Watch the Dallas Symposium LIVE, and fundraiser auction
Ticket proceeds support mindat.org! - click here...
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Li, Wenliang, Wu, Changshan, Choi, Woonsup (2018) Predicting future urban impervious surface distribution using cellular automata and regression analysis. Earth Science Informatics, 11 (1) 19-29 doi:10.1007/s12145-017-0312-8

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitlePredicting future urban impervious surface distribution using cellular automata and regression analysis
JournalEarth Science Informatics
AuthorsLi, WenliangAuthor
Wu, ChangshanAuthor
Choi, WoonsupAuthor
Year2018 (March)Volume11
Issue1
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s12145-017-0312-8Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID729779Long-form Identifiermindat:1:5:729779:7
GUID0
Full ReferenceLi, Wenliang, Wu, Changshan, Choi, Woonsup (2018) Predicting future urban impervious surface distribution using cellular automata and regression analysis. Earth Science Informatics, 11 (1) 19-29 doi:10.1007/s12145-017-0312-8
Plain TextLi, Wenliang, Wu, Changshan, Choi, Woonsup (2018) Predicting future urban impervious surface distribution using cellular automata and regression analysis. Earth Science Informatics, 11 (1) 19-29 doi:10.1007/s12145-017-0312-8
In(2018, March) Earth Science Informatics Vol. 11 (1) Springer Science and Business Media LLC

See Also

These are possibly similar items as determined by title/reference text matching only.

Nie, Qin, Xu, Jianhua, Liu, Zuhan (2015) Fractal and multifractal characteristic of spatial pattern of urban impervious surfaces. Earth Science Informatics, 8 (2) 381-392 doi:10.1007/s12145-014-0159-1
Li, Wenliang, Wu, Changshan (2014) Phenology-based temporal mixture analysis for estimating large-scale impervious surface distributions. International Journal of Remote Sensing, 35 (2). doi:10.1080/01431161.2013.873147
Aydın, Taha Kağan, Durduran, S. Savaş (2024) Determining future scenarios of urban areas with cellular automata/Markov Chain Model method; example of Ereğli District Konya-Türkiye (2030–2040) Earth Science Informatics, 17 (3) 2679-2697 doi:10.1007/s12145-024-01283-w
Wu, Hao, Zhou, Lu, Chi, Xu, Li, Yan, Sun, Yurong (2012) Quantifying and analyzing neighborhood configuration characteristics to cellular automata for land use simulation considering data source error. Earth Science Informatics, 5 (2) 77-86 doi:10.1007/s12145-012-0097-8
Abdolkhani, Ali, Attarchi, Sara, Alavipanah, Seyed Kazem (2024) A new classification scheme for urban impervious surface extraction from UAV data. Earth Science Informatics, 17 (5). doi:10.1007/s12145-024-01430-3
Lai, Terence, Dragićević, Suzana (2011) Development of an urban landslide cellular automata model: a case study of North Vancouver, Canada. Earth Science Informatics, 4 (2) 69-80 doi:10.1007/s12145-011-0078-3
Ding, Yuan, Zheng, Hengyi, Jin, Fuming, Chen, Dongming, Huang, Xinyu (2024) A Harris Hawks optimization-based cellular automata model for urban growth simulation. Earth Science Informatics, 17 (5). doi:10.1007/s12145-024-01399-z
Deng, Chengbin, Wu, Changshan (2013) A spatially adaptive spectral mixture analysis for mapping subpixel urban impervious surface distribution. Remote Sensing of Environment, 133. 62-70 doi:10.1016/j.rse.2013.02.005
Lee, Sangho, Suh, Jangwon, Choi, Yosoon (2018) Review of smartphone applications for geoscience: current status, limitations, and future perspectives. Earth Science Informatics, 11 (4) 463-486 doi:10.1007/s12145-018-0343-9
Salgado, Cesar, Zortea, Maciel, Scharcanski, Jacob (2018) Classify-normalize-classify. Earth Science Informatics, 11 (1) 77-97 doi:10.1007/s12145-017-0318-2
Ding, Yuan, Jiang, Nan, Wu, Changbin, Zhou, Xinxin (2018) A two-phase algorithm for point-feature cartographic label placement. Earth Science Informatics, 11 (2) 183-203 doi:10.1007/s12145-017-0320-8
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 15, 2025 18:01:27
Go to top of page