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Mapping Vegetation and Forest Types using Landsat TM in the Western Ghat Region of Maharashtra, India
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 76 - Number 1 |
| Year of Publication: 2013 |
| Authors: Sandipan Das, T. P. Singh |
10.5120/13214-0596
|
Sandipan Das, T. P. Singh . Mapping Vegetation and Forest Types using Landsat TM in the Western Ghat Region of Maharashtra, India. International Journal of Computer Applications. 76, 1 ( August 2013), 33-37. DOI=10.5120/13214-0596
Abstract
Vegetation plays a key role in reducing ambient temperature, moisture and pollutant capture, energy use and subsequent ground level ozone reduction. In recent years vegetation mapping has become increasingly important, especially with advancements in environmental economic valuation. The spatial information from the remote sensing satellites enables researchers to quantify and qualify the amount and health of vegetation. The present study highlights significance of remote sensing in the vegetation mapping of western ghat region of Maharashtra using satellite imageries from Landsat TM. A supervised (full Gaussian) maximum likelihood classification was implemented in our approach. The final classification product provided identification and mapping of dominant land cover types, including forest types and non-forest vegetation. Remote sensing data sets were calibrated using a variety of field verification measurements. Field methods included the identification of dominant forest species, forest type and relative state-of-health of selected tree species. Ground truth information was used to assess the accuracy of the classification. The vegetation type map was prepared from the classified satellite image. The moist deciduous forests constitute major portion of the total forest area. The application of remote sensing and satellites imageries with spatial analysis of land use land cover provides policy and decision makers with current and improved data for the purposes of effective management of natural resources.
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