Recent Advances in Novel Integration of Nighttime Remote Sensing and Spatiotemporal Big Data
Nighttime light data, which can effectively identify visible and near-infrared emission sources at night, plays an important role in Digital Earth communities. In particular, nighttime remote sensing provides a new perspective for discovering the Earth’s surface at a variety of scales. However, nighttime light data may not accurately reflect the spatial heterogeneity of socio-economic activities and environmental phenomena during daytime. To overcome this limitation, novel integrations of nighttime remote sensing and spatial-temporal big data, such as mobile phone signaling, social media records, GPS tracking, municipal service data, and volunteered geographic information, are urgently needed. Therefore, this Article Collection aims to explore the latest advances in the integration of nighttime remote sensing and spatiotemporal big data. The outcome of this Article Collection will not only be useful to understand and guide worldwide sustainable development from a new perspective, but also offer down-to-earth solutions to various social, economic, and environmental issues in the era of big data. We would like to invite you to submit original research that fits the aims and scope of this Article Collection. We look forward to receiving your well-prepared research. Potential subtopics include, but are not limited to: Urban carbon emission and energy conservation Socioeconomic-related activities mapping Long-term assessment of air and light pollution Monitoring of urban growth and urban shrinkage Quantification of United Nations’ SDGs Urban hazard susceptibility analysis and assessment Artificial intelligence in nighttime remote sensing New methodology in nighttime light data calibration
Edited by
Prof. Zhifeng Wu(Guangzhou University)
Prof. Jinyao Lin(Guangzhou University)
Prof. Shaoying Li(Guangzhou University)
Prof. Jinpei Ou(Sun Yat-sen University)