Data Management Plan

Hard and soft bottom seafloor substrate data and maps for the NOAA Habitat Blueprint West Hawaii Focus Area (WHFA) in the Main Hawaiian Islands. Cell values in the raster datasets reflect whether the seafloor is hard bottom or soft bottom based on an unsupervised classification run using ArcGIS software with the Spatial Analyst extension. The classifications are based on bathymetry, acoustic derivatives and verified using seafloor optical data.

The seafloor substrate map and associated data are accessible online via the Pacific Islands Benthic Habiat Mapping Center (PIBHMC) website at www.soest.hawaii.edu/pibhmc.

West Hawaii

Lineage Statement:
The Iso Cluster Unsupervised Classification tool in ArcGIS was used to classify the three-band Principle Component Analysis image into two distinct hard vs soft substrate classes. Ground truth optical imagery as well as existing shallow water habitat maps provided by the USGS and NOAA Biogeography Branch were used to validate and correct the hard soft classification.

Process Steps:

• Multibeam bathymetry data collected by NOAA CREP was processed and integrated with existing bathymetry datasets maintained by the University of Hawaii, Hawaii Mapping Research Group (HMRG) to produce a high-resolution (5m) bathymetry synthesis for the entire NOAA Habitat Blueprint West Hawaii Focus Area (WHFA). (Citation: 5m Bathymetric data of Kohala coast of Hawaii)
• The Benthic Terrain Modeler in ArcGIS 10.3 was used to derive a series of surface complexity layers using the WHFA bathymetry synthesis. Eight surface complexity layers (mean depth, standard deviation of depth, curvature, plan curvature, profile curvature, slope, slope of slope, and rugosity) and Bathymetric Position Index (BPI) layers for zone and structure were produced. (Citation: Wright, D.J., Pendleton, M., Boulware, J., Walbridge, S., Gerlt, B., Eslinger, D., Sampson, D., and Huntley, E. 2012. ArcGIS Benthic Terrain Modeler (BTM), v. 3.0, Environmental Systems Research Institute, NOAA Coastal Services Center, Massachusetts Office of Coastal Zone Management.)
• A Principle Component Analysis (PCA) using ENVI 5.3 software was performed on the bathymetry synthesis and eight complexity surface layers to remove highly correlated data by transforming the image into nine principle components. The first three principle components described 99% of the data variability. The complexity surfaces that contributed the most variance were depth, mean depth and rugosity. These three principle components were retained for use in the benthic classification process. (Citation: Costa BM and Battista TA (2013) The semi-automated classification of acoustic imagery for characterizing coral reef ecosystems. International Journal of Remote Sensing 34(18):6389–6422.)
• The Iso Cluster Unsupervised Classification tool in ArcGIS was used to classify the three-band Principle Component Analysis image into two distinct hard vs soft substrate classes. (Citation: Iso Cluster Unsupervised Classification Tool)
• To verify the accuracy of the automated delineation, the classified optical validation points were overlaid onto the delineated image to confirm or correct the substrate classes. The delineated classifications were manually corrected if they disagreed with the optical validation points. When optical validation points were absent, the USGS and NOAA Biogeography Branch benthic habitat maps were used as validation.

Corrections for tide variation and vessel attitude are applied to the multibeam data and a CTD (Conductivity, Temperature, and Depth instrument) cast is performed regularly during data collection to correct for variance within the water column.

Multibeam data are tested for internal consistency; however, no effort is made to compare these data to external references or to other published data.

Hard/soft results from unsupervised classification were validated and corrected using optical ground truth imagery.

Data can be accessed online via the Pacific Islands Benthic Habitat Mapping Center website at https://www.soest.hawaii.edu/pibhmc/pibhmc_mhi_haw.htm

University of Hawaii School of Ocean and Earth Science and Technology, NOAA IRC and NOAA Fisheries ITS resources and assets.