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Remote Sensing for Natural Resources    2021, Vol. 33 Issue (3) : 148-155     DOI: 10.6046/zrzyyg.2020358
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Application of intensity analysis theory in the land use change in Yijin Holo Banner under the background of coal mining
SANG Xiao1(), ZHANG Chengye1,2, LI Jun1,2(), ZHU Shoujie1, XING Jianghe1, WANG Jinyang1, WANG Xingjuan1, LI Jiayao1, YANG Ying1
1. College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083,China
2. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology-Beijing, Beijing 100083,China
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Abstract  

This study aims to explore the differences and characteristics of the impacts of coal mining activities at different stages on various land use types in mining areas. Taking Yijin Huoluo Banner-a major coal-producing area in China-as the study area and multi-stage Landsat remote sensing images of nearly 30 years during 1990-2019 as the main data source, this study extracted land use distribution information using the random forest classification method on the Google Earth Engine platform. Based on this as well as coal mining statistical data, this paper analyzed the characteristics of land use changes at three stages of coal mining using the intensity analysis theory. The results are as follows. ① The intensity change theory can be used to comprehensively analyze the land use change from the aspects of intervals, categories, and transformation and to more systematically exhibit the characteristics of land use changes and the impacts of human activities in the study area. These are greatly significant for the in-depth understanding of the land use change process. ② Coal mining produces different impacts on different types of land, and it primarily affects the vegetation, water areas, and bare land. ③ Coal mining imposes different impacts on various types of land at different stages. It produces slight impacts on various types of land at the initial stage. It produces increasing impacts on various types of land at the high-speed development stage, during which it mainly affects vegetation, bare land, and water areas in and around the mining area. Then the impacts decrease at the steady development stage of coal mining. The results of this study can serve the implementation of precise protection plans for different types of land at different coal mining stages and provide a scientific basis for the protection of the ecological environment in the mining area.
Keywords coal mining      Landsat remote sensing images      land use change      intensity analysis theory     
ZTFLH:  TP79  
Corresponding Authors: LI Jun     E-mail: sangxiao@student.cumtb.edu.cn;junli@cumtb.edu.cn
Issue Date: 24 September 2021
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Xiao SANG
Chengye ZHANG
Jun LI
Shoujie ZHU
Jianghe XING
Jinyang WANG
Xingjuan WANG
Jiayao LI
Ying YANG
Cite this article:   
Xiao SANG,Chengye ZHANG,Jun LI, et al. Application of intensity analysis theory in the land use change in Yijin Holo Banner under the background of coal mining[J]. Remote Sensing for Natural Resources, 2021, 33(3): 148-155.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2020358     OR     https://www.gtzyyg.com/EN/Y2021/V33/I3/148
Fig.1  Study area
Fig.2  Raw coal production in Yijin Holo Banner
Fig.3  Land use thematic map of study area
年份 总体精度 Kappa系数
1990年 0.91 0.81
2000年 0.91 0.81
2005年 0.94 0.85
2010年 0.91 0.78
2015年 0.95 0.86
2019年 0.90 0.73
Tab.1  Classification results accuracy
土地利
用类型		 1990年 2000年 2005年 2010年 2015年 2019年
面积/km2 占比/% 面积/km2 占比/% 面积/km2 占比/% 面积/km2 占比/% 面积/km2 占比/% 面积/km2 占比/%
水域 150.89 2.75 123.14 2.25 91.99 1.68 57.18 1.04 74.25 1.35 87.79 1.60
植被 3 898.04 71.07 3 931.19 71.66 4 115.91 75.03 4 332.48 78.99 4 388.27 80.00 4 547.15 82.91
耕地 43.02 0.78 128.74 2.35 214.25 3.91 320.12 5.84 389.98 7.11 459.45 8.38
人工用地 8.36 0.15 31.10 0.57 42.77 0.78 65.52 1.19 112.34 2.05 146.69 2.67
采矿用地 0 0 3.19 0.06 21.32 0.39 42.27 0.77 68.51 1.25 75.90 1.38
裸地 1 384.74 25.25 1 267.69 23.11 998.81 18.21 667.48 12.17 451.70 8.24 168.07 3.06
Tab.2  Area and ratio of land use types in study area
Fig.4  Land use intensity change of study area at interval level
类别 1990—2000年
(S=3.38%)		 2000—2005年
(S=6.08%)		 2005—2010年
(S=5.74%)		 2010—2015年
(S=5.57%)		 2015—2019年
(S=6.05%)
增加 减少 增加 减少 增加 减少 增加 减少 增加 减少
水域 3.94 5.78 6.71 11.77 4.44 12.01 14.65 8.68 14.67 10.11
植被 2.33 2.24 4.51 3.67 4.15 3.10 3.44 3.18 4.01 3.10
耕地 29.20 9.27 28.46 15.17 25.10 15.22 25.32 16.40 22.87 18.42
人工用地 35.07 7.87 25.36 17.85 26.85 16.21 27.17 12.88 21.45 13.81
采矿用地 — — 127.90 14.23 35.17 15.52 25.40 12.99 17.07 14.37
裸地 5.26 6.11 7.86 12.10 6.74 13.37 11.04 14.44 4.42 20.12
Tab.3  Land use intensity change of study area at category level
Fig.5  Land use intensity change of study area at transition level
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