2025-08-22 中国科学院（CAS）
＜関連情報＞
- https://english.cas.cn/newsroom/research_news/infotech/202508/t20250822_1051260.shtml
- https://www.sciencedirect.com/science/article/pii/S0034425725002901
中国都市圏におけるSDGSAT-1微光イメージャーデータを用いた人間活動検出に関する研究 A study on detection of human activity using SDGSAT-1 glimmer imager data over urban agglomerations in China
Lu Zhang, Huadong Guo, Dong Liang, Zhuoran Lv, Zilu Li, Yaqi Geng, Xuting Liu, Mingyang Lv, Changyong Dou
Remote Sensing of Environment Available online 1 July 2025
DOI:https://doi.org/10.1016/j.rse.2025.114886
Highlights
- Introduced new indicators to express construction and development for urban agglomerations.
- Designed a new method to describe the connections between cities based on SDGSAT-1 images.
- Obtained and analyzed the spatial development patterns of three urban agglomerations in China.
Abstract
Sustainable Development Goal (SDG) 11 aims to make cities and human settlements inclusive, safe, resilient, and sustainable. Understanding urban agglomerations, as highly developed products of urbanization, is important for achieving SDG 11. The Sustainable Development Science Satellite (SDGSAT-1), launched in 2021, aims to characterize “human activity traces” at a fine scale to fill data gaps and address incomplete methods in the implementation of the United Nations 2030 Agenda for Sustainable Development. The satellite, with a 10 m glimmer imager, provides a new and valuable data source for research related to urban agglomerations. To better describe the degree of construction and development of urban agglomerations, we established two new indicators—the City Activity Index (CAI) and the Population Activity Index (PAI)—based on SDGSAT-1 glimmer imager data. Additionally, we proposed a novel method for extracting the strength of intercity connections using 10 m glimmer imager data to reflect the current status of city linkages. These methods were combined and applied in three urban agglomerations in China: Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The findings not only enhance our understanding of spatial patterns and resource flows within major Chinese urban agglomerations, but also provide actionable data support for urban planning, infrastructure development, and governance. The study fully demonstrates the advantages of SDGSAT-1 high-precision glimmer imager data in depicting urban development, and provides data support for achieving SDG 11.
