# 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.