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Land Use Land Cover Change Detection Using Remote Sensing Data and GIS (Paperback)

Eskindir Ayele

ISBN 10: 3639094662 / ISBN 13: 9783639094664
Editorial: VDM Verlag, Germany, 2010
Nuevos Condición: New Encuadernación de tapa blanda
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Language: English. Brand new Book. Monitoring land use land cover change at all levels has become central element in sustainable development, natural resources management and environmental protection. Such daily issues of the FAO and others inspired me to conduct this work using RS data and GIS over the remnant forest area in south western part of Ethiopia, Bonga town and its environs, applying PCC change detection technique and Cellular Automata Markov LULCC model. The change detection involved processing of three Landsat images and PCC. Accordingly, a chained transition was observed between the land covers all at the expense of forest cover between the study years. The projection of change has also showed that if appropriate measures are not taken the study area will suffer from environmental degradation in the near future. Thereby, in this era of global environmental crisis, monitoring and management of land is unquestionable for all on the surface of the sphere. Thus, the empirical findings of this book can be used for detailed explanatory, impact assessment, prescription and evaluative studies on the subject. Furthermore, it will provide inputs for policy formulation and decision making at different levels. N° de ref. de la librería KNV9783639094664

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Detalles bibliográficos

Título: Land Use Land Cover Change Detection Using ...

Editorial: VDM Verlag, Germany

Año de publicación: 2010

Encuadernación: Paperback

Condición del libro: New

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Monitoring land use land cover change at all levels has become central element in sustainable development, natural resources management and environmental protection. Such daily issues of the FAO and others inspired me to conduct this work using RS data and GIS over the remnant forest area in south western part of Ethiopia, Bonga town and its environs, applying PCC change detection technique and Cellular Automata Markov LULCC model. The change detection involved processing of three Landsat images and PCC. Accordingly, a chained transition was observed between the land covers all at the expense of forest cover between the study years. The projection of change has also showed that if appropriate measures are not taken the study area will suffer from environmental degradation in the near future. Thereby, in this era of global environmental crisis, monitoring and management of land is unquestionable for all on the surface of the sphere. Thus, the empirical findings of this book can be used for detailed explanatory, impact assessment, prescription and evaluative studies on the subject. Furthermore, it will provide inputs for policy formulation and decision making at different levels.

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