Calculating macroalgal height and biomass using bathymetric LiDAR and a comparison with surface area derived from satellite data in Nova Scotia, Canada
-
Tim Webster
Tim Webster is a research scientist with the Nova Scotia Community College’s Applied Research Group since 2000. He has an MSc from Acadia University and a PhD from Dalhousie University. He was the 2010 recipient of the Gulf of Maine Council Visionary Award and the 2017 Award of Distinction for geomatics in Nova Scotia. He has worked in the private sector for a GIS software developer prior to becoming a faculty member in remote sensing and GIS at NSCC’s Centre of Geographic Sciences (COGS). His focus includes topographic-bathymetric lidar for mapping, monitoring and modelling processes in the coastal zone.
,
Candace MacDonald
Candace MacDonald is a Research Associate with Nova Scotia Community College’s Applied Geomatics Research Group since 2010. She holds a BSc in Biology from Acadia University and an Advanced Diploma in Remote Sensing from NSCC’s Centre of Geographic Sciences. Ms. MacDonald is a remote sensing and GIS expert focusing on topographic-bathymetric lidar, multispectral satellite, and aerial imagery interpretation and analysis for widely varied purposes such as flood risk mapping, seaweed mapping, and detection of forgotten archaeological features. She is an expert in complex raster and spatial GIS analysis, and in the construction of maps and other visual products.
Kevin McGuigan is a Research Associate with Nova Scotia Community College’s Applied Geomatics Research Group since 2010. He holds a BSc in Geology from St. Francis Xavier University and an Advanced Diploma in Remote Sensing from NSCC’s Centre of Geographic Sciences. He specialises in aerial lidar data research, low altitude aerial photography, and hydrodynamic modelling. He’s completed research projects involving high- resolution 1D-2D hydrodynamic flood modelling for various coastal and inland regions throughout the Maritimes. His recent research involves aerial bathymetric lidar feature recognition, waveform visualisation, and hydrological network mapping automation.
Nathan Crowell is a Research Associate with Nova Scotia Community College’s Applied Geomatics Research Group since 2009. He has an MSc in Applied Geomatics from Acadia University, an advanced diploma in Remote Sensing from NSCC’s Centre of Geographic Sciences, and a BSc in Biology from Acadia University. He specialises in lidar and multibeam sonar data collection and hydrodynamic modelling to support ecosystem and flood-risk management.
Jean-Sebastien Lauzon-Guay, after completing a BSc at the Université du Québec à Montréal, Jean-Sébastien Lauzon-Guay obtained his MSc and PhD from the University of New Brunswick studying blue mussel aquaculture and the spatial population dynamics of sea urchins feeding fronts. After a short post-doc at the University of Tasmania, he worked as a Research Scientist for Fisheries and Oceans Canada for 4 years before taking on the role of Resource Scientist for North America with Acadian Seaplants Ltd in Nova Scotia, Canada where he manages and studies the sustainable harvest of seaweed.
Abstract
The ability to map and monitor the macroalgal coastal resource is important to both the industry and the regulator. This study evaluates topo-bathymetric lidar (light detection and ranging) as a tool for estimating the surface area, height and biomass of Ascophyllum nodosum, an anchored and vertically suspended (floating) macroalga, and compares the surface area derived from lidar and WorldView-2 satellite imagery. Pixel-based Maximum Likelihood classification of low tide satellite data produced 2-dimensional maps of intertidal macroalgae with overall accuracy greater than 80%. Low tide and high tide topo-bathymetric lidar surveys were completed in southwestern Nova Scotia, Canada. Comparison of lidar-derived seabed elevations with ground-truth data collected using a survey grade global navigation satellite system (GNSS) indicated the low tide survey data have a positive bias of 15 cm, likely resulting from the seaweed being draped over the surface. The high tide survey data did not exhibit this bias, although the suspended canopy floating on the water surface reduced the seabed lidar point density. Validation of lidar-derived seaweed heights indicated a mean difference of 30 cm with a root mean square error of 62 cm. The modelled surface area of seaweed was 28% greater in the lidar model than the satellite model. The average lidar-derived biomass estimate was within one standard deviation of the mean biomass measured in the field. The lidar method tends to overestimate the biomass compared to field measurements that were spatially biased to the mid-intertidal level. This study demonstrates an innovative and cost-effective approach that uses a single high tide bathymetric lidar survey to map the height and biomass of dense macroalgae.
About the authors
Tim Webster is a research scientist with the Nova Scotia Community College’s Applied Research Group since 2000. He has an MSc from Acadia University and a PhD from Dalhousie University. He was the 2010 recipient of the Gulf of Maine Council Visionary Award and the 2017 Award of Distinction for geomatics in Nova Scotia. He has worked in the private sector for a GIS software developer prior to becoming a faculty member in remote sensing and GIS at NSCC’s Centre of Geographic Sciences (COGS). His focus includes topographic-bathymetric lidar for mapping, monitoring and modelling processes in the coastal zone.
Candace MacDonald is a Research Associate with Nova Scotia Community College’s Applied Geomatics Research Group since 2010. She holds a BSc in Biology from Acadia University and an Advanced Diploma in Remote Sensing from NSCC’s Centre of Geographic Sciences. Ms. MacDonald is a remote sensing and GIS expert focusing on topographic-bathymetric lidar, multispectral satellite, and aerial imagery interpretation and analysis for widely varied purposes such as flood risk mapping, seaweed mapping, and detection of forgotten archaeological features. She is an expert in complex raster and spatial GIS analysis, and in the construction of maps and other visual products.
Kevin McGuigan is a Research Associate with Nova Scotia Community College’s Applied Geomatics Research Group since 2010. He holds a BSc in Geology from St. Francis Xavier University and an Advanced Diploma in Remote Sensing from NSCC’s Centre of Geographic Sciences. He specialises in aerial lidar data research, low altitude aerial photography, and hydrodynamic modelling. He’s completed research projects involving high- resolution 1D-2D hydrodynamic flood modelling for various coastal and inland regions throughout the Maritimes. His recent research involves aerial bathymetric lidar feature recognition, waveform visualisation, and hydrological network mapping automation.
Nathan Crowell is a Research Associate with Nova Scotia Community College’s Applied Geomatics Research Group since 2009. He has an MSc in Applied Geomatics from Acadia University, an advanced diploma in Remote Sensing from NSCC’s Centre of Geographic Sciences, and a BSc in Biology from Acadia University. He specialises in lidar and multibeam sonar data collection and hydrodynamic modelling to support ecosystem and flood-risk management.
Jean-Sebastien Lauzon-Guay, after completing a BSc at the Université du Québec à Montréal, Jean-Sébastien Lauzon-Guay obtained his MSc and PhD from the University of New Brunswick studying blue mussel aquaculture and the spatial population dynamics of sea urchins feeding fronts. After a short post-doc at the University of Tasmania, he worked as a Research Scientist for Fisheries and Oceans Canada for 4 years before taking on the role of Resource Scientist for North America with Acadian Seaplants Ltd in Nova Scotia, Canada where he manages and studies the sustainable harvest of seaweed.
Acknowledgements
Funding for this project was provided by the Natural Sciences and Engineering Research Council of Canada and the Nova Scotia Department of Fisheries and Aquaculture. The authors thank the many summer students and research assistants who participated in the data collection and processing of the lidar data. The lidar sensor was funded from grants from the Canada Foundation Innovation and the Nova Scotia Research Innovation Trust. The authors would also like to thank the constructive reviews by three reviewers as their comments have greatly improved this manuscript.
References
Bennion, M., J. Fisher, C. Yesson and J. Brodie. 2018. Remote sensing of kelp (Laminariales, Ochrophyta): monitoring tools and implications for wild harvesting. Rev. Fish. Sci. Aquac. 27: 127–141.10.1080/23308249.2018.1509056Search in Google Scholar
Chust, G., M. Grande, I. Galparsoro, A. Uriarte and A. Borja. 2010. Capabilities of the bathymetric Hawk Eye LiDAR for coastal habitat mapping: a case study within a Basque estuary. Estuar. Coast. Shelf Sci. 89: 200–213.10.1016/j.ecss.2010.07.002Search in Google Scholar
Collin, A., B. Long and P. Archambault. 2011. Benthic classifications using bathymetric LIDAR waveforms and integration of local spatial statistics and textural features. J. Coastal Res. 62: 86–98.10.2112/SI_62_9Search in Google Scholar
Collin, A., B. Long and P. Archambault. 2012. Merging land-marine realms: spatial patterns of seamless coastal habitats using a multispectral LiDAR. Remote Sens. Environ. 123: 390–399.10.1016/j.rse.2012.03.015Search in Google Scholar
Cousens, R. 1984. Estimation of annual production by the intertidal brown alga Ascophyllum nodosum (L.) Le Jolis. Bot. Mar. 27: 217–227.10.1515/botm.1984.27.5.217Search in Google Scholar
Fearns, R.R.C., W. Klonowski, R.C. Babcock and E. Phillips. 2011. Shallow water substrate mapping using hyperspectral remote sensing. Cont. Shelf Res. 31: 1249–1259.10.1016/j.csr.2011.04.005Search in Google Scholar
Gagnon, P., R.E. Scheibling, W. Jones and D. Tully. 2008. The role of digital bathymetry in mapping shallow marine vegetation from hyperspectral image data. Int. J. Remote Sens. 29: 879–904.10.1080/01431160701311283Search in Google Scholar
Guillaumont, B., L. Callens and P. Dion. 1993. Spatial distribution and quantification of Fucus species and Ascophyullum nodosum beds in intertidal zones using SPOT imagery. Hydrobiologia 261: 297–305.10.1007/BF00049032Search in Google Scholar
Hogrefe, K.R., D.H. Ward, T.F. Donnelly and N. Dau. 2014. Establishing a baseline for regional scale monitoring of Eelgrass (Zostera marina) habitat on the lower Alaska Peninsula. Remote Sens. 6: 12447–12477.10.3390/rs61212447Search in Google Scholar
Kerr, J.M. 2011. Worldview-02 offers new capabilities for the monitoring of threatened coral reefs. Nova Southeastern University – National Coral Reef Institute, Dania Beach, FL.Search in Google Scholar
Kim, A.M., R.C. Olsen, K. Lee and D. Jablonski. 2010. Using panchromatic imagery in place of multispectral imagery for kelp detection in water. Ocean Sens. Mon. II 7678: 1–11.10.1117/12.850352Search in Google Scholar
Lyons, M., S. Phinn and C. Roelfsema. 2011. Integrating quickbird multi-spectral satellite and field data: mapping bathymetry, seagrass cover, seagrass species and change in Moreton Bay, Australia in 2004 and 2007. Remote Sens. 3: 42–64.10.3390/rs3010042Search in Google Scholar
Pan, Z., C. Glennie, J.C. Fernandez-Diaz and M. Starek. 2016. Comparison of bathymetric and seagrass mapping with hyperspectral and airborne bathymetric lidar in a shallow estuarine environment. Int. J. Remote Sens. 37: 516–536.10.1080/01431161.2015.1131869Search in Google Scholar
Phinn, S., C. Roelfsema, A. Dekker, V. Brando and J. Anstee. 2008. Mapping seagrass species, cover and biomass in shallow waters: an assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in Moreton Bay (Australia). Remote Sens. Environ. 112: 3413–3425.10.1016/j.rse.2007.09.017Search in Google Scholar
Reshitnyk, L., M. Costa, C. Robinson and P. Dearden. 2014. Evaluation of WorldView-2 and acoustic remote sensing for mapping benthic habitats in temperate coastal Pacific waters. Remote Sens. Environ. 153: 7–23.10.1016/j.rse.2014.07.016Search in Google Scholar
Sharp, G.J. 1986. Ascophyllum nodosum and its harvesting in Eastern Canada. In: Case studies of seven commercial seaweed resources. Food and Agriculture Organization Technical Report. Volume 281. pp. 3–46.Search in Google Scholar
Silva, C.D.D. 2011. Environmental monitoring and mapping in a tidal salt marsh creek affected by fish aquaculture using Worldview-2 multispectral imagery. Geospatial World Forum 2011 – Dimensions and Directions of Geospatial Industry.Search in Google Scholar
Theriault, C., B. Hatcher, R.E. Scheibling and W. Jones. 2006. Mapping the distribution of an invasive marine alga (Codium fragile spp. tomosoides) in optically shallow coastal waters using the compact airborne spectrographic imager (CASI). Can. J. Remote Sens. 32: 315–329.10.5589/m06-027Search in Google Scholar
Tulldahl, M.H. and S.A. Wikström. 2012. Classification of aquatic microvegetation and substrates with airborne lidar. Remote Sens. Environ. 121: 317–357.10.1016/j.rse.2012.02.004Search in Google Scholar
Ugarte, R. and G.J. Sharp. 2001. A new approach to seaweed management in Eastern Canada: the case of Ascophyllum nodosum. Cah. Biol. Mar. 42: 63–70.Search in Google Scholar
Ugarte, R. and G.J. Sharp. 2012. Management and production of the brown algae Ascophyllum nodosum in the Canadian maritimes. J. Appl. Phycol. 24: 409–416.10.1007/s10811-011-9753-5Search in Google Scholar
Vadas, R.L., W.A. Wright and B.F. Beal. 2004. Biomass and productivity of intertidal rockweeds (Ascophyllum nodosum LeJolis) in Cobscook Bay. Northeast. Nat. 11: 123–142.10.1656/1092-6194(2004)11[123:BAPOIR]2.0.CO;2Search in Google Scholar
Wang, C.-K. and W.D. Philpot. 2007. Using airborne bathymetric lidar to detect bottom type variation in shallow waters. Remote Sens. Environ. 106: 123–135.10.1016/j.rse.2006.08.003Search in Google Scholar
Webster, T., K. McGuigan, N. Crowell, K. Collins and C. MacDonald. 2016. Optimization of data collection and refinement of post-processing techniques for Maritime Canada’s first shallow water topographic-bathymetric lidar survey. J. Coastal Res. 76: 31–43.10.2112/SI76-004Search in Google Scholar
Woods, M., D. Pitt, M. Penner, K. Lim, D. Nesbitt, D. Etheridge and P. Treitz. 2011. Operational implementation of a LiDAR inventory in Boreal Ontario. Forest. Chron. 87: 512–528.10.5558/tfc2011-050Search in Google Scholar
Zavalas, R., D. Ierodiaconou, D. Ryan, A. Rattray and J. Monk. 2014. Habitat classification of temperate marine macroalgal communities using bathymetric LiDAR. Remote Sens. 6: 2154–2175.10.3390/rs6032154Search in Google Scholar
Zolkos, S.G., S.J. Goetz and R. Dubayah. 2013. A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing. Remote Sens. Environ. 128: 289–298.10.1016/j.rse.2012.10.017Search in Google Scholar
Article note
This article is part of the special issue series of Botanica Marina: Seaweed resources of the world: a 2020 vision, which has started publication in Botanica Marina 2019, vol. 62, issue 3. The series is guest-edited by Alan T. Critchley, Anicia Hurtado, Leonel Pereira, Melania Cornish, Danilo Largo and Nicholas Paul.
©2020 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- In this issue
- Editorial
- Seaweed resources of the world: a 2020 vision. Part 3
- Applications
- Development and objectives of the PHYCOMORPH European Guidelines for the Sustainable Aquaculture of Seaweeds (PEGASUS)
- Macroalgal diversity for sustainable biotechnological development in French tropical overseas territories
- Calculating macroalgal height and biomass using bathymetric LiDAR and a comparison with surface area derived from satellite data in Nova Scotia, Canada
- Biogeography
- Seaweed resources of the Baltic Sea, Kattegat and German and Danish North Sea coasts
- Seaweed resources of Poland
- The seaweed resources of Israel in the Eastern Mediterranean Sea
- The seaweed resources of Madagascar
- An update on the seaweed resources of Japan
Articles in the same Issue
- Frontmatter
- In this issue
- Editorial
- Seaweed resources of the world: a 2020 vision. Part 3
- Applications
- Development and objectives of the PHYCOMORPH European Guidelines for the Sustainable Aquaculture of Seaweeds (PEGASUS)
- Macroalgal diversity for sustainable biotechnological development in French tropical overseas territories
- Calculating macroalgal height and biomass using bathymetric LiDAR and a comparison with surface area derived from satellite data in Nova Scotia, Canada
- Biogeography
- Seaweed resources of the Baltic Sea, Kattegat and German and Danish North Sea coasts
- Seaweed resources of Poland
- The seaweed resources of Israel in the Eastern Mediterranean Sea
- The seaweed resources of Madagascar
- An update on the seaweed resources of Japan
