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Remote Sensing for Land & Resources    2019, Vol. 31 Issue (4) : 60-68     DOI: 10.6046/gtzyyg.2019.04.09
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Temporal and spatial evolution in landscape pattern of mining site area based on moving window method
Zhaorong MEI1, Yunju LI2, Xiang KANG1, Shanbao WEI1, Jianjun PAN3()
1. College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China
2. National Phosphate Resources Development and Utilization Engineering Technology Research Center, Kunming 650500, China
3. College of Resources and Environment, Nanjing Agricultural University, Nanjing 210095, China
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Abstract  

This study is aimed to discuss the temporal and spatial evolution of landscape pattern under the impact of mining work. With the support of moving window analysis and geographic information system (GIS) technology, the authors extracted the spatial distribution map of landscape fragmentation and diversity index from three remote sensing image data in one open-air mining site in Kunming from 2007 to 2017. On the basis of obtaining landscape types and determining appropriate window scales, the spatial distribution maps of landscape fragmentation and diversity index were extracted, and then mining site cores were connected to build transects for spatial overlay analysis. The result shows that, under the most suitable window range of 950 m, the high value center of landscape fragmentation and diversity index spread from the regional edge to the center from 2007 to 2017. The effect of patch aggregation in open mining area was remarkable, and the fragmentation and diversity effect of surrounding area in nearly 1~2 km were obvious year by year. At the same time, the area beyond 2.5 km of the mining center was on the whole not affected by mining activities. The result visually shows the rule for the temporal and spatial evolution of landscape pattern affected by mining activities, and the result can provide data support for follow-up work.
Keywords mining activities      moving window analysis      GIS technology      landscape pattern index     
:  TP79  
  P901  
Corresponding Authors: Jianjun PAN     E-mail: jpan@njau.edu.cn
Issue Date: 03 December 2019
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Zhaorong MEI
Yunju LI
Xiang KANG
Shanbao WEI
Jianjun PAN
Cite this article:   
Zhaorong MEI,Yunju LI,Xiang KANG, et al. Temporal and spatial evolution in landscape pattern of mining site area based on moving window method[J]. Remote Sensing for Land & Resources, 2019, 31(4): 60-68.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2019.04.09     OR     https://www.gtzyyg.com/EN/Y2019/V31/I4/60
Fig.1  Landscape type, transect setting and sample point distribution in study area in 2007, 2013 and 2017
景观类型 2007年 2013年 2017年
用户精度/% 制图精度/% 用户精度/% 制图精度/% 用户精度/% 制图精度/%
灌草地 85.88 88.29 88.68 95.84 80.81 79.66
林地 87.04 92.65 88.14 98.02 86.53 96.91
工矿用地 93.00 97.41 91.05 98.74 89.88 95.81
耕地 93.64 96.27 90.07 95.02 97.78 94.02
居民地 86.54 89.87 87.31 98.35 96.31 95.05
水体 87.04 82.65 92.46 100.00 100.00 100.00
Kappa系数 0.89 0.91 0.91
Tab.1  Precision evaluation of classified results
景观类型 2007年 2013年 2017年
TA/km2 PLAND/% TA/km2 PLAND/% TA/km2 PLAND/%
灌草地 39.03 39.53 20.23 20.49 25.98 26.31
林地 31.70 32.10 36.51 36.98 31.29 31.69
工矿用地 13.11 13.28 18.42 18.65 20.44 20.70
耕地 9.26 9.37 10.07 10.20 9.92 10.05
居民地 5.59 5.66 13.17 13.33 10.57 10.71
水体 0.06 0.06 0.35 0.35 0.54 0.54
总计 98.74 100.00 98.74 100.00 98.74 100.00
Tab.2  Area of each landscape types and their percentages during 2007—2017
Fig.2  Landscape index under the different scales
Fig.3  Distribution and change of PD in study area during 2007—2017
Fig.4  Distribution and change of LPI in study area during 2007—2017
Fig.5  Spatial distribution map of landscape diversity in study area during 2007—2017
Fig.6  Change of landscape fragmentation index along transcets
Fig.7  Change of SHDI along transcets
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