Assessing Electricity Supply Reliability by Detection of Anomalies in Daily Nighttime Light - Miaoying Chen; Yang Hu; Xin Cao; Shijie Li; Luling Liu (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing)
Reliable electricity supply is critical to achieving Sustainable Development Goal 7 (SDG7), but it is difficult to measure and assess, especially in less developed countries and regions. Nighttime light (NTL) remote sensing is particularly well-suited to monitor artificial light. However, the daily NTL from NASA's Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) Black Marble product fluctuates due to angular effect, making it challenging to capture NTL anomalies accurately. This study proposed a new method to overcome the angular effect and detect low-value anomalies, serving the assessment of electricity supply reliability. We identified the optimal number of viewing zenith angle (VZA) groups, determining the magnitude of the angular effect. Subsequently, we obtained the characteristics and typical thresholds of the NTL variations at different observation angles, resulting from the observation geometry and the spatial structure of the surface. Finally, the spatial structure information of the angular effect is integrated to monitor the NTL anomalies over the time series. Anomalies with actual power outages were validated at 200 random points in Johannesburg, South Africa. The results show that the method effectively overcomes the impact of angular effect and successfully detects the power outage signals with an overall accuracy of 89.41%, precision of 83.78%, and recall of 84.64%. Moreover, the electricity anomaly rate in Johannesburg increased from 36% to 51% between 2020 and 2023, with elevated areas mainly in densely residential areas and commercial centers. The proposed method can be used to assess electricity supply reliability at regional and global scales.