Synergy of Vegetation and Soil Microwave Scattering Model for Leaf Area Index Retrieval Using C-Band Sentinel-1A Satellite Data

• Published in: IEEE geoscience and remote sensing letters Vol. 19; pp. 1 - 5
• Main Authors: Yadav, Vijay Pratap, Prasad, Rajendra, Bala, Ruchi, Srivastava, Prashant K.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Agriculture; Algorithms; Autonomy; Backscattering coefficient; Biological system modeling; C band; Cereal crops; Computational modeling; Crops; Evapotranspiration; Landsat-8; Leaf area; Leaf area index; leaf area index (LAI); Leaves; Lookup tables; Mathematical models; Microwave scattering; Modelling; MODIS; Optimization; Parameter modification; Parameterization; Parameters; Remote sensing; Resolution; Retrieval; SAR (radar); Satellite data; Satellites; Scattering; Sentinel–1A; Soil; Soils; Spectroradiometers; Statistical analysis; Statistical methods; Surface energy; Surface properties; Synthetic aperture radar; Vegetation; Vegetation mapping; water cloud model (WCM)
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2020.3034420

The crops' biophysical parameters play an important role in balancing the land surface energy fluxes and are needed in crop simulation modeling, evapotranspiration, etc. The vegetation parameters' retrieval using microwave scattering model, mainly affected by the heterogeneous distribution of land targets, hampers an accurate retrieval of soil-vegetation parameters in microwave remote-sensing algorithms. To minimize the errors in biophysical parameters' retrieval, the synergetic approach of modified water cloud model (MWCM) and modified soil scattering model (MSSM) was attempted to retrieve the leaf area index (LAI) of wheat and barley crops. Due to the spatiotemporal resolution of Sentinel-1A synthetic aperture radar (SAR) mission, it could be more sensitive to vegetation condition and the retrieval accuracy than optical/IR satellites. The nonlinear least square optimization algorithms were used for the parameterization of modified scattering model. The lookup table (LUT)-based inversion algorithm was applied to compute the LAI values through the modified scattering models. The statistical analysis was performed to assess the model efficiency. In case of forward modeling, the highest <inline-formula> <tex-math notation="LaTeX">{R} ^{{2}} =0.96 </tex-math></inline-formula> and low RMSE = 0.20 dB were computed between the modeled <inline-formula> <tex-math notation="LaTeX">\sigma ^{\mathbf {0}} </tex-math></inline-formula> (dB) and SAR-derived <inline-formula> <tex-math notation="LaTeX">\sigma ^{\mathbf {0}} </tex-math></inline-formula> (dB) using vegetation descriptor (<inline-formula> <tex-math notation="LaTeX">{V} </tex-math></inline-formula>) = LAI. On the other hand, for inverse modeling, the LAI values obtained were more accurate at VV polarization (<inline-formula> <tex-math notation="LaTeX">{R} ^{\mathbf {2}} =0.94 </tex-math></inline-formula> and RMSE <inline-formula> <tex-math notation="LaTeX">=0.124~\text{m}^{\mathbf {2}}/\text{m}^{\mathbf {2}} </tex-math></inline-formula>), when compared with the in situ data. The overall product was also compared with the Project for On-Board Autonomy-Vegetation (PROBA-V) and Moderate Resolution Imaging Spectroradiometer (MODIS)-LAI to check the robustness of the approach.