PMID- 23814454 OWN - NLM STAT- PubMed-not-MEDLINE LR - 20211021 IS - 1045-8077 (Print) IS - 1045-8077 (Linking) VI - 20 IP - 1 DP - 2008 Jan 1 TI - Robust Principal Component Analysis and Geographically Weighted Regression: Urbanization in the Twin Cities Metropolitan Area of Minnesota. PG - 15-25 AB - In this paper, we present a hybrid approach, robust principal component geographically weighted regression (RPCGWR), in examining urbanization as a function of both extant urban land use and the effect of social and environmental factors in the Twin Cities Metropolitan Area (TCMA) of Minnesota. We used remotely sensed data to treat urbanization via the proxy of impervious surface. We then integrated two different methods, robust principal component analysis (RPCA) and geographically weighted regression (GWR) to create an innovative approach to model urbanization. The RPCGWR results show significant spatial heterogeneity in the relationships between proportion of impervious surface and the explanatory factors in the TCMA. We link this heterogeneity to the "sprawling" nature of urban land use that has moved outward from the core Twin Cities through to their suburbs and exurbs. FAU - Ghosh, Debarchana AU - Ghosh D AD - Department of Geography, University of Minnesota. FAU - Manson, Steven M AU - Manson SM LA - eng GR - R24 HD041023/HD/NICHD NIH HHS/United States PT - Journal Article PL - United States TA - J Urban Reg Inf Syst Assoc JT - Journal of the Urban and Regional Information Systems Association JID - 101595241 PMC - PMC3693392 MID - NIHMS416069 OTO - NOTNLM OT - Land use OT - geographically weighted regression OT - robust principal component analysis OT - urbanization EDAT- 2008/01/01 00:00 MHDA- 2008/01/01 00:01 PMCR- 2013/06/26 CRDT- 2013/07/02 06:00 PHST- 2013/07/02 06:00 [entrez] PHST- 2008/01/01 00:00 [pubmed] PHST- 2008/01/01 00:01 [medline] PHST- 2013/06/26 00:00 [pmc-release] PST - ppublish SO - J Urban Reg Inf Syst Assoc. 2008 Jan 1;20(1):15-25.