Driving mechanisms and multi-scenario simulation of land use change based on National Land Survey Data: a case in Jianghan Plain, China

Abstract

The Jianghan Plain is simultaneously responsible for ecological protection, food security and urbanization, and land use conflicts are prominent. Revealing the driving mechanism of land use/cover change (LUCC) and simulating the land use pattern can help to coordinate the land use conflicts in the future. Utilizing the National Land Survey Data (NLSD) of Jiangling County in Jianghan Plain (2011–2020) and the patch-generating land use simulation (PLUS) model, this paper analyzed the characteristics of land use evolution, applied the random forest classification (RFC) to analyze the driving mechanism, simulated the 2035 land use pattern under three scenarios of natural development, planning guidance and ecological protection through Markov and Cellular Automaton based on multiple random seeds (CARS) models, and proposed several countermeasures. The study found that: 1) From 2011 to 2020, town construction land increased, village construction land, agricultural land and ecological land decreased. 2) The factors driving LUCC were socio-economic factors, spatial factors, and natural factors in descending order. 3) In the three scenarios, the trend of construction land expansion, agricultural land and ecological land encroachment is inevitable by 2035. 4) It is imperative to actively advocate for large-scale mechanization and informatization of agricultural production, encourage the repurposing of idle and inefficiently used construction land, facilitate multi-purpose land utilization, and implement a policy of locally balancing occupation and compensation for cultivated and ecological land. 5) When employing the PLUS model to simulate LUCC, using continuous NLSD yielded more accurate results than remote sensing image interpretation data. This study offers a theoretical basis for the coordinated development of land use in Jianghan Plain, and presents a method to enhance the simulation accuracy of the PLUS model.