This study estimates a generalized spatial hedonic pricing model to assess how residential property values are impacted by inclusion within cluster developments and by proximity to various types of protected land. The estimated model simultaneously controls for the spatial dependence of residential housing prices and for the presence of spatial autocorrelation. The sample includes 4,008 single-family housing sales transactions within the non-urban portions of Larimer County in northern Colorado. The empirical framework accounts for topographical diversity across the study region, as well as distinguishing between several distinct types of publicly and privately protected land. The key findings of the study are: (i) proximity to national or state park land and to city or county open space has a significant positive impact on property values, while proximity to national forest land or to privately conserved land exhibits no significant effects; and, (ii) inclusion of a property within a cluster development decreases its value by 17 to 26 %. These findings are robust to different estimation techniques and model specifications, which suggests important considerations for policymakers who design development rules and alternative land protection measures aimed at preserving open space in non-urban areas.