Journal of Mathematical and Fundamental Sciences
Vol. 44 No. 1 (2012)

Land Degradation Model Based on Vegetation and Erosion Aspects Using Remote Sensing Data

Adhi Wibowo (1R&D Center for Coal and Mineral Technology, Indonesia)
Ishak H. Ismullah (2Department of Geodesy and Geomatics, Institute of Technology Bandung, Indonesia)
Bobby S. Dipokusumo (2Department of Geodesy and Geomatics, Institute of Technology Bandung, Indonesia)
Ketut Wikantika (2Department of Geodesy and Geomatics, Institute of Technology Bandung, Indonesia)



Article Info

Publish Date
21 Jul 2013

Abstract

The study of land degradation in various geographic conditions in the world using remote sensing is still become a concern amongst researchers because it has been proven as one of the most effective ways. In Indonesia, East Kalimantan province is one of the experiencing land area degradation due to intensive exploitation of natural resouces since 1970. The degradation model proposed in this study is modeled using a combination of ASTER and Landsat ETM+ imagery, both taken on February 27, 2001. The model composed of both two aspects: erosion aspect and vegetation aspect. Vegetation aspect is a function of suppression of vegetation from Crippen and Blom method and spectral angle a of Spectral Angle Mapper (SAM) algorithm. The erosion aspect is calculated from erosion prediction and depends on the constant factors of b as well, and the latter is said as a function of Normalized Difference Vegetation Index (NDVI) value. Based on the validation using spectral based degradation map and Land Degradation Index of Chikhaoui et al, our model proves the ability to map land degradation, especially to better distinguish the classification of land degradation at very-slightly to very-severe intensity and the ability to differentiate water body, swamp or river.

Copyrights © 2012






Journal Info

Abbrev

jmfs

Publisher

Subject

Astronomy Chemistry Earth & Planetary Sciences Mathematics Physics

Description

Journal of Mathematical and Fundamental Sciences welcomes full research articles in the area of Mathematics and Natural Sciences from the following subject areas: Astronomy, Chemistry, Earth Sciences (Geodesy, Geology, Geophysics, Oceanography, Meteorology), Life Sciences (Agriculture, Biochemistry, ...