RSEI-Based Modeling of Ecological Security and Its Spatial Impacts on Soil Quality: A Case Study of Dayu, China

Abstract

Rapid urbanization and industrialization have brought serious threats to urban ecological security, which refers to the health and integrity of urban ecosystems. By collecting multi-source data in the modeling of the ecological security pattern, we used the remote sensing ecological index (RSEI) to identify the ecological sources (ESOs), and applied five indicators to construct the resistance surface, including land-use type, normalized vegetation index (NDVI), normalized building index (NDBI), slope, and digital elevation model (DEM). Based on the ESOs and ecological resistance surface, we calculated the cost distance of each pixel to the nearest ESO using the minimum cumulative resistance model. With the natural breakpoint method, we classified the cost distance into five levels, and constructed the ecological security pattern of Dayu. In Dayu, there were areas of at least 40% with stable ecological security. We identified 39, 31, and 43 ESOs of Dayu in 2012, 2016, and 2020, respectively. During 2012 to 2016, the number of medium ESOs decreased from 16 to 5, and the number of small ESOs increased from 13 to 26. From 2016 to 2020, the number of medium-sized ESOs increased from 5 to 18, and the number of small-sized ESOs decreased from 26 to 20. The percentage of the Level-5 (the worst) ecological security was 5.84% in 2012, 6.80% in 2016, and 4.42% in 2020. The ecological security was negatively correlated with the intensity of the human activities and varied significantly in different towns. The soil quality was positively consistent with the ecological security, and the urbanization caused damage to the soil security. A few suggestions were finally provided for decision-makers to improve the ecological environments and the soil quality.