Journal of Geographical Sciences ›› 2021, Vol. 31 ›› Issue (2): 265-280.doi: 10.1007/s11442-021-1846-8

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

HUANG Huiping1,2(), CHEN Wei1,2, ZHANG Yuan1,*(), QIAO Lin1,2, DU Yunyan3,2   

  1. 1. Aerospace Information Research Institute, CAS, Beijing 100094, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2020-03-30 Accepted:2020-07-23 Online:2021-02-25 Published:2021-04-25
  • Contact: ZHANG Yuan;
  • About author:Huang Huiping (1973-), PhD and Professor, specialized in remote sensing for urban analysis.
  • Supported by:
    Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040401)


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) platform. The Remote Sensing Ecological Index (RSEI) was adopted, and calculated in an efficient way with the assistance of parallel cloud computing of the GEE platform. The RSEI was used in this paper to evaluate and monitor the eco-environmental quality of the Lhasa Metropolitan Area. Results 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 point. The 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 indicators. This 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.

Key words: Lhasa Metropolitan Area, ecological quality, remote sensing, ecological index, Google Earth Engine