基于谷歌地球引警和改进型遥感生态指数的西安市生态环境质量动态监测

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 基于谷歌地球引警和改进型遥感生态指数的西安市生态环境质量动态监测 DOI: 10.5846/stxb202112103510 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41371220，42071345）；陕西省重点研发项目（2020ZDLSF06-07） Dynamic monitoring of eco-environmental quality in Xi'an based on GEE and adjusted RSEI Author: Affiliation: Fund Project: National?Natural?Science?Foundation?of?China,No.41371220,No.42071345；Key Research and Development Program of Shaanxi Province,No.2020ZDLSF06-07 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:近年来，在经济全球化的背景下，西安市经济迅速增长，生态环境问题日益突出，快速全面地定量监测生态环境质量的时空变化，对指导生态环境保护具有重要意义。基于谷歌地球引警（GEE）平台，筛选2000、2004、2010、2015、2020年及其前后各一年的四季Landsat影像，利用主成分分析基于绿度（NDVI）、热度（LST）、干度（NDSI）、湿度（Wet）和气溶胶光学厚度（AOD）构建改进型遥感生态指数（ARSEI），实现西安市2000-2020年生态环境质量的动态监测，并运用莫兰指数（Moran's I）探讨西安市生态环境质量的空间自相关。以主成分效果最好的夏季为例，结果表明：（1）构建的ARSEI将大气污染因素考虑在内，第1主成分（PC1）贡献度在83%以上，能较好地集中各指标特征，有助于更加全面地评价研究区生态环境质量；（2）西安市2000-2020年平均ARSEI分别为0.565、0.521、0.572、0.644、0.695，生态环境质量总体呈现先退化后转好的趋势。20年来，生态环境质量较差和极差等级的面积减少了1339.08 km2，主要分布在秦岭以北地区，良好和极好等级区面积增加了2241.80 km2，主要位于南部的秦岭地区；（3）西安市生态环境质量改善区面积大于退化区，改善和退化情况在各辖区均有发生。2000-2004年退化情况最为严重，占比29.41%，而2010-2015年改善区占比最大，达31.62%；（4）5个年度的全局莫兰指数（Global Moran's I）均在0.627以上，表明西安市生态环境质量的空间分布具有较强的正相关，呈聚集分布，且以高-高、低-低分布为主。研究基于GEE平台实现了西安市生态环境质量的快速监测，可为生态环境监测与治理保护提供方法借鉴与数据支撑。 Abstract:As the capital city of Shaanxi Province, Xi'an has experienced rapid economic growth and urbanization under the economic globalization background in recent decades and still besets by increasingly prominent ecological problems. Xi'an is also one of the typical cities suffering from severe aerosol pollution in China. Rapidly and comprehensively quantitative monitoring of the spatio-temporal variations of eco-environmental quality in Xi'an is crucial for regional eco-environmental guidance and protection. This study was carried out on Google Earth Engine (GEE), a new cloud-computing platform with the merits of easy access to tremendous public resources and convenient processing of substantially geospatial data. Four-season Landsat images of 2000, 2004, 2010, 2015, 2020 and those previous-successive target years were selected firstly. Then, principal component analysis (PCA) was used to improve the previously developed remote sensing ecological index (RSEI) by adding aerosol optical depth (AOD) to it, and an adjusted RSEI (ARSEI) including greenness (NDVI), heat (LST), dryness (NDSI), humidity (Wet) and AOD was proposed to dynamically monitor the eco-environmental quality in Xi'an from 2000 to 2020. Moreover, Moran index was adopted to explore the spatial autocorrelation of the eco-environmental quality in Xi'an. Using summer, the season with the best principal component effect, as an example, the results showed that:(1) taking the effect of air pollution into account, the first principal component (PC1) contribution of ARSEI proposed in this paper was more than 83%. ARSEI could better concentrate the characteristics of each index and provide a more comprehensive evaluation for the eco-environmental quality of Xi'an. (2) The average ARSEIs of Xi'an from 2000 to 2020 were 0.565, 0.521,0.572, 0.644 and 0.695, respectively, indicating that the urban eco-environmental quality degraded from 2000 to 2004 and promoted from 2004 to 2020. In the past 20 years, the areas with poor and very poor eco-environmental quality decreased by 1339.08 km2, which were mainly located in the north of Qinling Mountains. The areas with good and excellent eco-environmental quality increased by 2241.80 km2 and were concentrated in Qinling areas, southern part of the city. (3) The improved areas were larger than the degraded areas in Xi'an over the past 20 years, and each district has undergone both the improvement and degradation processes. It was worth noting that the city experienced the worst degradation from 2000 to 2004, accounting for 29.41%, and the greatest improvement between 2010 and 2015, accounting for 31.62%. Generally speaking, the eco-environmental quality of Xi'an has been improved in the past 20 years. (4) All the five Global Moran's I values were above 0.627 in 2000, 2004, 2010, 2015 and 2020, which indicated that the spatial distribution of the urban eco-environmental quality has a strongly positive correlation. The LISA cluster map showed that the aggregation distribution was dominated by high-high and low-low patterns. The low-low areas were mainly located in the northern Qinling Mountains, while the high-high areas were concentrated in the southern part of the city. Based on GEE cloud platform, this study accomplished fast eco-environmental quality monitoring in Xi'an and will provide method reference and data support for regional eco-environmental monitoring, management and restoration. 参考文献 相似文献 引证文献