Title

Topographic and Bathymetric Mapping

Poster Number

5

Lead Author Major

Computer Engineering

Format

Poster Presentation

Faculty Mentor Name

Elizabeth Basha

Faculty Mentor Department

Electrical and Computer Engineering

Abstract/Artist Statement

Topographic and bathymetric maps represent a three-dimensional object in a two-dimensional plane, usually with contour lines representing the difference in elevation. Bathymetric maps represent submerged (underwater) terrain while topographic maps represent the natural contours of dry land. This research aims to use a quadcopter to generate detailed low-level topographic maps of terrain and bathymetric maps of riverbeds. Currently, the generation of these maps often misses the fine details of the terrain; we develop new methods to retain these details. Water provides a challenge in bathymetric maps. Normally LIDAR, or similar light sensors, can create fine scale contour maps; however, water attenuates signals making it difficult to measure with light. Sound travels well through water; using sound to generate bathymetric maps requires sonar to retrieve depth and position. These sonar systems utilize a depth sounder in order to collect depth measurements in an area. A program compiles this data and produces the final bathymetric map based on contour lines. To demonstrate the functionality of the bathymetric mapping system, we place different sized blocks in the school pool. We verify that the system detects these objects and includes them in the map. The quadcopter provides the challenge in the creation of small scale, high density topographic maps. The quadcopter severely limits the amount of weight that can be carried, which, therefore, limits the quality of camera that the system can use. A technique called Structure From Motion creates a point cloud of the terrain. Structure From Motion involves using multiple twodimensional images, matching common points across the images, and then using epipolar geometry to locate the points in a threedimensional space. To test the effectiveness of the Structure From Motion system, we take aerial pictures of a rock and confirm that the resulting point cloud contains the rock with reasonable accuracy.

Location

DeRosa University Center, Ballroom

Start Date

30-4-2016 10:00 AM

End Date

30-4-2016 12:00 PM

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Apr 30th, 10:00 AM Apr 30th, 12:00 PM

Topographic and Bathymetric Mapping

DeRosa University Center, Ballroom

Topographic and bathymetric maps represent a three-dimensional object in a two-dimensional plane, usually with contour lines representing the difference in elevation. Bathymetric maps represent submerged (underwater) terrain while topographic maps represent the natural contours of dry land. This research aims to use a quadcopter to generate detailed low-level topographic maps of terrain and bathymetric maps of riverbeds. Currently, the generation of these maps often misses the fine details of the terrain; we develop new methods to retain these details. Water provides a challenge in bathymetric maps. Normally LIDAR, or similar light sensors, can create fine scale contour maps; however, water attenuates signals making it difficult to measure with light. Sound travels well through water; using sound to generate bathymetric maps requires sonar to retrieve depth and position. These sonar systems utilize a depth sounder in order to collect depth measurements in an area. A program compiles this data and produces the final bathymetric map based on contour lines. To demonstrate the functionality of the bathymetric mapping system, we place different sized blocks in the school pool. We verify that the system detects these objects and includes them in the map. The quadcopter provides the challenge in the creation of small scale, high density topographic maps. The quadcopter severely limits the amount of weight that can be carried, which, therefore, limits the quality of camera that the system can use. A technique called Structure From Motion creates a point cloud of the terrain. Structure From Motion involves using multiple twodimensional images, matching common points across the images, and then using epipolar geometry to locate the points in a threedimensional space. To test the effectiveness of the Structure From Motion system, we take aerial pictures of a rock and confirm that the resulting point cloud contains the rock with reasonable accuracy.