Estimation of Fuel Moisture Content Based on Quad Polarimetric Decomposition Parameters of Radarsat-2 Data

Abstract

Fuel moisture content (FMC) is a critical variable in assessing wildfire risk and its behavior. Previous studies normally focused on the methodologies based on optical remote sensing data for FMC retrieval. However, active microwave technique, which processes the advantage of high sensitivity to surface moisture, all-weather and all-time work capability and strong penetrability, attracted more attention in surface parameter monitoring, particularly for the polarimetric SAR which provides more sufficient object scatter characteristic. In this paper, we retrieved the FMC for a grassland based on the multiple linear regression analysis of polarimetric decomposition parameters from Radarsat-2 data. The results show that the correlation coefficient (R) and root mean square error (RMSE) reached to 0.658 and 30.319% when compared to the measured FMC. Finally, the presented method was used for spatial and temporal mapping of FMC in the target study area.