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Wabasha County Survey Using Drone-Based Aerial LiDAR

LiDAR data extraction from Wabasha County survey project
Wabasha County Survey Using Drone-Based Aerial LiDAR

Location:  Wabasha County, Minnesota
Client:  Wabasha County Highway Department

Background

The Wabasha County Highway Department has nearly 15 miles of roadway coming out of the St. Croix River Valley. Many of these roadways are too steep and/or too heavily wooded to benefit from traditional LiDAR survey. 

The Wabasha County Highway Department asked Houston Engineering, Inc. (HEI) to help explore an alternative method to achieve the survey data that they need for future roadway repairs.

The Project

HEI determined that traditional survey methods were difficult and even dangerous. However, by using drone-based aerial LiDAR, accurate data could be gathered with a fraction of the effort. 

This type of survey can be completed with extreme accuracy and even with heavy tree coverage once leaf-off conditions are met in the fall through the spring. Additionally, using drone-based aerial survey methods equates to more cost-effective and efficient deliverables.

Thanks to the use of drone-based aerial LiDAR, the Wabasha County Highway Department will receive a product that is usable in a CAD environment at a cost and within a timeline that would not be feasible otherwise.

GIF animation of a fly-through of the point cloud dataA fly-through animation through the point cloud data captured along the roadway in Wabasha County, MN. 

GIF animation showing the featured extraction process
GIF animation showing the featured extraction process in Wabasha County, MN
The two animated images above show the featured extraction process of the roadway in Wabasha County, MN. The first sequence in these images shows the immense amount of LiDAR data originally collected. As these animations progress, the point cloud data is being scaled down to the featured extraction to a useable file size for AutoCAD software systems. 

Client Benefits

  • Quick and cost-efficient deliverables.
  • An accuracy of survey data that would be difficult to obtain through traditional surveying methods due to the topography.