ANALYSIS OF ROAD DAMAGE DETECTION USING ORTHOPHOTO MAP FROM UNMANNED AERIAL VEHICLE (UAV-PHOTOGRAMMETRY)
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Abstract
Survey of road damage data can be conducted by the direct survey method or manual inspection, but that mothod is quite long and requires a lot of employers, so it is not effective and efficient. This research focuses on the inspection of road damage using drone technology by taking aerial photos using the UAV-Photogrammetry method. Aerial photography was carried out along the roads in the study area. The partial aerial photos are processed using image processing software to become the orthophoto map and digital elevation model (DEM). Road damage data identification was carried out by measuring the dimensions (length, width, and depth) from the orthophoto map and DEM by the visual interpretation method. The research results show that the types of road damage identified from the orthophoto map and DEM in the study area are potholes, block cracks, continuous cracks, and patches. The accuracy of the dimensions of road damage produced from the orthophoto map and DEM compared to the dimensions of road damage measured directly has different values for horizontal of 0.001 - 0.088 m and vertical of 0.010 - 0.019 m, RMSE values range from 0.005 to 0.058. The results of the t-test statistical test show that there is no significant difference between measurements of road damage dimensions from the orthophoto map and DEM and the results of direct measurements.
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