Multi‐criteria evaluation (MCE) methods are useful tools to evaluate the land suitability for various uses and assist in the effective management of available land. Many common GIS‐based MCE methods, such as analytical hierarchy process (AHP), ordered weighted averaging (OWA), and a combination of AHP and OWA methods (AHP–OWA) are not able to fully represent all the logic that constitute a wide range of human decision‐making reasoning. Consequently, improved GIS‐based MCE methods such as Logic Scoring of Preference (LSP) method are needed. The main objectives of this study are to: (1) implement the GIS‐based LSP method for land suitability evaluation and (2) compare qualitatively and quantitatively the suitability maps generated by LSP and three GIS‐based MCE methods. This study was implemented with data sets from Boulder County, Colorado, USA for the case study of the urban land suitability evaluation. The qualitative properties of MCE methods and the Receiver Operating Characteristic (ROC) statistics were used as comparison metrics. The results indicate that soft computing methods and particularly LSP performed the best among GIS‐based MCE methods for the urban land use application.