Detecting Urban Sprawl through Nighttime Light Changes

Masanobu Kii () and Kunihiko Matsumoto
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Masanobu Kii: Graduate School of Engineering, Osaka University, Suita 565-0847, Japan
Kunihiko Matsumoto: Graduate School of Engineering, Osaka University, Suita 565-0847, Japan

Sustainability, 2023, vol. 15, issue 23, 1-18

Abstract: Numerous cities around the world are currently experiencing surges in population growth and urban expansion, often accompanied by uncontrolled sprawl. It is widely recognized that unplanned urban development contributes to a decline in urban sustainability. In this research, our goal is to identify instances of sprawl development in the Kansai region of Japan by utilizing remote sensing data. As a result, we have discovered that nighttime light data are valuable for gaining additional insights into sprawl, even when time-series land-use data and spatial population data are available. Specifically, when comparing the changes in these indices between circa 2010 and 2020, it becomes evident that these indices exhibit very weak correlations. Consequently, they can be used as independent variables for identifying urban sprawl. Each index comes with its own advantages and disadvantages in the context of urban sprawl detection. Therefore, we can conclude that a combination of multiple data sources is necessary for a comprehensive determination and detection of urban sprawl.

Keywords: urban sprawl; nighttime light; land use change; population; spatial analysis; agricultural land preservation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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