期刊
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷 14, 期 -, 页码 7179-7197出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2021.3096063
关键词
Change detection; interferometric phase; soil moisture; synthetic aperture radar (SAR)
This study investigated the impact of soil moisture changes on different crops and analyzed the relationship between ΔM-v and φ through regression techniques, suggesting that UAVSAR is more accurate for monitoring ΔM-v compared to Sentinel-1. The results demonstrate promising potential for using φ information from Sentinel-1 data in the early stages of crop growth, but recommend the use of L-band SAR data and shorter temporal baselines as crop biomass increases.
The soil moisture changes (Delta M-v) have a significant influence on forestry, hydrology, meteorology, agriculture, and climate change. Interferometric synthetic aperture radar (InSAR), as a potential remote sensing tool for change detection, was relatively less investigated for monitoring this parameter. DInSAR phase (phi) is sensitive to the changes in soil moisture (M-v), and thus, can be potentially used for monitoring Delta M-v. In this article, the relations between phi and Delta M-v over wheat, canola, corn, soybean, weed, peas, and bare fields were investigated using an empirical regression technique. To this end, dual-polarimetric C-band Sentinel-1A and quad-polarimetric L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) airborne datasets were employed. The regression model showed the coefficient of determination (R-2) of 40% to 56% and RMSE of 4.3 vol.% to 6.1 vol.% between the measured and estimated Delta M-v for different crop types when the temporal baseline (Delta T) was very short. As expected, higher accuracies were obtained using UAVSAR given its very short Delta T and its longer wavelength with R-2 of 47% to 59% and RMSE of 4.1 vol.% to 6.7 vol.% for different crop types. However, using the Sentinel-1 data with the long Delta T and shorter wavelength (5.6 cm), the accuracies of Delta M-v estimations decreased significantly. The results of this study demonstrated that using the phi information from Sentinel-1 data is a promising approach for monitoring Delta M-v at an early growing season or before the crop starts growing, but using L-band SAR data and lower temporal baselines are recommended once the biomass increases.
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