Rural Landscape Spatial Change Prediction and Environmental Optimization Based on CA-Markov Model
Year: 2025
Type: article
Abstract: This research investigates the evolving rural environment in Libo County, Guizhou Province, in the context of climate fluctuations and human interventions. By applying landscape ecology principles and land use information spanning from 1995 to 2020, a comprehensive quantitative assessment of land use composition, evolution, and transformation was performed. A cellular automaton combined with a Markov model was utilized to forecast land use configurations for the year 2030. The results reveal substantial urban and agricultural land alterations, indicative of swift economic growth and urban expansion. Although forest regions remained relatively constant, their spatial distribution became more focused, and grasslands experienced a significant reduction post-2000. Forecasts for 2030 project that agricultural land (45.66%) and forest land (40.25%) will be the predominant land uses, with urban land at 7.89%, grasslands at 6.01%, and water bodies at a minimal 0.19%. This study provides a scientific basis for regional sustainable development, ecological protection, and restoration, especially for protecting key ecosystems such as forests and grasslands. Predicting land use patterns in 2030 provides data support for urban planning and land resource optimization. Help with agricultural policy development and improve the efficiency of using arable land and forest land. Provide insights for environmental policymakers and promote the optimization of ecological protection policies. Environmental protection awareness is raised through education, public participation, and strategies to combat climate change are developed.
Authors: Liping Yu, Jingting Meng
Institution: China Jiliang University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409688791