A novel algorithm for calculating transition potential in cellular automata models of land-use/cover change

被引:57
|
作者
Roodposhti, Majid Shadman [1 ]
Aryal, Jagannath [1 ]
Bryan, Brett A. [2 ]
机构
[1] Univ Tasmania, Sch Technol Environm & Design, Discipline Geog & Spatial Sci, Churchill Ave, Hobart, Tas 7005, Australia
[2] Deakin Univ, Sch Life & Environm Sci, Ctr Integrat Ecol, 221 Burwood Hwy, Burwood, Vic 3125, Australia
关键词
Entropy; Land-use/cover change; Uncertainty; Urban planning; Modelling; Simulation; SUPPORT VECTOR MACHINES; CROSS-BORDER REGION; URBAN-GROWTH; LOGISTIC-REGRESSION; GENETIC ALGORITHM; NEURAL-NETWORK; ACCURACY; UNCERTAINTY; SIMULATION; INFORMATION;
D O I
10.1016/j.envsoft.2018.10.006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Despite recent advances in quantifying land-use/cover change (LUCC) transition potential, transition rules are often not transparent and uncertainty is rarely made explicit. Here, we introduce DoTRules-a dictionary of trusted rules-as a transparent alternative to calculate transition potential in cellular automata models. Rules relate LUCC variables to the observed historical changes. Shannon entropy is calculated to assess the uncertainty of each rule, and the most trusted rules are used to project future LUCC. DoTRules produces rule-level uncertainty estimates, which can be mapped. In a case study of the Ahvaz region of Iran, the overall accuracy of LUCC simulation calibrated using DoTRules was very similar to simulations calibrated with the state-of-the-art random forest, but DoTRules provides a more transparent approach where transition rule information and uncertainty can be readily accessed and interpreted. The results demonstrate that DoTRules has potential to derive new insights into LUCC processes.
引用
收藏
页码:70 / 81
页数:12
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