World Database and Access Portal Tools (WUDAPT) Level 0 method announced a workflow of mapping Local Climate Zones (LCZs). However, the low accuracy of LCZ classifications in Level 0 especially for the built-up areas caused by recognition of classes and operator bias is becoming an obstacle for further study in WUDAPT Level 1 and 2. Since the landscape in Japan is complicated, the recognition of classes and operator bias may exist for delineating training areas. This article argues an extended workflow of WUDAPT for mapping LCZs with pre-set recognition of classes and parameter analysis. The building coverage ratio (BCR), building height (BH), pervious surface fraction (PSF) were intersected with LCZ map for analysis and expound of the pre-set recognition of LCZ classes. Given the universality of WUDAPT workflow, a satellite method for deriving building data based on free available data sources was proposed. Contributing to WUDAPT level 1 and 2, a LCZ classification of Sendai, as a representative of Japanese large cities, was selected. The study will provide not only an improved methodology of development LCZ data, but also a new urban morphological dataset and its corresponding parameters for mesoscale climate modelling and simulations in Japan.