Land urbanization, ecological planning, and carbon stock dynamics in Xinjiang, China, using an integrated geospatial modeling workflow

This study developed and applied an integrated workflow that combined remote sensing, land-use simulation, ecosystem-service assessment, and spatial econometric methods to quantify how land urbanization and ecological planning influence carbon stock dynamics in the Xinjiang Uygur Autonomous Region of northwestern China. Using land-use/land-cover, impervious-surface, nighttime-light, vegetation, topographic, socioeconomic, and planning-constraint data from 2000 to 2020, the workflow identified historical urbanization patterns, simulated four future planning scenarios, estimated carbon stock using the InVEST carbon module, and evaluated direct and spatial spillover effects using spatial econometric models. The results show that built-up expansion occurred primarily through cropland conversion and was accompanied by increasing impervious-surface coverage and nighttime-light intensity. Scenario simulations indicate that the ecological protection scenario produces the highest carbon stock retention, whereas the natural development scenario results in the greatest carbon loss. Forest land was identified as the most vulnerable high-carbon land-use class, with a total carbon density of 144.9 Mg C/ha compared with 29.4 Mg C/ha for built-up land. Spatial Durbin model results show that land urbanization has a negative direct effect (−0.231) and indirect spillover effect (−0.117), yielding a total effect of −0.348 on carbon stock density, whereas ecological planning intensity has a positive total effect (+0.245). These findings support coordinated ecological planning across administrative boundaries to promote low-carbon regional development.