASA Technical Reports Server (NTRS)

    Jensen, M. L.; Laylander, P.

    1975-01-01

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

  19. 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 ...

  20. 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).

  1. Investigation of Satellite Imagery for Regional Planning

    NASA Technical Reports Server (NTRS)

    Harting, W. (Principal Investigator)

    1975-01-01

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

  2. 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.

  3. 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.

  4. Regional scale crop mapping using multi-temporal satellite imagery

    NASA Astrophysics Data System (ADS)

    Kussul, N.; Skakun, S.; Shelestov, A.; Lavreniuk, M.; Yailymov, B.; Kussul, O.

    2015-04-01

    One of the problems in dealing with optical images for large territories (more than 10,000 sq. km) is the presence of clouds and shadows that result in having missing values in data sets. In this paper, a new approach to classification of multi-temporal optical satellite imagery with missing data due to clouds and shadows is proposed. First, self-organizing Kohonen maps (SOMs) are used to restore missing pixel values in a time series of satellite imagery. SOMs are trained for each spectral band separately using nonmissing values. Missing values are restored through a special procedure that substitutes input sample's missing components with neuron's weight coefficients. After missing data restoration, a supervised classification is performed for multi-temporal satellite images. An ensemble of neural networks, in particular multilayer perceptrons (MLPs), is proposed. Ensembling of neural networks is done by the technique of average committee, i.e. to calculate the average class probability over classifiers and select the class with the highest average posterior probability for the given input sample. The proposed approach is applied for regional scale crop classification using multi temporal Landsat-8 images for the JECAM test site in Ukraine in 2013. It is shown that ensemble of MLPs provides better performance than a single neural network in terms of overall classification accuracy, kappa coefficient, and producer's and user's accuracies for separate classes. The overall accuracy more than 85% is achieved. The obtained classification map is also validated through estimated crop areas and comparison to official statistics.

  5. Mapping and assessing seagrass bed changes in Central Florida's west coast using multitemporal Landsat TM imagery

    NASA Astrophysics Data System (ADS)

    Pu, Ruiliang; Bell, Susan; Meyer, Cynthia

    2014-08-01

    Some seagrass meadows in coastal shallow waters have displayed large scale changes in seagrass spatial extent and hurricanes and/or tropical storms have been suggested as factors responsible for reduction in coverage. Taking advantage of the incidence of three tropical storms passing near a study site along the central west Florida coast within a two-month period in 2004, we evaluated whether satellite remote sensing techniques (Landsat 5 Thematic Mapper (TM) imagery) are useful for assessing dynamics of seagrass (=submerged aquatic vegetation: SAV) cover/abundance in response to these multiple disturbances. We also examined whether an image preprocessing procedure, which included water column correction, applied to the Landsat TM images could further improve the classification and mapping of detailed SAV coverage. We compared a historical set of Landsat TM images, acquired in Fall 2003 and Fall and late Summer 2005, which were processed to classify %SAV cover into five classes using a maximum likelihood classifier. Importantly, our experimental results demonstrated that the application of the image preprocessing procedures led to an overall accuracy 2-14% improvement in SAV classification due to water column correction compared to that currently reported in the literature when similar Landsat TM data are utilized. Based upon the classification results mapped from the TM images and as well as a similar classification of SAV interpreted from aerial photographs collected before and after the passage of these same storms, SAV coverage over the study areas was found to increase about 6% (integrating SAV losses and gains) by 2005/2006 in comparison to cover levels present prior to the repeated storm activity. We conclude that heavy rains during 2004 along with physical disturbance from gale force winds from the tropical storms/hurricanes did not produce any SAV bed loss at the study site that was sustained for more than one year after multiple storm passage.

  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. 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.

  8. 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...

  9. Maritime vessel recognition in degraded satellite imagery

    NASA Astrophysics Data System (ADS)

    Rainey, Katie; Parameswaran, Shibin; Harguess, Josh

    2014-06-01

    When object recognition algorithms are put to practice on real-world data, they face hurdles not always present in experimental situations. Imagery fed into recognition systems is often degraded by noise, occlusions, or other factors, and a successful recognition algorithm must be accurate on such data. This work investigates the impact of data degradations on an algorithm for the task of ship classification in satellite imagery by imposing such degradation factors on both training and testing data. The results of these experiments provide lessons for the development of real-world applications for classification algorithms.

  10. 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.

  11. Quality assessment of OpenStreetMap water mask using LANDSAT 8 imagery and Google Earth Engine

    NASA Astrophysics Data System (ADS)

    Donchyts, Gennadii; Schellekens, Jaap; Winsemius, Hessel; van de Giesen, Nick

    2015-04-01

    OpenStreetMap is one of the most used and cited Volunteered Geographic Information (VGI) platforms with an increasing popularity in the last years. Originally developed as a public global road database it is also used to digitize and share many other natural and manmade geospatial features, including water related such as rivers, lakes and coast boundaries. Due to its free nature, OpenStreetMap is a very attractive dataset to be used for many environmental applications, such as simulation of water flow in rivers, lakes and coastal zones. However, there is a lack of academic literature focusing on validation of the water mask quality used in OpenStreetMap. In this work we will analyse the quality of OpenStreetMaps water using a new water mask extracted from medium resolution (15-30m) multi-spectral imagery measured by the LANDSAT 8 satellite during 2013-2014. In order to generate the water mask from LANDSAT 8 imagery a number of essential steps need to be performed, such as the selection of cloud-free pixels, delineation of the maximum and minimum annual water mask and detection of false positive pixels due to mountain and cloud shadows. We will use Google Earth Engine (GEE) as a high-performance parallel processing platform to process LANDSAT 8 imagery.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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.

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

    PubMed Central

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

    2007-01-01

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

  19. 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

  20. SST and SS changes during Saemangeum seawall construction using Landsat TM and ETM imagery

    NASA Astrophysics Data System (ADS)

    Park, Jong-Hwa; Na, Sang-il

    2010-10-01

    Saemangeum, located on the southwest coast of the Korean peninsula, is a 40 100 ha ongoing "reclamation" project in South Korea, concomitance damming the estuaries of the Mangyong and Dongjin rivers, replacing vast tidal land and sea-shallows with land and a huge freshwater reservoir. In 1991, the South Korean government announced that a seawall (dyke) would be constructed to link two headlands just south of the South Korean industrial port city of Gunsan and Buan, 270 kilometers southwest of Seoul, to create 400 km2 of farmland and a freshwater reservoir. Started in 1991, the 33km long seawall was finally completed on April 2006. Chlorophyll-a concentration, Suspended solids (SS), Sea surface temperature (SST), and turbidity are four important water quality variables, among other environmental factors such as salinity and pH, for tidal land production in Saemangeum. Change detection of the SST and SS during Saemangeum seawall construction was carried out by using LANDSAT TM and ETM imagery data. The spatial and temporal distribution of SST and SS are estimated and mapped with various degrees of success in Saemangeum area. Here we assessed the potential of these data to derive water quality parameters in a reclaimed estuary environment. We found that the evolution of the estuary, coastline, delta, and change detection results derived from LANDSAT TM and ETM images recorded in 1989, 2001 and 2008, respectively. Due to the limitations of image acquisition and noise, many researchers have employed the image processing technique to improve satellite data in order to assess water quality. The interpolation approach is a useful tool for the analyses and assessment on SST and SS on the basis of available satellite imagery data. Ordinary kriging (OK) were used to improve the SST and SS images in the study area. Results indicate that sedimentary transport, SS, and SST in Saemangeum has significantly changed during the past 20 years, with a dramatic increase in the amount of

  1. 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.

  2. 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.

  3. 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

  4. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery... the United States not obscured by clouds or distortions. Orders or requests for information should...

  5. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery... the United States not obscured by clouds or distortions. Orders or requests for information should...

  6. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery... the United States not obscured by clouds or distortions. Orders or requests for information should...

  7. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery... the United States not obscured by clouds or distortions. Orders or requests for information should...

  8. 7 CFR 611.22 - Availability of satellite imagery.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery... the United States not obscured by clouds or distortions. Orders or requests for information should...

  9. 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.

  10. 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.

  11. EOS-WEBSTER - Providing Satellite Imagery for Everyone

    NASA Astrophysics Data System (ADS)

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

    2002-12-01

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

  12. Geological significance of features observed in Colorado from orbital altitudes. [using EREP and LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Sawatzky, D. L.; Prost, G. L.; Lee, K.; Knepper, D. H.

    1975-01-01

    Three major investigations using LANDSAT and Skylab imagery concerned with analyses of color anomalies and linear features of central Colorado are discussed. The studies conducted are concerned with the geological significance of spectral and spatial features on the images. Color anomalies in Skylab photographs were analyzed and evaluated for locating indicators of mineralization. The relationships were determined of all linear features in a LANDSAT image to the rock joint systems and the detectable larger geologic structures; techniques for extracting that geologic information are indicated. Some anomalous megalinear features in LANDSAT and Skylab images are analyzed which transect major structures and, their associated geologic features are described.

  13. 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.

  14. 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

  15. Monitoring flood damage with satellite imagery

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

  16. 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

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

    PubMed

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

    2014-01-01

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

  18. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  20. 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

  1. Semi-Automated Cloud/shadow Removal and Land Cover Change Detection Using Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Sah, A. K.; Sah, B. P.; Honji, K.; Kubo, N.; Senthil, S.

    2012-08-01

    Multi-platform/sensor and multi-temporal satellite data facilitates analysis of successive change/monitoring over the longer period and there by forest biomass helping REDD mechanism. The historical archive satellite imagery, specifically Landsat, can play an important role for historical trend analysis of forest cover change at national level. Whereas the fresh high resolution satellite, such as ALOS, imagery can be used for detailed analysis of present forest cover status. ALOS satellite imagery is most suitable as it offers data with optical (AVNIR-2) as well as SAR (PALSAR) sensors. AVNIR-2 providing data in multispectral modes play due role in extracting forest information. In this study, a semi-automated approach has been devised for cloud/shadow and haze removal and land cover change detection. Cloud/shadow pixels are replaced by free pixels of same image with the help of PALSAR image. The tracking of pixel based land cover change for the 1995-2009 period in combination of Landsat and latest ALOS data from its AVNIR-2 for the tropical rain forest area has been carried out using Decision Tree Classifiers followed by un-supervised classification. As threshold for tree classifier, criteria of NDVI refined by reflectance value has been employed. The result shows all pixels have been successfully registered to the pre-defined 6 categories; in accordance with IPCC definition; of land cover types with an overall accuracy 80 percent.

  2. 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

  3. 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

  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. 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)

  6. 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.

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

    USGS Publications Warehouse

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

    2013-01-01

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

  8. 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.

  9. 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.

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

    NASA Technical Reports Server (NTRS)

    Lecroy, S. R. (Principal Investigator)

    1982-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Formaggio, A. R. (Principal Investigator)

    1984-01-01

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

  12. 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.

  13. 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.

  14. 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. PMID:26251060

  15. 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.

  16. Cataloguing Large Amounts of Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Iturrate, E.; O'Connor, A. S.; Hulslander, D.; Farr, B.

    2012-12-01

    Remote sensing users face the challenge of managing hundreds, even thousands of scenes. These images are normally stored as files organized in a folder structure. Unless there are clearly defined rules about the organization of the directories and file naming conventions, users inevitably find it very difficult to find particular images. "Katalog" is a free satellite image cataloguing tool developed to solve this problem. It can crawl a particular folder structure in search of the satellite images, extracting both metadata, footprints, and thumbnails. This information is then searchable by a number of variables (e.g. name, sensor, geographic location, date, description, and so on) allowing users to quickly find scenes in their imagery libraries, discovering and rediscovering data they didn't even know they had. "Katalog" works as an extension to the ENVI software package, taking advantage of the large collection of satellite image readers that ENVI provides. Generated thumbnails and footprints are also compatible with other applications like Google Earth, Picasa, and Esri ArcGIS.

  17. 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.

  18. Hierarchical segmentation of urban satellite imagery

    NASA Astrophysics Data System (ADS)

    Yousefi, Bardia; Mirhassani, Seyed Mostafa; AhmadiFard, Alireza; Hosseini, MohammadMehdi

    2014-08-01

    This paper proposes a method to combine contextual, structural, and spectral information for classification. The method is an integrated method for automatically classifying urban-area objects in very high-resolution satellite imagery. The approach addresses three aspects. First, the Gabor wavelet is applied to the image along with morphological operations, with the sparsity of the outcome considered. A Bayesian classifier then categorizes the different classes, such as buildings, roads, open areas, and shadows. There are some false positives (wrong classification), and false negatives (non-classification) in the initial results. These results can be corrected by the relaxation labeling categorization of the unknown regions. The novelty of the proposed approach lies in the extensive use of spatiotemporal features considering the sparsity of urban objects. The results indicate improvement in classification through relaxation labeling compared with existing methods.

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

    NASA Technical Reports Server (NTRS)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

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

  20. 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.

  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. 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.

  3. 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.

  4. 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

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

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  6. 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).

  7. 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.

  8. 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

  9. Hydraulic parameter identification using satellite earth imagery

    NASA Astrophysics Data System (ADS)

    Roux, H.; Raclot, D.; Dartus, D.; Puech, C.

    2003-04-01

    Despite of the progresses recently realized in the implementation of open-channel flow models, the determination of the parameters involved in the simulation process is still uncertain. In alternative to traditional measurements in the field, the use of high resolution satellite earth imagery (visible satellite, infrared, radar) is considered to ascertain, implementing optimization methods, the value of a set of hydraulic parameters allowing to characterize the flow with a precision sufficient to make flood studies. These satellite images generally give a top sight of the flow or of the flooded area. The scope of data assimilation is to make the best possible estimate of the state of a physical system, given data and a model describing the phenomenon. This study focuses only on sequential methods, that is to say methods that correct the model state at the moment of the observations. Data assimilation techniques can be divided into two classes according to the processes of resolution employed. Variational methods minimize a cost function that is the sum of a distance to the observations and a distance to an a priori estimate (often a prevision) of the model state. Statistical methods or filters explicitly solve the assimilation problem by calculating the linear optimal combination between guess and observations that minimizes the estimate error variance. The most known filter, the Best Linear Unbiased Estimator or B.L.U.E., has been proposed by Kalman in 1960. Both approaches have been tested on a simple case. Parameter identification procedure has been implemented for a mono-dimensional steady flow in compound channel with a trapezoidal main channel and near horizontal overbanks. The observations or gauged data, that could be made by a satellite, are created by adding a gaussian noise, inherent to the interpretation of satellite images, to flow top width. Flow top width is obtained by a 1D hydraulic simulation of Saint-Venant equations realized on a known river

  10. 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.

  11. Regional analysis of tertiary volcanic Calderas (western U.S.) using Landsat Thematic Mapper imagery

    NASA Technical Reports Server (NTRS)

    Spatz, David M.; Taranik, James V.

    1989-01-01

    The Landsat Thematic Mapper (TM) imagery of the Basin and Range province of southern Nevada was analyzed to identify and map volcanic rock assemblages at three Tertiary calderas. It was found that the longer-wavelength visible and the NIR TM Bands 3, 5, and 7 provide more effective lithologic discrimination than the shorter-wavelength bands, due partly to deeper penetration of the longer-wavelength bands, resulting in more lithologically driven radiances. Shorter-wavelength TM Bands 1 and 2 are affected more by surficial weathering products including desert varnish which may or may not provide an indirect link to lithologic identity. Guidelines for lithologic analysis of volcanic terrains using Landsat TM imagery are outlined.

  12. An integrated study of reservoir-induced seismicity and Landsat imagery at Lake Kariba, Africa

    SciTech Connect

    Pavlin, G.B.; Langston, C.A.

    1983-04-01

    Seismological techniques combined with Landsat imagery were used to study the seismic activity near Lake Kariba in southern Africa. The activity began after construction of a reservoir. Under investigation since the 1930s, reservoir-induced seismicity (RIS) has been limited to reservoirs with a volume larger than 1.2 billion cu m. Attempts have been made to identify the fault plane orientation best correlated with RIS to understand the triggering mechanisms. Concatenated Landsat imagery from band 6 provided lineaments and constrained the fault parameter solutions. An occurrence of P and SH waveforms recorded during a 1963 6.0 Richter scale event served for identifying the faulting orientation, the seismic moments, source depth, and an estimation of the spatially integrated slip function at the source. The source depths were less than 10 km, and it is suggested that a Precambrian basement, separated by normal faults, was adjusting dynamically to the reservoir loads.

  13. Digital image correlation techniques applied to LANDSAT multispectral imagery

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

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

  14. 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.

  15. 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.

  16. Linear features determined from Landsat imagery in the Texas and Oklahoma panhandles

    USGS Publications Warehouse

    Cooley, M.E.

    1984-01-01

    A map (scale 1:500,000) shows the linear features determined from Landsat imagery in the Texas and Oklahoma panhandles. The linear features, sometimes called linear trends or lineaments, are not identified as to type or origin. Most probably represent fractures or fracture zones, which may affect the movement of water or other fluids through rocks. The linear features are classified as to length--less than 30 mi/mg and more than 30 mi/mg. (USGS)

  17. Mapping Giant Salvinia with Satellite Imagery and Image Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands)...

  18. 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.

  19. 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.

  20. 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.

  1. 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

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

    USGS Publications Warehouse

    Salamonowicz, P.H.

    1986-01-01

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

  3. 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.

  4. Techniques for the processing of remotely sensed imagery. [digital processing of satellite imagery

    NASA Technical Reports Server (NTRS)

    Deutsch, E. S.; Rosenfeld, A.

    1974-01-01

    The following techniques are considered for classifying low resolution satellite imagery: (1) Gradient operations; (2) histogram methods; (3) gray level detection; (4) frequency domain operations; (5) Hadamard transform in digital image matching; and (6) edge and line detection schemes.

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  6. 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).

  7. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  9. The development of an MSS satellite imagery classification expert system

    NASA Technical Reports Server (NTRS)

    Engle, S. W.

    1985-01-01

    Unsupervised image classification of Landsat MSS imagery entails a significant part of the remote sensing, image analysis effort. Expert systems, a technology developed in the field of artificial intelligence, offers the potential to automate this process, thus greatly increasing the efficiency with which an analyst can perform unsupervised image classification and making the knowledge of the image analyst available to a community of nonexperts. Such a system, under development at the NASA/Ames Research Center, is described and planned enhancements are discussed.

  10. 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.

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

    SciTech Connect

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

    1996-03-01

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

  12. 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.

  13. 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.

  14. 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.

  15. Generation of uniform chromaticity scale imagery from LANDSAT data

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

  16. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhao, J.; Ghedira, H.

    2013-12-01

    A large number of inland and offshore oil fields are located in the Arabian Gulf where about 25% of the world's oil is produced by the countries surrounding the Arabian Gulf region. Almost all of this oil production is shipped by sea worldwide through the Strait of Hormuz making the region vulnerable to environmental and ecological threats that might arise from accidental or intentional oil spills. Remote sensing technologies have the unique capability to detect and monitor oil pollutions over large temporal and spatial scales. Synoptic satellite imaging can date back to 1972 when Landsat-1 was launched. Landsat satellite missions provide long time series of imagery with a spatial resolution of 30 m. MODIS sensors onboard NASA's Terra and Aqua satellites provide a wide and frequent coverage at medium spatial resolution, i.e. 250 m and 500, twice a day. In this study, the capability of medium resolution MODIS and Landsat data in detecting and monitoring oil pollutions in the Arabian Gulf was tested. Oil spills and slicks show negative or positive contrasts in satellite derived RGB images compared with surrounding clean waters depending on the solar/viewing geometry, oil thickness and evolution, etc. Oil-contaminated areas show different spectral characteristics compared with surrounding waters. Rayleigh-corrected reflectance at the seven medium resolution bands of MODIS is lower in oil affected areas. This is caused by high light absorption of oil slicks. 30-m Landsat image indicated the occurrence of oil spill on May 26 2000 in the Arabian Gulf. The oil spill showed positive contrast and lower temperature than surrounding areas. Floating algae index (FAI) images are also used to detect oil pollution. Oil-contaminated areas were found to have lower FAI values. To track the movement of oil slicks found on October 21 2007, ocean circulations from a HYCOM model were examined and demonstrated that the oil slicks were advected toward the coastal areas of United Arab

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  6. 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.

  7. 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

  8. Development of methodology for the optimization of classification accuracy of Landsat TM/ETM+ imagery for supporting fast flood hydrological analysis

    NASA Astrophysics Data System (ADS)

    Alexakis, D. D.; Hadjimitsis, D. G.; Agapiou, A.; Retalis, A.; Themistocleous, K.; Michaelides, S.; Pashiardis, S.

    2012-04-01

    One of the important tools for detection and quantification of land-cover changes across catchment areas is the classification of multispectral satellite imagery. Land cover changes, may be used to describe dynamics of urban settlements and vegetation patterns as an important indicator of urban ecological environments. Several techniques have been reported to improve classification results in terms of land use discrimination and accuracy of resulting classes. The aim of this study is to improve classification results of multispectral satellite imagery for supporting flood risk assessment analysis in a catchment area in Cyprus (Yialias river). This paper describes the results obtained by integrating remote sensing techniques such as classification analysis and contemporary statistical analysis (maximum entropy) for detecting urbanization activities in a catchment area in Cyprus. The final results were incorporated in an integrated flood risk management model. This study aims to test different material samples in the Yialias region in order to examine: a) their spectral behavior under different precipitation rates and b) to introduce an alternative methodology to optimize the classification results derived from single satellite imagery with the combined use of satellite, spectroradiometric and precipitation data. At the end, different classification algorithms and statistical analysis are used to verify and optimize the final results such as object based classification and maximum entropy. The main aim of the study is the verification of the hypothesis that the multispectral classification accuracy is improved if the land surface humidity is high. This hypothesis was tested against Landsat derived reflectance values and validated with in-situ reflectance observations with the use of high spectral resolution spectroradiometers. This study aspires to highlight the potential of medium resolution satellite images such as those of Landsat TM/ETM+ for Land Use / Land cover

  9. 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

  10. 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.

  11. 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.

  12. Towards the objective analysis of clouds from satellite imagery data

    NASA Technical Reports Server (NTRS)

    Coakley, J. A., Jr.; Baldwin, D. G.

    1984-01-01

    It is suspected that clouds play a major role in climate dynamics. However, conclusive studies regarding the effects related to the cloud cover appear difficult because there is a lack of objective data. The present investigation is concerned with an objective scheme for deriving clouds and their properties from satellite imagery data for the oceans. The objective analysis makes use of the spatial coherence method for retrieving cloud cover from satellite imagery data. This method has advantages over other techniques often applied to imagery data. It is not necessary that clouds fill completely the observing instrument's field-of-view, and a priori or satellite derived knowledge of the cloud radiative properties is not needed.

  13. Comparison of Landsat MSS and TM imagery for long term forest land cover change assessment

    NASA Astrophysics Data System (ADS)

    Genc, Levent

    2003-10-01

    The main objective of this research is to determine forest cover change from 1975 to 2000 for a region in north Florida. In order to monitor long-term forest cover change for this project, Landsat MSS must be used with Landsat TM because Landsat MSS is the only datasets that is available for civilian use prior to the year of 1982. However, using these two different datasets in a project had been problematic and needed to be studied to obtain higher overall classification accuracy. Landsat MSS and TM classifications were achieved through a common approach. By increasing overall accuracy for both sensor types individually, images from these sensors will be more consistent. In order to achieve the main objective of this study, sixteen derived datasets were constructed and tested from March 24, 1986 Landsat MSS and Landsat TM imagery from the same area using low pass filtering, principal component Analysis (PCA), and tasseled cap transformation (TCT) to demonstrate the relationship between these two imageries. Similarities were 88.5% in best case. Results suggest that smoothing operations performed prior to classification improved the classification accuracy because they created a selection of homogeneous training sets. It was found that the smoothing operation performed prior to classification improved the classification accuracy by 7% compared to the original dataset classification. Performing the PCA and TCT to smoothed datasets also improved the classification accuracy by 4% compared to the smoothed datasets only. The first two principal components, PC1 and PC2, added to the first two indexes from TCT, BI and GI, were used to create new 4-band datasets for MSS and TM. These combinations of images were used to determine the forest land cover for the application site from the years 1975 to 2000. It was found that the determination of five land cover classes using these techniques produced moderate overall land cover classification accuracy ranging from 62.7% to 88

  14. 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

  15. [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

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

    NASA Technical Reports Server (NTRS)

    Crowe, M.

    1977-01-01

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

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

  19. 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.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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