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Please use this identifier to cite or link to this item: http://hdl.handle.net/10362/2316

Título: Forest cover monitoring in the Bara district (Nepal) with remote sensing and geographic information systems
Autor: Kandel, Chintamani
Orientador: Caetano, Mário
Gould, Michael
Cabral, Pedro
Palavras-chave: Change detection
Geographical information systems
Land cover change
Object-oriented image classification
Remote sensing
Spatial metrics
Issue Date: 5-Mar-2009
Relatório da Série N.º: Master of Science in Geospatial Technologies;TGEO0001
Resumo: This study uses Landsat Thematic Mapper of 1989, Enhanced Thematic Mapper of 1999 and 2005 imagery to evaluate forest cover dynamics during 1989-2005 in the Bara district, located in the Nepal's Central Terai region. The aim of the study is to analyse the extend and trend of forest cover dynamics, spatial pattern of forest and their driving forces. Forest cover change analysis was performed using object-oriented classification approach applying a standard nearest neighbour algorithm to classify the image in eCognition. The overall classification accuracies were 85.71% and 88.23% for the year 1999 and 2005 respectively. Initially, land cover maps for the year 1989, 1999, and 2005 were produced with seven land cover categories prevalent in study area. Classified images were further reclassified as forest and non-forest areas to analyse the forest cover dynamics effectively. Post-classification and times series analysis were carried out to detect the changes. Spatial metrics were computed for detecting the spatial pattern of forest. The classification showed that the amount of forest land decrease by 11.56% during 1989-2005. The result of the spatial metrics reveals that the forest area has been fragment and deforest with annual rate of 0.72%. The overall result demonstrates that forest area has experienced a significant shrinkage and mostly transferred into agricultural and bare land from 1989 to 2005. Expected change for the year 2021 was projected using Markov Chain Analysis (MCA). The MCA result showed that forest area including shrub will be decreased by 8.5% during 2005-21.
Descrição: Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
URI: http://hdl.handle.net/10362/2316
Appears in Collections:ISEGI - MSc Dissertations Geospatial Technologies (Erasmus-Mundus)

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