Volume Change Estimation of Underwater Structures Using 2-D Sonar Data

Sonar sensors are an important source of data for understanding underwater environments because the sound is invariant to water turbidity, as well as illumination condition changes. This work reconstructs the surface of underwater structures and quantifies the spatial variations between multiple readings using data acquired by a 2-D mechanical scanning imaging sonar (MSIS), attached to a remotely operated vehicle (ROV). The proposed methodology is general for any underwater structure, but its main application is the melting process estimation in submerged frontal portions of glaciers. This comes up as motivation since ablation processes occurring on glacier fronts remain as one of the main inaccurate components of the glacier mass balance. The quantification of this phenomenon is crucial for estimating the consequences of glacier melting to sea level rise. Two methods are proposed to estimate volume change using sonar data. A reference plane-based system (RPBS) uses a plane behind the comparison surfaces as a reference. Moreover, the sensor line-based system (SLBS) uses the movement line of the sensor during the data acquisition process. We evaluated the proposed methods using simulated and real data acquired with an ROV with MSIS. Results show the feasibility of both methods to estimate the volume change of underwater structures.