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生态学杂志 ›› 2024, Vol. 43 ›› Issue (1): 290-298.doi: 10.13292/j.1000-4890.202401.022

• 技术与方法 • 上一篇    下一篇

基于GEE平台的黄河源区生态环境质量动态评价

赵开鑫1,2,3,李雪梅1,2,3*,王桂钢1,2,3,孙旭伟4,5


  

  1. 1兰州交通大学测绘与地理信息学院, 兰州 730070; 2甘肃省地理国情监测工程实验室, 兰州 730070; 3地理国情监测技术应用国家地方联合工程研究中心, 兰州 730070; 4甘肃省生态环境科学设计研究院, 兰州 730020; 5甘肃省黄河上游水源涵养区生态保护和修复工程研究中心, 兰州 730020)

  • 出版日期:2024-01-10 发布日期:2024-01-11

Dynamic evaluation of ecological environment quality in the Yellow River source region based on GEE platform.

ZHAO Kaixin1,2,3, LI Xuemei1,2,3*, WANG Guigang1,2,3, SUN Xuwei4,5#br#

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  1. (1Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China; 2Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China; 3National Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China; 4Gansu Academy of Eco-environmental Sciences, Lanzhou 730020, China; 5Ecological Protection and Restoration Engineering Research Center for Water Conservation Area in the Upper Reaches of the Yellow River in Gansu Province, Lanzhou 730070, China).

  • Online:2024-01-10 Published:2024-01-11

摘要: 黄河源区为我国生态脆弱区之一,近年来其生态环境问题备受关注。基于Google Earth Engine (GEE)平台并结合1990—2021年黄河源区Landsat遥感影像,本文综合6个指标(热度、干度、空气质量、绿度、湿度和叶面积指数)构建了遥感生态指数,对该区域生态环境质量动态进行了评价。结果表明:黄河源区热度、干度和空气质量指标对其生态环境质量呈负反馈作用;绿度、湿度和叶面积指数对生态环境质量呈正反馈作用,其中绿度为最关键的影响因素;黄河源区生态环境质量改善区占74.51%,总体呈“南优北劣”的空间格局,1990—2021年生态环境质量总体持续向好;1990—2021年,黄河源区89.75%的生态环境质量变化幅度较小,稳定性较好;Hurst指数分析表明,66.36%的黄河源区生态环境质量具有中强持续性,未来该区生态环境质量将会持续得到改善。


关键词: 遥感生态指数, Google Earth Engine, 黄河源区, 时空变化, 中强持续性

Abstract: The source region of the Yellow River is one of the ecologically fragile regions in China. In recent years, its ecological environment problems have attracted much attention. Based on the Google Earth Engine (GEE) platform and combined with the remote sensing images of Landsat in the source region from 1990 to 2021, we synthesized six indicators (heat, dryness, air quality, greenness, humidity, and leaf area index) to construct a remote sensing ecological index, which were used to evaluate the dynamics of ecological environment quality in this region. The heat, dryness, and air quality had a negative feedback effect on the ecological environment quality in the source region, while greenness, humidity, and leaf area index had a positive effect, of which greenness was the most critical influencing factor. The area with ecological environment quality improvement accounted for 74.51% of total area of the source region, with an overall spatial pattern of “southern superiority and northern inferiority”. The overall quality of the ecological environment improved during 1990-2021. Over the past 30 years, the ecological environment quality of 89.75% of total area of the source region experienced relatively small changes and maintained good stability. Hurst index analysis showed that the ecological environment quality of 66.36% of total area of the source region had medium and strong sustainability, and that the ecological environment quality in the source region will be better in the future.


Key words: remote sensing ecological index, Google Earth Engine, the source area of the Yellow River, spatiotemporal variation, medium to strong sustainability