Using Side Scanning Sonar to Map Bottom Substrate Features in North Dakota Rivers Justin Tangen Valley City State University.

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Presentation transcript:

Using Side Scanning Sonar to Map Bottom Substrate Features in North Dakota Rivers Justin Tangen Valley City State University

Introduction The primary goal of this research is to map the substrate composition of a stretch of the Sheyenne River using side imaging sonar Using hands on inspections of 40 sites to confirm composition of the substrate Using ArcGIS to process the data Why?

Side Scanning Sonar Consumer grade side scanning sonar has made it more affordable to access this technology Safer and faster than traditional substrate composition analysis –Due to debris, depth, and turbidity –Can cover ~6 miles per hour, in comparison to ~1 mile per day

Side Scanning Sonar

Equipment Humminbird 1199ci HD SI –Receiving power supply from 12v deep cell marine battery Garmin GPSMap 78 –Connected to Humminbird via NMEA connection –Margin of accuracy ~3-5 meters Porta- bote Outboard motor

Equipment

Methods Maintaining river center to gather the best depth data and to get the best coverage of both banks Using the snapshot feature on the sonar, logging images every three seconds Gathering quality images that overlapped

Methods Extracting the files from SD for work in ArcGIS

Research Area

Side Scanning Sonar

Methods

Conclusion Geospatial analysis in ArcGis is ongoing –Working to create effective shapefiles that represent differences in the substrate After the 37 sites have been input to ArcGis, moving to the rest of the images for interpolation of substrate –Then inputting into ArcGis

Thank You Funding Agencies –NASA –Valley City State University SOAR program Andre DeLorme – VCSU science chair Lewis Weiland – VCSU research assistant Jason Rowell Michaela Halverson Shannon Hone

Sources nology/Side-Imaging/ nology/Side-Imaging/ US?gclid=CjwKEAjw55K4BRC53L6x9pyDzl4 SJAD_21V1qWHGEubdBWqjpa5bK126J6iuZ AfTBBNFDAzqwd2yKRoCctjw_wcBhttp:// US?gclid=CjwKEAjw55K4BRC53L6x9pyDzl4 SJAD_21V1qWHGEubdBWqjpa5bK126J6iuZ AfTBBNFDAzqwd2yKRoCctjw_wcB