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2022 Vol. 34, No. 3
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ZHANG Shu, ZHOU Zhongfa, WANG Lingyu, CHEN Quan, LUO Jiancheng, ZHAO Xin. 2022. Inversion of moisture in surface soil of farmland in karst mountainous areas using multi-temporal SAR images. Remote Sensing for Natural Resources, 34(3): 154-163. doi: 10.6046/zrzyyg.2021268
Citation: ZHANG Shu, ZHOU Zhongfa, WANG Lingyu, CHEN Quan, LUO Jiancheng, ZHAO Xin. 2022. Inversion of moisture in surface soil of farmland in karst mountainous areas using multi-temporal SAR images. Remote Sensing for Natural Resources, 34(3): 154-163. doi: 10.6046/zrzyyg.2021268
shu

Inversion of moisture in surface soil of farmland in karst mountainous areas using multi-temporal SAR images

  • 1. School of Geography and Environmental Science/School of Karst Science, Guizhou Normal University, Guiyang 550001, China；

  • 2. The State Key Laboratory Incubation Base for Karst Mountain Ecology Environment of Guizhou Province, Guiyang 550001, China；

  • 3. State Engineering Technology Institute for Karst Desertification Control, Guiyang 550001, China；

  • 4. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

Received Date:  30 August 2021
Revised Date:  15 September 2022
Publish Date:  21 September 2022
    Abstract
  • The farmland’s soil moisture plays an important role in crop yield estimation and drought monitoring and is also a key parameter for fine-scale monitoring of farmland in karst mountainous areas. Targeting the complex environmental impacts in karst regions such as farmland fragmentation and the fact that the inversion of soil moisture is vulnerable to cloud interference, this study employed both the water cloud model (WCM) and the support vector regression (SVR) model to conduct the block-scale inversion of the soil moisture in the growth periods of tobacco using the multi-temporal Sentinel-1 synthetic aperture Radar (SAR) images and the unmanned aerial vehicle (UAV) RGB images. The results are as follows. ① In this study, conventional vegetation parameters were replaced with the visible-band difference vegetation index (VDVI), which combined with its water cloud model was highly applicable to karst mountainous areas. The co-polarization method yielded higher inversion precision, with a coefficient of determination of 0.843 and RMSE of 0.983%. These provide a convenient method for the inversion of farmland’s soil moisture in cloudy and rainy mountainous areas. ② The trend of soil moisture in the four growth periods of tobacco is consistent with that of precipitation. Farmland with rocky desertification has low soil moisture, which is closely related to the bare rocks, complex terrain, and difficulties with irrigation in the experimental area. ③ Soil moisture has significant effects on tobacco growth. Specifically, high soil moisture promotes tobacco growth and low soil moisture inhibits tobacco growth, especially during T1—T3. This study can be utilized as a reference for the fine-scale inversion of the farmland’s soil moisture in cloudy and rainy mountainous areas.
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