Bathymetry and bottom albedo retrieval using Hyperion: a case study of Thitu Island and reef

Zhen Liu

doi:10.1007/s00343-013-2287-8

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Bathymetry and bottom albedo retrieval using Hyperion: a case study of Thitu Island and reef

Updated：2023-05-16

- Bathymetry and bottom albedo retrieval using Hyperion: a case study of Thitu Island and reef
- Journal of Oceanology and Limnology Vol. 31, Issue 6, Pages: 1350-1355(2013)
- Affiliations：
  
  College of Information Science and Engineering Ocean University of China
- Author bio：
- Funds：
- DOI：10.1007/s00343-013-2287-8
  CLC：
- Online First：06 November 2013，
  
  Published：2013
- Accepted：
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Liu, Z. Bathymetry and bottom albedo retrieval using Hyperion: a case study of Thitu Island and reef., Chin. J. Ocean. Limnol. 31, 1350–1355 (2013). https://doi.org/10.1007/s00343-013-2287-8
DOI：

Liu, Z. Bathymetry and bottom albedo retrieval using Hyperion: a case study of Thitu Island and reef., Chin. J. Ocean. Limnol. 31, 1350–1355 (2013). https://doi.org/10.1007/s00343-013-2287-8 DOI：

摘要

Abstract

The Spratly (Nansha) Islands in the South China Sea have considerable economic and important militarily strategic status. Ocean color remote sensing is an effective mean of surveying and research and especially it is useful for areas that are difficult to access

such as Thitu Island and its reef in the Spratly Islands. The Hyper-spectral Optimization Process Exemplar (HOPE) model

developed by Lee et al. (1999) is a rapid and robust bathymetry method that uses hyper-spectral remote sensing. In this study

using Hyperion hyper-spectral sensor data and HOPE

we derive bathymetry and bottom albedo measurements around Thitu Island and its reef. We compare the distribution of bottom depths from C-MAP with that derived from the Hyperion data. The retrieved bathymetry results correlate well with the distribution obtained from the bathymetry contour from 2.0 to 20 m. The average difference between Hyperion and C-MAP for two selected transects was 17.1% (n=59

R=0.848

RMSE=2.342) and 10.9% (n=59

R 2=0.834

RMSE=0.463). The retrieved bottom albedo is homogeneous in the lagoon and significantly non-homogeneous around the lagoon. These results indicate that HOPE could be very useful for bathymetry studies for the islands of the South China Sea.

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references

Adler-Golden S M, Acharya P K, Berk A, Matthew M W, Gorodetzky D. 2005. Remote bathymetry of the littoral zone from AVIRIS. LASH, and QuickBird imagery. IEEE Transactions on Geoscience and Remote Sensing, 43(2): 337–347.

Brando V E, Ansteea J M, Wettlea M, Dekkera A G, Phinnb S R, Roelfsemab C. 2009. A physics based retrieval and quality assessment of bathymetry from suboptimal hyperspectral data. Remote Sensing of Environment, 113(4): 755–770.

Bricaud A, Morel A, Prieur L. 1981. Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains. Limnology and Oceanography, 26(1): 43–53.

Goodman J, Ustin S L. 2007. Classification of benthic composition in a coral reef environment using spectral unmixing. Journal of Applied Remote Sensing, 1(1): 011501-1–011501-17.

Giardino C, Bartoli M, Candiani G, Bresciani M, Pellegrini L. 2007. Recent changes in macrophyte colonisation patterns: an imaging spectrometry-based evaluation of southern Lake Garda (northern Italy). Journal of Applied Remote Sensing, 1(1): 011509.

Gregg W W, Carder K L. 1990. A simple spectral solar irradiance model for cloudless maritime atmospheres. Limnology and Oceanography, 35(8): 1 657–1 675.

Klonowski W M, Fearns P R C S, Lynch M J. 2007. Retrieving key benthic cover types and bathymetry from hyperspectral imagery. Journal of Applied Remote Sensing, 1(1): 011505-1–011505-21.

Lee Z P, Carder K L, Mobley C D, Steward R G, Patch J S. 1998. Hyperspectral remote sensing for shallow waters. 1. A semianalytical model. Applied Optics, 37(27): 6 329–6 338.

Lee Z P, Carder K L, Mobley C D, Steward R G, Patch J S. 1999. Hyperspectral remote sensing for shallow waters: 2. Deriving bottom depths and water properties by optimization. Applied Optics, 38(18): 3 831–3 843.

Lee Z P, Carder K L, Chen R F, Peacock T G. 2001. Properties of the water column and bottom derived from AVIRIS data. Journal of Geophysical Research, 106(C6): 11 639–11 652.

Lee Z P, Casey B, Parsons A R, Goode W A, Weidemann A D, Arnone R A. 2005. Bathymetry of shallow coastal regions derived from space-borne hyperspectral sensor. Proceedings of OCEANS MTS/IEEE, 3: 2 160–2 170.

Lee Z P, Arnone R A, Casey B, Davis C O, Gao B C, Montes M J, Weidemann A D, Parsons A R, Goode W A, Dye J. 2007. Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform. Journal of Applied Remote Sensing, 1(1): 011502.

Liu A K, Hotta K, Hsu M K. 2007. Satellite Remote Sensing of Spratly Islands. Tingmao Publish Company, Taipei, Taiwan. p.73.

McIntyre M L, Naar D F, Carder K L, Donahue B T, Mallinson D J. 2006. Coastal bathymetry from hyperspectral remote sensing data: comparisons with high resolution multibeam bathymetry. Marine Geophysical Researches, 27(2): 128–136.

Reinersman P, Carder K L, Chen F R. 1998. Satellite-sensor calibration verification with the cloud-shadow method. Applied Optics, 37(24): 5 541–5 549.

Roesler C S, Perry M J, Carder K L. 1989. Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters. Limnology and Oceanography, 34(8): 1 510–1 523.

Sathyendranath S, Prieur L, Morel A. 1989. A three component model of ocean color and its application to remote sensing of phytoplankton pigments in coastal waters. International Journal of Remote Sensing, 10(8): 1 373–1 394.

Su H, Liu H, Heyman W D. 2008. Automated derivation of bathymetric information from multi-spectral satellite imagery using a non-linear inversion model. Marine Geodesy, 31(4): 281–298

Yamano H, Tamura M, Kunii Y, Hidaka M. 2003. Hyperspectral remote sensing and radiative transfer simulation as a tool for monitoring coral reef health. Marine Technology Society Journal, 36(1): 4–13.

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