Identification of shrinkage patterns in Japan’s four major metropolitan areas based on nighttime light and population data

• An urban vitality framework was developed to identify urban shrinkage patterns. • High-resolution NTL and population data analyzed urban shrinkage in Japan. • Distinct shrinkage patterns in core and peripheral areas of cities were identified. • The dual-dimensional approach identified the dynamics driving urban shrinkage. Urban shrinkage has become a critical global issue, influencing the sustainable development of cities across social, economic, and environmental dimensions. In Japan, which is characterized by an aging population and low birth rate, this phenomenon has now extended to metropolitan areas, presenting new challenges for urban sustainability. Although many studies have been conducted regarding urban decline in rural regions, the shrinkage dynamics within Japan’s major cities are poorly understood. Addressing this knowledge gap is crucial for devising targeted urban-planning strategies that ensure the long-term viability of urban areas. Here, we integrated Suomi National Polar-orbiting Partnership–Visible Infrared Imager Radiometer Suite nighttime light data with WorldPop population data to examine the patterns of urban shrinkage from 2012 to 2020 in Japan’s four largest metropolitan areas: Tokyo, Osaka, Nagoya, and Fukuoka. Using Theil–Sen median trend analysis and K-means clustering, we developed a method to quantify both shrinking and growing areas within these regions. It was found that Tokyo exhibited the highest urban vitality, with minimal shrinkage, whereas Nagoya and Osaka faced greater declines. Fukuoka displayed a distinct east–west spatial pattern of urban shrinkage. This study introduces the “triple V” theory, which evaluates urban vitality through the lenses of robustness and activity levels. Our analysis highlights the spatial complexities of urban shrinkage, emphasizing the importance of region-specific urban planning. By providing new insights obtained from a data-driven analysis, we offer a framework for policymakers to promote sustainable urban development in the face of demographic and spatial challenges.