The remote sensing-based estimation and spatial-temporal dynamic analysis of SOM in coal mining

GAO Wenlong; ZHANG Shengwei， LIN Xi; LUO Meng; REN Zhaoyi; ${author.authorNameEn}

doi:10.6046/zrzyyg.2020418

2021 Vol. 33, No. 4

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Article navigation > Remote Sensing for Natural Resources > 2021 > 33(4): 235-242

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GAO Wenlong, ZHANG Shengwei， LIN Xi, LUO Meng, REN Zhaoyi, . 2021. The remote sensing-based estimation and spatial-temporal dynamic analysis of SOM in coal mining. Remote Sensing for Natural Resources, 33(4): 235-242. doi: 10.6046/zrzyyg.2020418

Citation:

GAO Wenlong, ZHANG Shengwei， LIN Xi, LUO Meng, REN Zhaoyi, . 2021. The remote sensing-based estimation and spatial-temporal dynamic analysis of SOM in coal mining. Remote Sensing for Natural Resources, 33(4): 235-242. doi: 10.6046/zrzyyg.2020418

The remote sensing-based estimation and spatial-temporal dynamic analysis of SOM in coal mining

1. College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China；
2. Key Laboratory of Protection and Utilization of Water Resources of Inner Mongolia Atuonomous Region, Hohhot 010018, China；
3. Inner Mongolia Autonomous Region Key Laboratory of Big Data Research and Application of Agriculture and Animal Husbandry, Hohhot 010018, China

Received Date: 24 December 2020

Publish Date: 15 December 2021

Abstract

Abstract

Soil is the largest potential reservoir of carbon, and the content of soil organic matter (SOM) is the key influencing factor of soil carbon storage. Therefore, SOM is an important index in the analysis of the changes in soil carbon storage. This paper aims to understand the optimal response bands in spectra to the SOM content in the process of coal mining and the changes in the temporal-spatial dynamic patterns of the SOM in a whole coal mining area. Based on the linear regression analysis of measured SOM, near-earth hyperspectral reflectance, and satellite multispectral reflectance, the SOM changes in the study area on June 1, July 4, and September 21, 2019 were quantitatively analyzed, and the SOM changes in underground coal mines (named Dahaize, Balasu, Nalinhe 2, and Yingpanhao) and their surrounding river basins were monitored. The SOM inversion results obtained using the first-order differential transformation of the near-earth hyperspectral reflectance were the closest to the measured SOM. A regression inversion model was established based on the extracted hyperspectral and multispectral characteristic bands and their correlation with the SOM. As indicated by the precision verification results, the correlation between the values predicted through SOM reversion and measured SOM values reached 0.90. Meanwhile, the SOM content in the study area was high in the east and low in the west and it gradually decreased along the upper, middle, and lower reaches of rivers and estuaries. The SOM content obtained through pre-mining simulation was 5% higher than that acquired via remote sensing-based estimation, indicating that coal mining affects the SOM content to a certain extent. It is also proven that the linear regression model of SOM inversion has the prospect of wide application. The above results will provide bases for quantitative research, management, and sustainable development of soil resources and ecological environment in the study area.
- hyperspectral images /
- soil organic matter(SOM) /
- coal mine /
- soil moisture content /
- hyperspectral remote sensing /

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