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Abstract
The estimation of potential areas for afforestation (PAAs) provides the information base for planning, management and monitoring of environmental issues. A remotely sensed Landsat Enhanced Thematic Mapper Plus (ETM+) dataset was used for detection of PAAs. The existing forest densities in the study area were classified using the Normalized Difference Vegetation Index (NDVI), whereas soil moisture was based on distribution of the Soil Wetness Index (SWI). A combined map of NDVI and SWI was produced. Areas showing adequate soil moisture with inadequate/thin forest density on the combined map were considered as PAAs. Computation revealed that approximately 13% of the area under review had potential for dense afforestation, 27% for medium to dense afforestation and 53% for grasses. The methodology formulated in the present study can be used as a rapid assessment tool prior to afforestation planning.
Acknowledgements
The author thanks ITC, the Netherlands, for making the GIS software available (i.e. ILWS 3.4) and the Global Land Cover Facility (GLCF), USA, for providing the Landsat ETM+ dataset free of charge. Suyash Kumar is thanked for intellectual discussions and timely help.