Benthic monitoring with robotic platforms — The experience of Australia

Abstract

Australias Integrated Marine Observing System (IMOS) has a strategic focus on the impact of major boundary currents on continental shelf environments, ecosystems and biodiversity. To improve our understanding of natural, climate change, and human-induced variability in shelf environments, the IMOS Autonomous Underwater Vehicle (AUV) facility has been charged with generating physical and biological observations of benthic variables that cannot be cost-effectively obtained by other means. Starting in 2010, the IMOS AUV facility began collecting precisely navigated benthic imagery using AUVs at selected reference sites on Australias shelf. This observing program capitalizes on the unique capabilities of AUVs that have allowed repeated visits to the reference sites, providing a critical observational link between oceanographic and benthic processes. This paper provides a brief overview of the relevant capabilities of the AUV facility, the design of the IMOS benthic sampling program, and some preliminary results. We also report on some of the challenges and potential benefits to be realized from a benthic observation system that collects several TB of geo-referenced stereo imagery a year. This includes collaborative semi-automated image analysis, clustering and classification, large scale visualization and data mining, and lighting correction for change detection and characterization. We also mention some of the lessons from operating an AUV-based monitoring program and future work in this area.

Changes in deep reef benthic community composition across a latitudinal and environmental gradient in temperate Eastern Australia

“…Largely because deep-water environments are not accessible using traditional underwater sampling techniques such as visual surveys by SCUBA divers (Roberts & Davis 1996, Pizarro et al 2013, the distribution and ecology of deep reef communities including habitat-forming species remain poorly understood and are much less studied than their shallow coral reef and kelp-bed counterparts (Pizarro et al 2013). Comprehensive quantitative research on deep er reef communities has only emerged relatively recently with the development of remote sampling technologies such as towed videos or autonomous underwater vehicles (AUVs), which can routinely survey benthic environments by collecting both physical measurements and photographic images of seafloor communities (Schlacher et al 2010, Pizarro et al 2013.…”

“…Comprehensive quantitative research on deep er reef communities has only emerged relatively recently with the development of remote sampling technologies such as towed videos or autonomous underwater vehicles (AUVs), which can routinely survey benthic environments by collecting both physical measurements and photographic images of seafloor communities (Schlacher et al 2010, Pizarro et al 2013. Increasingly, AUVs are recognised as a valuable and effective tool to repeatedly survey and detect changes in community composition, abundance and distribution of benthic populations (Ling et al 2016).…”

“…A recent study on a reef at moderate depth (25−30 m) showed that AUV imagery detected space−time variability in the abundance of mobile macro-invertebrates in a manner comparable to traditional SCUBA diver surveys (Ling et al 2016). While the number of studies on Australia's deeper (> 30 m) reef communities has increased over the last decade with the emergence of these novel sampling technologies (Pizarro et al 2013), understanding of the structure and distribution of these communities remains limited. In temperate eastern Australia, despite dramatic changes in shallow reef habitat and community structure due to ongoing and rapid climate-driven ocean changes (Ling et al 2009, Johnson et al 2011, Marzloff et al 2013, 2016b, baseline information is lacking to monitor and predict the responses of deep reef communities to large-scale ocean changes.…”

“…Although underwater imagery now provides a unique way to study and monitor deeper ocean ecosystems (Schlacher et al 2010, Pizarro et al 2013, accurate, consistent and detailed description of the biota from seafloor imagery remains challenging, time-consuming, and subject to human error (Althaus et al 2015). Identification of invertebrate habitat-forming species based only on underwater imagery is limited and can rarely be performed at the species level.…”

Graph theory approach for match reduction in image mosaicing

“…This increases the need for methods that combine several overlapping images into a single image that gives an overall perspective of the area of interest. These methods are referred to as image mosaicing, and the final images are referred to as mosaics, which are among the most highly valuable sources of information in various applications such as geological surveys [5,6], archaeological surveys [7], ecological studies [8,9], environmental damage assessments [10], and the detection of temporal changes in the environment [11,12]. Therefore, creating optical maps establishes permanent visual records of areas of interest, which are essential inputs for different scientific communities.…”