Simulation Analysis of Spatiotemporal Evolution of Land Use in Yangchusn City using Markov-PLUS Model

This article is based on CLCD (China Land Cover Dataset) and employs the Markov-PLUS model to simulate and configure land use structure, predict future trends, deepen the understanding of the causes and mechanisms of land use change, provide a scientific foundation for the formulation of city land policies, and promote scientific planning, efficient utilization, and sustainable development of land resources. The key result is that forests and cropland are the majority of land types in Yangchun City, accounting for over 90%, with cropland distributed northeast to southwest strip. From 2015 to 2020, the dynamic degree of single land use in grassland was -6.39%, with the fastest drop rate. The dynamic degree of comprehensive land use is relatively small, at 0.13%, indicating that the overall changes in land use types are minor, but there are still changes, primarily the conversion of forests to cropland, with 7926.75 hectares of forest converted to cropland and 5669.37 hectares of cropland converted to forest. These variations are impacted by various factors such as building distance, GDP, slope, elevation, and annual average temperature. Prediction shows that urban growth would increase impermeable surfaces and harm the ecological environment; maintaining cropland can increase cropland area while slowing urbanization; and ecological conservation helps to safeguard water bodies and forests while reducing bare land. Therefore, it is suggested that Yangchun City should protect forests and farmland, implement appropriate land use policies, promote ecological agriculture and forestry, optimize land use structure, strengthen grassland and shrub land management, control the expansion of bare land and impermeable surfaces, implement ecological protection measures, establish monitoring systems, and strengthen public participation and publicity education to achieve sustainable use of land resources as well as social sustainable development.