Relevant bibliographies by topics / Landsat MSS satellite imagery

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  2. Dissertations / Theses
  3. Books
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Academic literature on the topic 'Landsat MSS satellite imagery'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Landsat MSS satellite imagery"

1

Dowdeswell, J. A., M. R. Gorman, Yu Ya Macheret, M. Yu Moskalevsky, and J. O. Hagen. "Digital comparison of high resolution Sojuzkarta KFA-1000 imagery of ice masses with Landsat and SPOT data." Annals of Glaciology 17 (1993): 105–12. http://dx.doi.org/10.1017/s0260305500012684.

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Russian satellite imagery of the polar regions has recently become available to western scientists through Sojuzkarta. The KFA-1000 photographic camera is of particular interest to glaciologists due to its high resolution (a nominal 5 m). Digitized photographic products from this instrument are compared with digital data from Landsat and SPOT series satellites for a partly glacierized area of northwest Spitsbergen. Comparison of KFA-1000 data with detailed maps of man-made structures at the settlement of Ny Ålesund demonstrates that the resolution of the photographic imagery is about 3 m, but scanner resolution limited our digital data to about 6 m. Significantly less detail can be resolved on Landsat TM imagery and Landsat MSS data fail to resolve any of the structures. KFA-1000 data are compared with Landsat TM and MSS images and SPOT HRV multispectral imagery for several tidewater glaciers in Spitsbergen. KFA-1000 imagery is of a significantly higher geometric resolution than the other sensors, allowing the clear identification of individual crevasses and other ice surface features. KFA-1000 scenes from 1985 and 1988 are used to measure ice marginal fluctuations for several northwest Spitsbergen glaciers, and the onset of a surge can also be identified. This imagery has a 60% overlap between scenes and the heighting accuracy of the stereoscopic data is calculated at 45 m. Radiometric analysis of KFA-1000 data is restricted to relative brightness values, since no absolute calibration is available. The photographic products appear speckled, and the range and standard deviation of normalized pixel brightness values over snow is greater than for equivalent Landsat TM data. The very high spatial resolution of the KFA-1000 camera is its principal attraction for glaciologists.
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Dowdeswell, J. A., M. R. Gorman, Yu Ya Macheret, M. Yu Moskalevsky, and J. O. Hagen. "Digital comparison of high resolution Sojuzkarta KFA-1000 imagery of ice masses with Landsat and SPOT data." Annals of Glaciology 17 (1993): 105–12. http://dx.doi.org/10.3189/s0260305500012684.

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Russian satellite imagery of the polar regions has recently become available to western scientists through Sojuzkarta. The KFA-1000 photographic camera is of particular interest to glaciologists due to its high resolution (a nominal 5 m). Digitized photographic products from this instrument are compared with digital data from Landsat and SPOT series satellites for a partly glacierized area of northwest Spitsbergen. Comparison of KFA-1000 data with detailed maps of man-made structures at the settlement of Ny Ålesund demonstrates that the resolution of the photographic imagery is about 3 m, but scanner resolution limited our digital data to about 6 m. Significantly less detail can be resolved on Landsat TM imagery and Landsat MSS data fail to resolve any of the structures. KFA-1000 data are compared with Landsat TM and MSS images and SPOT HRV multispectral imagery for several tidewater glaciers in Spitsbergen. KFA-1000 imagery is of a significantly higher geometric resolution than the other sensors, allowing the clear identification of individual crevasses and other ice surface features. KFA-1000 scenes from 1985 and 1988 are used to measure ice marginal fluctuations for several northwest Spitsbergen glaciers, and the onset of a surge can also be identified. This imagery has a 60% overlap between scenes and the heighting accuracy of the stereoscopic data is calculated at 45 m. Radiometric analysis of KFA-1000 data is restricted to relative brightness values, since no absolute calibration is available. The photographic products appear speckled, and the range and standard deviation of normalized pixel brightness values over snow is greater than for equivalent Landsat TM data. The very high spatial resolution of the KFA-1000 camera is its principal attraction for glaciologists.
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Johansen, Bernt, and Stein Rune Karlsen. "Monitoring vegetation changes on Finnmarksvidda, Northern Norway, using Landsat MSS and Landsat TM/ETM+ satellite images." Phytocoenologia 35, no. 4 (December 13, 2005): 969–84. http://dx.doi.org/10.1127/0340-269x/2005/0035-0969.

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Ferrigno, J. G., and W. G. Gould. "Substantial changes in the coastline of Antarctica revealed by satellite imagery." Polar Record 23, no. 146 (May 1987): 577–83. http://dx.doi.org/10.1017/s003224740000807x.

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ABSTRACTNoaa Avhrr and Landsat MSS imagery acquired between January and November 1986 has shown substantial changes in the Antarctic coastline near the Filchner Ice Shelf, Larsen Ice Shelf and Thwaites Glacier. In the Filchner Ice Shelf area some 11,500 km of ice calved from mid-April onward. In the Larsen Ice Shelf area two large bergs calved between February and August. The combined volume of ice from these two events equals approximately three years' normal calving from the entire Antarctic coastline. In the Thwaites Glacier area several changes appear to have occurred at the base of Thwaites Iceberg Tongue and Thwaites Glacier Tongue.
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Van Niekerk, Elna, and Luke Sandham. "Visual interpretation of ASTER satellite data, Part 1: Geologic mapping in the Cradle of Humankind World Heritage Site." Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 26, no. 3 (September 21, 2007): 177–95. http://dx.doi.org/10.4102/satnt.v26i3.132.

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Since the first earth observing satellite was launched in 1972, remote sensing has become a powerful tool in the arsenal of geoscientists. This satellite became known as Landsat 1 and carried the Multispectral Scanner (MSS) delivering imagery at a spatial resolution of 80, and spectral resolution from blue to near infrared. Ongoing satellite and sensor development to the end of the century produced the Landsat Thematic Mapper (TM) with improved spatial and spectral resolution, as well as the SPOT series of satellites delivering the highest spatial but limited spectral resolution. These developments culminated in the SPOT 4 (1998) and Landsat Enhanced Thematic Mapper (1999) sensors. While Landsat ETM in particular provided much improved spatial and spectral resolutions, on the basis of which a large amount of geoscientific remote sensing was conducted world wide, the data did not provide adequate spectral and spatial sensitivity to be optimally effective for geological mapping at the local scale. On 18 December 1999 the Terra platform was launched, carrying five remote sensing instruments, including ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer). ASTER consists of three separate instrument subsystems, each operating in a different spectral region, and using separate optical systems. These are the Visible and Very Near Infrared (VNIR) subsystem with a 15m-spatial resolution, the Short Wave Infrared (SWIR) subsystem with a 30m-spatial resolution and the Thermal Infrared (TIR) subsystem with a 90m-spatial resolution. ASTER effectively offers an improvement on Landsat MSS, Landsat TM, Landsat ETM+ and SPOT spectral and spatial resolutions. Given the paucity of published research on geological remote sensing at the local scale in South Africa, and particularly on the use of ASTER for geological mapping in South Africa, it is imperative that the value of ASTER be investigated. This article reports on the improved detail and scale achieved in the mapping of litho-stratigraphy, geological structures and mining-related features by the visual interpretation of processed ASTER images. ASTER imagery obtained from the EOS website was subjected to a range of image enhancement and analysis techniques including colour composites, band ratios, normalised difference indices, regression and decorrelation, in order to obtain optimal visual interpretability. Eight images thus obtained could be used for visual analysis, and it became evident that litho-stratigraphy, faults, fracture zones and elements of the regional seam system, as well as remnants of mining activities, were readily identifiable. Some of these were in accordance with the most recent and accurate geological map of the area, but many of them had apparently not been mapped. These features were annotated and were verified by field checks. In all cases the accuracy of detection and location from satellite imagery was confirmed on the ground. The improved detail and accuracy obtained by visual interpretation of processed ASTER satellite data for mapping a section of the Cradle of Humankind World Heritage Site demonstrated the potential value of this data for a variety of other geoscience applications. It appears that the improved accuracy can be ascribed jointly to the higher spatial and spectral resolution provided by ASTER data.
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Deguchi, C., and S. Sugio. "Estimations for Percentage of Impervious Area by the Use of Satellite Remote Sensing Imagery." Water Science and Technology 29, no. 1-2 (January 1, 1994): 135–44. http://dx.doi.org/10.2166/wst.1994.0659.

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This study aims to evaluate the applicability of satellite imagery in estimating the percentage of impervious area in urbanized areas. Two methods of estimation are proposed and applied to a small urbanized watershed in Japan. The area is considered under two different cases of subdivision; i.e., 14 zones and 17 zones. The satellite imageries of LANDSAT-MSS (Multi-Spectral Scanner) in 1984, MOS-MESSR(Multi-spectral Electronic Self-Scanning Radiometer) in 1988 and SPOT-HRV(High Resolution Visible) in 1988 are classified. The percentage of imperviousness in 17 zones is estimated by using these classification results. These values are compared with the ones obtained from the aerial photographs. The percent imperviousness derived from the imagery agrees well with those derived from aerial photographs. The estimation errors evaluated are less than 10%, the same as those obtained from aerial photographs.
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Dede, Moh, Millary Agung Widiawaty, Nurhanifah Nurhanifah, Arif Ismail, Ajeng Randhita Prabatiwakya Artati, Amniar Ati, and Yanuar Rizky Ramadhan. "Estimasi Perubahan Kualitas Udara Berbasis Citra Satelit Penginderaan Jauh Di Sekitar PLTU Cirebon." Jambura Geoscience Review 2, no. 2 (June 14, 2020): 78–87. http://dx.doi.org/10.34312/jgeosrev.v2i2.5951.

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Steam power plant construction and operation is an effort to meet electricity needs. In Indonesia, two steam power plants were built and changed the landscape in Cirebon. The presence of Cirebon steam power plants has disturbed the community and potential to decrease air quality. This study aims to estimate air quality changes around the power plants based on remote sensing satellite imageries. The main data in this study obtained from Landsat-8 OLI (2019) and Landsat-7 ETM (2004) satellite imageries were processed with four parameters of air quality algorithm namely PM10, CO, SO2, and NOx on AOI with ranging of 2000 m from the source point. Validation uses comparative data from MODIS and Sentinel-2 MSS satellite imageries in the same period. Changes analysis in air quality used the Mann-Whitney method (U-Test). This research shows that the Landsat series satellite imagery is suitable to be used as the main data for estimating air quality because it has a similar pattern to comparable data. The Cirebon PLTU operation caused a significant increase in CO levels of 1.25 mg/l on a wide range. In other air quality parameters such as PM10, SO2 and NOx were decreased.
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Hall, R. J., A. R. Kruger, W. C. Moore, J. Scheffer, and S. J. Titus. "A Statistical Evaluation of LANDSAT TM and MSS Data for Mapping Forest Cutovers." Forestry Chronicle 65, no. 6 (December 1, 1989): 441–49. http://dx.doi.org/10.5558/tfc65441-6.

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The cutover area and boundary placement mapping accuracies from currently used air photo techniques and LANDSAT TM and MSS imagery were determined for Alberta forestry conditions. Overall area accuracies for the air photo techniques. LANDSAT TM, and MSS images were 86.7%, 89.5%, and 86.9%, respectively. The influence of increasing accuracy with increasing cutover size, however, must be kept in perspective. Although interpreted cutover areas were generally smaller compared with their actual areas, the deviation was systematic and could therefore be corrected by regression techniques. Overall boundary placement errors for air photo techniques. LANDSAT TM, and MSS images were 30.1, 24.9, and 38.3 m, respectively. Most of the LANDSAT TM errors were in the 20-m range and were within 5 m of the target 15-20 m desired by the Alberta Forest Service. Improvements to this may be achieved by using larger scale satellite images. The base map scale of 1:20 000 was a limiting factor to this study, however, as it was too small with both plotting errors and pen line widths contributing to existing map errors. LANDSAT TM images offered a 12:1 cost savings in data acquisition and are more efficient in comparison with conventional air photos. Use of either medium scale air photos or LANDSAT TM images can be recommended depending on the level of timber commitment accuracy requirements and is presented in the paper as an operational cutover update mapping strategy. Keywords: Forest inventory, update, LANDSAT, change detection, mapping, accuracy analysis, remote sensing.
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Onuigbo, I. C., and J. Y. Jwat. "Change Detection Analysis Using Surveying and Geoinformatics Techniques." Nigerian Journal of Environmental Sciences and Technology 2, no. 1 (March 2018): 28–38. http://dx.doi.org/10.36263/nijest.2018.01.0051.

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The study was on change detection using Surveying and Geoinformatics techniques. For effective research study, Landsat satellite images and Quickbird imagery of Minna were acquired for three periods, 2000, 2005 and 2012. The research work demonstrated the possibility of using Surveying and Geoinformatics in capturing spatial-temporal data. The result of the research work shows a rapid growth in built-up land between 2000 and 2005, while the periods between 2005 and 2012 witnessed a reduction in this class. It was also observed that change by 2020 may likely follow the trend in 2005 – 2012 all things being equal. Built up area may increase to 11026.456 hectares, which represent 11% change. The study has shown clearly the extent to which MSS imagery and Landsat images together with extensive ground- truthing can provide information necessary for land use and land cover mapping. Attempt was made to capture as accurate as possible four land use and land cover classes as they change through time.
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Boyce, Mark, Evelyn Merrill, and Ronald Marrs. "Relationships between Climatic Variation and Grassland Biomass on the Northern Range of Yellowstone National Park." UW National Parks Service Research Station Annual Reports 11 (January 1, 1987): 153–59. http://dx.doi.org/10.13001/uwnpsrc.1987.2655.

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Summer range is not thought to be limiting to elk because abundant, high quality forage is available whereas a shortage of forage usually exists on elk winter ranges. Nevertheless, summer nutrition and fat reserves acquired on summer ranges influence growth, survival and reproduction of ungulates (Klein 1965, Verme 1963, 1965, Julander et al. 1961). The enormous area of summer range for the Northern Yellowstone elk herd renders detailed field surveys impractical. This study was initiated to evaluate the feasibility of using LANDSAT satellite imagery to (1) characterize vegetation communities on summer range from LANDSAT multispectral scanner (MSS) data and digitized vegetation maps of Yellowstone National Park, (2) predict plant production within grassland types and (3) correlate elk population characteristics with fluctuations in plant production and weather.
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Dissertations / Theses on the topic "Landsat MSS satellite imagery"

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Osburg, Thomas, and n/a. "Change detection in the Upper Yarra Valley using Landsat MSS satellite imagery." University of Canberra. Resource & Environmental Science, 1993. http://erl.canberra.edu.au./public/adt-AUC20060823.170057.

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Genc, Levent. "Comparison of Landsat MSS and TM imagery for long term forest land cover change assessment." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0001034.

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Morton, David Dean. "Land Cover of Virginia From Landsat Thematic Mapper Imagery." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36851.

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Knowledge of land cover is important in a variety of natural resources applications. This knowledge becomes more powerful within the spatial analysis capabilities of a geographic information system (GIS). This thesis presents a digital land cover map of Virginia, produced through interpretation of 14 Landsat Thematic Mapper (TM) scenes, circa 1991-1993. The land cover map, which has a 30m pixel size, was produced entirely with personal computers. Hypercluster aggregation, an unsupervised classification method, was used when hazy and mountainous conditions were not present. A haze correction procedure by Lavreau (1991) was used, followed by a supervised classification on coastal areas. An enhanced supervised classification, focusing on topographic shading, was performed in the mountains. Color infrared photographs, digital maplets, expert knowledge, and other maps were used as training data. Aerial videography transects were flown to acquire reference data. Due to the spatial inaccuracies inherent in the videography reference data, only homogeneous land cover areas were used in the accuracy assessment. The results of the overall accuracy for each scene determined the ordering of scenes within the statewide land cover mosaic (i.e., scenes with higher accuracy had a higher proportion of area represented). An accuracy assessment was then performed on the statewide land cover mosaic. An overall accuracy of 81.8% and a Kappa statistic of 0.81 resulted. A discussion of potential reasons for land cover class confusion and suggestions for classification improvements are presented. Overall deciduous forest was the most common land cover in Virginia. Herbaceous areas accounted for 20% of the land area, which was the second largest. Mixed forest and coastal wetlands were the cover types with the least area, each under 3%.
Master of Science
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Walker, Jessica. "Analysis of Dryland Forest Phenology using Fused Landsat and MODIS Satellite Imagery." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/39403.

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This dissertation investigated the practicality and expediency of applying remote sensing data fusion products to the analysis of dryland vegetation phenology. The objective of the first study was to verify the quality of the output products of the spatial and temporal adaptive reflectance fusion method (STARFM) over the dryland Arizona study site. Synthetic 30 m resolution images were generated from Landsat-5 Thematic Mapper (TM) data and a range of 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance datasets and assessed via correlation analysis with temporally coincident Landsat-5 imagery. The accuracy of the results (0.61 < R2 < 0.94) justified subsequent use of STARFM data in this environment, particularly when the imagery were generated from Nadir Bi-directional Reflectance Factor (BRDF)-Adjusted Reflectance (NBAR) MODIS datasets. The primary objective of the second study was to assess whether synthetic Landsat data could contribute meaningful information to the phenological analyses of a range of dryland vegetation classes. Start-of-season (SOS) and date of peak greenness phenology metrics were calculated for each STARFM and MODIS pixel on the basis of enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) time series over a single growing season. The variability of each metric was calculated for all STARFM pixels within 500 m MODIS extents. Colorado Plateau Pinyon Juniper displayed high amounts of temporal and spatial variability that justified the use of STARFM data, while the benefit to the remaining classes depended on the specific vegetation index and phenology metric. The third study expanded the STARFM time series to five years (2005-2009) to examine the influence of site characteristics and climatic conditions on dryland ponderosa pine (Pinus ponderosa) forest phenological patterns. The results showed that elevation and slope controlled the variability of peak timing across years, with lower elevations and shallower slopes linked to higher levels of variability. During drought conditions, the number of site variables that controlled the timing and variability of vegetation peak increased.
Ph. D.
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Davies, Diane. "Estimation of deforestation east of the Rio Grande, Bolivia, using Landsat satellite imagery." Thesis, Cranfield University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.580396.

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English, Amanda M. "Land Cover Change Analysis of the Mississippi Gulf Coast from 1975 to 2005 using Landsat MSS and TM Imagery." ScholarWorks@UNO, 2011. http://scholarworks.uno.edu/td/1306.

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The population, employment and housing units along the Gulf Coast of Mississippi have been increasing since the 1970s through the 2000s. In this study, an overall increasing trend in land cover was found in developed land area near interstates and highways along all three coastal counties. A strong positive correlation was observed in Hancock County between developed land and population and developed land and housing units. A strong negative correlation was observed between vegetation and housing units. Weak positive correlations were found in Harrison County between developed land and population, marsh and population, and marsh and housing units. A weak positive correlation was found in Jackson County between bare soil and population. Several study limitations such as unsupervised classification and misclassification are discussed to explain why a strong correlation was not found in Harrison and Jackson Counties.
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Razzano, Mandy L. "Monitoring Algal Production in Akron Water Supply Reserviors in Northeast Ohio Using Satellite Imagery." Kent State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=kent1310178613.

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Goggins, Gary Daniel. "IMPACTS OF CITY SIZE AND VEGETATION COVERAGE ON THE URBAN HEAT ISLAND USING LANDSAT SATELLITE IMAGERY." MSSTATE, 2009. http://sun.library.msstate.edu/ETD-db/theses/available/etd-04032009-125846/.

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The Urban Heat Island (UHI) effect is a function of excess heating of man-made impermeable surfaces and structures. Using Landsat satellite imagery along with its Thermal-Infrared (TIR) band, the UHI of Starkville, MS; Birmingham, AL; and Atlanta, GA were analyzed. Unsupervised classification of the Landsat imagery and temperature extraction from the TIR band revealed city size and amount of high-density urban land use are directly related to UHI intensity and higher than average surface temperatures. Vegetation analysis within the three study area cities, however, revealed an average surface temperature reduction of 2 °C with only 15% forest coverage within a 1km2 area. Results obtained can be useful as a potential monitoring tool that can characterize relationships between amount and percentage of urban tree cover and surface temperature. The information can be utilized by city planners and others who are interested in mitigating UHI effects in the ever- increasing urban America.
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Theel, Ryan T. "A 15-year evaluation of the Mississippi and Alabama coastline barrier islands, using Landsat satellite imagery." Master's thesis, Mississippi State : Mississippi State University, 2007. http://library.msstate.edu/etd/show.asp?etd=etd-06282007-120152.

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Bartholomew, Paul J. "Mapping and Modeling Chlorophyll-a Concentrations in the Lake Manassas Reservoir Using Landsat Thematic Mapper Satellite Imagery." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/32691.

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Carried out in collaboration with the Occoquan Water Monitoring Lab, this thesis presents the results of research that sought to ascertain the spatial distribution of chlorophyll-a concentrations in the Lake Manassas Reservoir using a combination of Landsat TM satellite imagery and ground based field measurements. Images acquired on May 14, 1998 and March 8, 2000 were analyzed with chlorophyll-a measurements taken on 13, 1998 and March 7, 2000. A ratio of Landsat TM band 3: Landsat Band 4 was used in a regression with data collected at eight water quality monitoring stations run by the Occoquan Watershed Monitoring Lab. Correlation coefficients of 0.76 for the 1998 data and 0.73 for the 2000 data were achieved. Cross validation statistical analysis was used to check the accuracy of the two models. The standard error and error of the estimate were reasonable for the models from both years. In each instance, the ground data was retrieved approximately 24 hours before the Landsat Image acquisition and was a potential source of error. Other sources of error were the small sample size of chlorophyll-a concentration measurements, and the uncertainty involved in the location of the water quality sampling stations.
Master of Science
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Books on the topic "Landsat MSS satellite imagery"

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McHale, Ryan K. Landsat and its valuable role in satellite imagery of earth. Hauppauge, NY: Nova Science Publisher's, Inc., 2011.

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Radhi, Moutaiz Ibrahim. The production of a map of moorland vegetation using Landsat MSS imagery. Norwich: University ofEast Anglia, 1993.

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F. B. van der Laan. Quantitative updating of land use information on 1:50,000 scale topographic maps using SPOT Landsat Thematic Mapper imagery. Amsterdam: National Aerospace Laboratory, 1989.

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Chen, Jing. BOREAS RSS-7 Landsat TM LAI images of the SSA and NSA. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Chen, Jing. BOREAS RSS-7 Landsat TM LAI images of the SSA and NSA. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Chen, Jing. BOREAS RSS-7 Landsat TM LAI images of the SSA and NSA. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Pitblado, J. Roger. The Mapping of lake surface water characteristics of northeastern Ontario using satellite imagery. Toronto, Ont: Queen's Printer for Ontario, 1992.

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J, Curran Paul. Seasonal LAI in slash pine estimated with Landsat TM. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1990.

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S, Jodoin Richard, Minnerick Russel J, Geological Survey (U.S.), and Michigan. Dept. of Natural Resources and Environment, eds. Predicting lake trophic state by relating Secchi-disk transparency measurements to Landsat-satellite imagery for Michigan inland lakes, 2003-05 and 2007-08. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2011.

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Landsat-4 Science Characterization Early Results Symposium (1983 Greenbelt, Md.). Landsat-4 science characterization early results: Proceedings of the Landsat-4 Science Characterization Early Results Symposium, February 22-24, 1983, held at NASA Goddard Space Flight Center, Greenbelt, Maryland. Edited by Barker John L, United States. National Aeronautics and Space Administration, and Landsat-4 Early Results Symposium (1983 : Greenbelt, Md.). Washington, D.C: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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Book chapters on the topic "Landsat MSS satellite imagery"

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Charvát, Karel, Vojtěch Lukas, Karel Charvát, and Šárka Horáková. "Delineation of Management Zones Using Satellite Imageries." In Big Data in Bioeconomy, 235–45. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_18.

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AbstractThe chapter describes the development of a platform for mapping crop status and long-time trends by using EO data as a support tool for fertilizing and crop protection. The main focus of the pilot is to monitor cereal fields by high-resolution satellite imagery data (Landsat 8, Sentinel 2) and delineation of management zones within the fields for variable rate application of fertilizers. The first part of the paper is focused on analysis of strategies for recommendations derived from satellite data. The second part is focused on development of a software application with the goal to offer farmers a GIS portal. Here, users can monitor their fields from EO data, based on the specified period and select cloudless scenesfor further analysis. The tool supports collaborative communication between farmers and advisors.
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Younas, Sana, Mukhtar Ahmed, and Naeem Abbas Malik. "Forecasting of Rainfed Wheat Yield in Pothwar Using Landsat 8 Satellite Imagery and DSSAT." In Systems Modeling, 261–93. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4728-7_9.

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Fichera, Carmelo Riccardo, Giuseppe Modica, and Maurizio Pollino. "Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics." In Geographic Information Analysis for Sustainable Development and Economic Planning, 228–44. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-1924-1.ch016.

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One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.
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Maruthi Sridhar, Balaji Bhaskar, and Robert K. "Mapping and Estimation of Chemical Concentrations in Surface Soils using LANDSAT TM Satellite Imagery." In Satellite Communications. Sciyo, 2010. http://dx.doi.org/10.5772/9990.

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5

Kosa, Preeyaphorn. "The Effect of Temperature on Actual Evapotranspiration based on Landsat 5 TM Satellite Imagery." In Evapotranspiration. InTech, 2011. http://dx.doi.org/10.5772/14012.

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6

Anyamba, Assaf, and Compton J. Tucker. "Monitoring Drought Using Coarse Resolution Polar-Orbiting Satellite Data." In Monitoring and Predicting Agricultural Drought. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780195162349.003.0012.

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There are two distinct categories of remotely sensed data: satellite data and aerial data or photographs. Unlike aerial photographs, satellite data have been routinely available for most of the earth’s land areas for more than two decades and therefore are preferred for reliably monitoring global vegetation conditions. Satellite data are the result of reflectance, emission, and/or back scattering of electromagnetic energy from earth objects (e.g., vegetation, soil, and water). The electromagnetic spectrum is very broad, and only a limited range of wavelengths is suitable for earth resource monitoring and applications. The gaseous composition (O2, O3, CO2, H2O, etc.) of the atmosphere, along with particulates and aerosols, cause significant absorption and scattering of electromagnetic energy over some regions of the spectrum. This restricts remote sensing of the earth’s surface to certain “atmospheric windows,” or regions in which electromagnetic energy can pass through the atmosphere with minimal interference. Some such windows include visible, infrared, shortwave, thermal, and microwave ranges of the spectrum. The shortwave-infrared (SWIR) wavelengths are sensitive to moisture content of vegetation, whereas the thermal-infrared region is useful for monitoring and detecting plant canopy stress and for modeling latent and sensible heat fluxes. Thermal remote sensing imagery is acquired both during the day and night, and it measures the emitted energy from the surface, which is related to surface temperatures and the emissivity of surface materials. This chapter focuses on the contribution of visible and infrared wavelengths to global drought monitoring, and chapter 6 discusses visible, infrared, and thermal wave contributions. Under microwave windows, the satellite data can be divided into two categories: active microwave and passive microwave. Chapters 7 and 8 describe applications of passive and active microwave remote sensing to drought monitoring, respectively. Early use of satellite data was pioneered by the Landsat series originally known as the Earth Resource Technology Satellite (ERTS; http://landsat7. usgs.gov/index.php). Landsat was the first satellite specifically designed for broad-scale observation of the earth’s land surface.
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Tarantino, Eufemia, Antonio Novelli, Mariella Aquilino, Benedetto Figorito, and Umberto Fratino. "Comparing the MLC and JavaNNS Approaches in Classifying Multi-Temporal LANDSAT Satellite Imagery over an Ephemeral River Area." In Civil and Environmental Engineering, 1398–415. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9619-8.ch063.

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This chapter analyzes two pixel-based classification approaches to support the analysis of land cover transformations based on multitemporal LANDSAT sensor data covering a time space of about 24 years. The research activity presented in this paper was carried out using Lama San Giorgio (Bari, Italy) catchment area as a study case, being this area prone to flooding as proved by its geological and hydrological characteristics and by the significant number of floods occurred in the past. Land cover classes were defined in accordance with on the CN method with the aim of characterizing land use based on attitude to generate runoff. Two different classifiers, i.e. Maximum Likelihood Classifier (MLC) and Java Neural Network Simulator (JavaNNS) models, were compared. The Artificial Neural Networks (ANN) approach was found to be the most reliable and efficient when lacking ground reference data and a priori knowledge on input data distribution.
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8

Horning, Ned, Julie A. Robinson, Eleanor J. Sterling, Woody Turner, and Sacha Spector. "Protected area design and monitoring." In Remote Sensing for Ecology and Conservation. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780199219940.003.0020.

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Researchers interested in remote locations have developed monitoring schemes, sometimes called “Watchful Eye” monitoring, that use a time series of remotely sensed images to assess changes over time to a protected area or habitat. For instance, the European Space Agency (ESA) and UNESCO have set up repeat analyses of satellite imagery for World Heritage sites. The first area for which they developed this technique was the habitat of the critically endangered mountain gorilla (Gorilla berengei berengei) in the Virunga Mountains in Central Africa, including the Bwindi and Mgahinga National Parks in Uganda, the Virunga and Kahuzi-Biega National Parks in the Democratic Republic of Congo, and the trans-boundary Volcanoes Conservation Area. The project developed detailed maps of these inaccessible zones so that protected area managers can monitor the gorilla habitat. Previously, available maps were old and inaccurate (at times handmade), did not completely cover the range of the gorillas, and did not cross national boundaries. Because there was no systematic information from the ground regarding changes over time, researchers also used remotely sensed data to complete change detection analyses over the past two decades. Using both optical (Landsat series) and radar (ENVISAT ASAR) satellite data, researchers were able to quantify rates of deforestation between 1990 and 2003 and relate these rates to human migration rates into the area resulting from regional political instability. Researchers constructed the first digital base maps of the areas, digital elevation models (DEMs), and updated vegetation and land use maps. They faced significant problems in both field and laboratory activities, including lack of existing ground data, dense vegetation cover, and fairly continuous cloud cover. They therefore used a combination of ESA ENVISAT ASAR as well as Landsat and ESA Medium Resolution Imaging Spectrometer (MERIS) optical data. The radar images allowed them to quantify elevation and distances between trees and homes. Landsat and MERIS data helped identify forest cover types, with Landsat providing finer-scale images at less frequent intervals and MERIS serving lower-resolution images more frequently.
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9

Chrysoulakis, Nektarios, Poulicos Prastacos, and Constantinos Cartalis. "Development of a Decision Support Tool for Technological Risk Management with Remote Sensing and GIS." In Information Systems for Sustainable Development, 342–53. IGI Global, 2005. http://dx.doi.org/10.4018/978-1-59140-342-5.ch022.

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In this study, a GIS based decision support tool is proposed for the support of technological risk management by integrating moderate and high spatial resolution satellite imagery with in-situ vector data. The Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA satellites has been used for the detection of fire as well as for the detection and monitoring of plumes caused by major technological accidents. The Thematic Mapper (TM) on board the Landsat satellite has been used for the depiction of the urban areas and the main road network as well as for the estimation of the spatial distribution of vegetation in the study area. A major technological accident scenario was developed for the broader area of Athens (Greece) in order to present the functionality of the GIS tool for the support of decision making during the crisis, as well as for the assessment of the accident’s impact on the natural and human environment.
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Whitesides, Clayton J., and Matthew H. Connolly. "Estimating Fractional Snow Cover in Mountain Environments with Fuzzy Classification." In Geographic Information Systems, 1953–73. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2038-4.ch116.

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The disproportionate amount of water runoff from mountains to surrounding arid and semiarid lands has generated much research in snow water equivalent (SWE) modeling. A primary input in SWE models is snow covered area (SCA) which is generally obtained via satellite imagery. Mixed pixels in alpine snow studies complicate SCA measurements and can reduce accuracy. A simple method was developed to estimate fractional snow cover using freely available Landsat and data derived from DEMs, commercial and free software, as well as fuzzy classification and recursive partitioning. The authors attempted to develop a cost effective technique for estimating fractional snow cover for resource and recreation managers confined by limited budgets and resources. Results indicated that the method was non-sensitive (P = 0.426) to differences in leaf area index and solar radiation between 4 March 2000 and 13 March 2003. Fractional snow cover was predicted consistently despite variation in model parameters between years, indicating that the developed method may be a viable way for monitoring fractional snow cover in mountainous areas where capital and resources are limited.
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Conference papers on the topic "Landsat MSS satellite imagery"

1

Civco, Daniel, Anna Chabaeva, and Jason Parent. "KH-series satellite imagery and Landsat MSS data fusion in support of assessing urban land use growth." In SPIE Europe Remote Sensing, edited by Ulrich Michel and Daniel L. Civco. SPIE, 2009. http://dx.doi.org/10.1117/12.830943.

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2

Elkafrawy, Sameh, Sameh Elkafrawy, Akram Soliman, Akram Soliman, Mohamed Bek, and Mohamed Bek. "EVALUATING SHORELINE, URBAN AND ROADS CHANGES IN THE HURGHADA AREA, EGYPT, USING MULTISPECTRAL SATELLITE IMAGES." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.31519/conferencearticle_5b1b9422c50d28.22324330.

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The rapid urban development in the Hurghada area since the 1980s has dramatically enhanced the potential impact of human activities. To inventory and monitor this urban development effectively, remote sensing provides a viable source of data from which updated land cover information can be extracted efficiently and cheaply. In this study, data from three satellite datasets, Landsat Thematic Mapper (Landsat 5 TM), Landsat Enhanced Thematic Mapper Plus (Landsat 7 ETM+) and Terra/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), acquired during 1987, 2000 and 2005, respectively, were used to detect and evaluate Hurghada's urban expansion. Five change detection techniques were tested to detect areas of change. The techniques considered were image differencing, image ratioing, image overlay, multidate principal component analysis (PCA) and post-classification comparison. The post-classification comparison was found to be the most accurate procedure and produced three land use/land cover (LULC) maps of the years 1987, 2000 and 2005 with overall accuracies of 87.8%, 88.9% and 92.0%, respectively. The urban expansion analysis revealed that the built-up area has expanded by 40 km2 in 18 years (1987–2005). In addition, 4.5 km2 of landfill/sedimentation was added to the sea as a result of the coastal urban development and tourist activities. The booming coastal tourism and population pressure were considered to be the main factors driving this expansion, and some natural and artificial constraints constrained the physical shape of the city. The expansion is represented by urban fringe development, linear, infill and isolated models. Topography, lithology and structures were also analysed as possible factors that influenced the expansion. The understanding of the spatial and temporal dynamics of Hurghada's urban expansion is the cornerstone for formulating a view about the future urban uses and for making the best use of the limited resources that are available [1]. A Landsat 5 Thematic Mapper (TM) image of 1987 and a Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image of 2000 were used to examine changes in land use/land cover (LULC) around Hurghada, Egypt, and changes in the composition of coral reefs offshore. Prior to coral reef bottom type classification, the radiance values were transformed to depth invariant bottom indices to reduce the effect of the water column. Subsequently, a multi component change detection procedure was applied to these indices to define changes. Preliminary results showed significant changes in LULC during the period 1987–2000 as well as changes in coral reef composition. Direct impacts along the coastline were clearly shown, but it was more difficult to link offshore changes in coral reef composition to indirect impacts of the changing LULC. Further research is needed to explore the effects of the different image processing steps, and to discover possible links between indirect impacts of LULC changes and changes in the coral reef composition [2]. Knowledge and detecting impacts of human activities on the coastal ecosystem is an essential management requirement and also very important for future and proper planning of coastal areas. Moreover, documentation of these impacts can help in increasing public awareness about side effects of unsustainable practices. Analysis of multidate remote sensing data can be used as an effective tool in environmental impact assessment (EIA). Being synoptic and frequent in coverage, multidate data from Landsat and other satellites provide a reference record and bird’s eye viewing to the environmental situation of the coastal ecosystem and the associated habitats. Furthermore, integration of satellite data with field observations and background information can help in decision if a certain activity has caused deterioration to a specific habitat or not. The present paper is an attempt to utilize remote sensing data for assessment impacts of some human activities on the major sensitive habitats of the north western Egyptian Red Sea coastal zone, definitely between Ras Gemsha and Safaga. Through multidate change analysis of Landsat data (TM & ETM+ sensors), it was possible to depict some of the human infringements in the area and to provide, in some cases, exclusive evidences for the damaging effect of some developmental activities [3]. The coastline of Hurghada has experienced considerable environmental stress from tourist and residential recreational activities. Uncontrolled tourist development has already caused substantial damage to inshore reefs and imbalance in the hydrodynamic pattern of the coastal sediments. The objective of this paper is to investigate environmental changes using multitemporal, multispectral satellite data to identify changes at Hurghada caused by anthropogenic influences. Major detected changes include resort beaches, protection structures and landfill areas; these changes are mainly due to human intervention. Two Landsat Thematic Mapper (TM) images acquired in 1984 and 1997 are used for this analysis. The landfill areas formed during this period are calculated at about 2.15 Km2 . Whilst landfill creates new inexpensive land and improves access to the sea for tourists, it is the cause of environmental problems. In addition, land-use/land-cover and beach changes are determined over the 13-year period [4]. The Red Sea coastal zone is characterized by its sensitive, fragile, unique natural resources and habitats. In the Hurghada coastal region, major changes in the tourism industry have taken place in the last few decades. The detection of environmental changes, in a selected site of the Red Sea coastal zone, will be helpful to protect and develop this coastal environment. A methodology for separating natural and man-made changes in satellite images was developed. It was based on the following assumptions: (1) slow changes, which occur within the range of the class reflectance, represent a natural change rather than an anthropogenic one; (2) natural changes tend to be in the same land-use/land-cover class in each date, i.e. slow changes in the reflectance, not leading to changes in the type of land-use/land-cover class from the master image to the destination one; and (3) rapid changes in the reflectance of the Earth's objects are usually related to anthropogenic activities. This technique is used to identify and assess changes along the coast of Hurghada and Ras Abu Soma, the Red Sea. Results indicate serious human impacts and the necessity for control measures and monitoring. Recommendations are presented [5]. The rapid urban development of the Hurghada area began in early 1980 to build villages and huge tourist resorts and this has continued urban development and subsequent land filling and dredging of the shoreline and the destruction of coral so far. These coastal developments have led to an increase in shoreline land filling and dredging. Despite all the environmental laws of the organization to reduce infringement on the shoreline, the abuses are still ongoing. Change detection analysis using remote sensing is a very good tool to monitor the changes condition in urban development and shoreline. Four sensors was used in this study, three of them are, Landsat Multispectral Scanner (Landsat 1 MSS), Landsat Thematic Mapper (Landsat 5 TM), Landsat Enhanced Thematic Mapper Plus (Landsat 7 ETM+) and the another one is SPOT XS 4 (Originally Système Probatoire de l’Observation de la Terre), acquired during 1972, 1984, 1992, 2004 and 2011, respectively, were used to detect and evaluate Hurghada’s urban expansion and shoreline changes. After the images have been geometrically, radio-metrically and atmospherically corrected using ENVI 5.0 software, the digital number was transformed to the reflectance values and the images were ready to change detection process with the integration of geographic information system using Arc GIS 10 software. The results show that changes during the 39 years of the shoreline is 6.29 km2, (5.65 km2 accretion and 0.64 km2 erosion) and urban development is 16.47 km2 the road network is the 8.738 km2.
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3

Elkafrawy, Sameh, Sameh Elkafrawy, Akram Soliman, Akram Soliman, Mohamed Bek, and Mohamed Bek. "EVALUATING SHORELINE, URBAN AND ROADS CHANGES IN THE HURGHADA AREA, EGYPT, USING MULTISPECTRAL SATELLITE IMAGES." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.21610/conferencearticle_58b4316250187.

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The rapid urban development in the Hurghada area since the 1980s has dramatically enhanced the potential impact of human activities. To inventory and monitor this urban development effectively, remote sensing provides a viable source of data from which updated land cover information can be extracted efficiently and cheaply. In this study, data from three satellite datasets, Landsat Thematic Mapper (Landsat 5 TM), Landsat Enhanced Thematic Mapper Plus (Landsat 7 ETM+) and Terra/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), acquired during 1987, 2000 and 2005, respectively, were used to detect and evaluate Hurghada's urban expansion. Five change detection techniques were tested to detect areas of change. The techniques considered were image differencing, image ratioing, image overlay, multidate principal component analysis (PCA) and post-classification comparison. The post-classification comparison was found to be the most accurate procedure and produced three land use/land cover (LULC) maps of the years 1987, 2000 and 2005 with overall accuracies of 87.8%, 88.9% and 92.0%, respectively. The urban expansion analysis revealed that the built-up area has expanded by 40 km2 in 18 years (1987–2005). In addition, 4.5 km2 of landfill/sedimentation was added to the sea as a result of the coastal urban development and tourist activities. The booming coastal tourism and population pressure were considered to be the main factors driving this expansion, and some natural and artificial constraints constrained the physical shape of the city. The expansion is represented by urban fringe development, linear, infill and isolated models. Topography, lithology and structures were also analysed as possible factors that influenced the expansion. The understanding of the spatial and temporal dynamics of Hurghada's urban expansion is the cornerstone for formulating a view about the future urban uses and for making the best use of the limited resources that are available [1]. A Landsat 5 Thematic Mapper (TM) image of 1987 and a Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image of 2000 were used to examine changes in land use/land cover (LULC) around Hurghada, Egypt, and changes in the composition of coral reefs offshore. Prior to coral reef bottom type classification, the radiance values were transformed to depth invariant bottom indices to reduce the effect of the water column. Subsequently, a multi component change detection procedure was applied to these indices to define changes. Preliminary results showed significant changes in LULC during the period 1987–2000 as well as changes in coral reef composition. Direct impacts along the coastline were clearly shown, but it was more difficult to link offshore changes in coral reef composition to indirect impacts of the changing LULC. Further research is needed to explore the effects of the different image processing steps, and to discover possible links between indirect impacts of LULC changes and changes in the coral reef composition [2]. Knowledge and detecting impacts of human activities on the coastal ecosystem is an essential management requirement and also very important for future and proper planning of coastal areas. Moreover, documentation of these impacts can help in increasing public awareness about side effects of unsustainable practices. Analysis of multidate remote sensing data can be used as an effective tool in environmental impact assessment (EIA). Being synoptic and frequent in coverage, multidate data from Landsat and other satellites provide a reference record and bird’s eye viewing to the environmental situation of the coastal ecosystem and the associated habitats. Furthermore, integration of satellite data with field observations and background information can help in decision if a certain activity has caused deterioration to a specific habitat or not. The present paper is an attempt to utilize remote sensing data for assessment impacts of some human activities on the major sensitive habitats of the north western Egyptian Red Sea coastal zone, definitely between Ras Gemsha and Safaga. Through multidate change analysis of Landsat data (TM & ETM+ sensors), it was possible to depict some of the human infringements in the area and to provide, in some cases, exclusive evidences for the damaging effect of some developmental activities [3]. The coastline of Hurghada has experienced considerable environmental stress from tourist and residential recreational activities. Uncontrolled tourist development has already caused substantial damage to inshore reefs and imbalance in the hydrodynamic pattern of the coastal sediments. The objective of this paper is to investigate environmental changes using multitemporal, multispectral satellite data to identify changes at Hurghada caused by anthropogenic influences. Major detected changes include resort beaches, protection structures and landfill areas; these changes are mainly due to human intervention. Two Landsat Thematic Mapper (TM) images acquired in 1984 and 1997 are used for this analysis. The landfill areas formed during this period are calculated at about 2.15 Km2 . Whilst landfill creates new inexpensive land and improves access to the sea for tourists, it is the cause of environmental problems. In addition, land-use/land-cover and beach changes are determined over the 13-year period [4]. The Red Sea coastal zone is characterized by its sensitive, fragile, unique natural resources and habitats. In the Hurghada coastal region, major changes in the tourism industry have taken place in the last few decades. The detection of environmental changes, in a selected site of the Red Sea coastal zone, will be helpful to protect and develop this coastal environment. A methodology for separating natural and man-made changes in satellite images was developed. It was based on the following assumptions: (1) slow changes, which occur within the range of the class reflectance, represent a natural change rather than an anthropogenic one; (2) natural changes tend to be in the same land-use/land-cover class in each date, i.e. slow changes in the reflectance, not leading to changes in the type of land-use/land-cover class from the master image to the destination one; and (3) rapid changes in the reflectance of the Earth's objects are usually related to anthropogenic activities. This technique is used to identify and assess changes along the coast of Hurghada and Ras Abu Soma, the Red Sea. Results indicate serious human impacts and the necessity for control measures and monitoring. Recommendations are presented [5]. The rapid urban development of the Hurghada area began in early 1980 to build villages and huge tourist resorts and this has continued urban development and subsequent land filling and dredging of the shoreline and the destruction of coral so far. These coastal developments have led to an increase in shoreline land filling and dredging. Despite all the environmental laws of the organization to reduce infringement on the shoreline, the abuses are still ongoing. Change detection analysis using remote sensing is a very good tool to monitor the changes condition in urban development and shoreline. Four sensors was used in this study, three of them are, Landsat Multispectral Scanner (Landsat 1 MSS), Landsat Thematic Mapper (Landsat 5 TM), Landsat Enhanced Thematic Mapper Plus (Landsat 7 ETM+) and the another one is SPOT XS 4 (Originally Système Probatoire de l’Observation de la Terre), acquired during 1972, 1984, 1992, 2004 and 2011, respectively, were used to detect and evaluate Hurghada’s urban expansion and shoreline changes. After the images have been geometrically, radio-metrically and atmospherically corrected using ENVI 5.0 software, the digital number was transformed to the reflectance values and the images were ready to change detection process with the integration of geographic information system using Arc GIS 10 software. The results show that changes during the 39 years of the shoreline is 6.29 km2, (5.65 km2 accretion and 0.64 km2 erosion) and urban development is 16.47 km2 the road network is the 8.738 km2.
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4

Kanellopoulos, Ioannis, Graeme G. Wilkinson, and Claudio Chiuderi. "Land cover mapping using combined Landsat TM imagery and textural features from ERS-1 synthetic aperture radar imagery." In Satellite Remote Sensing, edited by Jacky Desachy. SPIE, 1994. http://dx.doi.org/10.1117/12.196731.

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5

Walker, Charles L., and Maria T. Kalcic. "Gram-Schmidt orthogonalization technique for atmospheric and sun glint correction of Landsat imagery." In Satellite Remote Sensing, edited by Jacky Desachy. SPIE, 1994. http://dx.doi.org/10.1117/12.196778.

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6

Dai, Sheng Pei, Hong Xia Luo, Ji Hua Fang, Jian Hua Cao, Hai Liang Li, Mao Fen Li, Ling Ling Wang, and Wei Luo. "Object-oriented classification of rubber plantations from Landsat satellite imagery." In 2014 Third International Conference on Agro-Geoinformatics. IEEE, 2014. http://dx.doi.org/10.1109/agro-geoinformatics.2014.6910635.

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7

Bogliolo, M. P., Maria F. Buongiorno, and Stefano Salvi. "Integration of digital elevation model and spectral radiance for topographic normalization of Landsat TM imagery." In Satellite Remote Sensing, edited by Pat S. Chavez, Jr., Carlo M. Marino, and Robert A. Schowengerdt. SPIE, 1994. http://dx.doi.org/10.1117/12.197225.

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8

Ramdhani, Nur Faiz, Endah Sulistyawati, and Sutrisno Sutrisno. "Land surface temperature analysis of post-mining area using Landsat 8 imagery." In Sixth International Symposium on LAPAN-IPB Satellite, edited by Tien Dat Pham, Kasturi D. Kanniah, Kohei Arai, Gay Jane P. Perez, Yudi Setiawan, Lilik B. Prasetyo, and Yuji Murayama. SPIE, 2019. http://dx.doi.org/10.1117/12.2541811.

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9

Mehl, Harald, Wolfgang Reimer, and Hubert Miller. "Spectral discrimination of ignimbritic rocks of southern Argentina in Landsat Thematic Mapper imagery using GER SIRIS laboratory data." In Satellite Remote Sensing, edited by Eugenio Zilioli. SPIE, 1994. http://dx.doi.org/10.1117/12.197296.

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10

Tampubolon, Togi, Rita Juliani, and Juniar Hutahaean. "Utilization of Landsat Satellite Imagery to Observe Environmental Change at Sinabung Mountain Area." In Proceedings of The 5th Annual International Seminar on Trends in Science and Science Education, AISTSSE 2018, 18-19 October 2018, Medan, Indonesia. EAI, 2019. http://dx.doi.org/10.4108/eai.18-10-2018.2287308.

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Reports on the topic "Landsat MSS satellite imagery"

1

Becker, Sarah, Megan Maloney, and Andrew Griffin. A multi-biome study of tree cover detection using the Forest Cover Index. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42003.

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Tree cover maps derived from satellite and aerial imagery directly support civil and military operations. However, distinguishing tree cover from other vegetative land covers is an analytical challenge. While the commonly used Normalized Difference Vegetation Index (NDVI) can identify vegetative cover, it does not consistently distinguish between tree and low-stature vegetation. The Forest Cover Index (FCI) algorithm was developed to take the multiplicative product of the red and near infrared bands and apply a threshold to separate tree cover from non-tree cover in multispectral imagery (MSI). Previous testing focused on one study site using 2-m resolution commercial MSI from WorldView-2 and 30-m resolution imagery from Landsat-7. New testing in this work used 3-m imagery from PlanetScope and 10-m imagery from Sentinel-2 in imagery in sites across 12 biomes in South and Central America and North Korea. Overall accuracy ranged between 23% and 97% for Sentinel-2 imagery and between 51% and 98% for PlanetScope imagery. Future research will focus on automating the identification of the threshold that separates tree from other land covers, exploring use of the output for machine learning applications, and incorporating ancillary data such as digital surface models and existing tree cover maps.
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2

Zimmerman, P. D. Study of the Nevada Test Site using Landsat satellite imagery. Office of Scientific and Technical Information (OSTI), July 1993. http://dx.doi.org/10.2172/10107312.

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