Ecological Indicators (Feb 2023)
Evaluation of ecological space and ecological quality changes in urban agglomeration on the northern slope of the Tianshan Mountains
Abstract
Rapid urbanization and human activities make the contradiction between human and ecological environment more obvious, maintaining ecological balance and achieving harmonious development between living environment has also become the main goal of sustainable development. The urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM) is a typical arid inland emerging urban agglomeration, and the relationship between human activities and the ecological environment here is very sensitive. To reveal the spatiotemporal changes in ecological quality in the UANSTM from 2000 to 2020, this study used Google Earth Engine (GEE) platform, calculating remote sensing ecological index (RSEI) based on the MODIS data products, in addition to achieving an ecological space atlas based on the Land-Use and Land-Cover Change (LUCC) data sets. At same time, the geographical detector model (GDM) has been used to exploring the main influencing factor of RSEI. The result shows that 1) The mean value of RESI in the study area continued to rise in the first 15 a and decreased slightly in the last 5 a. 2) In the past 20 a, the area of improvement obvious (IO) has gradually expanded, and the proportion has gradually increased. The sum of the areas of deterioration obvious (DO) and deterioration slight (DS) is far smaller than the sum of the areas of improvement slight (IS) and improvement obvious (IO), which indicates that the ecological quality of UANSTMN is tends to improve. 3) The distribution of ecological space in the study area is ecological used land (EL) > semi-ecological used land (SEL) > weak ecological used land (WEL). The area of EL is gradually decreasing, while the area of SEL and WEL is gradually increasing. 4) In the past 20 a, the main influencing factor of RSEI in the study area is greenness, and the interaction of heat, dryness, and greenness had a more obvious effect on RSEI. The value of RSEI is better with higher greenness and wet, and with lower dryness or heat.
