Application of LCZ to Time-Series Urban Morphology Detection

Over the past few decades, urbanization has led to significant changes in land use and cover, impacting urban climate and public health, as well as energy consumption. In 2012, the local climate zone (LCZ) classification system was introduced to better represent the complexity of urban morphology. However, mapping LCZ over a long period has been challenging. This chapter presents a machine learning-based framework for mapping annual LCZ time series in three major urban agglomerations in China, providing spatial-temporal consistency in the resulting maps. The chapter also reveals the spatial and temporal patterns of LCZ time series, with the high-rise and open urban LCZ types becoming more prominent in urban morphology over the past two decades. Urban morphology varies considerably in urban expansion and urban renewal areas. From 2000 to 2020, inter-city urban morphology differences narrowed between the three urban agglomerations, but intra-city urban morphology differences widened.