Habitat Classification of Temperate Marine Macroalgal Communities Using Bathymetric LiDAR

Remote Sensing

Richard Zavalas¹  Daniel Ierodiaconou¹  David Ryan²  Alex Rattray¹ 

[1] Faculty of Science, Engineering and Built Environment, School of Life & Environmental Sciences, Deakin University, P.O. Box 423, Warrnambool 3280, Australia; E-Mails:;Worley Parsons, 250 St Georges Terrace, Perth 6000, Australia; E-Mail:

关键词: LiDAR;    subtidal macroalgae;    coastal;    habitat mapping;    exposed coast;    bathymetry;    reflectance;    groundtruth video;   

DOI  :  10.3390/rs6032154

来源: mdpi

【 摘 要 】

Here, we evaluated the potential of using bathymetric Light Detection and Ranging (LiDAR) to characterise shallow water (<30 m) benthic habitats of high energy subtidal coastal environments. Habitat classification, quantifying benthic substrata and macroalgal communities, was achieved in this study with the application of LiDAR and underwater video groundtruth data using automated classification techniques. Bathymetry and reflectance datasets were used to produce secondary terrain derivative surfaces (e.g., rugosity, aspect) that were assumed to influence benthic patterns observed. An automated decision tree classification approach using the Quick Unbiased Efficient Statistical Tree (QUEST) was applied to produce substrata, biological and canopy structure habitat maps of the study area. Error assessment indicated that habitat maps produced were primarily accurate (>70%), with varying results for the classification of individual habitat classes; for instance, producer accuracy for mixed brown algae and sediment substrata, was 74% and 93%, respectively. LiDAR was also successful for differentiating canopy structure of macroalgae communities (i.e., canopy structure classification), such as canopy forming kelp versus erect fine branching algae. In conclusion, habitat characterisation using bathymetric LiDAR provides a unique potential to collect baseline information about biological assemblages and, hence, potential reef connectivity over large areas beyond the range of direct observation. This research contributes a new perspective for assessing the structure of subtidal coastal ecosystems, providing a novel tool for the research and management of such highly dynamic marine environments.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland