| Abstract: | There is a lack of scientific data on extent, type and the condition of tropical forests. In India, the forest cover assessment is being carried out by the Forest Survey of India (FSI) biennially satellite images. The assessment has not been able to present realistic details, especially for north-east India due to the nature of deforestation/degradation processes (primarily shifting cultivation). The present study suggests a methodology to monitor forest cover using IRS-1C Wide Field Sensor (WiFS) data. It avoids illumination differences and has a better temporal resolution. NOAA Advanced Very High Resolution Radiometer (AVHRR) data have also found considerable acceptance for land cover studies at the regional level. Many studies have found NOAA data deficient in presenting the regional status monitoring due to its coarse resolution. IRS-1C WiFS data with 188 m 2 188 m spatial resolution overcomes this deficiency. The study focuses on the approach of using temporal IRS-1C WiFS data for monitoring the phenological fluxes of forested landscape of north-east India. The Normalized Difference Vegetation Index (NDVI) is evaluated for monitoring seasonal changes in vegetation. Attempts are made to classify forest using the phenological characters as discriminant. A hybrid approach (unsupervised and supervised) of classification provided better results. The overall accuracy of different classes was found to be 82.15%. The Khat ( K hat ) significance coefficient was found to be 0.80. The present assessment of forest cover in the north-east region is 42.24% of the total geographical area. The estimate made by FSI is 64.31% of the geographical area. The estimate that is made based on visual interpretation has always been contested to be on the higher side. Comparison of the map and statistics reveals that inclusion of abandoned and current shifting cultivation areas in forest cover have led to the overestimation. The results indicate that IRS-1C WiFS data can be used to map and monitor vegetation cover at the regional scale. The stratification thus achieved can provide valuable input for land surface characterization for geosphere-biosphere studies. |
