文献类型：期刊文献

英文题名：Application and Assessment of a CA-ANN Model for Land Use Change Simulation and Multi-Temporal Prediction in Guiyang City, China

作者：Hu, Lanjun Duan, Xiaoqi Liu, Jianhao

第一作者：Hu, Lanjun

通信作者：Liu, JH[1]

机构：[1]Guizhou Univ, Sch Architecture & Urban Planning, Guiyang 550025, Peoples R China;[2]Guizhou Univ, Sch Comp Sci & Technol, Guiyang 550025, Peoples R China;[3]Guizhou Inst Technol, Sch Civil Engn, Guiyang 550025, Peoples R China

第一机构：Guizhou Univ, Sch Architecture & Urban Planning, Guiyang 550025, Peoples R China

通信机构：corresponding author), Guizhou Inst Technol, Sch Civil Engn, Guiyang 550025, Peoples R China.|贵州理工学院土木工程学院;贵州理工学院;

年份：2026

卷号：18

期号：3

外文期刊名：SUSTAINABILITY

收录：;WOS:【SSCI(收录号:WOS:001688098700001)，SCI-EXPANDED(收录号:WOS:001688098700001)】；

基金：Practical Research on the Integration Path of Yangming Culture Transformation and Application in Guizhou Rural Revitalization and Study Tour (Project No.: 2023GCC035). Civil Engineering Guizhou Province Science and Technology Innovation Leading Talent Workstation (Qiankehe Platform KXJZ[2024]020). National Natural Science Foundation of China (Grant No. 42461057). Guizhou Provincial Science and Technology Plan Project (Grant No. Qian Kehe support PA[2025]001). China Postdoctoral Science Foundation (No. 2025MD784075). Guizhou Provincial Science and Technology Plan Project (Grant No. Qian Kehe support XKBF[2025]016). Guizhou Provincial Basic Research Program (Natural Science) (Grant No. [2024] 130).

语种：英文

外文关键词：Land Use and Land Cover (LULC); Cellular Automata (CA); Artificial Neural Network (ANN); MOLUSCE; urban expansion; simulation

摘要：Land use and land cover change (LULC) is a critical catalyst for global climate patterns, environmental conditions, and ecological dynamics. Remote sensing and geographic information system (GIS) methods have accelerated research on the impacts and variability of climate change. In ecologically sensitive karst regions, LULC poses significant challenges to sustainable urbanization. As a representative karst mountain city in China, Guiyang has undergone rapid spatial transformation, yet quantitative studies on its long-term LULC trajectories within an integrated spatial modeling framework remain insufficient. This study analyzed LULC dynamics in Guiyang from 2007 to 2022 and projected changes for 2027, 2032, 2037, and 2042. Using the CA-ANN model within the QGIS MOLUSCE plugin, we calibrated the model with multi-temporal LULC data and nine spatial drivers, including topographic, proximity, and socioeconomic factors. The model structure was optimized through iterative testing, resulting in a final configuration of 8 hidden layers and 500 iterations. This setup achieved high validation accuracy during training, with a hindcast simulation overall accuracy of 84.42% and a Kappa coefficient of 0.73 for simulating the 2022 land cover. Future projections indicate that impervious surfaces will continue to expand in a spatially constrained manner, reaching 332.82 km2 by 2042, while shrubland area will sharply decrease to 10.75 km2. Cultivated land and forest areas show relative stability with fluctuations. The projected patterns may exacerbate risks associated with surface runoff and ecological fragmentation due to established linkages between land use/cover change and ecosystem services. Through spatially explicit, multi-temporal scenario simulations, the findings underscore the urgent need in Guiyang's unique karst setting to deeply integrate land-use planning with ecological conservation strategies, so as to strengthen regional ecological resilience.