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Against rapid development in urban areas, timely urban land cover change (ULCC) information is beneficial for understanding the urban environment and promoting sustainable development. To realize real-time ULCC detection, high-frequency remotely sensed data are urgently needed. In this study, we tested the detection capability of ULCCs using a new daily nighttime light (NTL) image (Black Marble). First, time series of VNP46V2 from 2012 to 2019 was collected and decoded into annual trend segments using the BFAST Monitor model. Then, we recognized the jump point in trend segments and defined the corresponding pixel as ULCC. We analyzed the normalized difference vegetation index (NDVI) time series from Landsat images spanning 2014–2019 and removed pixels without significant seasonal fluctuations from ULCC assembled. Finally, the magnitude and change time of ULCC pixels were …