Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/40401
Title: Methodology for remote assessment of pavement distresses from point cloud analysis
Authors: Berney, Ernest S.
Ganesh, Naveen B.
Ward, Andrew B.
Rushing, John F.
Keywords: Remote assessment
Pavement
Runways (Aeronautics)--Maintenance and repair
Cracking
Rutting
Point cloud
Military bases
Air bases
LiDAR
Photogrammetry
Airfields
Optical radar
Remote sensing
Publisher: Geotechnical and Structures Laboratory (U.S.)
Coastal and Hydraulics Laboratory (U.S.)
Engineer Research and Development Center (U.S.)
Series/Report no.: Technical Report (Engineer Research and Development Center (U.S.)) ; no. ERDC TR-21-7
Abstract: The ability to remotely assess road and airfield pavement condition is critical to dynamic basing, contingency deployment, convoy entry and sustainment, and post-attack reconnaissance. Current Army processes to evaluate surface condition are time-consuming and require Soldier presence. Recent developments in the area of photogrammetry and light detection and ranging (LiDAR) enable rapid generation of three-dimensional point cloud models of the pavement surface. Point clouds were generated from data collected on a series of asphalt, concrete, and unsurfaced pavements using ground- and aerial-based sensors. ERDC-developed algorithms automatically discretize the pavement surface into cross- and grid-based sections to identify physical surface distresses such as depressions, ruts, and cracks. Depressions can be sized from the point-to-point distances bounding each depression, and surface roughness is determined based on the point heights along a given cross section. Noted distresses are exported to a distress map file containing only the distress points and their locations for later visualization and quality control along with classification and quantification. Further research and automation into point cloud analysis is ongoing with the goal of enabling Soldiers with limited training the capability to rapidly assess pavement surface condition from a remote platform.
Description: Technical Report
Gov't Doc #: ERDC TR-21-7
Rights: Approved for Public Release; Distribution is Unlimited
URI: https://hdl.handle.net/11681/40401
http://dx.doi.org/10.21079/11681/40401
Appears in Collections:Technical Report

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