COUPLING SENTINEL-1 AND SENTINEL-2 IMAGES FOR OPERATIONAL SOIL MOISTURE MAPPING

被引:0
作者
El Hajj, Mohammad [1 ]
Baghdadi, Nicolas [1 ]
Zribi, Mehrez [2 ]
Bazzi, Hassan [1 ]
机构
[1] Univ Montpellier, TETIS, IRSTEA, F-34090 Montpellier, France
[2] CNRS, CESBIO, 18 Av Edouard Belin,Bpi 2801, F-31401 Toulouse 9, France
来源
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年
关键词
neural networks; soil moisture; Sentinel 1&2; SAR; C-band; INTEGRAL-EQUATION MODEL; SAR DATA; C-BAND; CALIBRATION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The objective of the present paper is to develop an operational approach for soil moisture mapping in agricultural areas at a high spatial resolution over bare soils, as well as soils with vegetation cover. The developed approach is based on the synergic use of radar and optical data and uses the neural network technique to invert the radar signal. Three inversion SAR (Synthetic Aperture Radar) configurations were tested: (1) VV polarization, (2) VH polarization, and (3) both VV and VH polarization, all in addition to the NDVI information extracted from optical images. Neural networks were developed and validated using synthetic and real databases. The results showed that the soil moisture could be estimated in agricultural areas with an accuracy of approximately 5 vol.%.
引用
收藏
页码:5537 / 5540
页数:4
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