<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Paul E. Grams</dc:contributor>
  <dc:contributor>Matthew A. Kaplinski</dc:contributor>
  <dc:creator>Daniel D. Buscombe</dc:creator>
  <dc:date>2017</dc:date>
  <dc:description>&lt;p&gt;&lt;span&gt;Multibeam acoustic backscatter has considerable utility for remote characterization of spatially heterogeneous bed sediment composition over vegetated and unvegetated riverbeds of mixed sand and gravel. However, the use of high-frequency, decimeter-resolution acoustic backscatter for sediment classification in shallow water is hampered by significant topographic contamination of the signal. In mixed sand-gravel riverbeds, changes in the abiotic composition of sediment (such as homogeneous sand to homogeneous gravel) tend to occur over larger spatial scales than is characteristic of small-scale bedform topography (ripples, dunes, and bars) or biota (such as vascular plants and periphyton). A two-stage method is proposed to filter out the morphological contributions to acoustic backscatter. First, the residual supragrain-scale topographic effects in acoustic backscatter with small instantaneous insonified areas, caused by ambiguity in the local (beam-to-beam) bed-sonar geometry, are removed. Then, coherent scales between high-resolution topography and backscatter are identified using cospectra, which are used to design a frequency domain filter that decomposes backscatter into the (unwanted) high-pass component associated with bedform topography (ripples, dunes, and sand waves) and vegetation, and the (desired) low-frequency component associated with the composition of sediment patches superimposed on the topography. This process strengthens relationships between backscatter and sediment composition. A probabilistic framework is presented for classifying vegetated and unvegetated substrates based on acoustic backscatter at decimeter resolution. This capability is demonstrated using data collected from diverse settings within a 386&amp;nbsp;km reach of a canyon river whose bed varies among sand, gravel, cobbles, boulders, and submerged vegetation.&lt;/span&gt;&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1002/2017JF004302</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>American Geophysical Union</dc:publisher>
  <dc:title>Compositional signatures in acoustic backscatter over vegetated and unvegetated mixed sand-gravel riverbeds</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>