Starting with WRF v4.6, support for distributed urban parameters has been integrated into the Single-Layer Urban Canopy Model (SLUCM). This update allows modelers to incorporate spatially heterogeneous urban canopy characteristics into numerical weather simulations. Key Features & Parameters The distributed urban parameters available in this release include: Aerodynamic Roughness Parameters: Roughness length for momentum and […]
Annual Past-Present Land Cover Classification from Landsat using Deep Learning for Urban Agglomerations Worameth Chinchuthakun, David Winderl, Alvin C.G. Varquez, Yukihiko Yamashita, Manabu Kanda Overview UrbanLC is a Python library for land cover classification (LCC) from Landsat Images. It features pretrained deep learning models, which are compatible with all Landsat sensors up-to-date: MSS, TM, and […]
A github repository for the tools introduced in this site and the tools used to construct the datasets can be found below: https://github.com/TokyoTechGUC The above repository is continually being improved and advanced by the members of the lab.
Updated March 17, 2023: Additional paper reference and manual In collaboration with the Hanaoka Research Group led by Prof. Shinya Hanaoka, an update of the SLEUTH model is proposed to consider railway-induced urban growth in a widely known cellular-automaton-based urban growing model called SLEUTH. The papers related to the work can be found below: Varquez, […]