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Articles 121 - 128 of 128

Full-Text Articles in Remote Sensing

Station Exposure And Resulting Bias In Temperature Observations: A Comparison Of He Kentucky Mesonet And Asos Data, James Kyle Thompson Dec 2014

Station Exposure And Resulting Bias In Temperature Observations: A Comparison Of He Kentucky Mesonet And Asos Data, James Kyle Thompson

Masters Theses & Specialist Projects

Station siting, exposure, instrumentation, and time of observations influence longterm climatic records. This thesis compared and analyzed temperature data from four Kentucky Mesonet stations located in Fayette (LXGN), Franklin (LSML), Clark (WNCH), and Bullitt (CRMT) counties to two nearby Automated Surface Observation Systems (ASOS) stations in Kentucky. The ASOS stations are located at Louisville International Airport (Standiford Field - KSDF) and at Lexington Airport (Blue Grass Field - KLEX). The null hypothesis states that there is no significant difference in temperature measurements between the two types of stations. To quantify the differences in temperature measurements, geoprofiles and the following statistical …

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Spatial Analysis Of Post-Hurricane Katrina Thermal Pattern And Intensity In Greater New Orleans: Implications For Urban Heat Island Research, Aram P. Lief May 2014

Spatial Analysis Of Post-Hurricane Katrina Thermal Pattern And Intensity In Greater New Orleans: Implications For Urban Heat Island Research, Aram P. Lief

LSU New Orleans Theses and Dissertations

In 2005, Hurricane Katrina’s diverse impacts on the Greater New Orleans area included damaged and destroyed trees, and other despoiled vegetation, which also increased the exposure of artificial and bare surfaces, known factors that contribute to the climatic phenomenon known as the urban heat island (UHI). This is an investigation of UHI in the aftermath of Hurricane Katrina, which entails the analysis of pre and post-hurricane Katrina thermal imagery of the study area, including changes to surface heat patterns and vegetative cover. Imagery from Landsat TM was used to show changes to the pattern and intensity of the UHI effect, …

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Numerical Simulation Of “An American Haboob”, A. Vukovic, M. Vujadinovic, G. Pejanovic, J. Andric, M. J. Kumjian, V. Djurdjevic, M. Dacic, Anup K. Prasad, Hesham El-Askary, B. C. Paris, S. Petkovic, W. Sprigg, S. Nickovic Jan 2014

Numerical Simulation Of “An American Haboob”, A. Vukovic, M. Vujadinovic, G. Pejanovic, J. Andric, M. J. Kumjian, V. Djurdjevic, M. Dacic, Anup K. Prasad, Hesham El-Askary, B. C. Paris, S. Petkovic, W. Sprigg, S. Nickovic

Mathematics, Physics, and Computer Science Faculty Articles and Research

A dust storm of fearful proportions hit Phoenix in the early evening hours of 5 July 2011. This storm, an American haboob, was predicted hours in advance because numerical, land–atmosphere modeling, computing power and remote sensing of dust events have improved greatly over the past decade. High-resolution numerical models are required for accurate simulation of the small scales of the haboob process, with high velocity surface winds produced by strong convection and severe downbursts. Dust productive areas in this region consist mainly of agricultural fields, with soil surfaces disturbed by plowing and tracks of land in the high Sonoran Desert …

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A Synergetic Use Of Satellite Imagery From Sar And Optical Sensors To Improve Coastal Flood Mapping In The Gulf Of Mexico, Naira Chaouch, Marouane Temimi, Scott Hagen, John Weishampel, Stephen Medeiros, Reza Khanbilvardi Jan 2011

A Synergetic Use Of Satellite Imagery From Sar And Optical Sensors To Improve Coastal Flood Mapping In The Gulf Of Mexico, Naira Chaouch, Marouane Temimi, Scott Hagen, John Weishampel, Stephen Medeiros, Reza Khanbilvardi

United States Department of Commerce: Staff Publications

This work proposes a method for detecting inundation between semi-diurnal low and high water conditions in the northern Gulf of Mexico using high-resolution satellite imagery. Radarsat 1, Landsat imagery and aerial photography from the Apalachicola region in Florida were used to demonstrate and validate the algorithm. A change detection approach was implemented through the analysis of red, green and blue (RGB) false colour composites image to emphasise differences in high and low tide inundation patterns. To alleviate the effect of inherent speckle in the SAR images, we also applied ancillary optical data. The flood-prone area for the site was delineated …

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Biomass Estimation Using Statistical And Neural Network Analysis Of Aster Data, Vijay O. Lulla Dec 2005

Biomass Estimation Using Statistical And Neural Network Analysis Of Aster Data, Vijay O. Lulla

All-Inclusive List of Electronic Theses and Dissertations

This study assessed the performance of different biomass estimation methods using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) lll data in a temperate forest. Multiple linear regression statistics of spectral band data and derived indices with biomass values were compared with advanced neural network models created with spectral band data and indices to model biomass values. Biomass for the study area was estimated using both of these methods and the results were discussed. The data were analyzed using multivariate statistical analysis. Correlation analysis and regression analysis were employed to understand the relationship of biomass to the spectral data and …

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Estimation Of Forest Stand Parameters And Application In Classification And Change Detection Of Forest Cover Types In The Brazilian Amazon Basin, Dengsheng Lu May 2001

Estimation Of Forest Stand Parameters And Application In Classification And Change Detection Of Forest Cover Types In The Brazilian Amazon Basin, Dengsheng Lu

All-Inclusive List of Electronic Theses and Dissertations

This research focuses on measurement of forest stand parameters using remote sensing which is applied to classification and change detection of tropical successional and mature forests in selected areas in the Brazilian Amazon Basin. Three study areas, Altamira, Bragantina, and Pedras, each with different biophysical environments, were selected for this research. Previous research has indicated that relationships between selected stand parameters and remotely sensed data are not clearly understood, especially in tropical areas. Rarely has remote sensing research been successfully conducted in quantitative estimation of forest stand parameters (e.g. biomass) and identification of vegetation growth stages. In this research, atmospherically …

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Postfire Vegetation Change Detection Using Landsat Mss And Tm Data, Mark Edward Jakubauskas Aug 1988

Postfire Vegetation Change Detection Using Landsat Mss And Tm Data, Mark Edward Jakubauskas

All-Inclusive List of Electronic Theses and Dissertations

Three dates of Landsat digital data were classified and then analyzed using a geographic information system (GIS). The intent of this study was to determine if differences in burn severity relate to later vegetative cover within a northern pines forest. The May 5, 1980, Mack Lake Fire in the Huron National Forest, Michigan, was selected as the study site for this research. This wildfire burned over 9000 hectares of jack pine, red pine, and mixed deciduous forest within a six-hour period. Landsat MSS data from June 1973 and TM data from October 1982 were classified using an unsupervised approach to …

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Application Of Satellite Data And Lars' Data Processing Techniques To Mapping Vegetation Of The Dismal Swamp, Jeffrey Allan Messmore Oct 1975

Application Of Satellite Data And Lars' Data Processing Techniques To Mapping Vegetation Of The Dismal Swamp, Jeffrey Allan Messmore

Biological Sciences Theses & Dissertations

This study concerned the feasibility of using digital satellite imagery and automatic data processing (ADP) techniques as a means of mapping swamp forest vegetation. Multispectral scanner data acquired by the Earth Resources Technology Satellite (ERTS-1; renamed LANDSAT-1) was analyzed using ADP techniques developed by Purdue University's Laboratory for Applications of Remote Sensing (LARS). The site for this investigation was the Dismal Swamp, a 210,000 acre swamp forest located south of Suffolk, Va. on the Virginia-North Carolina border. Two basic classification strategies were employed in determining the vegetation mapping capability of ERTS-1 data. The initial classification utilized unsupervised techniques which produced …

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