Optimization of Residential Green Space for Environmental Sustainability and Property Appreciation in Metropolitan Phoenix, Arizona.
This github repo deposits the python programming code by using Gurobi Optimizer to minimize the outdoor water use and land surface temperature as well as maximize the property appreciation with the best residential green space percertage.
Wang, C., Turner, V. K., Wentz, E. A., Zhao, Q., & Myint, S. W. (2021). Optimization of residential green space for environmental sustainability and property appreciation in metropolitan Phoenix, Arizona. Science of The Total Environment, 763, 144605. https://doi.org/10.1016/j.scitotenv.2020.144605
This research was based upon work supported by the National Oceanic and Atmospheric Administration under grant number NA12OAR4310100 and is supported the ongoing Central Arizona Phoenix Long-Term Ecological Research (CAP-LTER) program at Arizona State University that is funded by the National Science Foundation under grant number BCS-1026865. Dr. Qunshan Zhao from the Urban Big Data Centre (UBDC) at the University of Glasgow received support from the UK Economic and Social Research Council under grant number of ES/L011921/1 and ES/S007105/1. We also would like to thank the Gurobi Optimizer for providing a free academic license for solving the integer programming problems and the anonymous reviewers for their insightful comments and suggestions on an earlier version of this manuscript.