@article{amindarbari_baran_meentemeyer_2022, title={Spatially disaggregated simulation of interactions between home prices and land-use change}, volume={12}, ISSN={["2399-8091"]}, url={https://doi.org/10.1177/23998083221142603}, DOI={10.1177/23998083221142603}, abstractNote={Land-use regulations play a key role on both sides of the real estate market by regulating the supply of housing (e.g., through restrictions on unit density or building height) and by controlling the location and density of places of work, which are the primary drivers of the demand for housing. Developing geospatial models for this interaction between land use and home price on a spatially disaggregated level enables decisionmakers to evaluate the impact of their land-use decisions from the housing affordability perspective. However, existing standalone residential real estate pricing models are insensitive to changes in land use. In addition, the data preparation, calibration, and training of integrated land-use and transportation models is nontrivial too, and still impractical for most municipalities and planning agencies. This paper presents a simple-to-implement framework, SimP-R, for simulating changes in housing prices on a spatially disaggregated level in response to land-use change. It is composed of a residential real estate pricing model and an algorithm for computing a novel measure of supply-to-demand ratio. This paper then demonstrates the implementation of SimP-R in the city of San Francisco, with the entire Bay Area serving as the influence geography. Our findings showed our proposed measure of the supply-to-demand ratio is a strong predictor of and inversely related to housing prices. Simulation experimentation results highlighted SimP-R’s ability to capture the effect of local land-use changes on housing prices across the metropolitan area.}, journal={ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE}, author={Amindarbari, Reza and Baran, Perver and Meentemeyer, Ross K. K.}, year={2022}, month={Dec} }
 @article{sevtuk_amindarbari_2021, title={Does metropolitan form affect transportation sustainability? Evidence from US metropolitan areas}, volume={48}, ISSN={["2399-8091"]}, DOI={10.1177/2399808320971310}, abstractNote={In this paper, we examine transportation sustainability in American metropolitan areas using transportation-related CO2 emissions, public transit accessibility, and commuting times as indicators. Though variations in these indicators may stem from historic contexts, policies, institutional arrangements, social and cultural origins, the spatial structure of metropolitan areas—in particular their formal characteristics—may also be a contributing factor. To test this relationship, we identify metropolitan form metrics from prior literature that are expected to impact transportation outcomes, and choose five metrics to which we introduce significant improvements. We apply the metrics to all 166 Combined Statistical Areas in the US, using an open-source GIS toolbox released along with the paper. Our findings demonstrate that form-based metrics provide a better explanation to CO2 emissions, public transit accessibility, and commuting times in US metro areas than the simpler population size or density metrics typically used in practice. We also show that counter to prior literature on urban scaling laws and economies of scale, which have argued that larger cities and metro areas are more sustainable per capita, transport-related CO2 emissions and transit accessibility are actually less favorable in larger CSAs when controlling for formal characteristics of metropolitan areas. Instead of scale, compactness has the highest elasticity with respect to transportation sustainability of metro areas.}, number={8}, journal={ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE}, author={Sevtuk, Andres and Amindarbari, Reza}, year={2021}, month={Oct}, pages={2385–2401} }