Nighttime light imagery or mobile phone footprints: Which better reflects urban socio-economics at the grid level? A case study in the Pearl River Delta, China

Jinzhou Cao, Xianyu Cao, Wei Tu, Xiaoliang Tan, Tong Wang, Guanzhou Chen, Xiaodong Zhang, Qingquan Li

Abstract: Highlights•Evaluate mobile phone footprints(MOB) and nighttime light data(NTL) within a 500 m grid to assess socioeconomic indicators.•NTL is great for mapping POIs and roads, while MOB is suitable for building info and GDP.•NTL distorts urban-rural socioeconomic disparities; MOB provides consistent reliability across urban-rural spaces.•MOB clarifies how NTL reflect economic activity.