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The Assessment of Required Hydrographic Data for Remote Sensing Bathymetry
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Mojde Ebrahimi kia *   , Mohammad Saadat Seresht |
| University of Tehran |
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Abstract: (5315 Views) |
| Today, depth mapping of coastal and waterfront areas is necessary for various aims such as shipping, dredging, underwater piping, hazardous area detection, hydrological studies, material mapping of water bed, information collection from marine settlements for environment preservation, military and engineering applications. Periodical depth mapping of wide water areas by classic hydrographic method (via ecosounder) is expensive and time consuming. Therefore, due to high capability of remote sensing in rapid data collection from wide area, it can be an effective and proper complementary method for this purpose. Attention to this issue is more important for our country which has long shorelines. At this paper two physical and mathematical bathymetric methods are evaluated. The first method is based on physical behaviour of light attenuation in water column while the second method is a numerical fitting between image gray levels and according water depths by means of artificial neural network (ANN). Our initial experiments show that although the first method has physical meaning but the second method is more accurate and simpler too. Both methods require a set of known hydrographic depthes as calibration data. Therefore, our next experiments try to answer two principal questions: how much can reduce the hydrographic filed operations in remote sensing bathymetry and how much is the accuracy of waterbed topography extracting from satelite images? The result of our experiments showes that introducing of only one hydrographic line perpendicular to coastline as calibration data to ANN method is able to produce satisfied result with depth accuracy RMSE 1.6m and correlation coefficient 92%. |
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| Keywords: Bathymetry, light attenuation physic, Satellite images. |
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Full-Text [PDF 1643 kb]
(1805 Downloads)
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Type of Study: Research |
Received: 2015/07/11 | Accepted: 2015/07/11 | Published: 2015/07/11
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