Mapping local climate zones for cities: A large review

The local climate zone (LCZ) system provides a universal classification mechanism for urban and natural landscapes and plays an increasingly important role in urban climate research. With the rapid development of various LCZ mapping methods, a thorough survey of the LCZ mapping literature is urgently needed to better understand current progress, challenges, and future directions. Accordingly, this study provided a comprehensive review of the LCZ mapping literature during 2012-2021, with a detailed analysis on literature statistics, research topics, LCZ cities, and active research groups. Furthermore, remote sensing (RS)-based LCZ mapping methods were elucidated from feature sets, classification units, training areas, classification algorithms, and accuracy assessment; geographic information system (GIS)-based LCZ mapping methods were elaborated from LCZ pa-rameters, basic spatial units, classification algorithms, and accuracy assessment; and their combination methods were summarized from two typical integration strategies. Finally, several challenges and future directions for LCZ mapping were discussed. The topics include exploiting multi-source RS and GIS data, determining appro-priate LCZ mapping unit sizes, acquiring high-quality LCZ ground truth data, improving LCZ classification al-gorithms, optimizing LCZ parameters and subclasses, exploring the transferability of LCZ models, conducting global interannual LCZ mapping, and expanding the application of LCZs. The research community can quickly obtain abundant information on the LCZ mapping literature, understand the frameworks of different LCZ mapping methods, and inspire new directions for future research.

Automated summary

This study provides a comprehensive review of the LCZ mapping literature from 2012 to 2021, with an analysis of literature statistics, research topics, LCZ cities, and active research groups. It further elaborates on remote sensing and GIS-based LCZ mapping methods, as well as their combination methods. Finally, it discusses challenges and future directions for LCZ mapping.