## 5 Results  
### Survey Design  
The purpose of the overall approach is to efficiently collect visual data on possibly damaged buildings in a realistic urban environment. A full scale test in a post-earthquake situation has not yet been possible, hence in order to evaluate the expected performance of the system in a realistic environment a pre-event data collection has been carried out in the study area. The survey has been designed with a two-stage format, with iterative sampling and routing. A focus map was generated as described in Section 3 with a linear (additive) pooling approach in order to widen the range of the survey, since it was mostly considered a pre-event one. The resulting focus map for the first acquisition day is presented in Figure 7.  
In our case the following datasets have been used:  
* distribution of buildings, also accounting for the density of policies (number of policies per building),
* hazard map in terms of expected PGV with exceedance probability of 10% in 50 years. The latter represents a proxy for the expected location of building damage, in the absence of a particular scenario, while the first dataset encodes both the spatial distribution of buildings and the co-variant distribution of policies. Layers have been normalized with a standard linear approach, using (1%, 99%) rejection bounds (see [11] for details on available normalization techniques). The two layers have been assigned respective weights (0.7, 0.3), therefore giving priority to the location of policies, but also taking into account the expected hazard (hence the expected damage). A second-level focus map has been computed considering as the additional layer a polygon around the geometrical path obtained from the first focus map, and considered using a negative weight in the pooling phase. Two sampling sets have then been generated with a PPS sampling scheme (see Section 3 and [11,12]). The two focus maps and the related optimized routes are shown in Figure 7. As can be seen from the figure, the optimized paths for a two-day multi-stage survey provide a good coverage of the areas where the focus maps have higher values, with a small amount of superposition. The routing of the second day not only follows the underlying focus map, but also considers the previously captured route. Table 3 lists the main geometric features of the two individual surveys. The overall distance expected to be traveled is around 145 km. In normal conditions (in urban environments) a mobile mapping system can cover between 80 and 120 km within a 6-8 h time span. The first day survey is along this line, while the survey on the second day is shorter, and can be thought of as a refinement survey. A simulation of a post-event survey has also been performed using the available data. A focus map (see Figure 8D) based on log-linear (multiplicative) pooling is suggested in this case, since a higher level of selectivity should be sought in order to optimize the survey efforts. In order to simulate a more realistic case, the basic layers used in the pre-event case (distribution of buildings/policies and seismic hazard) have been considered. A further layer describing the expected spatial distribution of road blockages has been added (displayed in Figure 8C). This can be further integrated, in a real case, by either the expected damage distribution from satellite/aerial observations, or by _in situ_ information provided by local authorities. This information can moreover be used to constrain the path optimization, for instance by assigning a higher cost to route segments of reduced width (e.g., small lateral roads frequent in the Besiktas district) in areas subject to collapses, which would be more prone to blockage due to debris. Figure 7: Computation of pre-event focus map. (**A**) spatial distribution of buildings weighted with related number of earthquake policies. (**B**) expected seismic hazard (PGA) with exceedance probability of 10% in 50 years. (**C**) resulting focus map obtained by linear pooling of the normalized layers with weights (0.7,0.3).