Remote Sensing Monitoring and Driving Force Analysis of Salinized Soil in Grassland Mining Area

Zhenhua Wu, Mingliang Che, Shutao Zhang, Linghua Duo, Shaogang Lei, Qingqing Lu and Qingwu Yan
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Zhenhua Wu: School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China
Mingliang Che: School of Geographic Science, Nantong University, Nantong 226019, China
Shutao Zhang: Jiangsu Energy Sumeng Branch Office of Xuzhou Coal Mining Group, Xilinhot 026021, China
Linghua Duo: Faculty of Geomatics, East China University of Technology, Nanchang 330013, China
Shaogang Lei: Engineering Research Center of Ministry of Education for Mine Ecological Restoration, China University of Mining and Technology, Xuzhou 221116, China
Qingqing Lu: College of Environmental Engineering, Xuzhou University of Technology, Xuzhou 221018, China
Qingwu Yan: School of Public Policy & Management, China University of Mining and Technology, Xuzhou 221116, China

Sustainability, 2022, vol. 14, issue 2, 1-16

Abstract: To deal with the problem of soil salinization that exists widely in semi-arid grassland, the Shengli Coalfield in Xilinhot City was selected as the study area. Six periods of Landsat remote sensing data in 2002, 2005, 2008, 2011, 2014, and 2017 were used to extract the salinity index (SI) and surface albedo to construct the SI-Albedo feature space. The salinization monitoring index (SMI) was used to calculate and classify the soil salinization grades in the study area. The soil salinization status and its dynamic changes were monitored and analyzed. Combined with the logistic regression model, the roles of human and natural factors in the development of soil salinization were determined. The results were as follows: (1) The SMI index constructed using the SI-Albedo feature space is simple and easy to calculate, which is conducive to remote sensing monitoring of salinized soil. R 2 of the SMI and soil salt content in the 2017 data from the study area is 0.7313, which achieves good results in the quantitative analysis and monitoring of soil salinization in the Xilinhot Shengli Coalfield. (2) The study area is a grassland landscape. However, grassland landscapes are decreasing year by year, and town landscapes, mining landscapes, and road landscapes are greatly increased. The areas of soil salinization reversion in the Shengli mining area from 2002–2005, 2005–2008, 2008–2011, 2011–2014, 2014–2017, and 2002–2017 were 65.64 km 2 , 1.03 km 2 , 18.44 km 2 , 0.9 km 2 , 7.52 km 2, and 62.33 km 2 , respectively. The overall trend of soil salinization in the study area was reversed from 2002 to 2017. (3) The driving factors of salinized land from 2002 to 2008 are as follows: the distance to the nearest town landscape > the distance to the nearest mining landscape > the distance to the nearest road landscape. The driving factors of salinized land from 2008 to 2017 are as follows: the distance to nearest mining landscape > the distance to the nearest water landscape > the distance to nearest town landscape > altitude > aspect. Coal exploitation and town expansion have occupied a large amount of saline land, and petroleum exploitation and abandoned railway test sites have intensified the development of saline land. This study provides a reference for the treatment and protection of soil salinization in semi-arid grassland mining areas.

Keywords: grassland mining area; SI-Albedo feature space; soil salinization remote sensing monitoring; driving force analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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