ORIGINAL ARTICLE Spatially filtered ridge regression (SFRR): A regression framework to understanding impacts of land cover patterns on urban climate Chao Fan | Sergio J. Rey | Soe W. Myint School of Geographical Sciences and Urban Planning, Arizona State University Correspondence Chao FAN, School of Geographical Sciences and Urban Planning, Arizona State University, Coor Hall, 975 S Myrtle Ave, Fifth Floor, Tempe, AZ 85287, USA, Email: cfan13@asu.edu Abstract Understanding the impacts of land cover pattern on the heat island effect is essential for sustainable urban development. Conventional model fitting methods have restricted ability to produce accurate esti- mates of the land cover-temperature association due to the lack of procedures to address two important issues: spatial dependence in proximal spatial units and high correlations among predictor variables. In this study, we seek to develop an effective framework called spa- tially filtered ridge regression (SFRR) to estimate the variations in the quantity and distribution of land surface temperature (LST) in response to various land cover patterns. The SFRR effectively integra- tes spatial autoregressive models and ridge regression, and it achieves reliable parameter estimates with substantially reduced mean square errors. We show this by comparing the performance of the SFRR to other widely adopted models using Monte Carlo simulation followed by an empirical study over central Phoenix. Results highlight the great potential of the SFRR in producing accurate statistical estimates, pro- viding a positive step toward informed and unbiased decision-making across a wide variety of disciplines. (Code and data to reproduce the results in the case study are available at: https://github.com/cfan13/ SFRRTGIS.git.) KEYWORDS spatial dependence, multicollinearity, spatial filtering, ridge regression, spatial configuration 1 | INTRODUCTION Urbanization is one of the most drastic forms of human modification to the environment. The replacement of natural landscapes with impervious man-made infrastructure has dramatically altered the surface energy balance of the urban environment, causing elevated temperatures in the urban area relative to its rural surroundings; this is referred to as an urban heat island (UHI) (Lo & Quattrochi, 2003; Oke, 1987). The UHI has important and extensive implications for Transactions in GIS 2016; 00: 00-00 wileyonlinelibrary.com/journal/tgis V C 2016 John Wiley & Sons Ltd | 1 DOI 10.1111/tgis.12240