Abstract:
Land use or cover change (LUCC) is an important factor leading to the change of carbon storage in regional ecosystems. Exploring the spatio-temporal evolution law of land use and carbon storage is of great significance to regional land spatial planning and ecological management, as well as to the realization of the strategic goal of "dual carbon". The GeoDetector-PLUS-InVEST model was built to analyze the spatio-temporal evolution characteristics of land use and carbon storage of Chang-Zhu-Tan 3+5 urban agglomeration from 2000 to 2020 based on multi-source data, to predict the changes of land use and carbon storage under different scenarios in 2030, and to analyze the spatial distribution regularity of carbon storage through the spatial autocorrelation model. The results showed that: 1) Kappa coefficient, FoM coefficient and overall accuracy of the optimized simulation model were 0.81%, 1.00% and 0.67%, respectively, higher than those of the non-optimized simulation. 2) From 2000 to 2020, the land use changes in the study areas showed that the areas of cultivated land, forest land, grassland and water decreased, and the areas of construction land and unused land increased. 3) The carbon storage of the three phases in 2000, 2010 and 2020 were 31.262 4×10
8、31.218 1×10
8 and 31.089 1×10
8 t, respectively, during which the carbon storage decreased by 17.328 7×10
6 t. 4) Compared with 2020, carbon storage under the natural development scenario in 2030 would decrease by 12.148 3×10
6 t, carbon storage decrease by 11.746 7 ×10
6 t under the urban development scenario, carbon storage increase by 14.754 0×10
6 t under the ecological protection scenario. The spatial distribution of carbon storage under the three different scenarios was relatively similar, with the remarkable characteristic of spatial agglomeration, and it was closely related to land use. The research results could provide decision-making reference for the land space planning and formulation of "dual carbon" policy within Chang-Zhu-Tan 3+5 urban agglomeration.