Roads are means of transportation that play an important role in supporting people's lives such as economic, social, educational and cultural activities. In its service, the age of road is often not as planned because it has damage to the surface layer. Maintenance, repair and rehabilitation efforts are needed. However, before that steps are needed to identify each type and level of damage that occurs so that recommendations can be proposed for improvement. Road distresses identification is still done manually by surveyors who fill out forms and sketches of road distress. On the other hand, UAV (Unmaned Aerial Vehicle) which have many advantages, such as: save time, money, labor and able to produce a geographical database for transportation issue. In this research data acquisition use automatic mode along road corridor. Aerial photo data is processed and analyzed by using SfM (structure from Motion) software to produce DSM (Digital Surface Model) and orthophoto. DSM is used to determine the depth profile of road distress. While the orthophoto results are then used in the process of visual interpretation to identify road distress. This research using quadcopter platform using digital camera with flight altitude less than 20 metres to obtain precise DSM and orthophoto. The results obtained by several types of road distress can be identified by using UAVs in the form of alligator cracking, potholes, edge cracking, shoving and depression. This type of road distress classification was obtained based on visual interpretation obtained an accuracy rate of 96.36 %.
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