ASTER Spectral Analysis Based Vegetation Species Identification of the Forest Areas Situated in Ghatsila, Musabani and Dhalbhumgarh

Abstract

Reflectance-converted imagery is a requirement for establishing remote sensing algorithms for mapping vegetation species using their specific absorption and reflectance spectra. The differences among the spectral signatures, the unique patterns of absorption and reflection of visible and infrared energy help the researcher to identify types of plants. During the last few decades remote sensing technology has become increasingly important tool for mapping and inventorying forest resources around the world. Jharkhand state has a vast forest area and a rich biodiversity. The ability to map vegetation and in particular individual trees is a key component in forest management and long-term forest monitoring. The aim of this study is to analyze the ASTER derived spectral informations on which it is possible to discriminate species spectrally from each other. An ASTER image based spectral classification method such as SAM and SID has demonstrated its capability to map the dominant vegetation species found in the study area.

Keywords: ASTER imagery, SAM, SID, vegetation species, spectral analysis

Cite this Article

Somnath Maiti, Rajat Satpathy, Jatisankar Bandyopadhyay, Ayyeum Perumal Thillai Jeyaseelan. ASTER Spectral Analysis Based Vegetation Species Identification of the Forest areas situated in Ghatsila, Musabani and Dhalbhumgarh. Journal of Remote Sensing & GI. 2015; 6(2): 41–50p.