Remote Sensing and GIS based ecotourism planning: A case study for western Midnapore, West Bengal, India
Data Used:
Satellite data: IRS 1D LISS III (Path/Row: 108/55. 108/56, 109/55, 109/56) IRS 1D PAN (Path/Row: 108/55B, 108/56D, 109/55A, 109/56B) Ancillary Data: Census Data , District Planning map. Methodology: Ecotourism planning requires exploring diverse types of natural and cultural attractions along with demographic characteristics, to provide the base for designing the travel industry different from the mass tourism standard. To fulfill this purpose Remote Sensing and GIS approach has been used. The methodology is given in the Fig 1.2 
IRS 1D LISS III Data has been used for the study. The study area was then extracted using the block map generated from the census data. The extracted digital data was further analyzed to generate vegetation density map, land use/land cover map and soil productivity map. Vegetation Density Map: The information regarding the vegetation density can be of great help to identify and declare ecotourism potential site. In order to get these informations, NDVI approach has been used , which is highly correlated with vegetation parameter such as green leaf, biomass, leaf area and is indicator of photosynthetic activity and hence is of considerable value for vegetation discrimination and monitoring. NDVI values ranges between -1 to +1 and except vegetation, other features show either negative or zero NDVI values, using informations derived from NDVI, the study area is broadly classified into five categories among which the higher values show agricultural region while the most of the forest area fall under moderate value and lowest value reflect no vegetation, most of them are fallow or waste land. This has been shown in Fig 1.3.and 1.3.1. 
The weightage (Eagle, 1997)1 has been given on the basis of the relative importance of vegetation cover from point of view of ecotourism development. The table 1.1.shows the area under different NDVI values.
Table 1.1 Vegetation Density of the Study Area
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