院报 ›› 2023, Vol. 40 ›› Issue (11): 56-62.DOI: 10.11988/ckyyb.20220860

• 水土保持与生态修复 • 上一篇    下一篇

长寿区长时序生态质量评价及影响因素分析

林娜, 张迪, 潘建平, 冯珊珊, 潘鹏   

  1. 重庆交通大学 智慧城市学院,重庆 400074
  • 收稿日期:2022-07-20 修回日期:2022-10-10 出版日期:2023-11-01 发布日期:2023-11-09
  • 作者简介:林娜(1981-),女,湖北襄阳人,副教授,博士,硕士生导师,主要研究方向为遥感图像处理。E-mail:56654072@qq.com
  • 基金资助:
    国家重点研发计划项目(2021YFB2600600,2021YFB2600603);宁夏自治区重点研发计划项目(2022CMG02014)

Long-time Series Ecological Quality Assessment and Influencing Factors Analysis for Changshou District, Chongqing

LIN Na, ZHANG Di, PAN Jian-ping, FENG Shan-shan, PAN Peng   

  1. School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China
  • Received:2022-07-20 Revised:2022-10-10 Online:2023-11-01 Published:2023-11-09

摘要: 分析长寿区生态质量时空演变过程和影响因素对三峡库区生态建设及恢复具有重要意义。选取长寿区为研究区,以2002—2021年多景Landsat-5 TM 影像和 Landsat-8 OLI 影像构建遥感生态指数(RSEI),从时间和空间两个维度研究生态质量演变过程,并通过随机森林模型分析生态质量和影响因子之间的关系。结果表明:①长寿区RSEI均值由2002年的0.642 7降低到2006年的0.566 5,2010年以后RSEI均值稳步增加,生态质量呈“先恶化后好转,整体向好发展”的趋势;②生态质量较好的区域集中在高程较高的区域,较差的区域集中在长江两岸的工业园区、化工园区、城镇居民居住区;③2002—2021年长寿区生态质量改善面积为628.838 km2,占比44.16%;退化面积为183.269 km2,占比12.87%,改善效果明显;④随机森林模型分析发现高程和人口密度是影响RSEI空间变化的主要因子,人类活动和地形因素对区域生态质量变化起主导作用。利用RSEI和随机森林模型可以对长寿区及三峡库区内其他相似区域进行生态质量评价。

关键词: 生态质量, RSEI, 随机森林, 时空变化, 驱动力, 三峡库区, 长寿区

Abstract: Studying the spatio-temporal evolution process and changing factors of ecological quality in Changshou District of Chongqing is of great significance for the ecological construction and restoration of the Three Gorges Reservoir area. In this study, we utilized Landsat-5 TM images and Landsat-8 OLI images from 2002 to 2021 and constructed the Remote Sensing Ecological Index (RSEI). With the RSEI, we investigated the evolution of ecological quality in Changshou District from both temporal and spatial perspectives. Additionally, we employed the random forest model regression to analyze the correlation between ecological quality and potential driving factors. Our findings revealed the following: 1) The average RSEI in Changshou District declined from 0.642 7 in 2002 to 0.566 5 in 2006. However, since 2010, the average RSEI has exhibited a steady increase, indicating an overall improvement in ecological quality after a previous deterioration. 2) The areas with better ecological quality mainly concentrates in higher elevation regions, whereas the industrial park, chemical industry park, and urban residential areas along the Yangtze River exhibited relatively poorer ecological conditions. 3) Over the period from 2002 to 2021, Changshou District experienced an improved area of 628.838 km2, accounting for 44.16% of the total, and a degraded area of 183.269 km2, which represented 12.87% of the total. The overall effect of ecological quality improvement was evident. 4) Through random forest regression analysis, we identified elevation and population density as the primary potential driving factors influencing RSEI changes. Moreover, human activities and terrain factors played a dominant role in regional ecological changes. As a result, RSEI and the random forest model can be effectively utilized for evaluating the ecological quality of both Changshou District and similar areas within the Three Gorges Reservoir region.

Key words: ecological quality, RSEI, random forest, space-time variations, driving factors, Three Gorges Reservoir area, Changshou District

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