Cooperative Inversion of Winter Wheat Covered Surface Soil Moisture Based on Sentinel-1/2 Remote Sensing Data

Jianhui ZHAO; Bei ZHANG; Ning LI; Zhengwei GUO

doi:10.11999/JEIT200416

Volume 43 Issue 3

Mar. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(3): 692-699

Jianhui ZHAO, Bei ZHANG, Ning LI, Zhengwei GUO. Cooperative Inversion of Winter Wheat Covered Surface Soil Moisture Based on Sentinel-1/2 Remote Sensing Data[J]. Journal of Electronics & Information Technology, 2021, 43(3): 692-699. doi: 10.11999/JEIT200416

Citation:

Jianhui ZHAO, Bei ZHANG, Ning LI, Zhengwei GUO. Cooperative Inversion of Winter Wheat Covered Surface Soil Moisture Based on Sentinel-1/2 Remote Sensing Data[J]. Journal of Electronics & Information Technology, 2021, 43(3): 692-699. doi: 10.11999/JEIT200416

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Cooperative Inversion of Winter Wheat Covered Surface Soil Moisture Based on Sentinel-1/2 Remote Sensing Data

doi: 10.11999/JEIT200416

1.
Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng 475004, China
2.
Henan Engineering Research Center of Intelligent Technology and Application, Henan University, Kaifeng 475004, China
3.
College of Computer and Information Engineering, Henan University, Kaifeng 475004, China

Funds: The National Natural Science Foundation of China (61871175), The Plan of Science and Technology of Henan Province (182102210233, 192102210082), The Youth Talent Lifting Project of Henan Province (2019HYTP006), The College Key Research Project of Henan Province (19A420005)

Received Date: 2020-05-29
Rev Recd Date: 2020-12-06

Available Online: 2020-12-18

Publish Date: 2021-03-22

Abstract

Abstract

Winter wheat is one of the most important food crops in China. Monitoring the soil moisture over winter wheat covered surface can help to solve the problem of poor harvest of winter wheat and waste of agricultural water due to soil water supply. In order to reduce the influence of winter wheat on radar backscattering coefficient in the process of microwave remote sensing retrieval of soil moisture covered by winter wheat, based on the Synthetic Aperture Radar (SAR) data carried by Sentinel-1 and the MultiSpectral Imager (MSI) data carried by Sentinel-2, combined with the water cloud model, the collaborative inversion of soil moisture over winter wheat mulching surface is carried out. Firstly, based on the MSI data from Sentinel-2, a new vegetation index called Fusion Vegetation Index (FVI) is defined for inversion of winter wheat moisture. Secondly, a semi-empirical soil moisture inversion model based on active and passive remote sensing data is developed to correct the influence of winter wheat on radar backscatter coefficient. Finally, by taking a winter wheat field in Henan Province as the study area, the comparative experiments of soil moisture inversion are carried out under six combinations, which are composed of two vegetation indexes, Normalized Difference Water Index (NDWI) and FVI respectively, and three types of polarization data, VV, VH and VV/VH respectively. Through the experimental results, FVI shows a better performance than NDWI in reducing the influence of winter wheat on radar backscatter coefficient. Meanwhile, among the six inversion combinations, the one of FVI and VV/VH achieves the optimal inversion precision, with a determination coefficient of 0.7642, a Root Mean Square Error of 0.0209 cm³/cm³, and a Mean Absolute Error of 0.0174 cm³/cm³, demonstrating the application potential of the soil inversion model developed in this paper.
- Radar soil moisture inversion,
- Water cloud model,
- Fusion Vegetation Index(FVI),
- Sentinel-1/2

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References(20)

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