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      Satellite data lift the veil on offshore platforms in the South China Sea

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          Abstract

          Oil and gas exploration in the South China Sea (SCS) has garnered global attention recently; however, uncertainty regarding the accurate number of offshore platforms in the SCS, let alone their detailed spatial distribution and dynamic change, may lead to significant misjudgment of the true status of offshore hydrocarbon production in the region. Using both fresh and archived space-borne images with multiple resolutions, we enumerated the number, distribution, and annual rate of increase of offshore platforms across the SCS. Our results show that: ( 1) a total of 1082 platforms are present in the SCS, mainly located in shallow-water; and ( 2) offshore oil/gas exploitation in the SCS is increasing in intensity and advancing from shallow to deep water, and even to ultra-deep-water. Nevertheless, our findings suggest that oil and gas exploration in the SCS may have been over-estimated by one-third in previous reports. However, this overestimation does not imply any amelioration of the potential for future maritime disputes, since the rate of increase of platforms in disputed waters is twice that in undisputed waters.

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          Oil spill: Deep wounds.

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            Review of oil spill remote sensing.

            Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing.
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              Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities.

              Most environmental satellite radiometers use solar reflectance information when it is available during the day but must resort at night to emission signals from infrared bands, which offer poor sensitivity to low-level clouds and surface features. A few sensors can take advantage of moonlight, but the inconsistent availability of the lunar source limits measurement utility. Here we show that the Day/Night Band (DNB) low-light visible sensor on the recently launched Suomi National Polar-orbiting Partnership (NPP) satellite has the unique ability to image cloud and surface features by way of reflected airglow, starlight, and zodiacal light illumination. Examples collected during new moon reveal not only meteorological and surface features, but also the direct emission of airglow structures in the mesosphere, including expansive regions of diffuse glow and wave patterns forced by tropospheric convection. The ability to leverage diffuse illumination sources for nocturnal environmental sensing applications extends the advantages of visible-light information to moonless nights.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                19 September 2016
                2016
                : 6
                : 33623
                Affiliations
                [1 ]Department of Geographic Information Science, Nanjing University , Nanjing, 210023, P. R. China
                [2 ]Collaborative Innovation Center for the South China Sea Studies, Nanjing University , Nanjing, Jiangsu Province 210023, P. R. China
                [3 ]International Institute for Earth System Science, Nanjing University , Nanjing, 210023, P. R. China
                [4 ]Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application , Nanjing, 210023, P. R. China
                Author notes
                Article
                srep33623
                10.1038/srep33623
                5027537
                27641542
                96d0d35f-6b79-42fd-ab09-c130409cb622
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 01 March 2016
                : 01 September 2016
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