The combination of complex, multiple minerogenic stages and mineral superposition during geological processes has resulted in dynamic spatial distributions and nonstationarity of geological variables. For example, geochemical elements exhibit clear spatial variability and trends with coverage type changes. Thus, bias is likely to occur under these conditions when general regression models are applied to mineral prospectivity mapping (MPM). In this study, we used a spatially weighted technique to improve general logistic regression and developed an improved model, i.e., the improved logistic regression model, based on a spatially weighted technique (ILRBSWT, version 1.0). The capabilities and advantages of ILRBSWT are as follows: (1) it is a geographically weighted regression (GWR) model, and thus it has all advantages of GWR when managing spatial trends and nonstationarity; (2) while the current software employed for GWR mainly applies linear regression, ILRBSWT is based on logistic regression, which is more suitable for MPM because mineralization is a binary event; (3) a missing data processing method borrowed from weights of evidence is included in ILRBSWT to extend its adaptability when managing multisource data; and (4) in addition to geographical distance, the differences in data quality or exploration level can be weighted in the new model.

The Chinese government encourages villagers to withdraw from rural homesteads and puts these homesteads into the land market to revitalize rural homestead resources and make up for the lack of new construction land. Unfortunately, the implementation of the withdrawal from rural homesteads (WRH) policy remains slow. To realize the effective promotion of WRH policy, exploring the impact of policy cognition (PC) on villagers’ WRH intentions has become the key to solving the above problems. Thus, field survey data on 280 villagers in 13 administrative villages in the Yangling Demonstration district of Shaanxi province were collected through a face-to-face household survey. In addition, combined with the extended theory of planned behavior (TPB), this study used the structural equation model (SEM) to empirically analyze the influence of PC on the intentions of villagers’ WRH. Our empirical results indicated that benefit cognition and difficulty cognition were the focus of the villagers and had positive and negative effects on the intention of WRH, respectively. Government behavior also played a positive role in villagers’ WRH intentions. Villagers would consider compensation standards, pay closer attention to improving the living environment and employment opportunities, and express individual intentions. We believe policymakers should systematically consider the various impacts of WRH policy on villagers and build the villagers’ participation system of WRH and cross-regional transaction system for WRH indicators. This paper further enriches the conceptual framework of PC, which may help us better understand villagers’ responses to relevant policy reforms.