The centralized nature of BioBase cloud technologies coupled with sophisticated, yet low-cost consumer electronics like Lowrance or Simrad depth sounders/chartplotters have created fertile grounds for developing, testing, and verifying algorithms for typing aquatic environments. The more users upload from a greater range of systems, the more refined algorithms can become addressing a wider range of conditions and use cases!
Early in 2014, we released a revision to our bottom composition (hardness) algorithm that is more sensitive and robust in a greater range of depths and bottom conditions. Many outside researchers were involved with collecting important “ground truth” information while they logged their BioBase data. This blog not only serves to describe the new Bottom Composition algorithm, but also publish the results and acknowledge the scientists that helped with this effort.
How it works and the outputs produced
The Composition algorithm processes the 200 kHz Broadband downlooking signal and produces a data point for GPS signals (Typically 1 pt every 1-2 seconds). Algorithms estimate the acoustic reflectivity of the bottom. Signals bounce more on a hard bottom than a soft bottom where signal is absorbed. Hardness ratings are consistent across all mapped systems and not relative to a trip (e.g., a trip with muck and silt will show all light tan colors). GPS point data along tracks are sent to an interpolation (kriging) algorithm to predict hardness between sampled areas and create a uniform map
|Figure 1. Continuous, unitless data are created with each GPS coordinate to reflect relative hardness from soft 0-0.25 (light tan), to medium 0.25 – 0.4 to hard 0.4 – 0.5 (dark red).|
How does it compare with actual data? Verification results from independent researchers
Unlike conventional models or software programs that use limited datasets in a narrow range of conditions to calibrate and verify model outputs, BioBase is able to draw from our central database and network of professionals using the system to develop new or improved algorithms.
For revisions to the composition algorithm, Navico technical staff worked with scientists from the University of Florida (Mark Hoyer), USGS in Little Rock AR and Reston VA and (Drs. Reed Green, Nancy Rybicki and Elizabeth Striano), and across the pond with the Center for Ecology and Hydrology (Drs. Ian Winfield, Helen Miller, and Joey van Rijn) evaluating the agreement of their independently collected bottom composition data with companion BioBase hardness datasets. Despite field error in the precise estimation of actual hardness and overlap with simultaneously collected BioBase data, we were encouraged by the high agreement of compared data sets. See for yourself below!
Table 1. Agreement between visually estimated substrate hardness while collecting Lowrance/BioBase composition data from 9 of 23 samples in coastal Back Bay, Virginia Beach VA, USA in 2012. BioBase composition data at the remaining 13 sites were not generated due to depth or vegetation thresholds. Bottoms cannot be typed where vegetation fills > 60% of the water column or in depths less than 2.4 feet from the transducer face. Data were collected by Dr Nancy Rybicki and Elizabeth Striano, USGS – Reston VA as a component of a vegetation assessment study.
|Figure 4A. Hardness data from Windermere (Cumbria, England) as scored by visual estimation from underwater imagery as it relates to hardness from Lowrance and BioBase. Data were collected in 2012 by Dr. Ian Winfield and Joey van Rijn and described in a previous blog post. The biological context and other companion composition data are presented in Miller et al. 2014.|
|Figure 4B. Bottom substrate (and Northern Pike) as viewed from a camera mounted on a Remote Operated Vehicle (ROV) in Windermere. See Figure 5A for the Hardness Score and Corresponding BioBase Hardness data|
Create your own sediment thickness models
The BioBase composition algorithm will not predict sediment depth, only whether the bottom is hard or soft based on the “echo” of the acoustic signal. Still, what we show in Figures 2 and 3 are that sediment depth may correspond predictably with bottom hardness as estimated by BioBase. The primary benefit of BioBase is to provide a full-system understanding of where hard and soft areas exist (Figure 5). Investigators can follow up with a couple of dozen coring points in areas of interest (e.g., sedimentation deltas) to develop system-specific relationships like those in Figures 2 and 3. The paradigm shift that BioBase has brought is a new way to focus more detailed sediment depth sampling, rather than using a coring probe as the sole mapping tool.
|Figure 5. Full system map of bottom composition. Data were exported from a fully interactive free demo account. Log in and view trips and data and how they correspond to the sonar log.|