Forest cover is of great interest to a variety of scientific and land management applications, many of which require not only information on forest categories, but also tree canopy density. Forest maps are a basic information source for habitat modelling, prediction and mapping of forest insect infestations, and plant and animal biodiversity assessment. Foresters and forest managers especially require information for gap filling activities to restore forest wealth. Forest managers require accurate maps of forest type, structure, and seral state for fire (Roy, et al., 1997) and insect damage assessment and prediction (Chandrasehkhar et al., 2003), wildlife habitat mapping, and regional-scale ecosystem assessment (Blodgett et al., 2000). Few attempts have been reported to stratify the forest density using satellite remote sensing digital data (Roy et al. 1990). Previous efforts to estimate tree canopy density as a continuous variable have utilized linear spectral mixture analysis or linear regression techniques (Iverson et al., 1989; Zhu and Evans, 1994; DeFries et al., 2000). Other techniques such as physically based models and fuzzy logic have also been explored but are probably premature for use over large areas (Baret et al., 1995; Maselli et al., 1995). International Tropical Timber Organisation (ITTO) and Japan Overseas Forestry Consultants Association (JOFCA) while working on project entitled "Utilization of Remote Sensing" developed methodology wherein biophysical spectral indices were developed to stratify forest density (Anon., 1993 and Rikimaru, 1996). In this study the methodology has been validated on an Indian test site.
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