Evaluation of ecological environment quality and analysis of influencing factors based on IRSEI: A case study of the southern region of Panzhihua
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摘要:
矿业活动区生态环境脆弱，水土流失、植被破坏、生物多样性降低等生态环境问题频现。为深层次、多样化评价矿业活动区生态环境质量，本文提出一种改进型遥感生态指数（IRSEI），它在原有遥感生态指数（RSEI）基础上，引入生物多样性指数，更好地描述了生态环境的多样性和复杂性。本文以攀枝花南部地区为例，利用陆地卫星（Landsat）影像和数字高程模型（DEM）数据计算了2000—2022年的IRSEI值，基于转移路径和局部空间自相关指标分析了生态环境质量时空分布和变化特征，并采用地理探测器开展了成因分析。结果表明，研究区生态环境质量呈现出明显两极分化趋势，生态质量优良和较差的区域面积均呈现增加趋势，而中等生态质量区域面积减少。研究区生态环境质量在空间上呈现出显著聚集性，高度聚集区主要分布在北部和东部的山区，低度聚集区主要分布在金沙江两岸和城镇区。影响生态环境质量的主要因素是归一化植被指数（NDVI）、干度指数（NDBSI）和生物多样性指数（BI），而热度指数（LST）的影响较小。生态环境质量改善主要归因于植被覆盖度提高和生物多样性增加，而生态环境质量恶化主要受到矿业开发、石漠化和城市扩张影响。本文为区域生态环境监测和保护提供了一种新的方法和参考。
Abstract:The ecological environment in mining activity areas is fragile, with frequent ecological problems such as soil erosion, vegetation damage, and reduced biodiversity.To provide a comprehensive and diverse evaluation of ecological environment quality in mining areas, this paper presents an improved remote sensing ecological index (IRSEI). By incorporating a biodiversity index into the original remote sensing ecological index (RSEI), it better depicts the diversity and complexity of the ecological environment. Taking the southern region of Panzhihua as a case study, IRSEI values were calculated for the years 2000 to 2022 utilizing landsat images and digital elevation model (DEM) data. Based on transfer path analysis and local spatial autocorrelation indicators, the spatiotemporal distribution and change characteristics of ecological environment quality were analyzed. Additionally, causality analysis was conducted using geographic detectors. The results show that there is a clear polarization trend in the ecological environment quality of the study area. Areas with excellent and poor ecological quality both exhibit an increasing trend in area, while areas with moderate ecological quality are decreasing. The spatial distribution of ecological environment quality in the study area shows significant clustering. Highly clustered areas are mainly distributed in the mountainous regions in the north and east, while lowly clustered areas are mainly distributed along the banks of the Jinsha River and in urban areas. The main factors influencing the ecological environment quality are normalized difference vegetation index (NDVI), normalized difference built-up and soil index (NDBSI), and biodiversity index (BI), while the influence of land surface temperature (LST) is relatively minor. The improvement in ecological environment quality is mainly attributed to increased vegetation coverage and biodiversity. Conversely, the deterioration of ecological environment quality is mainly affected by mining development, rocky desertification, and urban expansion. This paper provides a new method and reference for regional ecological environment monitoring and protection.
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表 1 研究区数据源信息表
Table 1. Data source information table for the study area
数据类型 获取时间 空间分辨率 数据质量 数据来源 TM 2000年12月19日 30 m 无云，沿河有水汽影响 遥感影像数据来源于GEE、
DEM数据下载于地理空间数据云
（ASTER GDEM ）2005年1月31日 30 m 无云，质量好 2010年1月29日 30 m 无云，质量好 OLI 2015年1月27日 30 m、15 m 无云，质量好 2022年1月30日 30 m、15 m 无云，质量好 DEM 2010年 30 m / 
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表 2 生物多样性指标权重表（刘少阳等，2020）
Table 2. Weight table of biodiversity indicators
序号 BI指标 数据来源 计算方法 指标值权重 1 HQI 土地利用数据 InVEST软件 0.35 2 NPP TM与OLI CASA软件 0.25 3 EVI TM与OLI 遥感软件 0.15 4 SP 土地利用数据 Fragstats软件 0.1 5 SHDI 土地利用数据 Fragstats软件 0.15
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表 3 研究区2000—2022年生态质量面积统计表
Table 3. Statistical table of ecological quality area in the study area from 2000 to 2022
时间 面积及占比 差 较差 中等 良 优 2000年 面积/km2 13.69 90.11 300.00 1420.59 748.72 占比/% 0.53 3.50 11.66 55.21 29.10 2005年 面积/km2 88.23 178.88 314.22 1076.60 915.16 占比/% 3.43 6.95 12.21 41.84 35.57 2010年 面积/km2 81.19 181.68 271.55 1194.07 844.61 占比/% 3.16 7.06 10.55 46.41 32.82 2015年 面积/km2 72.73 144.79 283.39 1194.70 877.48 占比/% 2.83 5.63 11.01 46.43 34.10 2022年 面积/km2 120.20 162.64 282.46 1104.15 903.64 占比/% 4.67 6.32 10.98 42.91 35.12
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表 4 研究区各期生态因子解释力探测结果
Table 4. Results of ecological factor interpretation detection in the study area
生态因子 2000年 2005年 2010年 2015年 2022年 P值 q值 P值 q值 P值 q值 P值 q值 P值 q值 NDVI ＜0.001 0.874 ＜0.001 0.893 ＜0.001 0.910 ＜0.001 0.849 ＜0.001 0.908 WET ＜0.001 0.624 ＜0.001 0.587 ＜0.001 0.614 ＜0.001 0.576 ＜0.001 0.625 NDBSI ＜0.001 0.758 ＜0.001 0.852 ＜0.001 0.836 ＜0.001 0.847 ＜0.001 0.903 LST ＜0.001 0.378 ＜0.001 0.271 ＜0.001 0.187 ＜0.001 0.416 ＜0.001 0.355 BI ＜0.001 0.851 ＜0.001 0.863 ＜0.001 0.921 ＜0.001 0.857 ＜0.001 0.912
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表 5 RSEI和IRSEI第一主成分（PC1）的百分比
Table 5. Percentages of the first principal component （PC1） derived from RSEI and IRSEI
方法 PC1值 2000年 2005年 2010年 2015年 2022年 RSEI 78.1% 80.34% 77.59% 79.2% 83.12% IRSEI 85.14% 86.84% 86.87% 89.1% 88.74%
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表 6 生态质量为“差”的区域地质因素分析表
Table 6. Distribution of regions with poor ecological quality and their stratigraphic lithology
序号 区块 成因 地质环境条件 面积 1 研究区金沙江上段福田镇一带 煤矿开采 以含煤沉积岩为主 20.42 km2 2 研究区金沙江中段 城市扩张 各岩类均有覆盖，以变质岩占比最多 6.17 km2 铁矿开采 以岩浆岩和变质岩为主 30.00 km2 3 研究区金沙江下段 石漠化 以碳酸盐岩为主 32.03 km2 4 新九乡、益民乡、红格镇北部 煤矿开采 以含煤沉积岩为主 18.48 km2
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