Worldwide urbanization has brought about diverse types of urban land use and land cover (LULC) changes. The diversity of urban land changes, however, have been greatly under studied, since the major focus of past research has been on urban growth. In this study, we proposed a framework to characterize diverse urban land changes of 30 global megacities using monthly nighttime light time series from VIIRS data. First, we developed a Logistic-Harmonic model to fit VIIRS time series. Second, by leveraging the uniqueness of urban land change and nighttime light data, we incorporated temporal information of VIIRS time series and proposed a new classification scheme to produce monthly maps of built-up areas and to disentangle urban land changes into five categories. Third, we provided an in-depth analysis and comparison of urban land change patterns of the selected megacities. Results demonstrated that the Logistic-Harmonic model yielded a robust performance in fitting VIIRS time series. Temporal features based classification can not only significantly improve the mapping accuracy of built-up areas, especially for regions with heterogeneous built-up and non-built-up landscapes, but also promoted temporal consistency and classification efficiency. Urban land changes occurred in 51% of the built-up pixels of the megacities. Compared with urban growth, other types of urban land change, particularly land use intensification, contributed to an unexpectedly large proportion of the changes (83%). The findings of this study offer an insightful understanding on global urbanization processes in megacities, and evoke further investigation on the environmental and ecological implications of urban land changes.

世界范围的城市化带来了多种类型的城市土地利用和土地覆盖（LULC）变化。但是，由于过去研究的重点一直放在城市增长上，因此对城市土地变化的多样性进行了大量研究。在这项研究中，我们提出了一个框架，该框架使用来自VIIRS数据的每月夜间光照时间序列来表征30个全球特大城市的城市土地变化。首先，我们开发了Logistic-Harmonic模型以适合VIIRS时间序列。其次，通过利用城市土地变化和夜间光数据的独特性，我们结合了VIIRS时间序列的时间信息，并提出了一种新的分类方案，以生成建筑面积月度地图，并将城市土地变化分为五类。第三，我们对选定大城市的城市土地变化模式进行了深入的分析和比较。结果表明，Logistic-Harmonic模型在拟合VIIRS时间序列方面表现出强大的性能。基于时间特征的分类不仅可以显着提高建成区的制图精度，特别是对于具有异质建成和非建成景观的区域，还可以提高时间一致性和分类效率。在51％的特大城市建成像素中，发生了城市土地变化。与城市增长相比，其他类型的城市土地变化，尤其是土地利用集约化，造成了意想不到的很大比例的变化（83％）。这项研究的发现为大城市的全球城市化进程提供了深刻的认识，