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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151459
Doc. No : ET23251
Main Entry : STACY LEE OZESMI
Title Proper : SATELLITE REMOTE SENSING OF WETLANDS AND A COMPARISON OF CLASSIFICATION TECHNIQUES
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Wetland conservation and management requires inventory and monitoring of wetlandsand their adjacent uplands. Satellite remote sensing has several advantages for monitoringwetland resources, especially for large geographic areas. This dissertation summarizes theIitenture on satellite remote sensing of wetlands, inchding what classification techniqueswere most successful in identiQing wetIands and separating them fiom other land cover types.Then the use of different features and classification methods were evaluated for their effect onclassification accuracy in two large study areas with heterogeneous landcover types, the TwinCities Metropolitan Area in Minnesota, USA (TCMA) and the Kizilirmak Delta on the BlackSea coast of Turkey. The features examined were all derived from the Landsat MSS or TMimagery: texture, landscape metrics, and indices. The classification methods wereconventional per pixel maximum Iikelihood, three contextual techniques. ma-ximum likelihoodw t h 3 x 3 majority filter, ECHO, and a hybrid segmention method, and one artificial neuralnetwork technique, the feedforward multilayer perceptron with backpropagation for training.The use of multitemporal Landsat TM imagery, June, September. and April image dates, andmdices were the set o f features that gave the highest classification accuracy....-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46487.pdf
Title and statement of responsibility and : SATELLITE REMOTE SENSING OF WETLANDS AND A COMPARISON OF CLASSIFICATION TECHNIQUES [Thesis]
 
 
 
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