Simulation of land-cover change in Jing-Jin-Ji region under different scenarios of SSP-RCP

How to simulate land-cover change, driven by climate change and human activity, is not only a hot issue in the field of land-cover research but also in the field of sustainable urbanization. A surface-modeling method of land cover scenario (SSMLC) driven by the coupling of natural and human factors was developed to overcome limitations in existing land-cover models. Based on the climatic scenario data of CMIP6 SSP1-2.6, SSP2-4.5, and SSP5-8.5 released by IPCC in 2020, which combines shared socioeconomic paths (SSPs) with typical concentration paths (RCPs), observation climatic data concerning meteorological stations, the population, GDP, transportation data, land-cover data from 2020, and related policy refences, are used to simulate scenarios of land-cover change in the Jing-Jin-Ji region using SSP1-2.6, SSP2-4.5, and SSP5-8.5 for the years 2040, 2070 and 2100, respectively. The simulation results show that the total accuracy of SSMLC in the Jing-Jin-Ji region attains 93.52%. The change intensity of land cover in the Jing-Jin-Ji region is the highest (plus 3.12% per decade) between 2020 and 2040, gradually decreasing after 2040. Built-up land has the fastest increasing rate (plus 5.07% per decade), and wetland has the fastest decreasing rate (minus 3.10% per decade) between 2020 and 2100. The change intensity of land cover under scenario SSP5-8.5 is the highest among the abovementioned three scenarios in the Jing-Jin-Ji region between 2020 and 2100. The impacts of GDP, population, transportation, and policies on land-cover change are generally greater than those on other land-cover types. The results indicate that the SSMLC method can be used to project the change trend and intensity of land cover under the different scenarios. This will help to optimize the spatial allocation and planning of land cover, and could be used to obtain key data for carrying out eco-environmental conservation measures in the Jing-Jin-Ji region in the future.