Forest Resource Quality and Human Activity Intensity Change and Spatial Autocorrelation Analysis in Yulin City, China

Abstract

With the rapid development of society and the economy, human activities are increasing, which often brings potential threats such as a decline in forest resource quality and ecological function. In order to investigate the change in forest resource quality and human activity intensity, this study constructed a calculation model for a forest resource quality index and a human activity intensity index and conducted a quantitative analysis of the temporal and spatial changes in forest resource quality and human activity intensity in Yulin City based on sub-compartment data in 2017 and 2020. By combining spatial autocorrelation analysis, the changes in human activity intensity and spatial forest resource quality were explored, and key areas such as the prominent contradictions between humans and the land were superimposed and coupled as potential areas of concern. The results show the following: From 2017 to 2020, the forest resource quality in Yulin City improved as a whole, especially in Zizhou County, but there were increases and decreases in other regions. Human activity intensity increased as a whole, and the most obvious increase was in Hengshan District. Both the forest resource quality and human activity intensity indexes had spatial aggregation, the differences in forest resource quality between regions were reduced, and human activity intensity showed a trend towards aggregated development. The high–high cluster area for human activity intensity showed a decreasing trend, but it expanded outward in urban areas and other human-gathering areas, such as the surrounding area of Yulin City, Jingbian County, and Shenmu City. The high–high cluster area for forest resource quality showed a shrinking trend. Four specific regions were identified through a spatial coupled superposition analysis to reveal the dynamic relationship between forest resource quality and human activity intensity. The most obvious region was the Yuyang District, where the forest resource quality improved because of a reduction in the pressure of human activities on the natural environment.

Industrial Heat Source-Related PM2.5 Concentration Estimates and Analysis Using New Three-Stage Model in the Beijing–Tianjin–Hebei Region

“…Spatial autocorrelation analysis: Spatial autocorrelation analysis is a statistical approach used to evaluate whether the spatial distribution of a variable shows systematic clustering or scattering [61]. This study applied spatial autocorrelation analysis to determine the spatial distribution patterns of IHS-related PM 2.5 concentrations.…”