\section{Introduction}\label{introduction}

The Monterey Bay Aquarium Research Institute has established a core
technical roadmap in which the theme of visualizing the ocean is a vital
component. In many fields, imaging provides insights into the inner
workings of the environment under study. In the ocean, the methods of
imaging are limited by the harsh constraints of the environment.
Ship-based sonars provide data at varying scales, driven primarily by
water depth. Over the past fifteen years, improvements in autonomous
underwater vehicles (AUV) and sonar technologies have yielded AUVs
optimized for 1-m scale seafloor mapping at abyssal depths
\cite{ROB:ROB20191}\cite{Caress2008}. Autonomous underwater vehicles
(AUVs) can conduct hydrographic surveys with finer control and constant
altitudes in targeted areas. These vehicles are typically designed in
such a way to survey a large area per mission, limited by battery
duration. The availability of these higher definition mapping tools has
revealed a variety of seafloor features not seen before, and allowed for
measurement of seafloor changes associated with phenomena such as
submarine volcanic eruptions and sediment transport in canyons. These
features are often investigated by scientists from remotely operated
vehicle (ROV) platforms.

The problem we intend to address is that ROV-based surveys can be costly
and inefficient for tasks that extend beyond targeted sampling, without
providing quantitative assessments of the environment. ROV dives that
revisit areas for repeated surveys can also disturb the areas under
study, invalidating planned future surveys. Many ROVs are limited by
sensors that can visualize only the immediate area around the vehicle.
Specifically, we propose that there is a domain of surveys that span the
divide of traditional AUV-collected hydrographic data and the common
data collected during an ROV dive. These surveys cover areas in which
specialized systems are needed to detect minute change over practical
periods of time. This observational range has been characterized as a
survey covering a 100-m by 100-m area. Factors driving that size goal
are discussed in the description of the payload to follow in Section
\ref{payload-description}.

Our working group has taken the first steps by assembling and
integrating a set of observational tools aimed at collecting information
at resolutions no larger than 1-cm and as small as 1-mm. This is an
approach focused on developing the tools and data processing techniques
first. By testing first on an ROV, the gained knowledge can eventually
be used to better inform the design process of an autonomous platform
aimed at conducting surveys using this payload. The three primary data
collection tools are multibeam sonar, lidar, and stereo imagery.
Improved accuracy of the overall survey can be accomplished by merging
these data. Here some cases where more complex comparison of the data
can also yield unique observations are presented.

Light detection and ranging (lidar) has a growing role in underwater
research, both in topographic data collection as part of coastal
assessment, often coupled with other optical systems
\cite{doi:10.2112/SI53-001.1}. Merging these data with sonar data has
also occurred \cite{doi:10.1080/11035897.2015.1055513}
\cite{Foster2009BackscatterLidar}, resulting in comprehensive topography
needed for environmental assessment. These examples all discuss lidar
data gathered from airplane synthesized with multibeam sonar data to
create improved results. The challenge to move these solutions forward
is to package lidar for underwater use and to assemble a stable platform
that can collect these data coincidentally at the scales discussed.

In testing, each sensor has produced high quality and self-consistent
data fit for hydrographic survey operations. Surveys conducted with this
prototype system demonstrate the benefits for studying fine scale
changes in the seafloor. Section \ref{fine-scale-surveys} presents
detail regarding how these coincident surveys are conducted. Initial
comparison of the data sets will be discussed.

Other results show how progressive changes in seafloor morphology can be
quantified at this resolution. Specifically, we will discuss on how
repeat mapping (Section \ref{repeat-mapping}) techniques can yield
insights into long timescale changes in observed benthic environments,
highlighting a site in the Monterey Canyon.

By investigating the relationships between these concurrently collected
survey data, another observational technique has emerged. In Section
\ref{benthic-organism-detection}, a case is presented in which benthic
animals can be identified by subtracting acoustic map data from lidar
map data. Simultaneously, the photographic imagery allows animal health
to be assessed.
