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An Arcgis Seabed Characterization Toolbox Developed For Investigating Benthic Habitats

机译:开发了用于调查底栖生境的Arcgis海底特征化工具箱

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Using data sets collected north of San Francisco Bay (CA) an ArcGIS classification toolset was developed using supervised image classification tools to characterize potential shallow marine benthic habitats. First-derivative images and a topographic algorithm, called Bathymetric Position Index were created from the bathymetry data set using ArcGIS Spatial Analyst tools. Backscatter intensity was also analyzed by creating training samples based on the collected sediment samples and then applying multivariate statistical tools to delinate textural classes. The data collected revealed a rugged and complex seafloor and imaged in detail basement and bedrock outcrops, sand and gravel bedforms, and flat sediment covered seabed.
机译:利用从旧金山湾(CA)北部收集的数据集,开发了ArcGIS分类工具集,该工具集使用监督图像分类工具来表征潜在的浅海底栖生境。使用ArcGIS Spatial Analyst工具从测深数据集中创建了一阶导数图像和一种地形算法,称为测深位置索引。还通过基于收集的沉积物样本创建训练样本,然后应用多元统计工具来简化纹理类别,来分析反向散射强度。收集的数据显示出崎a而复杂的海底,并对地下室和基岩露头,沙子和砾石床形以及平坦的沉积物覆盖的海床进行了详细成像。

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