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                                       Details for article 4 of 9 found articles
  Detection of barrels and waste disposal sites on the seafloor using spatial variability analysis on sidescan sonar and bathymetry images
Title: Detection of barrels and waste disposal sites on the seafloor using spatial variability analysis on sidescan sonar and bathymetry images
Author: Chavez, Pat S.
Karl, Herman A.
Appeared in: Marine geodesy
Paging: Volume 18 (1995) nr. 3 pages 197-211
Year: 1995-07
Contents: The availability and use of remotely sensed digital image data have increased rapidly over the last two decades. One application where remotely sensed image data are a critical component is environmental analysis and monitoring. In our case it involves using sidescan sonar images to detect and map the location of 55-gal drums that were disposed of near the Farallon Islands (about 50 nautical miles west of San Francisco). About 48,000 drums containing low-level radioactive waste were dumped in water depths ranging from 100 to 2500 m covering 1400 km2. The high number of drums littering the seafloor and the rather large area involved makes remotely sensed image data one of the few promising tools to detect and map drum locations. In our analysis, sidescan sonar images collected by the SeaMarc IA and having about 1-m pixel resolution were used. Spatial variability analysis (SVA) and other digital processing procedures were applied to the sidescan sonar images to automatically detect and map the location of the barrels on the seafloor. Spatial amplitude index (SAI) and spatial variability index (SVI) images at three different scales were generated using high-pass spatial filters. The resulting multispatial data set was used to study and analyze the digital image based on its spatial characteristics, as well as its backscatter/spectral information. The objective was to detect potential “targets” characterized by a strong vertical spatial component and a backscatter amplitude that is higher than the surrounding background. In most cases, the targets (barrels) that we were mapping had a relatively strong backscatter amplitude as compared to the background, which generates a relatively large SAI value. In areas where the backscatter difference or contrast between the target and the surrounding background was not sufficiently large, we had to employ other techniques, such as preprocessing before applying the spatial variability analysis. Our results show good correlation in areas where barrels have been located by using underwater cameras. The large effort required to locate thousands of barrels points to a pressing need to use as much information as possible to help identify potential disposal sites. Part of this project involves investigating various data sets and ways they can be used to help select disposal sites. This article shows a simple example of what can be done using only a digital elevation model (DEM) and SVA.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften

                             Details for article 4 of 9 found articles
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