Modeling urban land surface dynamics using Arizona single-layer urban canopy model in Python (ASLUM-Py).

Urban ecosystems are increasingly challenged by numerous environmental issues in the face of global climate change. The efficacy of sustainable urban planning strategies depends largely on the capability of resolving urban land surface dynamics. In this study, we developed a state-of-the-art urban land surface model, viz. Arizona Single-Layer Urban Canopy Model (ASLUM), on the Python platform (ASLUM-Py). ASLUM-Py enables users to simulate complex interactions in the urban environment and provides an integrated platform with user-friendly graphical interfaces accessible through the Python Package installation directory. This newly developed modeling framework is used to test and improve heat mitigation strategies in urban ecosystems, with a testbed in Phoenix, Arizona. In particular, we evaluate the effectiveness of three commonly adopted heat mitigation strategies, i.e., white roofs, irrigation, and urban trees. While all these methods are effective in reducing land surface temperature, the use of urban trees, in conjunction with strategic irrigation, is a preferred nature-based solution with potential environmental co-benefits. The results highlight the importance of strategic urban greening initiatives in combating excessive heat and promoting ecological well-being in fast-growing urban areas by facilitating more effective urban planning strategies.