An improved assessment method for urban growth simulations across models, regions, and time

Gao, Chen; Feng, Yongjiu; Xi, Mengrong; Wang, Rong; Li, Pengshuo; Tang, Xiaoyan; Tong, Xiaohua

doi:10.1080/13658816.2023.2264942

International Journal of Geographical Information Science

2023

DOI: 10.1080/13658816.2023.2264942

|View full text |Cite

An improved assessment method for urban growth simulations across models, regions, and time

Chen Gao,

Yongjiu Feng,

Mengrong Xi

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Dynamic simulation and projection of ESV changes in arid regions caused by urban growth under climate change scenarios

Tang,

Feng,

et al. 2024

Environ Monit Assess

View full text Add to dashboard Cite

Dynamic simulation and projection of ESV changes in arid regions caused by urban growth under climate change scenarios

Tang,

Feng,

et al. 2024

Environ Monit Assess

View full text Add to dashboard Cite

Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact

Tang,

Feng,

Lei

et al. 2024

J. Arid Land

View full text Add to dashboard Cite

An urban cellular automata model based on a spatiotemporal non-stationary neighborhood

Zeng,

Wang,

Zhang

2024

International Journal of Geographical Information Science

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

An improved assessment method for urban growth simulations across models, regions, and time

Cited by 3 publications

References 52 publications

Dynamic simulation and projection of ESV changes in arid regions caused by urban growth under climate change scenarios

Dynamic simulation and projection of ESV changes in arid regions caused by urban growth under climate change scenarios

Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact

An urban cellular automata model based on a spatiotemporal non-stationary neighborhood

Contact Info

Product

Resources

About