\section{Conclusions}\label{conclusions}

Multi-sensor hydrography enables a wide array of techniques which
involve collecting surveys simultaneously using a selection of sensors
that produce different but comparable bathymetric data sets. MBARI has
produced an ROV payload to match the demands of scientists. This
multi-sensor platform produces distinct but correlated datasets at high
enough resolution to study detailed processes within a 100-m by 100-m
observed area over a 12-hr mission.

By conducting fine scale surveys in a repeatable and controlled manner,
we have proven that excellent topographic maps can be generated by this
platform using either sonar, lidar, or photogrammetry. These data sets
vary in resolution, but comparison between the data are possible,
leading to significant scientific observations. The examples of repeat
mapping can certainly be applied to more fields than the
geomorphological one presented in Section \ref{repeat-mapping}. The
benthic clam community shown in Figure \ref{fig:clams} has in fact been
mapped over several years, and change in the clam community is evident.
The quantitative measurements obtained from the lidar and multibeam
sonar provide an effective way to measure deposition rates. Small change
repeat measurements would also have applications in the commercial
sector as well, most notably pipeline surveys conducted by the oil and
gas industry.

The technique of soft matter detection enabled by comparing lidar and
sonar data validates the design choice to place multiple bathymetric
sensors next to each other on this platform. The underlying physics of
those measurements can lead to a better understanding of the
environment. The ability to isolate matter with similar acoustic
impedance to seawater has applications past the example of benthic
ecology presented in Section \ref{benthic-organism-detection}. Possible
studies of soft animal bio-fouling could be possible. Overall, these
examples all validate that study over these scales can produce
quantitative measures of change and state for systems difficult to
characterize.