The conversion of natural lands to developed uses poses a great threat to global terrestrial biodiversity. Natural resource managers, tasked with managing wildlife as a public trust, require techniques for predicting how much and where wildlife habitat is likely to be converted in the future. Here, we develop a methodology to estimate the “social carrying capacity for development” – SK_d – for 251 towns across the state of Vermont, USA. SK_d represents town residents’ minimum acceptable human population size and level of development within town boundaries. To estimate SK_d across towns within the state of Vermont (USA), as well as the average state-wide SK_d, we administered a visual preference survey (n = 1505 responses) to Vermont residents, and asked respondents to rate alternative landuse scenarios in a fictional Vermont town on a scale of +4 (highly acceptable) to −4 (highly unacceptable). We additionally collected demographic data such as age and income, as well as ancillary information such as participation in town-planning meetings and location of residence. We used model selection and AIC to fit a cubic function to the response data, allowing us to estimate SK_d at a town scale based on town demographic characteristics. On average, Vermonters had a SK_d of 9.1% development on the landscape; this estimate is 68% higher than year 2000 levels for development (5.4%). Respondents indicated that management action to curb development was appropriate at 9.4% development (roughly the statewide SK_d average). Management by local, regional, and state levels were considered acceptable for curbing development while federal level management of development was considered unacceptable. Given a scenario where development levels were at SK_d, we predicted a 16,753 km² reduction in forested land (−11.16%) and a 1038 km² reduction in farmland (−60.45%). Such changes would dramatically alter biodiversity patterns state-wide. In a companion paper, we estimate how these changes would affect the distribution of wildlife species.