Spatial and seasonal patterns of night-time lights in global ocean derived from VIIRS DNB images
Authors:
- 9 September 2018
- journal article
- research article
- Published by Taylor & Francis in International Journal of Remote Sensing
- Vol. 39 (22) , 8151-8181
Abstract
The majority of the research using night-time data has focused on the terrestrial environment, while the light flooding our oceans is less studied. Meanwhile, given the rapid development of imaging technology at night, remotely sensed night-time light data can now provide a great opportunity to improve understanding of the spatiotemporal distribution of light over large areas. In this article, we used monthly cloud-free night-time imagery from the Suomi National Polar-Orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite Day/Night Band, collected from 2014 to 2016, to explore the spatial distribution of night-time light in marine ecosystems. Morphological methods were used to extract light agglomeration areas. Using the Empirical Mode Decomposition method, we detected seasonal change patterns. Our results show that the distribution of light at night is clustered, and mainly concentrated in coastal and offshore waters, with about 70% of the total light found in 0.3% of the global marine waters. Flares from oil and gas well may not create a distinctive seasonal pattern, although fishing lights may show a seasonal pattern. The five largest agglomeration areas of light are centred in the eastern and southeast waters of Asia with little seasonal fluctuation. The cyclical light pattern of the entire marine system had a period of about 0.94 years, while varied from 0.5 to 1.1 years in the agglomeration areas. The proportions of seasonal energy for 49% of the top 100 agglomeration areas were below 10%, while the areas located in the waters near northern Japan, North Korea, eastern Indonesia, and eastern Argentina experienced large seasonal changes.Keywords
Funding Information
- Natural Science Foundation of China (No. 41771386)
- the Fundamental Research Funds for the Central Universities (No. 2042016kf0162)
- Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University (No. 2016LSDMIS03)
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