Remote Sensing Monitoring of Soil Salinization Based on SI-Brightness Feature Space and Drivers Analysis: A Case Study of Surface Mining Areas in Semi-Arid Steppe

Zhenhua Wu; Qingwu Yan; Shutao Zhang; Shaogang Lei; Qingqing Lu; Xia Hua

doi:10.1109/ACCESS.2021.3101873

IEEE Access (Jan 2021)

Remote Sensing Monitoring of Soil Salinization Based on SI-Brightness Feature Space and Drivers Analysis: A Case Study of Surface Mining Areas in Semi-Arid Steppe

Zhenhua Wu,
Qingwu Yan,
Shutao Zhang,
Shaogang Lei,
Qingqing Lu,
Xia Hua

Affiliations

Zhenhua Wu: ORCiD; Engineering Research Center of Ministry of Education for Mine Ecological Restoration, China University of Mining and Technology, Xuzhou, China
Qingwu Yan: School of Public Policy & Management, China University of Mining and Technology, Xuzhou, China
Shutao Zhang: Jiangsu Energy Sumeng Branch Office of Xuzhou Coal Mining Group, Xilinhot, China
Shaogang Lei: Engineering Research Center of Ministry of Education for Mine Ecological Restoration, China University of Mining and Technology, Xuzhou, China
Qingqing Lu: School of Public Policy & Management, China University of Mining and Technology, Xuzhou, China
Xia Hua: Engineering Research Center for Coal Mining Subsided Land and Goaf Treatment of Shandong, Jining, China

DOI: https://doi.org/10.1109/ACCESS.2021.3101873
Journal volume & issue: Vol. 9
pp. 110137 – 110148

Abstract

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The real-time monitoring and driving force research of soil salinization in semi-arid grassland are of great significance for regional and local ecological environment protection, management, and sustainable development. We selected a typical “mine-town-agriculture-pastureland-industry” interlaced ecologically fragile area as the study area. Based on the method of SI (Salinization Index)-Brightness feature space, we constructed a new spectral index named Semi-Arid Steppe Salinization Index (SASSI), which is more suitable for soil salinization remote sensing monitoring in semi-arid steppe. The geodetector method was used to analyze the driving forces of the temporal-spatial changes of soil salinization. The results indicated that: (1) SASSI presented a high correlation with soil surface salt content (R2 = 0.7698), and made full use of multi-dimensional remote sensing information. SASSI can reflect the salinization status of surface soil. The indicator calculation was simple and easy to obtain, which was conducive to the quantitative analysis and monitoring of salinization. (2) The driving factors affecting the spatial distribution and change of soil salinization were water, surface mines, town, agriculture, industry, road network, and elevation. The salinized areas were mainly distributed around the wetlands of the Xilin River Basin, mining landscapes, and town landscapes. (3) The total area of salinized soil in the study area increased from 32.03 km2 in 2002 to 150.46 km2 in 2017. The area of salinized soil increased rapidly from 2005 to 2014, but the growth rate slowed down after 2014. The salinized soil was mainly located in the salt marsh wetland in 2002, however had spread to the whole study area in 2017. This study provides references for remote sensing monitoring of soil salinization and the impact of land use, topography and other natural factors on soil salinization in the semi-arid steppe.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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