REMOTE SENSING BASED BIOPHYSICAL CHARACTERIZATION OF TROPICAL DECIDUOUS FOREST IN CENTRAL INDIA

Abstract

The paper reports the measurements of biophysical parameters using field and satellite data over a tropical deciduous forest Kanha National Park (KNP), central India. Field measurement (GBH, LAI, litter, soil moisture) was carried out over ten quadrates of 0.1ha in KNP for characterization of biophysical parameters with specified measurement protocol and sampling. Satellite based remote sensing analysis (LAI, Phenology, and NPP) was carried out using multi date observations of IRS-LISS-III, IMS-1MX, SPOT-VEGETATION and EOS-MODIS instruments. Rank correlation analysis using field data collected in the selected quadrates at KNP showed Sal (Shorea robusta) is dominant forest species followed by Lendia, Jamun (Syzygium cumini), Saja, Harra and Dhawda etc. Field measurement of Sal showed GBH range from 20 cm to 170 cm. Different forest classes such as Sal; Sal mixed with Jamun, Bamboo (Dendrocalamus strictus) etc, including grasslands/scrubland were classified with overall accuracy of 85.56 percent using March, May and October multi spectral data. Sal has distinct growth characteristics (low vegetation growth/ leaf fall in March instead of May) as compared to other vegetation species. As per the Leaf Area Index (LAI) measurement using hemispherical photographs, Sal showed the highest LAI (6.95 m2/m2) during September and lowest LAI (2.63 m2/m2) during March. Overall good agreement (r= 0.79) was found between the LAI generated from LISS-III and MODIS data product. It was observed from SPOT-VEGETATION analysis that NPP varied from 8.4 tC/ha/year (dry deciduous forest) to 14.25 tC/ha/year (Moist deciduous forest) in KNP.