Survey of reefs based on Landsat 8 operational land imager (OLI) images in the Nansha Islands, South China Sea

DUAN Yuewei; LIU Yongxue; LI Manchun; ZHOU Minxi; YANG Yuhao

doi:10.1007/s13131-016-0898-6

Article Contents

Article Navigation > Acta Oceanologica Sinica > 2016 > 35(10): 11-19

DUAN Yuewei, LIU Yongxue, LI Manchun, ZHOU Minxi, YANG Yuhao. Survey of reefs based on Landsat 8 operational land imager (OLI) images in the Nansha Islands, South China Sea[J]. Acta Oceanologica Sinica, 2016, 35(10): 11-19. doi: 10.1007/s13131-016-0898-6

Citation:

DUAN Yuewei, LIU Yongxue, LI Manchun, ZHOU Minxi, YANG Yuhao. Survey of reefs based on Landsat 8 operational land imager (OLI) images in the Nansha Islands, South China Sea[J]. Acta Oceanologica Sinica, 2016, 35(10): 11-19. doi: 10.1007/s13131-016-0898-6

Citation:

PDF( 48884 KB)

Survey of reefs based on Landsat 8 operational land imager (OLI) images in the Nansha Islands, South China Sea

doi: 10.1007/s13131-016-0898-6

1.
Department of Geographic Information Science, Nanjing University, Nanjing 210023, China
2.
Department of Geographic Information Science, Nanjing University, Nanjing 210023, China;Collaborative Innovation Center for the South China Sea Studies, Nanjing University, Nanjing 210023, China

Received Date: 2015-12-20
Rev Recd Date: 2016-05-05

Abstract

Abstract

A detailed survey of the reefs in the Nansha Islands' sea that are of strategic importance is conducive to their future development. In this study, a total of 50 Landsat 8 operational land imager (OLI) images were used to analyze the geological features and spectral characteristics of the Nansha reefs. The exposed islands/sandbanks, reef flats and sub-tidal reefs were identified with the near-infrared band, the red and green bands, and the blue band, respectively. Based on the relationships among various characteristics and bands illustrated in the OLI images, the maximum between-cluster variance threshold algorithm (OTSU method) and the mathematical morphology were employed to extract characteristic parameters of the spatial geometry of the reefs from top to bottom, which were subsequently operated by a series of post-processing methods such as vectorization, simplification and topological analysis. Among the 132 standalone reefs and 16 atolls that are identified in the study, four reefs have yet to be named in the Standard Names of Various Islands in the South China Sea and the website Nansha Islands Online (http://www.nansha.org/). Another 24 ones are exposed to the atmosphere even during high tides. Taiping Island with an area of 0.57 km² represents the largest exposed geological feature. This study demonstrated the applicability of medium-resolution satellite images to derive the coral reef information effectively and thus provided information for the related departments that are responsible to manage the coast. An improved resolution of multispectral bands with the panchromatic band in higher spatial resolution (15 m for OLI image) is expected to provide an optimum satellite based approach to map marine habitats.
- remote sensing,
- coral reefs,
- OLI imagery,
- Nansha Islands

FullText(HTML)

References(25)

References

Andréfouët S, Kramer P, Torres-Pulliza D, et al. 2003. Multi-site eval-uation of IKONOS data for classification of tropical coral reef environments. Remote Sensing of Environment, 88(1-2):128-143

Brock J C, Wright C W, Clayton T D, et al. 2004. LIDAR optical rugos-ity of coral reefs in Biscayne National Park, Florida. Coral Reefs, 23(1):48-59

Call K A, Hardy J T, Wallin D O. 2003. Coral reef habitat discrimina-tion using multivariate spectral analysis and satellite remote sensing. International Journal of Remote Sensing, 24(13):2627-2639

Chen Jianyu, Mao Zhihua, Zhang Huaguo, et al. 2007. Analysis on coral reefs mapping using SPOT5 at Dongsha Atoll. Haiyang Xuebao (in Chinese), 29(3):51-57

Clayton D G. 1971. Algorithm AS 46:Gram-schmidt orthogonaliza-tion. Journal of the Royal Statistical Society. Series C-Applied Statistics, 20(3):335-338

Gao Junguo, Liu Baoyin. 2009. The Nansha Islands Spatial Informa-tion Fusion Analysis and Warning:Reefs Development Military Regional Warning System (in Chinese). Beijing:China Ocean Press, 1-3

Hochberg E J, Atkinson M J. 2003. Capabilities of remote sensors to classify coral, algae, and sand as pure and mixed spectra. Re-mote Sensing of Environment, 85(2):174-189

Hochberg E J, Atkinson M J, Andréfouët S. 2003. Spectral reflectance of coral reef bottom-types worldwide and implications for cor-al reef remote sensing. Remote Sensing of Environment, 85(2):159-173

Holden H, LeDrew E. 1998. Spectral discrimination of healthy and non-healthy corals based on cluster analysis, principal com-ponents analysis, and derivative spectroscopy. Remote Sensing of Environment, 65(2):217-224

Holden H, LeDrew E. 1999. Hyperspectral identification of coral reef features. International Journal of Remote Sensing, 20(13):2545-2563

Hu Leiqiu, Liu Yalan, Ren Yuhuan, et al. 2010. Research on the ex-traction method of coral reef at Spratly Islands using SPOT5. Remote Sensing Technology and Application (in Chinese), 25(4):493-501

Kutser T, Dekker A G, Skirving W. 2003. Modeling spectral discrimin-ation of Great Barrier Reef benthic communities by remote sensing instruments. Limnology and Oceanography, 48(1):497-510

Li Cunjun, Liu Liangyun, Wang Jihua, et al. 2004. Comparison of two methods of fusing remote sensing images with fidelity of spec-tral information. Journal of Image and Graphics (in Chinese), 9(11):1376-1385

Lim A, Hedley J D, LeDrew E, et al. 2009. The effects of ecologically determined spatial complexity on the classification accuracy of simulated coral reef images. Remote Sensing of Environment, 113(5):965-978

Lubin D, Li W, Dustan P, et al. 2001. Spectral signatures of coral reefs:Features from space. Remote Sensing of Environment, 75(1):127-137

Mumby P J, Green E P, Edwards A J, et al. 1997. Coral reef habitat mapping:how much detail can remote sensing provide?. Mar-ine Biology, 130(2):193-202

Mumby P J, Skirving W, Strong A E, et al. 2004. Remote sensing of cor-al reefs and their physical environment. Marine Pollution Bul-letin, 48(3-4):219-228

Palandro D, Andréfouët S, Muller-Karger F E, et al. 2003. Detection of changes in coral reef communities using Landsat-5 TM and Landsat-7 ETM+ data. Canadian Journal of Remote Sensing, 29(2):201-209

Pan Chunmei, Ding Qian, Cao Wenyu. 2002. TM image analysis of is-land reef topography of The Nansha Islands. Remote Sensing for Land & Resources (in Chinese), (2):34-37, 60

Smith V E, Rogers R, Reed L. 1975. Automated mapping and invent-ory of Great Barrier Reef zonation with LANDSAT data. In:OCEAN 75 Conference. San Diego, CA:IEEE, 775-780

Sun Zongxun, Zhan Wenhuan, Zhu Junjiang. 2004. Rockmass struc-ture and engineering geological zones of coral reefs Nansha Is-lands of South China Sea. Journal of Tropical Oceanography (in Chinese), 23(3):11-20

Yu Kefu. 2000. The recent fifty years high-resolution climate of Nan-sha Islands recorded in reef coral (in Chinese)[dissertation]. Guangzhou:Guangzhou Institute of Geochemistry, Chinese Academy of Sciences

Zhao Ziyu, Shen Sanwei. 2011. The rise and hold, highlighting the strategic position of South China. National Think Tank (in Chinese), (1):7-12

Zou Yarong, Liang Chao, Zhu Haitian. 2012. Research about monitor-ing the development status of coral reefs based on QuickBird data. Haiyang Xuebao (in Chinese), 34(2):57-62

Zou Yarong, Lin Mingsen, Wang Hua, et al. 2006. Study on high resol-ution image classification for Dongsha Island based on fuse in-formation. Haiyang Xuebao (in Chinese), 28(1):56-61

Relative Articles

Supplements(0)

Cited By

Proportional views