Spatial correlation analysis between human disturbance intensity (HDI) and ecosystem services value (ESV) in the Chengdu-Chongqing urban agglomeration

Distribution and Change Characteristics of Ecosystem Services in Highly Urbanized Areas along Gradients of Human Activity Intensity: A Case Study of Shenzhen City, China

“…From the point of view of methodological difficulties, the global disturbance index method is the simplest in that it directly uses MODIS product data, followed by the land type change method [56]; however, the global disturbance index method is only applicable to forested areas and can only evaluate the impacts of a few types of human activities, while the land type change method has obvious shortcomings in terms of the accuracy of the evaluation results [57]. From this point of view, the comprehensive index method is the best, followed by the human footprint index method [1], but data prepared using the comprehensive index method have obvious shortcomings in terms of spatial refinement and fineness [58]. In summary, we found that the human footprint index model is more suitable for the spatial quantification of HAI in terrestrial systems.…”

“…research objectives are as follows: (1) to understand the spatial and temporal characteristics of ESs and HAI in economically developed areas and (2) to explore the relationship between gradient differences in ESs and gradient changes in HAI. This study overcomes the deficiencies of existing research findings and explores the spatial relationship between HAI and ESs from a gradient perspective, in order to provide data support and a scientific basis for the sustainable development in high-utilization urban areas.…”

“…Human activity intensity (HAI) refers to the degree of disturbance caused by human activities in a certain area [1]; as a universal phenomenon in nature, HAI directly or indirectly affects the succession of ecosystems [2]. Ecosystem services (ESs) are defined as benefits or contributions provided by natural ecosystems that can be utilized by humans [3,4]; these services are the material basis for human survival and development, and are the bridge between natural ecosystems and human beings [5].…”

“…In terms of research methodology, scholars have further explored the quantitative correlation between human activities and environmental systems with the help of coupled coordination models [20], while less research has been conducted on the spatial correlation between HAI and ESs, as well as on the spatial distribution of the degree of correlation. There needs to be more research on whether a spatial autocorrelation exists between HAI and ESs [1], what kinds of characteristics that spatial aggregation may present, and whether the spatial relationship between the two evolves with spatial and temporal changes. In real contexts, there are different scales of action for the effect of HAI on ESs, and thus a single bandwidth cannot well reflect the spatial process of the action intensity between variables [40].…”

A Dynamic Perspective on the Coevolution of Urbanization and Ecosystem Services in the Yangtze River Delta: Patterns, Processes, and Implications

“…In terms of research methods, most studies have adopted spatial analysis and spatial statistics, using software such as ArcGIS, FRAGSTATS, and GeoDa to depict the impact of urbanization on the spatial patterns of ecosystem services from the perspectives of landscape patterns and spatial autocorrelation. Among these, the global spatial autocorrelation (Global Moran's I) and local spatial autocorrelation (Anselin Local Moran's I) methods in GeoDa effectively reveal the spatial aggregation characteristics and spatial heterogeneity of ecosystem services, gaining increasing attention from scholars [19][20][21]. Despite the substantial achievements in exploring the impact of Urbanization I on ecosystem services, there is insufficient attention to the implicit characteristics of Urbanization II.…”