UrbanVCA: a vector-based cellular automata framework to simulate the urban land-use change at the land-parcel level
Abstract
Vector-based cellular automata (CA) based on real land-parcel has become an important trend in current urban development simulation studies. Compared with raster-based and parcel-based CA models, vector CA models are difficult to be widely used because of their complex data structures and technical difficulties. The UrbanVCA, a brand-new vector CA-based urban development simulation framework was proposed in this study, which supports multiple machine-learning models. To measure the simulation accuracy better, this study also first proposes a vector-based landscape index (VecLI) model based on the real land-parcels. Using Shunde, Guangdong as the study area, the UrbanVCA simulates multiple types of urban land-use changes at the land-parcel level have achieved a high accuracy (FoM=0.243) and the landscape index similarity reaches 87.3%. The simulation results in 2030 show that the eco-protection scenario can promote urban agglomeration and reduce ecological aggression and loss of arable land by at least 60%. Besides, we have developed and released UrbanVCA software for urban planners and researchers.
Keywords
Cite
@article{arxiv.2103.08538,
title = {UrbanVCA: a vector-based cellular automata framework to simulate the urban land-use change at the land-parcel level},
author = {Yao Yao and Linlong Li and Zhaotang Liang and Tao Cheng and Zhenhui Sun and Peng Luo and Qingfeng Guan and Yaqian Zhai and Shihao Kou and Yuyang Cai and Lefei Li and Xinyue Ye},
journal= {arXiv preprint arXiv:2103.08538},
year = {2021}
}
Comments
27 pages, 7 figures, 6 tables