Analysis of ecological quality in Lhasa Metropolitan Area during 1990-2017 based on remote sensing and Google Earth Engine platform

作     者：HUANG Huiping CHEN Wei ZHANG Yuan QIAO Lin DU Yunyan HUANG Huiping;CHEN Wei;ZHANG Yuan;QIAO Lin;DU Yunyan

作者机构：Aerospace Information Research InstituteCASBeijing 100094China University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Resources and Environmental Information SystemInstitute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China 

出 版 物：《Journal of Geographical Sciences》 (地理学报（英文版）)

年 卷 期：2021年第31卷第2期

页      面：265-280页

核心收录：

学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0709[理学-地质学] 07[理学] 08[工学] 0704[理学-天文学] 0713[理学-生态学] 

基　　金：Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040401) 

主　　题：Lhasa Metropolitan Area ecological quality remote sensing ecological index Google Earth Engine 

摘      要：Based on a total of 519 images,the composite images with the lowest possible cloud cover were generated at pixel level with image synthesis method on Google Earth Engine(GEE)*** Remote Sensing Ecological Index(RSEI)was adopted,and calculated in an efficient way with the assistance of parallel cloud computing of the GEE *** RSEI was used in this paper to evaluate and monitor the eco-environmental quality of the Lhasa Metropolitan *** show that:(1)The ecological quality is better in the west than in the east of Lhasa Metropolitan Area,with Lhasa as an approximate dividing *** ecological quality improved and then deteriorated dramatically before 2000,with the mean RSEI value dropping from 0.51 to 0.46;the trend was followed by a gradual increase up until 2017,with the mean RSEI value increased from 0.46 to 0.55.(2)The RSEI is weakly and positively correlated with socioeconomic *** indicates that the population growth and economic development did not negatively influence the ecological quality,but actually boosted it.(3)The GEE can serve as an efficient computing platform for the assessment and monitoring of eco-environmental quality in vast regions.