# Tsunami Modeling and Satellite-Based Emergency Mapping: Workflow Integration Opportunities
## 2 Materials and Methods: Tsunami Modelling and Satellite-Based Emergency Mapping
### Early Tasking Approaches Based on the Tsunami Model Output  
According to [4], the tsunami primary impact zone is distributed along approximately 5000 km of the Chilean coast. The locations resulted as affected by the tsunami model are distributed along more than 4000 km of the Peruvian and Chilean coast, from 10.57\({}^{\circ}\) S to 43.90\({}^{\circ}\) S. Considering only the 3 rd quantile of the distribution of the estimated wave height on the coast (>0.43 m), the length of the coast possibly impacted is approximately 2300 km, from 18.30\({}^{\circ}\) S to 39.21\({}^{\circ}\) S (Figure 11).  
Assessing the damages caused by the tsunami over the whole length of the Pacific coast possibly affected by the tsunami on the basis of the model outputs is not feasible for a SEM mechanism, mainly for the following reasons:  
* tsunami damage assessment based on satellite data requires very high resolution (VHR) optical imagery. Even assuming that one or more satellite data providers can cover similar extents with the required resolution exploiting (virtual) constellations, the related data costs would be extremely high;
* even if CEMS-RM benefits from the possibility to plan acquisitions for most of the satellite data providers (Copernicus contributing missions), the current mechanism activations on large areas increase the possibility to generate tasking conflicts (possibly also with other SEM mechanisms) which may result in losing time and in the worst case even missing an acquisition opportunity;
* the possibly impacted area is significantly larger than the maximum capacity of the service, leading to significant delays in the generation of products;
* CEMS-RM production costs (for damage assessments currently visual interpretation is the standard approach) are proportional to the area examined and an extent similar to the one in discussion would not be sustainable.  
Therefore, it is crucial to prioritize the areas where to trigger satellite acquisitions and perform satellite-based damage assessment. The optimum would be to have an automatic prioritization process to identify the areas of interest in the shortest time frame possible to avoid delay in the post-event image acquisition (as discussed in Section 2.2.1).  
Figure 10: Example of one of the grading products issued in the CEMS-RM activation: detail of the affected area (**a**), full extent of the map (**b**) and related legend (source: Copernicus Emergency Management Service © European Union 2015, [EMSR137] Coquimbo North: Grading Map).  
In order to automatically prioritize the areas for satellite acquisitions, three different approaches based on integration of tsunami model outputs and exposure data are proposed, described and discussed, namely:  
1. Maximum wave height and populated place categories
2. Maximum wave height and population estimates
3. Maximum wave height and number of buildings  
The aforementioned approaches are all based on geoprocessing workflows generating 3-class impact indexes in form of 0.25\({}^{\circ}\) by 0.25\({}^{\circ}\) raster outputs providing information on relative priorities among the impacted areas. Given the lack of additional case studies to further validate the proposed approaches, the current analysis is limited to a detailed discussion on benefits and drawbacks of each method. Further tests will be carried out on future major tsunami events for which also a SEM response will be in place.  
Figure 11: Impacted locations and related maximum wave height generated by the tsunami model, compared with the primary impact zone defined by [4].