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中国沙漠 ›› 2025, Vol. 45 ›› Issue (4): 139-152.DOI: 10.7522/j.issn.1000-694X.2025.00116

• • 上一篇    

京津风沙源治理工程区生态环境质量及驱动力

王卫国(), 谢欢, 冯国庆, 家淑珍   

  1. 山西师范大学 地理科学学院,山西 太原 030031
  • 收稿日期:2025-05-15 修回日期:2025-07-10 出版日期:2025-07-20 发布日期:2025-08-18
  • 作者简介:王卫国(1992—),男,山西忻州人,博士,副教授,主要从事生态环境遥感方面的研究。E-mail: wangwg@sxnu.edu.cn
  • 基金资助:
    山西省哲学社会科学规划课题(2023YJ055);山西省基础研究计划(自由探索类)青年项目(202303021222182);山西省基础研究计划(自由探索类)青年项目(202303021222183);山西师范大学自然科学基金基础研究项目(JCYJ2024023)

Ecological environment quality and driving forces in the Beijing-Tianjin Sandstorm Source Control Project area

Weiguo Wang(), Huan Xie, Guoqing Feng, Shuzhen Jia   

  1. College of Geographical Sciences,Shanxi Normal University,Taiyuan 030031,Shanxi,China
  • Received:2025-05-15 Revised:2025-07-10 Online:2025-07-20 Published:2025-08-18

摘要:

作为中国北方核心生态屏障,京津风沙源治理工程区长期面临沙尘暴频发、土地沙化加剧及植被显著退化等复合型生态胁迫,提升生态工程效能对厘清其生态环境质量时空演化机制具有迫切需求。本研究耦合Google Earth Engine(GEE)云平台与多源遥感数据,构建融合热度、绿度、湿度、干度四维特征的遥感生态指数,系统分析2000—2020年京津风沙源二期治理工程区生态环境质量时空分异规律。通过最优参数地理探测器模型定量解析多维驱动因子的独立及交互效应。结果表明:(1)京津风沙源治理工程区2000—2020年生态质量呈上升趋势,生态环境质量为差、较差等级面积减小,一般、良、优等级面积增加;生态环境质量地域差异明显,总体呈现东南部生态环境优越、西北部生态环境恶劣的特点。(2)探究区域生态环境影响因素表明影响因素、分级方法、分级数量均对生态环境质量的解释力产生重要影响。(3)各影响因素对生态环境质量的影响程度不同,年降水量与植被净初级生产力对生态环境质量的影响最显著。

关键词: 遥感生态指数, 最优参数地理探测器, MODIS, 京津风沙源治理工程区

Abstract:

The Beijing-Tianjin Sandstorm Source Control Project area (BTSSCPA) serves as a crucial ecological barrier in northern China, which has long been subjected to ecological pressures including sandstorms, desertification, and vegetation degradation. There is an urgent need to conduct scientific assessments of the spatiotemporal evolution patterns and driving mechanisms of ecological environment quality in the BTSSCPA. This study monitored and analyzed the ecological environment quality in the BTSSCPA based on the remote sensing ecological index (RSEI). Leveraging the Google Earth Engine (GEE) platform, we constructed four indicators-heat, greenness, wetness, and dryness-using MODIS datasets to characterize the spatiotemporal patterns of ecological environment quality from 2000 to 2020. The Optimal Parameters-based Geographical Detector (OPGD) was employed to identify key influencing factors. Results were showed on the following: (1) The ecological environment quality of the BTSSCPA demonstrated a significant upward trend from 2000 to 2020. Analysis of ecological environment quality grading revealed a notable reduction in areas classified as "poor" and "relatively poor", accompanied by a simultaneous expansion of regions categorized as "moderate", "good", and "excellent". Distinct spatial heterogeneity was observed in environmental quality distribution, manifesting a clear geographical pattern: superior ecological conditions predominated in southeastern sectors, while northwestern regions exhibited comparatively inferior environmental status. (2) Different factors, classification methods (e.g., natural breaks vs. quantile) and the number of classification strata critically impacted the explanatory power of ecological environment quality assessments. (3) The influence of factors varied substantially, with annual precipitation and vegetation net primary productivity (NPP) demonstrating the most significant effects on ecological environment quality.

Key words: remote sensing ecological index, optimal parameters-based geographical detector, MODIS, Beijing-Tianjin Sandstorm Source Control Project area

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