Modeling　agriculture　land　suitability　at　a　regional　scale　plays　an　important　role　in　designing　the　best　sustainable　management　systems.　The　aim　of　this　study　was　to　derive　a　land　suitability　map　for　wheat　farming　by　combining　the　Geostatistics　and　analytic　hierarchy　(AHP)-Fuzzy　algorithm　in　geographic　information　system　(GIS)　in　calcareous　and　saline-sodic　soils,　southern　Iran.　The　local　expert＇s　opinions　were　used　to　make　a　decision　on　the　weighting　of　climate,　terrain,　and　soil　data　by　applying　an　AHP　method.　The　input　data　were　transformed　to　a　fuzzy-set　data.　The　Spherical　and　Gaussian　semi-variogram　models　had　the　best　performance　for　fitting　the　soil　parameters.　The　results　revealed　that　soil　texture　(w　=　0.207),　pH　(w　=　0.121),　slope　(w　=　0.120),　electrical　conductivity　(w　=　0.113),　and　exchangeable　sodium　percentage　(w　=　0.111)　had　the　highest　specific　weighting　for　wheat　production,　respectively.　The　land　suitability　map　indicated　that　25.65%　(48306.6　ha)　of　the　studied　area　was　for　highly　suitable,　38.2%　(71939.7　ha)　was　moderately　suitable,　and　27.63%　(52017.2　ha)　was　marginally　suitable.　Only　8.52%　(16042.4　ha)　of　the　studied　area　was　not　suitable　for　wheat　farming.　In　conclusion,　a　combination　of　AHP,　Fuzzy,　and　GIS　could　be　a　potential　approach　for　site-specific　soil　management,　land-use　planning,　and　protection　of　the　environment.