Dynamic Monitoring and Spatio-temporal Pattern of Ecological Environmental Quality in Nanning City Based on Google Earth Engine - Liu Qiuhua; Xie Yuchu; Qin Yutian; Zhang Yu; Yang Kunshi (Shuitu baochi tongbao, 2023)
[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.