文献类型：期刊文献

英文题名：Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model

作者：Xu, Linfeng[1];Liu, Xuan[2];Tong, De[3];Liu, Zhixin[1];Yin, Lirong[4];Zheng, Wenfeng[5]

机构：[1]Shaoxing Univ, Sch Life Sci, Shaoxing 312000, Peoples R China;[2]Univ Elect Sci & Technol China, Sch Publ Affairs & Adm, Chengdu 610054, Peoples R China;[3]Peking Univ Shenzhen Grad Sch, Lab Urban Future, Shenzhen 518055, Peoples R China;[4]Louisiana State Univ, Dept Geog & Anthropol, Baton Rouge, LA 70803 USA;[5]Univ Elect Sci & Technol China, Sch Automat, Chengdu 610054, Peoples R China

年份：2022

卷号：11

期号：5

外文期刊名：LAND

收录：SSCI(收录号：WOS:000801315600001)、、Scopus(收录号：2-s2.0-85129798354)、WOS

基金：This research was funded by the Tiehan Project Fund of Laboratory for Urban Future, Peking University (Shenzhen), and jointly supported by the National College Students Innovation and Entrepreneurship Training Program of China (No.202110349021).

语种：英文

外文关键词：urban expansion; LEAS; CARS; land use interpretation; China

外文摘要：Nowadays, cities meet numerous sustainable development challenges in facing growing urban populations and expanding urban areas. The monitoring and simulation of land use and land-cover change have become essential tools for understanding and managing urbanization. This paper interprets and predicts the expansion of seven different land use types in the study area, using the PLUS model, which combines the Land use Expansion Analysis Strategy (LEAS) and the CA model, based on the multi-class random patch seed (CARS) model. By choosing a variety of driving factors, the PLUS model simulates urban expansion in the metropolitan area of Hangzhou. The accuracy of the simulation, manifested as the kappa coefficient of urban land, increased to more than 84%, and the kappa coefficient of other land use types was more than 90%. To a certain extent, the PLUS model used in this study solves the CA model's deficiencies in conversion rule mining strategy and landscape dynamic change simulation strategy. The results show that various types of land use changes obtained using this method have a high degree of accuracy and can be used to simulate urban expansion, especially over short periods.