UAV imagery has become more potential in various applications such as topographic mapping, infrastructure maintenance, construction monitoring, inspection, etc. At the same time, this strongly depends on the photogrammetric process of UAV image block. If the photogrammetric results of an image block, for instance, the estimated image positions and scale information do not meet the required conditions e.g. the geometric accuracy, then these results will be seen as not valid and therefore not recommended to use in farther applications. From this point of view, we are motived to use depth-map data obtained from smartphones/iPad mounted to handheld RTK Rover as additional datasets that should be integrated/implemented into UAV photogrammetric image block (Fig. 1). In other words, we aim to realize an intelligent combination between smartphone and UAV based photogrammetry. In general, a smartphone can not only be used anytime and anywhere, but is also more cost-effective than an existing photogrammetric UAV. It provides high-resolution imagery and attitude data, and recently laser-based range data (depth-maps), which can be used to define the image scale.
