Natural and man-made disasters that may take place due to a catastrophic incident (e.g., earthquake, explosion, terrorist attack) often result in trapped humans under rubble piles. In such emergency response situations, Urban Search and Rescue (USaR) teams have to make quick decisions under stress in order to determine the location of possible trapped victims. Fast 3D modelling of fully or ... [Show full abstract] partially collapsed buildings using images from Unmanned Aerial Vehicles (UAVs) can considerably help USaR efforts, thus improving disaster response and increasing survival rates. The a-priori establishment of a proper workflow for fast and reliable image-based 3D modelling and the a priori determination of the parameters that have to be set in each step of the photogrammetric pipeline are critical aspects that ensure the readiness in an emergency response situation. This paper evaluates powerful commercial and open-source software solutions for the 3D reconstruction of disaster scenes for rapid response situations. The software packages are tested using UAV datasets of a real earthquake scene. A thorough analysis on the parameters of the various modelling steps that may lead to desired results for USaR tasks is made and indicative processing chains are proposed, taking into account the restriction of time. Furthermore, some weaknesses of the data acquisition process that have been detected by performing the experiments are outlined and some improvements and additions are proposed, including an initial preprocessing of the images using a graph-based approach.