Singh, U; Srivastava, PK; Pandey, DK; Chaurasia, S; Gupta, DK; Chaudhary, SK; Prasad, R; Raghubanshi, AS (2020). ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 17(4), 563-567.

The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (ISRO), provides data at a higher temporal and spatial resolution for various applications. Due to its all-weather operational capability, it could be used as an alternative to the optical/IR sensors for the LAI estimation. In the technical literature domain, no testing has been done to estimate the LAI using ScatSat-1 scatterometer data. Therefore, the objective of this study is to retrieve the LAI using the ScatSat-1 backscattering by modifications of two different models viz. water cloud model (WCM) and the recently developed Oveisgharan et al. model and compared against the PROBA-V, MODIS, and ground-based LAI products. To assess the performance of these models, coefficient of determination ( $R<^>{2}$ ), root-mean-squared error (RMSE) and bias are computed. For Oveisgharan et al., the values of $R<^>{2}$ , RMSE and bias were obtained as 0.87, 0.57 m(2)m(-2), and 0.05 m(2)m(-2) respectively, whereas for WCM model, the values were found as 0.82, 0.67 m(2)m(-2), and 0.32 m(2)m(-2) respectively. This investigation showed that the modifications in Oveisgharan et al. model provide marginally better results in the retrieval of LAI using ScatSat-1 data than the WCM model. The models' limitation may be less serious for crop management studies because the majority of crops attains its maturity at LAI values less than 6 m(2)/m(2).