Biophysical Characterization of Forests in Western Ghats of India by Integration of Space-Borne LiDAR and Multispectral Remote Sensing

Periodic estimation of biophysical parameters is important for understanding the functioning and productivity status of forest ecosystems. Multispectral remote sensing has serious limitations in biophysical characterization of complex forest ecosystems like Western Ghats of India. The objective of the study is the integration of structural parameters from space-borne ICESat1 GLAS data with spectral parameters from Landsat imagery at the pixel level for the estimation of biophysical parameters for two complex protected national forests (Mudumalai, and Sholayar) in the Western Ghats of India. Based on spatial variation and correlation of the geometric attributes from GLAS data and multispectral data, biophysical parameters including understory vegetation height are estimated. The results were validated with field measurements and with canopy height extracted from ICESat 2 data. The results indicate a strong correlation (r 2 = 0.98, r 2 =0.97) with ground measurements and with the canopy heights obtained from ICESat 2 satellite. The locations of forest regions where retrieval of the height of understory vegetation is possible are correlated with locations where aggressive invasive species are thriving indicating the possibility of undergrowth vegetation monitoring using space-borne LiDAR data.