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Document Type : Latin Dissertation
Language of Document : English
Record Number : 148404
Doc. No : ET20196
Main Entry : Ludmila Monika Moskal
Title Proper : SPATIOTEMPORAL MODELING OF POST-DISTURBANCE FOREST REGENERATION IN THE YELLOWSTONE NATIONAL PARK REGION
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : This research focused on the development of methods that draw on the spatialautocorrelation, spectral content, hierarchical relationships and hypertemporal contentinherent in remotely sensed datasets to model the dynamics of post-disturbance forestregeneration. Spectral and spatial components of Landsat 7 Enhanced Thematic Mapper Plus(ETM+) data were used to discriminate forest stand classes. The application of the spatialcomponent of the data improved the classification by 36 , compared to a classificationbased on only the spectral content of the imagery. Therefore, the spatial component of thedata allowed for the best discrimination of forest successional classes. The use ofhyperspectral data allowed for mapping of seven gradients of.
Subject : Electericl tess
: برق
electronic file name : TL43322.pdf
Title and statement of responsibility and : SPATIOTEMPORAL MODELING OF POST-DISTURBANCE FOREST REGENERATION IN THE YELLOWSTONE NATIONAL PARK REGION [Thesis]
 
 
 
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