MAI Xiamei, HU Zhenqi, ZHAO Yanling. Monitoring of soil moisture in coal mining subsidence area with high-level groundwater based on the GF-2 satellite image[J]. Journal of China Coal Society, 2019, (2). DOI: 10.13225/j.cnki.jccs.2018.0607
Citation: MAI Xiamei, HU Zhenqi, ZHAO Yanling. Monitoring of soil moisture in coal mining subsidence area with high-level groundwater based on the GF-2 satellite image[J]. Journal of China Coal Society, 2019, (2). DOI: 10.13225/j.cnki.jccs.2018.0607

Monitoring of soil moisture in coal mining subsidence area with high-level groundwater based on the GF-2 satellite image

  • Coal mining could destroy and lead to surface subsidence resulting in water accumulation and land sloping in the areas with a high submersible water level. The water content in the subsided soil will not be evenly distributed, which seriously affects the growth of crops,and the life of residents in the mining area. Therefore,it is of practical sig- nificance to monitor the soil water content in the coal mining area with a high submersible water level. Satellite RS technology can quickly and accurately monitor the soil moisture content of mining areas. The RS technology is used to monitor the soil water content in the coal mining area with a high submersible water level,and to find a more conven- ient,rapid and reasonable method for monitoring the distribution of soil water content in the coal mining area with a high submersible water level. It provides a reference for the environmental impact assess-ment of mining areas,crop yield estimation, damage grade evaluation, farmland damage compensation and the compilation of land reclamation plan. Based on the experience of RS monitoring of soil moisture,the soil samples in the field are collected,the soil spectral data are measured and the relationship between the measured ground spectral data and soil moisture is ana- lyzed by indoor soil moisture measurement. Combining the measured soil water content and spectral characteristic data, the correlation between soil water content and measured water spectrum is analyzed to obtain the sensitive band range of soil water content spectral data. According to the characteristics of GF-2 image band data,the measured spectral wavelength is divided into four bands corresponding to the image band of GF-2,namely 450-520,520-590,630-690 and 770-890 nm. Then the correlation between the average reflectance of each band and the spectral reflectance of soil moisture content is analyzed. The most sensitive band data for monitoring soil water content with GF-2 is found. On the basis of determining the sensitive band of RS detection,the RS inversion models of soil water content and spectral reflectance are established,which are S curve model and inverse function model. Then the RS inversion of soil water content in subsidence area is carried out through the pre-processed GF-2,and the spatial distribution of soil water con- tent in coal mining subsidence area with a high groundwater level is obtained. The results show that the spectral char- acteristics of different soil moisture content are basically similar,and the relationship between measured surface spec- tral data and soil moisture content demonstrates that the soil spectral reflectance increases with the increase of wave- length and the soil moisture content has a significant negative correlation with the reflectance of GF-2 image data in B3 . Therefore,the B3 band can be used as the most sensitive band for monitoring soil water content. Through the analy- sis and test of S-curve model and inverse function model,the results indicate that S-curve model is closer to the meas- ured value than inverse function model. Based on the RS image of GF-2,using S-curve model for RS inversion,the spatial grade distribution map of soil water content in coal mining subsidence area with a high groundwater level can be quickly obtained.
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