Mechanism of Urban Spatial Morphology and Eco-Environmental Risk: A Case Study of Shenzhen, China

A new perspective on the relationship between urban spatial morphology (USM) and eco-environmental risk (ER) is provided by Local Climate Zones (LCZs). This paper takes Shenzhen as the research area: first, to construct the ER assessment index system based on the social-ecological subsystem, and quantify the level of ER and uncertainty with the help of Monte Carlo simulation; second, to perform the classification of LCZ with the help of Google Earth Engine (GEE) cloud platform, and identify the characteristic of morphology (including mean building height (MBH), floor area ratio (FAR), sky view factor (SVF), etc.); finally, to explore the mechanism of ER and USM in the risk hotspot areas from global and local scales with methods of multiscale geographically weighted regression (MGWR) and optimal parameter geodetic detector (OPGD). The findings are as follows: first, the average value of ER in 2020 was 0.58, which was at a higher-risk level overall, and its spatial distribution was differentiated, while the risk hotspot areas were mainly distributed in the west and center of the study area. Second, the USM was dominated by compact mid-rise (LCZ02), open high-rise (LCZ04), and densely forest (LCZ A), and the urban three-dimensional spatial structure indicators (MBH, FAR and SVF, etc.) also presents significant differences. Third, at the global and local scales, the effect intensity, scale and direction of urban three-dimensional spatial indicators in ecological and environmental risk hotspots on ER are different, and management decision-makers need to formulate differentiated improvement measures.