Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

REMOTE SENSING OF ENVIRONMENT

卷:247

Article

Mandal, Dipankar¹  Kumar, Vineet^1,2  Ratha, Debanshu¹  Dey, Subhadip¹  Bhattacharya, Avik¹  Lopez-Sanchez, Juan M.³  McNairn, Heather⁴  Rao, Yalamanchili S.¹ 

[1] Indian Inst Technol, Ctr Studies Resources Engn, Microwave Remote Sensing Lab, Mumbai, Maharashtra, India

[2] Delft Univ Technol, Dept Water Resources, Delft, Netherlands

[3] Univ Alicante, Inst Comp Res, Alicante, Spain

[4] Agr & Agri Food Canada, Ottawa Res & Dev Ctr, Ottawa, ON, Canada

关键词: Canola;    Degree of polarization;    RVI;    PAI;    DpRVI;    Vegetation water content;   

DOI  :  10.1016/j.rse.2020.111954

来源: Elsevier

【 摘 要 】

Sentinel-1 Synthetic Aperture Radar (SAR) data have provided an unprecedented opportunity for crop monitoring due to its high revisit frequency and wide spatial coverage. The dual-pol (VV-VH) Sentinel-1 SAR data are being utilized for the European Common Agricultural Policy (CAP) as well as for other national projects, which are providing Sentinel derived information to support crop monitoring networks. Among the Earth observation products identified for agriculture monitoring, indicators of vegetation status are deemed critical by end-user communities. In literature, several experiments usually utilize the backscatter intensities to characterize crops. In this study, we have jointly utilized the scattering information in terms of the degree of polarization and the eigenvalue spectrum to derive a new vegetation index from dual-pol (DpRVI) SAR data. We assess the utility of this index as an indicator of plant growth dynamics for canola, soybean, and wheat, over a test site in Canada. A temporal analysis of DpRVI with crop biophysical variables (viz., Plant Area Index (PAI), Vegetation Water Content (VWC), and dry biomass (DB)) at different phenological stages confirms its trend with plant growth dynamics. For each crop type, the DpRVI is compared with the cross and co-pol ratio (sigma(0)(VH)/sigma(0)(VV)) and dual-pol Radar Vegetation Index (RVI = 4 sigma(0)(VH)/(sigma(0)(VV) + sigma(0)(VH))), Polarimetric Radar Vegetation Index (PRVI), and the Dual Polarization SAR Vegetation Index (DPSVI). Statistical analysis with biophysical variables shows that the DpRVI outperformed the other four vegetation indices, yielding significant correlations for all three crops. Correlations between DpRVI and biophysical variables are highest for canola, with coefficients of determination (R-2) of 0.79 (PAI), 0.82 (VWC), and 0.75 (DB). DpRVI had a moderate correlation (R-2 >= 0.6) with the biophysical parameters of wheat and soybean. Good retrieval accuracies of crop biophysical parameters are also observed for all three crops.

【 授权许可】

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