M. Balakrishna Reddy

Abstract

IRS-LISS III satellite imagery corresponding to Nongkhyllem Wildlife Sanctuary area of Ri-Bhoi District, Meghalaya was used for remote sensing analysis of the landuse pattern and vegetation types occurring thereat. Maximum likelihood classifier algorithm of ERDAS Imagine 9.1 version was used to secure supervised classification of pixels into various landuse types and vegetation types among the forest class cover. For the purpose of preparation of training sets thematic maps of the area, and knowledge accruing from extensive personal field visitswere taken aid of. Sample field plots were laid at 30 different locations of the Sanctuary to carry out accuracy assessment. Normalized Difference Vegetative Index value of the LISS III satellite imagery was also computed. Digital Elevation Model of the Sanctuary was erected in the GIS domain. Such GIS database was integrated with remote sensing data in proof of Integrated Geographic Information System capabilities to achieve higher accuracy in classification. There was indeed marked increase in classification accuracy on account of such integration. Bivariate correlation analysis was performed between spectral and DEM variables to cross check the results.

Keywords

LISS-III Satellite Imagery, Maximum Likelihood Classifier, DEM, Integrated
Geographic Information System

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M. Balakrishna Reddy , Baiantimon Blah

Abstract

Though Shillong and adjoining regions have been favourite sites for collection of plant specimens ever since Hooker showcased to the world the unique biodiversity in Khasi-Jaintia hills there has been no systematic study of the diverse vegetation types occurring exclusively within the district. The terrain through its inaccessibility in several places poses a considerable challenge for an exhaustive vegetation type mapping exercise. IRS P6 LISS III imageries when fused with PAN data provided high resolution imagery capable of providing precise details towards detailed delineation of principal vegetation types occurring in East Khasi Hills district of Meghalaya. The present study has emerged as the first instance when remote sensing technique has been pressed to use for delineation types appearing exclusively within any particular district in Eastern Himalayas thereby settling the vexed issue of the actual vegetation types occurring in and around Shillong.

Keywords

Vegetation Types, Liss III PAN Fused Imagery, Visual Interpretation Technique, Maximum

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