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Vacant land is a ubiquitous urban phenomenon. The existence of vacant land in a neighborhood can either lower or heighten nearby housing values, depending on its relative development potential. However, this condition has rarely been examined longitudinally, nor has it been examined thoroughly across different socioeconomic conditions. This research examines the impact of vacant lots on housing premiums using 2006–2015 single-family home sale transactions in the City of Minneapolis, Minnesota. The study area was divided into low-, middle-, and high-income levels. The results show that vacant lands have negative impacts on nearby single-family houses and these impacts differ by income level per neighborhood. The study sheds light on how planners and researchers should conceive vacant lands differently in various surroundings and conditions.

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This research examines the impact of light rail stations on housing market by analyzing the 1993–2013 single-family home sale transactions in the City of Los Angeles, California. The study period was divided into seven 3-year periods, and the area was divided into three different groups by income level: low-, middle-, and high-income. The result shows that the opening of light railways increased property values in general. It also revealed the differentiated impacts by neighborhood income levels.

Energy-efficient urban development and carbon footprints (CFs) are often discussed in relation to climate change. The optimal level of urban density from a carbon reduction perspective at the city level has been much debated. However, considering possible trade-offs or co-benefits for CFs in the housing and travel sectors, it remains difficult to evaluate how intra-urban/residential densities and mixed land-use patterns relate to individual CFs at a community level in different seasons. The study objective was to demonstrate the changes in the CFs of residents in summer and winter according to spatiotemporal changes in urban forms, such as intra-urban/residential densities and mixed land-use patterns. Based on geographical data and CF survey results from Seoul and Gyeonggi in 2009 and 2018, four path analysis models were used to verify the spatiotemporal variances of the relationships between urban forms and the CFs of the housing/travel sectors (HCF/TCF). Path analysis with a set of mediation variables enables the evaluation of possible trade-offs, or co-benefits, when investigating the impacts of different measures of intra-urban densities and mixed land-use patterns on the CFs. Furthermore, the moderating effects of different cooling and heating patterns in different seasons on CFs were verified by comparing the four path analysis models in different spatiotemporal contexts. The results showed spatiotemporal changes in urban density and different impacts of urban and residential densities on the TCF. It was also revealed that a low percentage of residential land use in urbanized areas offsets the advantage of high density in reducing TCF and HCF. Seasonal differences were also observed in the effects of residential density and HCF. The results of this study help us understand the spatiotemporal characteristics of TCF and HCF in urban settings, which can assist efforts to achieve carbon neutrality goals.