Variability in and mixtures among residential vacancies at granular levels: Evidence from municipal water consumption data

Pan, Yongting; Zeng, Wen; Guan, Qingfeng; Yao, Yao; Liang, Xun; Zhai, Yuling; Pu, Shengyan

doi:10.1016/j.compenvurbsys.2021.101702

Computers, Environment and Urban Systems

2021

DOI: 10.1016/j.compenvurbsys.2021.101702

|View full text |Cite

Variability in and mixtures among residential vacancies at granular levels: Evidence from municipal water consumption data

Yongting Pan

Wen Zeng

Qingfeng Guan

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

2024

Publication Types

Select...

Article5

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 6 publications

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Identification of rural courtyards’ utilization status using deep learning and machine learning methods on unmanned aerial vehicle images in north China

Wang,

Xu,

Cao

et al. 2024

Build. Simul.

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

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

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.

Variability in and mixtures among residential vacancies at granular levels: Evidence from municipal water consumption data

Cited by 6 publications

References 62 publications

Identification of rural courtyards’ utilization status using deep learning and machine learning methods on unmanned aerial vehicle images in north China

Identification of rural courtyards’ utilization status using deep learning and machine learning methods on unmanned aerial vehicle images in north China

Collaborative energy–water–carbon management based on energy substitution and multiple compound responses

Estimating housing vacancy rates at block level: The example of Guiyang, China

Contact Info

Product

Resources

About