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Scientific RepoRts | 6:33623 | DOI: 10.1038/srep33623
www.nature.com/scientificreports
Satellite data lift the veil on
oshore platforms in the South
China Sea
Yongxue Liu1,2,3, Chao Sun1, Jiaqi Sun1, Hongyi Li1, Wenfeng Zhan4, Yuhao Yang1 &
Siyu Zhang1
Oil and gas exploration in the South China Sea (SCS) has garnered global attention recently; however,
uncertainty regarding the accurate number of oshore platforms in the SCS, let alone their detailed
spatial distribution and dynamic change, may lead to signicant misjudgment of the true status of
oshore 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 oshore
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) oshore 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 ndings
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.
Oshore oil/gas platforms are the essential infrastructure for the extraction, processing, and temporary storage
of crude oil and natural gas in the sea. e question of exactly how many oil and gas oshore platforms are dis-
tributed in the South China Sea (SCS) is of signicant interest both for academic research and economic and
geopolitical considerations, and from national level to trans-national level: (1) Understanding the regional distri-
bution of the oshore associated petroleum gas (APG) aring is essential for the drive to assess APG utilization
led by the Global Gas Flaring Reduction Partnership (GGFR)1. (2) Energy resources are an undeniable factor
underlying sovereignty and maritime disputes in the SCS, and tension is growing in line with increasing oshore
energy exploitation2,3. Accurate knowledge of the total number of platforms and its rate of change may aid the
SCS claimants to better manage their safety and security risks. (3) More than one half of the world’s oil tankers
and merchant ships pass through the SCS every year4, and detailed knowledge of the locations of the platforms
will reduce the potential for collisions within this vital sea lane5. (4) Oshore platforms promote neighboring sec-
ondary production6,7, but they also pose potentially serious risks to the marine environment8–12, especially from
oil spillages13–16. Moreover, the growing number of aging platforms, approaching or exceeding their design life,
increases the potential for environmental hazards, and knowledge of the ages of platforms will facilitate screening
of high-risk areas. (5) Many platforms are equipped with rescue facilities (e.g., stand-by vessels and helipads),
and knowledge of the types of platforms may be valuable when preparing for futures hazards such as tsunamis.
Admittedly, the relevant authorities, such as oshore oil/gas producing countries, oshore energy producers,
and even oshore platform producers, are familiar with the details of their own platforms. However, they are usu-
ally reluctant to make this information available publically–for reasons of business secrecy or national interests
and security. is creates transnational knowledge barriers, and even state powers may lack timely and complete
information concerning oshore platforms located in neighboring waters. For example, the Ministry of Defense
of Japan has had to resort to aerial reconnaissance in order to assess the spatial distribution of platforms in the
East China Sea17. Similarly, related parties of the SCS are confronted by the same dilemma, and there are various
opinions regarding the number of oshore oil/gas platforms in the SCS18–21. us, the uncertainty with regard to
1Department of Geographic Information Science, Nanjing University, Nanjing, 210023, P. R. China. 2Collaborative
Innovation Center for the South China Sea Studies, Nanjing University, Nanjing, Jiangsu Province 210023, P. R. China.
3International Institute for Earth System Science, Nanjing University, Nanjing, 210023, P. R. China. 4Jiangsu Center
for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023,
P. R. China. Correspondence and requests for materials should be addressed to Y.L. (email: yongxue@nju.edu.cn)
Received: 01 March 2016
Accepted: 01 September 2016
Published: 19 September 2016
OPEN
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Scientific RepoRts | 6:33623 | DOI: 10.1038/srep33623
the total number of oshore platforms, let alone their detailed spatial distribution and dynamic changes, may lead
to signicant misjudgment of the true status of hydrocarbon production in the SCS. Earth observation satellites
provide remote and regular access to inaccessible areas22,23, and the large amount of new and archived satellite
data, most of which is free and web enabled24–26, and which is continuously improving in spatial, temporal and
spectral resolution, provides the opportunity to overcome the knowledge barrier.
In order to enable non-professionals, including managers and decision-makers, to rene their strategies for
marine energy exploitation, environmental management, and marine security/safety maintenance, we focus pri-
marily on revealing the exact number, spatial distribution, rate of increase and type of oil and gas platforms in the
SCS via analysis of time series satellite images with a variety of spatial resolutions.
Results
Offshore persistent-flaring regions detected from the nighttime light (NTL) products. A
total of 112 oshore persistent-aring regions (aring consecutively for more than two years) in the SCS were
determined from the annual NTL products generated from the operational line-scan system (OLS) of Defense
Meteorological Satellite Program satellites (DMSP). ese aring regions are distributed on the continental shelf
o the mouth of the Pearl River and the Gulf of Tonkin, the southeast coast of the Indo-China Peninsula, the
region from the Gulf of ailand to the west Natuna Islands, the north coast of Kalimantan Island, and the west
coast of the Philippine Islands (Supplementary Fig. S1). Oshore persistent aring regions derived from the
monthly NTL products acquired by the visible infrared imaging radiometer suite (VIIRS) boarded on the Suomi
National Polar-orbiting Partnership (S-NPP) weather satellite exhibit a remarkably similar spatial distribution
(Supplementary Fig. S2). Although it is impossible to determine accurately the number and exact position of plat-
forms from NTL products because of their coarse spatial resolution, the distribution of persistent aring regions
overall provides valuable heuristic information for more detailed platform detection in the entire SCS.
Up-to-date distribution of oshore platforms detected from moderate resolution images. Our
detection shows there were a total of 1082 platforms across the SCS by March 2015 (Fig.1). Among these plat-
forms, 1040 platforms were detected from 1059 candidates retrieved from more than a thousand Landsat-8 oper-
ational land imager (OLI) images between 2013 and 2015 (with 19 were incorrectly detected), and the rest 42
platforms were detected based on other remote sensing data ranging from SAR to high-resolution optical images
(Supplementary: data sets). e elaborate crosscheck illustrates that the omission error and the commission rate
are 3.88% and 1.76%, respectively (Supplementary: validation). Aer the renement by the use of multi-source
data across the entire SCS, the accuracy of this number (1082) is likely to be robust, because the omissions and
commissions conrmed by those time-series images from various sensors have been further corrected.
e spatial distribution of the detected platforms accords well with that of the persistent aring regions
(Supplementary Figs S1 and S2). Combining our results with the marine claims made by the littoral states of
the SCS, we determined that ailand had the greatest number of platforms (356), followed by Malaysia (317),
Brunei (166), Vietnam (91), China (76), Indonesia (29), Philippine (8), Cambodia (1), the Malaysian-ai Joint
Development Area (MTJDA, 25), and the Malaysian-Vietnamese Joint Economic Development Zone (MVJEDZ)
(13).
Satellite images and bathymetry data reveal the majority of oil and gas exploitation in the SCS is charac-
terized by small-installation and shallow-water production (Supplementary Figs S3–S5). We found that a total
of 892 platforms were single-structure and of small/medium size; 81 were hybrid structures comprising sev-
eral sub-platforms; and 109 were ship-shaped, presumably oating production storage and ooading units
(FPSO) (Supplementary Fig. S4). More than 95% of platforms (1031) were located in shallow water (< 100 m
water-depth), 40 installations were located in water depths from 100 to 500 m, and only 11 were deep-water plat-
forms (> 500 m water-depth) (Supplementary Fig. S5).
Proliferation of offshore platforms documented in archived moderate resolution images.
According to more than 4,000 archived images acquired from 1991 to 2015 (see Supplementary: data sets for more
detail), we detected a continuous increase in oshore hydrocarbon exploitation in the SCS: (i) e number of
oshore platforms in the SCS increased steadily from 230 in 1992 to 1082 in 2015–an average of 37 new platforms
per year, and a rate of increase approximately 4.7 greater than during the two previous decades (Supplementary
Table S1 and Supplementary Fig. S6). (ii) By overlapping the distribution of annual persistent aring regions
detected from NTL products with our detection results, we determined that the number of oshore platforms
operating at night maintained a higher growth rate, with the number increasing from 86 to 466, an increase by a
factor of 5.41 (Fig.2a). (iii) ere was a similar trend in the number of FPSO, ranging from 18 in 1992 to 109 in
2015, an increase by a factor of 6.06 (Fig.2b). e data demonstrate that the pattern of oshore oil/gas exploration
and exploitation in the SCS exhibits consistency in terms of operational depth as well as in the distance to the
mainland (Fig.2c,d). (iv) e operational depth ranges from shallow water to deep water, and even approaches
ultra-deep water (> 1500 m), with the maximum depth increasing from approximately 119 m in 1992 to 1469 m in
2015. (v) e distance to the mainland ranged continuously from near-shore to open sea, with several platforms
located more than 340 km from the mainland.
Discussion
Possible overestimation of the number of oshore platforms in previous reports. Until now,
there was no available spatial distribution data of oshore platforms across the SCS, and the precise number of
oshore platforms over the region remained in dispute. Several reports claimed that approximately 127818, 135019,
138020 platforms had been erected in the SCS by 2010, while later reports asserted that the number had increased
to 1511 by August 201521. All of these previous reported numbers were primarily obtained by integrations,
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Figure 1. Annual proliferation of oshore platforms in the SCS from 1992 to 2015. (a) e entire SCS;
(b) Gulf of Tonkin and oshore of the Pearl River mouth; (c) the southeast coast oshore of the Indo-China
Peninsula; (d) from the Gulf of ailand to the west of the Natuna Islands; (e) the north coast oshore of
Kalimantan Island; (f) the coast oshore of the Philippine Islands. e map data was made with Natural Earth
(http://www.naturalearthdata.com/). e gure was generated by Y. L. and W. C. using ArcMap 10.0
(http://www.esrichina.com.cn/).
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estimations, and speculations from decommissioned studies, proprietary and commercial databases, and Internet
searches. ey vary as a result of data availability, classication criteria of platforms, and date of assessment19.
In contrast, we enumerated a total of 870 platforms by 2010 from archived time-series images covering the
entire SCS (Supplementary Table S1). is number is signicantly lower than the numbers in previous reports.
However, in a country-by-country comparison, the number of platforms belonging to most of the SCS claimants/
joint-development-areas, including Philippine, Vietnam, ailand, Malaysia, MTJDA, and MVJEDZ, are gen-
erally consistent or slightly higher than those previously reported (Fig.3). We consider that a timely update of
these earlier reports across the SCS is lacking, because every oshore platform we detected has been convincingly
evidenced by time-series satellite images (Supplementary: validation).
Figure 2. Annual proliferation of oshore platforms in the SCS. (a) Annual number of platforms activating
at nighttime; (b) annual number of FPSO; (c) annual mean depth of oshore platforms; and (d) annual mean
distance of oshore platforms to the mainland. e gure was generated by Y. L. J. S., and W. C. using SigmaPlot
12.5 (http://www.sigmaplot.com/).
Figure 3. Comparison of the number of oshore platforms distributed in the SCS by 2010 between our
results and that reported in the previous studies. e gure was generated by Y. L., J. S. and W. C. using
SigmaPlot 12.5 (http://www.sigmaplot.com/).
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e most striking divergence between previous results and our own ndings occurs in the case of China and
Indonesia: the number of oshore platforms we detected belonging to China is less than half that previously
reported, and the number belonging to Indonesia is approximately one-twentieth of that previously reported.
We suggest that the data in the previous reports may include platforms outside the SCS but which are owned
by the SCS claimants. Evidence in support of this conclusion is the fact that three types of quasi-synchronous
space-borne image, acquired by Landsat-5/7 TM/ETM+ , ALOS-1 PALSAR, and ENVISAT ASAR, covering all
the areas of Chinese exploitation in the SCS, indicate that the number was no more than 55. According to our
extended remote sensing monitoring, by 2010 the total of oshore platforms in the Bohai Bay (87, Fig.4b), in
the East China Sea (4, Fig.4c), and the SCS (55, Fig.1b), was 146. Further evidence is provided by the fact that
by 2010 the total will reach 1256, excluding the oshore platforms owned by Indonesia but which lie outside the
SCS (Fig.4d,e), such as the water to the east of Kalimantan Island (42, Fig.4d), south of Sumatra and Java (253,
Fig.4e). ese regions are not geographically part of the SCS (Fig.4a).
Figure 4. Oshore platforms outside the SCS (a). Platforms owned by China in Bohai Bay (b) and in the East
China Sea (c); platforms owned by Indonesia oshore the east Kalimantan Island (d) and oshore the Sumatra
Island and Java Island (e). e map data was made with Natural Earth (http://www.naturalearthdata.com/). e
gure was generated by Y. L. using ArcMap 10.0 (http://www.esrichina.com.cn/).
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Even taking into account the fact of statistical region, the following two factors may also result in an overes-
timation: (i) Decommissioned platforms – Our results show that at least 290 platforms across the SCS have been
operating for more than 20 years (Fig.1 and Supplementary Table S1), approaching their designed service life
(25-year). ese decommissioned platforms may not have been excluded in previous reports. For example, in the
sea area claimed by Brunei, 23 scenes of GF-1/ZY-3 high resolution images covering the entire region indicate
that the number was no more than 156 (Supplementary: validation), slightly less than the number of 160 reported
in a previous study. In addition, we determined that at least four platforms had been removed from 2007–2009,
which may explain the divergence. (ii) Classication criteria – Our results demonstrate that there were 81 hybrid
platforms consisting of several sub-platforms in the SCS (Supplementary Fig. S4). ese complex structures have
been expanding for several years (Supplementary Fig. S7), resulting in their being enumerated several times.
We consider that the combination of these factors, i.e., region of the statistics, decommissioned platforms, and
classication criteria, has likely resulted in a roughly one-third overestimation of the number of platforms in the
SCS.
Future geopolitical tension caused by oil and gas exploitation in the SCS. Clearly, overestima-
tion of the number of oshore platforms in the SCS does not imply any future amelioration in maritime tension
caused by the proliferation of oshore oil and gas exploitation in the region. Our data reveal that by March
2015, 90 platforms were located in regions of overlapping maritime claims, almost 10 times the number in 1992
(Supplementary Fig. S8). is rate of increase in disputed waters was more than twice that in undisputed waters.
We predict that by 2020 the number of oshore platforms in areas of overlapping claims will reach 120, based on
the average of 6 new platforms per year during the past decade, and approximately 130 based on the average of 8
during the past ve years.
Obviously, the proliferation of oshore oil and gas exploitation will continuously intensify maritime tensions
in the SCS, and this situation is likely to be further exacerbated with the surging domestic demand and the deple-
tion of inshore hydrocarbon energy resources of the littoral states of the SCS2. Furthermore, the SCS is an area
of major and long-term economic and strategic interest for several major powers, and the overlapping factors of
sovereignty disputes and energy aspirations, as well as the intertwining of the political and economic interests
of neighboring countries and the strategic involvement of external countries, result in considerable geopolitical
complexity27–29. erefore, disputes triggered by the proliferation of oshore oil and gas exploitation may escalate
to conicts which are grounded in eorts to maintain national sovereignty which transcend the desire simply to
maintain oil and gas production. Such conicts may potentially lead to serious international crises.
Data and Methods
e enumeration of oshore platforms in the SCS, an area of more than 3.8 million km2 (Supplementary: the
South China Sea), by means of remote sensing (oen inuenced by poor image conditions, complex underly-
ing surface, and ubiquitous noise), is problematic. To address the aforementioned diculties, a top-down data
framework incorporating macro/meso/micro scales of satellite images, and a generic oshore platforms detection
method for various capable space-borne sensors, was designed (Fig.5).
Top-down space-borne data framework for oshore platform detection. e past unsuccessful
search for Flight MH370 highlights the fact that the search for marine targets, e.g., plane debris, should be based
on the premise of coarse/ne location information30. Similarly, pre-knowledge of oshore platforms, e.g., their
approximate but timely spatial-distribution, is critical for their detection. Hence, a multi-resolution space-borne
image framework was designed to eciently detect oshore platforms across a large area of sea (Fig.5a):
(1) Heuristic information derived from low resolution nighttime light products – Gas aring of APG and lights from
oshore platforms at night can be recorded in the DMSP OLS, or in the VIIRS boarded on the S-NPP weather
satellite31,32. us, the persistent aring regions in time-series NTL images, reecting the timely and coarse
distribution of platforms, can be used as an indicator for determining which moderate-scale sensors are qual-
ied for oshore platform detection, and for which areas moderate resolution images need to be collected.
(2) Detailed information derived from competent moderate resolution images – Using NTL products for guidance,
we nd that Synthetic Aperture Radar (SAR) images acquired by ENVISAT, ALOS, Sentinel, and the like, and
short wave infrared (SWIR) images photographed by Landsat thematic mapper (TM), enhanced thematic
mapper plus (ETM+ ), and operational land imager (OLI), are capable of presenting oshore platforms. Note
that the aforementioned sensors vary greatly in terms of available time-span, spatial coverage, archived num-
ber, geometric accuracy, and cost of space-borne imagery (Supplementary Table S2). Aer considering their
merits and demerits, we selected Landsat-8 OLI images, which oer the latest and almost complete coverage
of the SCS, to detect the up-to-date distribution of platforms in the SCS, while employing the other archived
images to determine the ages of oshore platforms (the year of rst appearance). Furthermore, by combining
platform positions with bathymetry data, the water depth of oshore platforms can also be retrieved.
(3) Validation from high resolution images – High resolution images from the Chinese satellites GF-1 and ZY-3,
were used to validate and rene the detections from moderate resolution images.
According to the aforementioned multi-resolution space-borne image framework, a total of more than 4,000
satellite images covering the SCS were used, including 1035 Landsat-8 OLI images (2013–2015), 1196 Landsat-5/7
TM/ETM + images (1991–2013), 1280 tiles ALOS-1 PALSAR images (2007–2010), 573 ENVISAT ASAR images
(2005–2009), 86 Sentinel SAR images (2014–2015), and 89 images from Chinese high resolution satellites GF-1
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and ZY-3. More information on the data used, such as the available time-span, spatial coverage and number, is
given in Supplementary: data sets.
Generic platform extraction method for various capable sensors. Oshore platforms documented
in the competent space-borne images, usually exhibit the following characteristics: (1) Tiny, spot-like features with
a sparse distribution (Fig.5a). (2) Invariance characteristics–In a time-series of satellite images with high geomet-
ric accuracy, the positions of oshore gas-aring/platforms can be regarded as almost xed relative to moving
vessels. According to these two characteristics, we extend the automated method for extracting oshore platforms
(AMEOP) from time-series OLI images which we proposed previously33, to time-series satellite images acquired
by other capable sensors (Fig.5b):
(1) Detecting oshore platform candidates according to spot-like principles – Sea surface targets, including plat-
forms, vessels, and noise, usually exhibiting a homogeneous compact region in competent images, can be
regarded as salient points with DN values higher than their surroundings. ese salient targets, striking or
Figure 5. e proposed data framework and general framework for oshore platform detection. e DMSP
OLS NTL data was downloaded from the NGDC Earth Observation Group (EOG) of NOAA (http://ngdc.noaa.
gov/eog/download.html). e Landsat-8 OLI SWIR data were available from the Global Visualization Viewer
of the U.S. Geological Survey (http://glovis.usgs.gov). e ALOS PALSAR Standard Product ((c) JAXA/METI)
were downloaded from the Japan Aerospace Exploration Agency (JAXA, http://www.eorc.jaxa.jp/). e GF-1
images were downloaded from the China Center for Resource Satellite Data and Applications (CRESDA, China,
http://www.cresda.com/). e gure was generated by Y. L. using ArcMap 10.0 (http://www.esrichina.com.cn/)
and Oce Visio 2010 (https://products.oce.com/en-us/visio).
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not, can be segmented using an adaptive threshold calculated by order-statistic ltering (OSF). Admittedly,
not all oshore platform candidates can be completely extracted from a single phase satellite image because of
weak imaging conditions, or the inuence of noise. We detect oshore platform candidates from a time-series
of images acquired in a short time span to minimize the omissions: the undetected platform candidates in a
given phase would be compensated in other phase images with high quality.
(2) Excluding false positives according to the position invariance principle – Usually, noise among the candi-
dates was randomly distributed in the spatiotemporal dimension, and we apply pairwise intersection to the
time-series of oshore platform candidates to mitigate the mixed errors. In each pairwise intersection, some
oshore platforms may be improperly removed because they are undetected in paired images, or some noise
may be retained because of the over-density of noise in coupled images. Subsequently, all pairwise intersec-
tions were accumulated to compensate for omissions and to suppress noise. In the accumulation image, the
oshore platforms (with a high degree of position invariance in image time-series) usually had an occurrence
frequency higher than that of randomly-distributed noise sources. us, those pixels with high frequency
were segmented as potential oshore platforms.
(3) Conrmation – To maximize the robustness of the detection, all platforms automatically detected from
time-series images were then repeatedly examined and carefully assessed by time-series of high quality
Landsat-8 OLI images, ALOS PALSAR validation all over the entire SCS, Sentinel-1 SAR validation along
the coastal zones, and high resolution image validation in the coastal zones and areas of oshore platform
agglomeration. In addition, in the process of manual validation, the type of oshore platform was determined
as a byproduct according to their shape exhibited in the Landsat-8 OLI images.
Clearly, the position-invariance characteristic of oshore platforms/gas aring regions documented in the
time-series images is of vital importance for their detection, and the rst two steps mentioned above can be
automatically applied to competent satellite images with eligible geometric accuracy (e.g., < 2 pixels), such as
images acquired by DMSP OLS, S-NPP VIIRS, Landsat-8 OLI, and ALOS-1 PALSAR. Other competent images
with a poor geometric accuracy, e.g., Landsat TM/ETM+ , ENVISAT ASAR images covering areas far from land
in which the shi of the same platform may span dozens of pixels, were geometric-corrected to ensure their
position-invariance, using the platforms detected from Landsat-8 images as ground control points. More details
on the generic platform extraction method for various capable sensors are given in Supplementary: Table S3,
Figs S11–S16, and Method for oshore platform detection.
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Acknowledgements
is research is supported by the Key research and development program of China (No. 2016YFB0501502),
Jiangsu Provincial Natural Science Foundation (No. BK20160023), and the National High Technology Research
and Development Program of China (863 Program, No. 2012AA12A406). e authors are grateful to the Global
Visualization Viewer of the United States Geological Survey (USGS, http://glovis.usgs.gov/) for providing all of
the Landsat TM/ETM+ /OLI images, to the China Center for Resource Satellite Data and Applications (CRESDA,
http://www.cresda.com) for providing all of the GF-1 and ZY-3 images, and to the Japan Aerospace Exploration
Agency (JAXA, http://www.eorc.jaxa.jp/) for providing ALOS PALSAR HH polarization mosaic data. We are also
grateful to the valuable comments made on the manuscript by Dr. Liu Beibei (Nanjing University). Note that any
errors or shortcomings in the paper are the responsibility of the authors.
Author Contributions
Y.L. designed the study, collected data, performed analysis and wrote the paper. Y.L. and C.S. programmed the
oshore platform detection algorithm. Y.Y., S.Z., W.Z. and J.S. rened study design and analyses and co-wrote the
paper. All other authors discussed results and co-wrote the paper.
Additional Information
Supplementary information accompanies this paper at http://www.nature.com/srep
Competing nancial interests: e authors declare no competing nancial interests.
How to cite this article: Liu, Y. et al. Satellite data li the veil on oshore platforms in the South China Sea.
Sci. Rep. 6, 33623; doi: 10.1038/srep33623 (2016).
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