Urban Expansion Simulation and Prediction Based on Night-Time Light and Land Use and Land Cover Change Data - Taking Tokyo Metropolis as an Example

Abstract

Urban expansion can indirectly reflect the economic development level and social resource environment of a region while night-time light data is closely bound up with human economic activities. Taking urbanized regions with a high population density as a research area demonstrates a clear correlation between night-time light data and urban expansion. Based on the night-time light and land use/land cover (LULC) change data of Tokyo Metropolis in 2020 and 2022, Land Change Modeler (LCM) model is utilized to assess the LULC situation of Tokyo Metropolis in 2024, which is then compared with the observed data through accuracy assessment method to examine the relationship connecting night-time light data with urban expansion. It can not only explain the driving mechanisms behind past urban expansion but also predict future expansion scenarios. The research suggests that the LCM model exhibits high precision and can be employed for the simulation and prediction of future urban expansion in Tokyo Metropolis which provides crucial references for Tokyo’s urban planning and development trajectory.