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Scattering Parameters from Sentinel-1 SAR Data for Crop Growth Assessment
Journal
2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2022 - Proceedings
Date Issued
2022-01-01
Author(s)
Bhogapurapu, Narayanarao
Dey, Subhadip
Homayouni, Saeid
Bhattacharya, Avik
Rao, Y. S.
Abstract
Accurate and high-resolution spatio-temporal information on crop growth is essential for agronomic management and grain yield estimation. Data provided by the dual-pol Synthetic Aperture Radar (SAR) on board Sentinel-1 is an effective way for crop mapping and monitoring from space independent of weather conditions. In this study, we propose a target characterization parameter, θxP that utilizes the 2D Barakat degree of polarization and the elements of the covariance matrix representing dual-pol SAR data. We also propose an unsupervised clustering scheme using θxP and the scattering entropy, H_xP. We utilize time-series Sentinel-1 data of wheat fields over a Canadian test site to show the sensitivity of θxP to the development of crop morphology at different phenological stages. Similarly, the effectiveness of the unsupervised H_xP/θxP clustering plane is also examined using a sequence of temporal clustering plots. This innovative clustering framework will be convenient for the operational use of Sentinel-1 SAR data for agricultural applications.
Subjects