DOI: 10.1016/j.jag.2016.07.022
Scopus记录号: 2-s2.0-84997796226
论文题名: Integrating the system dynamic and cellular automata models to predict land use and land cover change
作者: Xu X ; , Du Z ; , Zhang H
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 52 起始页码: 568
结束页码: 579
语种: 英语
英文关键词: Cellular automata model
; Land use and land cover change
; Prediction
; Spatial pattern
; System dynamic model
Scopus关键词: accuracy assessment
; cellular automaton
; land cover
; land use change
; prediction
; spatial planning
; China
; Shanxi
英文摘要: Land use and land cover change (LULCC) is a widely researched topic in related studies. A number of models have been established to simulate LULCC patterns. However, the integration of the system dynamic (SD) and the cellular automata (CA) model have been rarely employed in LULCC simulations, although it allows for combining the advantages of each approach and therefore improving the simulation accuracy. In this study, we integrated an SD model and a CA model to predict LULCC under three future development scenarios in Northern Shanxi province of China, a typical agro-pastoral transitional zone. The results indicated that our integrated approach represented the impacts of natural and socioeconomic factors on LULCC well, and could accurately simulate the magnitude and spatial pattern of LULCC. The modeling scenarios illustrated that different development pathways would lead to various LULCC patterns. This study demonstrated the advantages of the integration approach for simulating LULCC and suggests that LULCC is affected to a large degree by natural and socioeconomic factors. © 2016 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80034
Appears in Collections: 气候变化事实与影响
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作者单位: Institute of Loess Plateau, Shanxi University, Taiyuan, China; College of Environment and Resource Sciences, Shanxi University, Taiyuan, China
Recommended Citation:
Xu X,, Du Z,, Zhang H. Integrating the system dynamic and cellular automata models to predict land use and land cover change[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,52