基于GEE云计算的南宁市生态环境质量时空分异监测

刘秋华; 谢余初; 覃宇恬; 张宇; 杨坤士

doi:10.13961/j.cnki.stbctb.2023.05.015

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基于GEE云计算的南宁市生态环境质量时空分异监测

试验研究

- 基于GEE云计算的南宁市生态环境质量时空分异监测
- Dynamic Monitoring and Spatio-temporal Pattern of Ecological Environmental Quality in Nanning City Based on Google Earth Engine
- 水土保持通报 2023年43卷第5期页码：121-127
- 作者机构：
  
  1. 南宁师范大学北部湾环境演变与资源利用教育部重点实验室,广西,南宁,530001
  2. 南宁师范大学地理科学与规划学院广西地表过程与智能模拟重点实验室,广西,南宁,530001
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“北部湾经济区南流江流域生态系统服务时空变化与权衡研究”(41761039)，“喀斯特峰丛洼地土壤养分过程及其生态系统服务权衡”(42071135);广西科技基地与人才专项(桂AD20159065);广西特聘专家人才项目(2019B16)
- DOI：10.13961/j.cnki.stbctb.2023.05.015
  中图分类号： X87;TP79;X826
- 纸质出版：2023
- 稿件说明：
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刘秋华, 谢余初, 覃宇恬, 等. 基于GEE云计算的南宁市生态环境质量时空分异监测[J]. 水土保持通报, 2023,43(5):121-127.

Liu Qiuhua, Xie Yuchu, Qin Yutian, et al. Dynamic Monitoring and Spatio-temporal Pattern of Ecological Environmental Quality in Nanning City Based on Google Earth Engine[J]. Bulletin of Soiland Water Conservation, 2023, 43(5): 121-127.
刘秋华, 谢余初, 覃宇恬, 等. 基于GEE云计算的南宁市生态环境质量时空分异监测[J]. 水土保持通报, 2023,43(5):121-127. DOI： 10.13961/j.cnki.stbctb.2023.05.015.

Liu Qiuhua, Xie Yuchu, Qin Yutian, et al. Dynamic Monitoring and Spatio-temporal Pattern of Ecological Environmental Quality in Nanning City Based on Google Earth Engine[J]. Bulletin of Soiland Water Conservation, 2023, 43(5): 121-127. DOI： 10.13961/j.cnki.stbctb.2023.05.015.

摘要

[目的] 利用遥感技术及时、动态、客观地监测和评估城市生态环境质量变化，为城市生态环境规划与管理提供参考。[方法] 以南宁市为案例，利用Google Earth Engine (GEE)平台对2000—2020年Landsat系列遥感影像进行像元级融合、消除色彩、去云等预处理，计算绿度、湿度、干度和热度这4个遥感指标，并采用主成分分析法构建遥感生态指数，定量评价南宁市生态环境质量动态变化及空间分异特征。[结果] 南宁市RSEI多年平均值为0.615，总体呈现“下降—上升—稳定”的波动上升趋好的态势。生态环境质量较好的区域主要是自然保护区、山林地、草地和水域，生态环境质量较差的区域则集中于人类活动频繁，土地利用强度较大的城镇及城乡交错区、农耕区。生态环境质量与植被绿度和湿度指标呈正相关，与干度和热度指标呈负相关，且干度指标因子对RSEI影响程度最大。[结论] 南宁市2000—2020年生态环境质量总体处于良好水平且呈上升态势。结合GEE和RSEI指数能够较好地反映城市生态环境质量，为城市生态环境质量长时间序列监测提供计算平台。

Abstract

[Objective] Remote sensing technology is used to monitor and evaluate the change of urban ecological environment quality timely

dynamically and objectively

in order to provide reference for urban ecological environment planning and management. [Methods] Landsat TM/ETM+/OLS historical images of the same season from 2000 to 2020 were collected. The Google Earth Engine (GEE) platform was used to perform pixel-level cloud removal and chromatic aberration correction. The median value composite was used to calculate four remote sensing indicators including greenness

wetness

dryness

and heat. The remote sensing ecological index (RSEI) was constructed by principal component analysis (PCA) to evaluate the dynamic changes and spatial differentiation characteristics of urban ecological environmental quality in Nanning City with the help of the parallel cloud computing ability in GEE. [Results] The average value of RSEI was 0.615 in Nanning City

and its ecological environmental quality was observed to follow an overall fluctuating upward trend of “decreasing-increasing-stable”. The spatial heterogeneity of ecological environmental quality in Nanning City was obvious. The areas with better ecological environmental quality were mainly concentrated in the nature reserves

forest lands

grasslands and water areas

while the degraded areas of ecological environmental quality were mainly located in the cities

urban-rural transition zones and farming areas with frequent human activities and greater land use intensity. RSEI was positively correlated with greenness and wetness indicators

and negatively correlated with dryness and heat

and dryness index factor had the greatest influence on RSEI. [Conclusion] The ecological environmental quality of Nanning City was well characterized by RSEI

and the overall ecological environmental quality was at a good level from 2000 to 2020. The combination of GEE and RSEI could effectively improve the use of remote sensing images

and therefore could be used for long-term monitoring and assessing of ecological environmental quality in the urban region.

关键词

Keywords

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