地理信息技术支撑下的南海岛礁资源环境研究进展与展望

doi:10.18306/dlkxjz.2018.11.002

地理科学进展 ›› 2018, Vol. 37 ›› Issue (11): 1454-1462.doi: 10.18306/dlkxjz.2018.11.002

• 专栏：南海与“一带一路” • 上一篇下一篇

地理信息技术支撑下的南海岛礁资源环境研究进展与展望

李弘毅^1,^2,³(), 刘永学^1,^2,^3,^*(), 张思宇^1,³, 孙超^1,³, 孙佳琪^1,³

1. 南京大学地理与海洋科学学院,南京 210023
2. 中国南海研究协同创新中心,南京 210023
3. 海岸带开发与保护国土资源部重点实验室,南京 210023

收稿日期:2016-10-09 修回日期:2017-05-31 出版日期:2018-11-28 发布日期:2018-11-28
通讯作者: 刘永学
作者简介:
作者简介：李弘毅(1992-),女,江苏南京人,硕士研究生,研究方向为海洋遥感与GIS,E-mail: lu_leftright@sina.com。
基金资助:
国家重点研发计划项目(2016YFB0501502);江苏省杰出青年基金项目(BK20160023)

Progress and prospects on coral reefs research in the South China Sea based on the application of geographic information technologies

LI Hongyi^1,^2,³(), LIU Yongxue^1,^2,^3,^*(), ZHANG Siyu^1,³, SUN Chao^1,³, SUN Jiaqi^1,³

1. Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
2. Collaborative Innovation Center for the South China Sea Studies, Nanjing University, Nanjing 210023, China
3. Key Laboratory of Coastal Zone Development and Protection, Ministry of Land and Resources of China, Nanjing 210023, China

Received:2016-10-09 Revised:2017-05-31 Online:2018-11-28 Published:2018-11-28
Contact: LIU Yongxue
Supported by:
Key Research and Development Program of China, No.2016YFB0501502;Jiangsu Provincial Natural Science Foundation, No.BK20160023

摘要/Abstract

摘要：

面积辽阔的南海是中国未来重要的能源接续区与资源基地,也是涉及国家海洋权益最为集中的区域。本文针对地理信息技术支撑下的南海岛礁研究现状,从南海岛礁现有基础数据成果、遥感手段岛礁基础地理信息提取方法及提取成果所做的岛礁分析与评价3方面,系统地回顾了国内外涉及南海岛礁资源环境研究的相关进展,评述了现有研究技术方法存在的不足,并对未来的研究进行了展望,在此基础上,提出了3个主要方向作为未来研究的重点：①促进遥感数据获取多源化,构建海量多源、多尺度南海岛礁遥感数据仓库;②加强技术协同创新,结合地理信息技术的发展,提升岛礁信息提取与监测的准确性与可靠性;③提升遥感分析智能化,研究并建立综合分析与情势推演平台及战略决策辅助支撑系统,以期为南海岛礁的进一步深入研究提供参考。

关键词: 南海, 岛礁, 地理信息技术, 资源环境, 进展与展望

Abstract:

The South China Sea region is an important prospective energy supply area and a resource base for China. Although coral reef resources are extremely abundant in the South China Sea, research on coral reef data extraction, and analysis and evaluation of coral reef resources have not attracted enough attention. This article put forward an analytical framework based on the application of geographic information technologies in the South China Sea, and reviewed the main progresses in three aspects: current availability of basic geographic data, methods on the extraction of basic geographic information, and evaluation of coral reefs in the Siuth China Sea. Based on the review and analysis, this article proposed three research directions in the future: (1) promote multi-source remote sensing data acquisition, build massive remote sensing databases; (2) strengthen collaborative technological innovation, improve the accuracy and reliability of information extraction and monitoring results; and (3) promote intelligent remote sensing analysis, establish comprehensive analysis and decision-support systems which will provide theoretical reference for the further development of coral reef research in the South China Sea.

Key words: South China Sea, coral reefs, geographic information technology, resources and environment, progress and prospects

李弘毅, 刘永学, 张思宇, 孙超, 孙佳琪. 地理信息技术支撑下的南海岛礁资源环境研究进展与展望[J]. 地理科学进展, 2018, 37(11): 1454-1462.

LI Hongyi,LIU Yongxue,ZHANG Siyu,SUN Chao,SUN Jiaqi. Progress and prospects on coral reefs research in the South China Sea based on the application of geographic information technologies[J]. PROGRESS IN GEOGRAPHY, 2018, 37(11): 1454-1462.

图/表 1

参考文献 53

[1]	陈建裕, 毛志华, 张华国, 等. 2007. SPOT5数据东沙环礁珊瑚礁遥感能力分析[J]. 海洋学报: 中文版, 29(3): 51-57. doi: 10.3321/j.issn:0253-4193.2007.03.007
	[Chen J Y, Mao Z H, Zhang H G, et al.2007. Analysis on coral reefs mapping using SPOT5 at Dongsha Atoll[J]. Acta Oceanologica Sinica, 29(3): 51-57.] doi: 10.3321/j.issn:0253-4193.2007.03.007
[2]	陈韶阳. 2011. 南沙群岛价值分类评价和开发策略研究[D]. 青岛: 中国海洋大学.
	[Chen S Y.2011. Research on classified value evaluation and development strategy of Nansha Islands[D]. Qingdao, China: Ocean University of China.]
[3]	成王玉, 刘永学, 李满春, 等. 2013. 基于AHP与模糊综合评价方法的南沙东部岛礁战略价值评价[J]. 热带地理, 33(4): 381-386.
	[Cheng W Y, Liu Y X, Li M C, et al.2013. Strategic value evaluation of the atolls in the eastern Nansha Islands based on AHP and Fuzzy Comprehensive Evaluation Method[J]. Tropical Geography, 33(4): 381-386.]
[4]	党福星, 丁谦. 2003. 利用多波段卫星数据进行浅海水深反演方法研究[J]. 海洋通报, 22(3): 55-60. doi: 10.3969/j.issn.1001-6392.2003.03.008
	[Dang F X, Ding Q.2003. Research on reefs bathymetry estimation by remote sensing using multi-band satellite data[J]. Marine Science Bulletin, 22(3): 55-60.] doi: 10.3969/j.issn.1001-6392.2003.03.008
[5]	何宇华, 王永江. 1998. 卫星遥感在岛、礁、滩、沙资源分布现状综合调查中的应用[J]. 中国地质, (8): 43-46.
	[He Y H, Wang Y J.1998. Satellite remote sensing applications on the island, reef, beach, sand distribution resources comprehensive survey[J]. Geology of China, (8): 43-46.]
[6]	胡蕾秋, 刘亚岚, 任玉环, 等. 2010. SPOT5多光谱图像对南沙珊瑚礁信息提取方法的探讨[J]. 遥感技术与应用, 25(4): 493-501.
	[Hu L Q, Liu Y L, Ren Y H, et al.2010. Research on the extraction eethod of coral reef at Spratly Islands using SPOT5[J]. Remote Sensing Technology and Application, 25(4): 493-501.]
[7]	蒋洁, 刘永学, 李满春, 等. 2014. 南海岛礁风能资源及风力发电评价: 基于QuikSCAT风场数据与Landsat ETM+影像[J]. 资源科学, 36(1): 139-147.
	[Jiang J, Liu Y X, Li M C, et al.2014. Wind energy resources and wind power generation on islands and reefs in the South China Sea based on QuikSCAT wind data and Landsat ETM+ images[J]. Resources Science, 36(1): 139-147.]
[8]	廖彬彬. 2013. 热带珊瑚岛礁生态系统风险评价与管理研究[D]. 上海: 华东师范大学.
	[Liao B B.2013. Risk assessment and management of tropical coral reef ecosystems[D]. Shanghai, China: East China Normal University.]
[9]	潘春梅, 丁谦, 曹文玉. 2002. 南沙群岛岛礁地形地貌TM影像特征分析[J]. 国土资源遥感,(2): 34-37, 60. doi: 10.6046/gtzyyg.2002.02.08
	[Pan C M, Ding Q, Cao W Y.2002. The applicaion of the adjustment technique to TM satellite imagery in Nansha Islands[J], Remote Sensing for Land & Resources,(2): 34-37, 60.] doi: 10.6046/gtzyyg.2002.02.08
[10]	盛琳, 王双亭, 周高伟, 等. 2015. 非线性模型岛礁礁盘遥感水深反演[J]. 测绘科学, 40(10): 43-47. doi: 10.16251/j.cnki.1009-2307.2015.10.008
	[Sheng L, Wang S T, Zhou G W, et al.2015. Research on reefs bathymetry estimation by remote sensing based on nonlinear model[J]. Science of Surveying and Mapping, 40(10): 43-47.] doi: 10.16251/j.cnki.1009-2307.2015.10.008
[11]	石伟, 苏奋振, 周成虎, 等. 2014. 南沙岛礁及周边港口可达性评价模型研究[J]. 地理学报, 69(10): 1510-1520. doi: 10.11821/dlxb201410010
	[Shi W, Su F Z, Zhou C H, et al.2014. Research on accessibility model of Nansha Islands and surrounding seaports[J]. Acta Geographica Sinica, 69(10): 1510-1520.] doi: 10.11821/dlxb201410010
[12]	孙超, 刘永学, 李满春, 等. 2014. 近35年来热带风暴对我国南海岛礁的影响分析[J]. 国土资源遥感, 26(3): 135-140. doi: 10.6046/gtzyyg.2014.03.22
	[Sun C, Liu Y X, Li M C, et al.2014. An analysis of tropical storms impact on islands and reefs in the South China Sea in the past 35 years[J]. Remote Sensing for Land & Resources, 26(3): 135-140.] doi: 10.6046/gtzyyg.2014.03.22
[13]	唐盟. 2015. 被越南侵占的中国南沙群岛岛礁的时空分布特征及战略格局[J]. 热带地理, 35(5): 739-744. doi: 10.13284/j.cnki.rddl.002749
	[Tang M.2015. Spatial distribution characteristic and strategic situation of the islands and reefs invaded by Vietnam in the Chinese Nansha Islands[J]. Tropical Geography, 35(5): 739-744.] doi: 10.13284/j.cnki.rddl.002749
[14]	汪业成, 刘永学, 李满春, 等. 2013. 基于场强模型的南沙岛礁战略地位评价[J]. 地理研究, 32(12): 2292-2301. doi: 10.11821/dlyj201312011
	[Wang Y C, Liu Y X, Li M C, et al.2013. The strategic position of Spratly Islands: An evaluation based on the field spread model[J]. Geographical Research, 32(12): 2292-2301.] doi: 10.11821/dlyj201312011
[15]	张荷霞. 2014. 南沙群岛岛礁战略价值评价研究[D]. 南京: 南京大学.
	[Zhang H X.2014. Research on strategic value evaluation of the islands and reefs in the Nansha Islands[D]. Nanjing, China: Nanjing University.]
[16]	张荷霞, 刘永学, 李满春, 等. 2013a. 南海中南部海域油气资源开发战略价值评价[J]. Resources Science, 35(11): 2142-2150.
	[Zhang H X, Liu Y X, Li M C, et al.2013a. Strategic value assessment of oil and gas exploitation in the central and southern South China Sea[J]. Resources Science, 35(11): 2142-2150.]
[17]	张荷霞, 刘永学, 李满春, 等. 2013b. 基于 JASON-1 资料的南海海域海面风、浪场特征分析[J]. 地理与地理信息科学, 29(5): 53-57. doi: 10.7702/dlydlxxkx20130512
	[Zhang H X, Liu Y X, Li M C, et al.2013b. Characteristic analysis on sea surface wind and wave fields in the South China Sea based on JA SON-1 data[J]. Geography and Geo-Information Science, 29(5): 53-57.] doi: 10.7702/dlydlxxkx20130512
[18]	张荷霞, 刘永学, 李满春, 等. 2014. 基于AHP和EWCM的部分南沙岛礁战略价值模糊综合评价[J]. 海洋通报, 33(4): 377-382.
	[Zhang H X, Liu Y X, Li M C, et al.2014. Fuzzy comprehensive evaluation of the strategic value for several reefs in the Spratly Islands based on AHP and EWCM[J]. Marine Science Bulletin, 33(4): 377-382.]
[19]	张靖宇. 2015. 浅海水深多维度遥感反演融合方法研究[D]. 青岛: 国家海洋局第一海洋研究所.
	[Zhang J Y.2015. Study on fusion models of multi-dimensional bathymetry inversion in shallow sea with remote sensing: A case study of the islands and reefs in South China Sea[D]. Qingdao, China: First Institute of Oceanography of National Bureau of Oceanography.]
[20]	赵赛帅, 刘永学, 李满春, 等. 2015. 基于AHP-变异系数法的越占南沙岛礁战略价值评价[J]. 海洋科学, 39(6): 114-121. doi: 10.11759/hykx20130605003
	[Zhao S S, Liu Y X, Li M C, et al.2015. Strategic assessment of the Nansha Islands occupied by Vietnam based on AHP-variation coefficient method[J]. Marine Sciences, 39(6): 114-121.] doi: 10.11759/hykx20130605003
[21]	周旻曦, 刘永学, 李满春, 等. 2015. 多目标珊瑚岛礁地貌遥感信息提取方法: 以西沙永乐环礁为例[J]. 地理研究, 34(4): 677-690. doi: 10.11821/dlyj201504007
	[Zhou M X, Liu Y X, Li M C, et al.2015. Geomorphologic information extraction for multi-objective coral islands from remotely sensed imagery: A case study for Yongle Atoll, South China Sea[J]. Geographical Research, 34(4): 677-690.] doi: 10.11821/dlyj201504007
[22]	邹亚荣, 林明森, 王华, 等. 2006. 对东沙岛基于融合信息高分辨遥感影像分类研究[J]. 海洋学报: 中文版, 28(1): 56-61. doi: 10.3321/j.issn:0253-4193.2006.01.008
	[Zou Y R, Lin M S, Wang H, et al.2006. Study on high resolution image classification for Dongsha Island based on fuse information[J]. Acta Oceanologica Sinica, 28(1): 56-61.] doi: 10.3321/j.issn:0253-4193.2006.01.008
[23]	Andréfouët S, Berkelmans R, Odriozola L, et al.2002. Choosing the appropriate spatial resolution for monitoring coral bleaching events using remote sensing[J]. Coral Reefs, 21(2): 147-154. doi: 10.1007/s00338-002-0233-x
[24]	Andréfouët S, Kramer P, Torres-Pulliza D, et al.2003. Multi-site evaluation of IKONOS data for classification of tropical coral reef environments[J]. Remote Sensing of Environment, 88(1-2): 128-143. doi: 10.1016/j.rse.2003.04.005
[25]	Baker A C, Glynn P W, Riegl B.2008. Climate change and coral reef bleaching: An ecological assessment of long-term impacts, recovery trends and future outlook[J]. Estuarine, Coastal and Shelf Science, 80(4): 435-471. doi: 10.1016/j.ecss.2008.09.003
[26]	Barnes B B, Hu C.2016. Island building in the South China Sea: detection of turbidity plumes and artificial islands using Landsat and MODIS data[J]. Scientific Reports, 6: 1-12. doi: 10.1038/s41598-016-0001-8
[27]	Benfield S L, Guzman H M, Mair J M, et al.2007. Mapping the distribution of coral reefs and associated sublittoral habitats in Pacific Panama: a comparison of optical satellite sensors and classification methodologies[J]. International Journal of Remote Sensing, 28(22): 5047-5070. doi: 10.1080/01431160701258062
[28]	Botha E J, Brando V E, Anstee J M, et al.2013. Increased spectral resolution enhances coral detection under varying water conditions[J]. Remote Sensing of Environment, 131: 247-261. doi: 10.1016/j.rse.2012.12.021
[29]	Burke L, Selig E, Spalding M. 2006. Reefs at risk in Southeast Asia [M]. Washington D.C., USA: World Resources Institute.
[30]	Chen T, Li S, Yu K, et al.2013. Increasing temperature anomalies reduce coral growth in the Weizhou Island, northern South China Sea[J]. Estuarine, Coastal and Shelf Science, 130: 121-126. doi: 10.1016/j.ecss.2013.05.009
[31]	Chen T, Yu K, Shi Q, et al.2009. Twenty-five years of change in scleractinian coral communities of Daya Bay (northern South China Sea) and its response to the 2008 AD extreme cold climate event[J]. Chinese Science Bulletin, 54(12): 2107-2117. doi: 10.1007/s11434-009-0007-8
[32]	Duan Y, Liu Y, Li M, et al.2016. Reefs survey of the Nansha Islands based on Landsat 8 OLI images[J]. Acta Oceanologica Sinica, 35: 11-19.
[33]	Goodman J A, Ustin S L.2007. Classification of benthic composition in a coral reef environment using spectral unmixing[J]. Journal of Applied Remote Sensing, 1(1): 341-353. doi: 10.1117/1.2815907
[34]	Graham N A, McClanahan T R, MacNeil M A, et al.2008. Climate warming, marine protected areas and the ocean-scale integrity of coral reef ecosystems[J]. PLoS One, 3(8): 1-9. doi: 10.1371/journal.pone.0003039 pmid: 18728776
[35]	Hochberg E J, Atkinson M J.2003. Capabilities of remote sensors to classify coral, algae, and sand as pure and mixed spectra[J]. Remote Sensing of Environment, 85(2): 174-189. doi: 10.1016/S0034-4257(02)00202-X
[36]	Hoegh-Guldberg O, Mumby P, Hooten A, et al.2007. Coral reefs under rapid climate change and ocean acidification[J]. Science, 318(5857): 1737-1742. doi: 10.1126/science.1152509
[37]	Hsu M K, Liu A K, Zhao Y, et al.2008. Satellite remote sensing of Spratly Islands using SAR[J]. International Journal of Remote Sensing, 29(21): 6427-6436. doi: 10.1080/01431160802175405
[38]	Knudby A, LeDrew E, Newman C.2007. Progress in the use of remote sensing for coral reef biodiversity studies[J]. Progress in Physical Geography, 31(4): 421-434.
[39]	Kutser T, Dekker A G, Skirving W.2003. Modeling spectral discrimination of Great Barrier Reef benthic communities by remote sensing instruments[J]. Limnology and Oceanography, 48(1): 497-510. doi: 10.4319/lo.2003.48.1_part_2.0497
[40]	Li S, Yu K, Chen T, et al.2011. Assessment of coral bleaching using symbiotic zooxanthellae density and satellite remote sensing data in the Nansha Islands, South China Sea[J]. Chinese Science Bulletin, 56(10): 1031-1037. doi: 10.1007/s11434-011-4390-6
[41]	Liu H, Yao Y, Deng H.2011. Geological and geophysical conditions for potential natural gas hydrate resources in southern South China Sea waters[J]. Journal of Earth Science, 22: 718-725. doi: 10.1007/s12583-011-0222-5
[42]	Maina J, Venus V, McClanahan T R, et al.2008. Modelling susceptibility of coral reefs to environmental stress using remote sensing data and GIS models[J]. Ecological Modelling, 212(3-4): 180-199. doi: 10.1016/j.ecolmodel.2007.10.033
[43]	Mumby P J, Edwards A J.2002. Mapping marine environments with IKONOS imagery: Enhanced spatial resolution can deliver greater thematic accuracy[J]. Remote Sensing of Environment, 82(2-3): 248-257. doi: 10.1016/S0034-4257(02)00041-X
[44]	Mumby P J, Skirving W, Strong A E, et al.2004. Remote sensing of coral reefs and their physical environment[J]. Marine Pollution Bulletin, 48(3-4): 219-228. doi: 10.1016/j.marpolbul.2003.10.031 pmid: 14972573
[45]	Roelfsema C M, Phinn S R.2010. Integrating field data with high spatial resolution multispectral satellite imagery for calibration and validation of coral reef benthic community maps[J]. Journal of Applied Remote Sensing, 4(1): 1-28 . doi: 10.1117/1.3430107
[46]	Rosenberg D, Chung C.2008. Maritime security in the South China Sea: Coordinating coastal and user state priorities[J]. Ocean Development & International Law, 39(1): 51-68. doi: 10.1080/00908320701641602
[47]	Strong A E, Liu G, Skirving W, et al.2011. NOAA's Coral Reef Watch program from satellite observations[J]. Annals of GIS, 17(2): 83-92. doi: 10.1080/19475683.2011.576266
[48]	Trung N N.2012. The gas hydrate potential in the South China Sea[J]. Journal of Petroleum Science and Engineering, 88: 41-47. doi: 10.1016/j.petrol.2012.01.007
[49]	Wang J, Li M, Liu Y, et al.2014. Safety assessment of shipping routes in the South China Sea based on the fuzzy analytic hierarchy process[J]. Safety Science, 62: 46-57. doi: 10.1016/j.ssci.2013.08.002
[50]	Webb A P, Kench P S.2010. The dynamic response of reef islands to sea-level rise: Evidence from multi-decadal analysis of island change in the Central Pacific[J]. Global and Planetary Change, 72(3): 234-246. doi: 10.1016/j.gloplacha.2010.05.003
[51]	Yamano H, Shimazaki H,Matsunaga T, et al.2006. Evaluation of various satellite sensors for waterline extraction in a coral reef environment: Majuro Atoll, Marshall Islands[J]. Geomorphology, 82(3): 398-411. doi: 10.1016/j.geomorph.2006.06.003
[52]	Yu K.2012. Coral reefs in the South China Sea: Their response to and records on past environmental changes[J]. Science China Earth Sciences, 55(8): 1217-1229. doi: 10.1007/s11430-012-4449-5
[53]	Zheng C, Zhuang H, Li X, et al.2011. Wind energy and wave energy resources assessment in the East China Sea and South China Sea[J]. Science China Technological Sciences, 55(1): 163-173.

地理信息技术支撑下的南海岛礁资源环境研究进展与展望

Progress and prospects on coral reefs research in the South China Sea based on the application of geographic information technologies

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