Insights into environmental drivers of acoustic angular response using a self-organising map and hierarchical clustering

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• 作者：James Daniell ; Justy Siwabessy ; Scott Nichol ; Brendan Brooke
• 刊名：Geo-Marine Letters
• 出版年：2015
• 出版时间：October 2015
• 年：2015
• 卷：35
• 期：5
• 页码：387-403
• 全文大小：10,783 KB
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• 作者单位：James Daniell (1) (3)
  Justy Siwabessy (2)
  Scott Nichol (2)
  Brendan Brooke (2)
  
  1. James Cook University, Townsville, QLD, 4811, Australia
  3. College of Science Technology and Engineering, James Cook University, Townsville, QLD, 4811, Australia
  2. Geoscience Australia, GPO Box 378, Canberra, ACT, 2601, Australia
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geology
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-1157

文摘

Acoustic backscatter from the seafloor is a complex function of signal frequency, seabed roughness, grain size distribution, benthos, bioturbation, volume reverberation, and other factors. Angular response is the variation in acoustic backscatter with incident angle and is considered be an intrinsic property of the seabed. An unsupervised classification technique combining a self-organising map (SOM) and hierarchical clustering was used to create an angular response facies map and explore the relationships between acoustic facies and ground truth data. Cluster validation routines indicated that a two cluster solution was optimal and separated sediment dominated environments from mixtures of sediment and hard ground. Low cluster separation limited cluster validation routines from identifying fine cluster structure visible with an AR density plot. Cluster validation, aided by a visual comparison with an AR density plot, indicated that a 14 cluster solution was also a suitable representation of the input dataset. Clusters that were a mixture of hard and unconsolidated substrates displayed an increase in backscatter with an increase in the occurrence of hard ground and highlighted the sensitivity of AR curves to the presence of even modest amounts of hard ground. Remapping video observations and sediment data onto the SOM matrix is innovative and depicts the relationship between ground truth data and cluster structure. Mapping environmental variables onto the SOM matrix can show broad trends and localised peaks and troughs and display the variability of ground truth data within designated clusters. These variables, when linked to AR curves via clusters, can indicate how environmental factors influence the shape of the curves. Once these links are established they can be incorporated into improved geoacoustic models that replicate field observations.