Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China

Abstract

Scientific territorial spatial planning is of great significance in the realization of the sustainable development goals in China, especially in the context of China’s ecological civilization construction and territorial spatial planning. However, limited research has been carried out to understand the spatio-temporal change in EEQ and territorial spatial planning. In this study, Changsha County and six districts of Changsha City were selected as the research objects. Based on the remote sensing ecological index (RSEI) model, the spatio-temporal changes in the EEQ and spatial planning response in the study area during 2003–2018 were analyzed. The results reveal that (1) the EEQ of Changsha declined and then rose between 2003 and 2018, showing an overall decreasing trend. The average RSEI declined from 0.532 in 2003 to 0.500 in 2014 and then increased to 0.523 in 2018, with an overall decrease of 1.7%. (2) In terms of spatial pattern changes, the Xingma Group, the Airport Group and the Huangli Group in the east of the Xiangjiang River had the most serious EEQ degradation. The EEQ degradation of Changsha showed an expanding and polycentric decentralized grouping pattern. (3) Massive construction land expansion during rapid urbanization caused significant EEQ degradation in Changsha. Particularly, the areas with low EEQ were concentrated in the areas with concentrated industrial land. Scientific territorial spatial planning and strict control were conducive to regional EEQ improvement. (4) The prediction using the urban ecological model demonstrates that every 0.549 unit increase in NDVI or 0.2 unit decrease in NDBSI can improve the RSEI of the study area by 0.1 unit, thus improving EEQ. In the future territorial spatial planning and construction of Changsha, it is necessary to promote the transformation and upgrading of low-end industries into high-end manufacturing industries and control the scale of inefficient industrial land. The EEQ degradation caused by industrial land expansion needs to be noted. All of these findings can provide valuable information for relevant decision-makers to formulate ecological environment protection strategies and conduct future territorial spatial planning.

Evolution and Spatiotemporal Response of Ecological Environment Quality to Human Activities and Climate: Case Study of Hunan Province, China

“…These results are similar to those of prior studies [16,44]. Between 2000 and 2020, the ecological environment quality of approximately half (49.4%) of the regions substantially changed, of which approximately 46.97% and 2.42% of the regions experienced ecological environment quality improvement and deterioration, respectively, the latter of which mainly occurred around various towns, especially around the provincial capital Changsha [45].…”

Balancing Urban Expansion and Ecological Connectivity through Ecological Network Optimization—A Case Study of ChangSha County

“…In 2020, the total industrial output of Changsha County reached CNY 77.848 billion [26]. It has about one-third of Changsha City's construction plants, and the industrial level is the highest among all counties in Changsha City [34]. However, there is also the fact that the ecological environment in Changsha County is deteriorating.…”

“…However, there is also the fact that the ecological environment in Changsha County is deteriorating. From 2003 to 2018, 26.94% of the area of Changsha City was severely degraded in terms of ecological environment quality, with Changsha County accounting for the largest share [34].…”

Spatial and Temporal Dynamic Evolution and Correlation of Ecological Quality and Ecosystem Service Value in Fujian Province

“…In addition to integrating four easily accessible ecological evaluation indicators, namely green, dry, wet and heat, the RSEI also uses a Principal Component Analysis (PCA) to automatically and objectively weight each indicator. There have been numerous studies using this method to quantify and accurately evaluate EQ [9], such as those conducted in watersheds [10][11][12], mining areas [13,14], wetlands [15,16], cities [17][18][19][20], etc.…”