Once a map showing the depth, or bathymetry, of a survey site has been generated, it is possible to classify the seafloor into zones based on variations in the bathymetry. These zones have distinct environmental conditions, and form the basis of ecosystem mapping (see above).
Ocean Ecology has used two models for terrain or habitat mapping.
Universal Model Builder (UMB)
UMB is a universal normalized-additive raster model that allows grouping and weighting of rasters on multiple levels. UMB attempts to be universal. It makes very minimal requirements of the input data and can be adapted to many uses based on the inputs and the user’s desires. UMB is a raster model. It does all of its processing using rasters as the storage format for spatial data. The final output is a single raster created by rasterizing the inputs, weighting them, adding them together and normalizing them to produce an individual layer, then a theme, and finally an end result.
The flowchart below shows how UMB combines rasters to generate a final model result.
The image below is the raster generated by this model.
Benthic Terrain Modeler (BTM)
The benthic terrain classification process developed for the BTM was derived from several existing methods used within the terrestrial and seafloor mapping communitites. A central theme in the process is the creation of bathymetric position index (BPI) data sets. BPI is a measure of where a referenced location is relative to the locations surrounding it. When created, standardized, and examined at fine and broad scales, BPI provides BTM users with a useful parameter for terrain classification. Additional outputs created by the BTM include slope, rugosity, and classified benthic terrain data sets. A graphical depiction of the process utilized by the BTM appears below.
An illustrated example of terrain modelling using the BTM is given below.
A depth map is used to create a map of Bathymetric Position Index (BPI). BPI is a measure of where a referenced location is relative to the locations surrounding it. BPI data sets are created through a neighborhood analysis function. Positive cell values within a BPI data set denote features and regions that are higher than the surrounding area. Therefore, areas of positive values generally characterize ridges and other associated features within the benthic terrain. Likewise, negative cell values within a BPI data set denote features and regions that are lower than the surrounding area. Areas of negative cell values generally characterize valleys and other associated features within a bathymetric data set. BPI values near zero are either flat areas (where the slope is near zero) or areas of constant slope (where the slope of the point is significantly greater than zero).
The depth map can also be used to calculate the slope and rugosity of the benthic terrain.
Slope values are reported in angular units from the horizontal. Slope can be used as an additional parameter for terrain classification, especially when the BPI values for a particular location are close to zero. In this case, slope is used to differentiate between flat areas and areas with slopes.
Rugosity can be best defined as the ratio of surface area to planar area. Basically, rugosity is a measure of terrain complexity or the “bumpiness” of the terrain. In the benthic environment, rugosity can be used to aid in the identification of areas with high biodiversity.
The information from the depth, slope, and BPI data sets is used to create a classification scheme for the terrain. This produces a benthic habitat map (see below).
The habitat classification map can be overlain on the 3-D depth map for the site. This map, shown below, clearly illustrates the relationship between the bathymetry of the site and the habitat classifications.