Lessons and Challenges in Land Change Modeling Derived from Synthesis of Cross-Case Comparisons-Reference-Cited by-同舟云学术

Lessons and Challenges in Land Change Modeling Derived from Synthesis of Cross-Case Comparisons

Published:2017-10-24 Issue: Volume: Page:143-164
ISSN:2365-0575
Container-title:Geotechnologies and the Environment
language:
Short-container-title:

Author:

Pontius Robert Gilmore,Castella Jean-Christophe,de Nijs Ton,Duan Zengqiang,Fotsing Eric,Goldstein Noah,Kok Kasper,Koomen Eric,Lippitt Christopher D.,McConnell William,Mohd Sood Alias,Pijanowski Bryan,Verburg Peter,Veldkamp A. Tom

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-52522-8_8

Reference58 articles.

1. Aldwaik SZ, Pontius RG Jr (2013) Map errors that could account for deviations from a uniform intensity of land change. Int J Geogr Inf Sci. doi: 10.1080/13658816.2013.787618

2. Aldwaik SZ, Onsted JA, Pontius RG Jr (2014) Behavior-based aggregation of land categories for temporal change analysis. Int J Appl Earth Obs Geoinf 35:229–238

3. Boissau S, Castella J-C (2003) Constructing a common representation of local institutions and land use systems through simulation-gaming and multi-agent modeling in rural areas of Northern Vietnam: the SAMBA-Week methodology. Simul Gaming 34(3):342–347

4. Box GEP (1979) Robustness in the strategy of scientific model building. In: Launer RL, Wilkinson GN (eds) Robustness in statistics. Academic, New York, pp 201–236

5. Brown DG, Page S, Riolo R, Zellner M, Rand W (2005) Path dependence and the validation of agent-based spatial models of land use. Int J Geogr Inf Sci 19(1):153–174

Cited by 38 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Performance of CA_Markov and DINAMICA EGO models to evaluate urban risk in Antofagasta and Mejillones, Chile;Natural Hazards;2024-04-03

2. A user-friendly assessment of six commonly used urban growth models;Computers, Environment and Urban Systems;2023-09

3. Four Fundamental Questions to Evaluate Land Change Models with an Illustration of a Cellular Automata–Markov Model;Annals of the American Association of Geographers;2023-08-25

4. Performance of CA_Markov and DINAMICA EGO models to evaluate urban risk in Antofagasta and Mejillones, Chile;2023-08-17

5. The Chesapeake Bay Land Change Model: Simulating future land use scenarios and potential impacts on water quality;JAWRA Journal of the American Water Resources Association;2023-07-25