# 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
#### 3.3.3 Maximum Wave Height and Number of Buildings  
To be independent from population datasets or populated places categories and to exploit a potentially more updated dataset, the authors explored the possibility to use a different proxy for identifying the level of exposure of each location, i.e., the number of buildings in the areas identified as being at risk by the tsunami model output. In this specific case, OpenStreetMap (OSM), a map of the world created by volunteers and free to be used under an open license, has been adopted as a source for building dataset. Among the features present in OSM, building footprints are among those considered more relevant, especially for emergency response: for this reason, building footprints together with the road network, are the most requested features to be digitized by Humanitarian OpenStreetmap Team (HOT) volunteers, the humanitarian branch of OSM mobilized after major emergencies.  
In the specific case study, as of 12 April 2019 almost 120,000 OSM building footprints are present in the areas identified as affected by the tsunami model. Those building footprints have been associatedwith one of the tsunami affected locality based on a proximity criterion: every building footprint within 5 km from an affected locality has uniquely been assigned to its nearest locality. In this way, it has been possible to enrich the locality attributes by adding the number of buildings associated to each of the locations.  
By simply combining 3 classes (based on quantile classification method) of estimated maximum wave height and number of buildings in each potentially affected location, it is possible to identify four clusters that can be used to define higher priority areas of interest (AOIs): La Serena/Coquimbo, 2 areas North of Valparaiso and San Antonio (Figure 12c). The first 3 clusters correspond to the actual AOIs of the CEMS-RM activation.  
The main advantage of this approach, in comparison with the previous two, is to provide an overall better correspondence between the priority level and the actual damages: i.e., the EMSR137 AOIs are all located in correspondence with red or yellow pixels. Furthermore, a shorter portion of the coast between La Serena and Valparaiso, where no actual damage has been reported, is estimated as  
Figure 12: Prioritization of areas of interest based on impact classes defined considering the estimated maximum wave height (tsunami model) and: (**a**) locality importance, (**b**) population estimates and (**c**) number of buildings (OpenStreetMap, OSM). Bottom images correspond to the red rectangles shown on the top ones. Service Layer Credits: © OpenStreetMap (and) contributors, CC-BY-SA.  
possibly impacted. The main disadvantage of this approach is that most of the overall impact area is flagged as medium and high priority, partially failing in addressing the goal of having a relative estimation of the impact level for immediate decision making. Additionally, the main concern in adopting a similar approach is related to actual availability and coverage of building information in the immediate aftermath of a specific event: despite the high number of registered users (including the HOT-OSM community) and although nodes and ways are constantly growing in OSM and the amount of OSM information increases over specific areas where a disaster occurs, there is a risk that the same area may be not covered at all by OSM when the priority areas must be identified. Other datasets of human presence at coarser resolution and global scale can, therefore, be used for the impact estimate, as detailed in Section 4.