Unified Geomorphological Analysis Workflows with Benthic Terrain Modeler

Shaun Walbridge,Dawn Wright,Noah Slocum,Marjean Pobuda

doi:10.3390/geosciences8030094

Abstract

High resolution remotely sensed bathymetric data is rapidly increasing in volume, but analyzing this data requires a mastery of a complex toolchain of disparate software, including computing derived measurements of the environment. Bathymetric gradients play a fundamental role in energy transport through the seascape. Benthic Terrain Modeler (BTM) uses bathymetric data to enable simple characterization of benthic biotic communities and geologic types, and produces a collection of key geomorphological variables known to affect marine ecosystems and processes. BTM has received continual improvements since its 2008 release; here we describe the tools and morphometrics BTM can produce, the research context which this enables, and we conclude with an example application using data from a protected reef in St. Croix, US Virgin Islands.

Highlights

The marine environment is under heavy pressure from a host of human activities, with a large portion of the system strongly impacted by anthropogenic threats [1]
To demonstrate Benthic Terrain Modeler (BTM)’s classification mapping capabilities, a subset of the light detection and ranging (LiDAR) bathymetry dataset shown in Figure 7 was classified using the Run All Model Steps tool
An accessible but powerful analysis framework is available by combining BTM and ArcGIS with the broader scientific software ecosystem in Python and R

Summary

Introduction

The marine environment is under heavy pressure from a host of human activities, with a large portion of the system strongly impacted by anthropogenic threats [1]. While satellite derived gravity data has increased the nominal resolution of global bathymetry data to 30 arc-seconds [3], and recent efforts have mapped global marine units [4], these data are unable to resolve finer-scale oceanic processes. Applications in seascape ecology, marine spatial planning, morphological evolution, and understanding human ocean uses require higher resolution data [5]. Habitat mapping is a first step to further our understanding of the ocean environment, and is typically informed by bathymetric gradients, which influence species abundance and distribution [6,7]. Geomorphic derivatives can be used to infer the effects of bathymetric gradients, increasing the value of limited data. Increased availability of bathymetric data has led to new methodologies to infer bathymetric gradients from geomorphic derivatives and map seafloor habitat [8].

Methods

Results

Conclusion