TL;DR
The results indicate that green space changes are explained more strongly by population density and land-use structure than by climate variables, which can support future studies on climate change adaptation, urban planning, environmental management, and sustainable land-use policy.
This study analyzes changes in green space area across 11 cities and counties in Chungcheongbuk-do and develops future projection data under Shared Socioeconomic Pathways (SSP)1-2.6 and SSP5-8.5 climate scenarios using machine learning and explainable artificial intelligence techniques. Ordinary least squares (OLS) reg...
Purpose— This study examines how forest fire area, industrial-sector gross regional domestic product (GRDP), and population density are associated with Indonesia’s Environmental Quality Index (Indeks Kualitas Lingkungan Hidup, IKLH) at the provincial level. Research Methodology— A quantitative panel-data design uses 15...
Urban shrinkage causes inefficient land utilization and landscape fragmentation. Green spaces are critical nature-based solutions for the sustainable development of shrinking cities, and play an important role in enhancing urban environmental quality and promoting residents’ physical and mental well-being. Using landsc...
This article presents a comprehensive assessment of degradation risk in the arid territories of the Ili district, Almaty region, based on Sentinel-2 satellite indices, MODIS NPP and ERA5-Land hydroclimatic variables. The aim of the study was to identify the spatial distribution of degradation risk and to determine how...
Amid China’s pursuit of ecological civilization and high-quality development, a central policy challenge lies in designing environmental governance instruments that can simultaneously deliver ecological improvement and socially inclusive outcomes. Using the National Forest City (NFC) program as a representative urban e...
Population change is closely associated with urban land use structure, yet their nonlinear relationship and distributional heterogeneity remain poorly understood. Drawing on panel data for 2000–2020 from urban districts across 284 Chinese prefecture-level cities, this study applies generalized additive models, segmente...
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