The identification and quantification of full-depth patching need using remote sensing technology
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The current methods for manually inspecting asphalt pavement to identify sections for full-depth patching are time-consuming and labor-intensive. This thesis proposes a novel methodology for using 3D laser data to identify and quantify the need for full-depth patching on asphalt pavements. This is done by observing the topological crack characteristics of asphalt pavements in need of patching to mimic the identification processes done in-field by engineers. The method is validated using pavement cores that give subsurface conditions. The proposed method shows promise for identifying and quantifying full-depth patching locations more efficiently than current methods.