Related studies analyzing the spatial structure of soil moisture from both horizontal and vertical directions, as well as the spacing interval distances of soil moisture sampling points in typical karst demonstration zones, are relatively rare. This study applied classical statistics, geostatistics, and “3S” technology to analyze the spatial structure, influencing factors, and spacing interval distances of soil moisture sampling points in the Guohua Demonstration Zone. The results showed that Moran’s I indices of soil moisture at different soil depths in the Guohua Demonstration Zone presented positive spatial correlation, and the spatial distribution of soil moisture at different soil depths showed a distinct spatial clustering pattern, with few spatially isolated zones. The spatial autocorrelation distance for soil moisture at 5 cm and 10 cm soil depths was 2400 m, while the autocorrelation distances for soil moisture at 20 cm and 30 cm soil depths were 2200 m and 2000 m, respectively. The spatial range value for soil moisture at a soil depth of 20 cm in the Guohua Demonstration Zone was the largest (Range = 6318.0 m), while the spatial range value for soil moisture at a soil depth of 30 cm was the smallest (Range = 646.0 m). The minimum value (threshold: 646.0 m) between the spatial autocorrelation distance and the spatial range of soil moisture at different soil depths in the Guohua Demonstration Zone could serve as an appropriate spacing interval distance of soil moisture sampling points. Soil moisture at different soil depths in the Guohua Demonstration Zone was primarily influenced by rock desertification, vegetation cover, soil layer thickness, and elevation. The synergistic effect of “rocky desertification + vegetation”, “rocky desertification + soil thickness”, and “vegetation + soil thickness” had a greater influence on soil moisture. Through high-density soil moisture sampling points in typical karst areas, the study results strengthened the application research on soil moisture in typical karst areas, providing scientific references for studies on the spatial structure, influencing factors, and appropriate spacing interval distance of soil moisture sampling points in karst areas.

Against the backdrop of rapid development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), the spatiotemporal evolution of Production-Living-Ecological Land (PLEL) in its peri-urban regions has emerged as a critical research focus for achieving regional coordinated development. This study employs Huiyang District as a representative case study area, utilizing multisource geospatial data and analytical methodologies including land use dynamic degree, land transfer matrix, binary logistic regression, and ROC analysis to systematically investigate PLEL’s spatiotemporal evolution patterns and underlying driving mechanisms from 2007 to 2023. The empirical results demonstrate that: (1) During the observation period, aggregate production and ecological land areas exhibited a declining trend, while living land manifested persistent expansion, reflecting accelerated urbanization process and intensified population concentration. Specifically, between 2007 and 2015, production and ecological land areas decreased significantly while living land expanded markedly, reflecting accelerated urbanization. From 2015 to 2023, the decline in production land substantially moderated, whereas ecological land diminution accelerated. Living land maintained a consistent expansion throughout both periods. (2) Spatial analysis revealed a stable concentric pattern emerged, characterized by living land at the urban core, encircled by production land, with ecological land occupying the peripheral zones. Notable land conversion dynamics were observed between ecological and production land, revealing the tension between conservation and development. Living land conversions to other categories remained negligible, with its expansion predominantly sourced from production land, suggesting urban expansion has largely occurred through agricultural land appropriation. (3) Driving factor analysis identified population size as the predominant influence. Following GBA development, the impact of population size on living land expansion intensified. Model validation through ROC curve analysis confirmed robust predictive performance. This research systematically elucidates PLEL’s spatiotemporal evolution patterns and driving mechanisms within a GBA peripheral urban unit, thereby contributing scientific insights for territorial spatial optimization in rapidly urbanizing regions.