Global Dynamic Exposure and the OpenBuildingMap

Abstract:

Detailed understanding of local risk factors regarding natural catastrophes requires in-depth characterization of the local exposure. Current exposure capture techniques have to find the balance between resolution and coverage. We aim at bridging this gap by employing a crowd-sourced approach to exposure capturing focusing on risk related to earthquake hazard.

OpenStreetMap (OSM), the rich and constantly growing geographical database, is an ideal foundation for us. More than 2.5 billion geographical nodes, more than 150 million building footprints (growing by ~100'000 per day), and a plethora of information about school, hospital, and other critical facility locations allow us to exploit this dataset for risk-related computations. We will harvest this dataset by collecting exposure and vulnerability indicators from explicitly provided data (e.g. hospital locations), implicitly provided data (e.g. building shapes and positions), and semantically derived data, i.e. interpretation applying expert knowledge. With this approach, we can increase the resolution of existing exposure models from fragility classes distribution via block-by-block specifications to building-by-building vulnerability.

To increase coverage, we will provide a framework for collecting building data by any person or community. We will implement a double crowd-sourced approach to bring together the interest and enthusiasm of communities with the knowledge of earthquake and engineering experts.

The first crowd-sourced approach aims at collecting building properties in a community by local people and activists. This will be supported by tailored building capture tools for mobile devices for simple and fast building property capturing. The second crowd-sourced approach involves local experts in estimating building vulnerability that will provide building classification rules that translate building properties into vulnerability and exposure indicators as defined in the Building Taxonomy 2.0 developed by the Global Earthquake Model (GEM). These indicators will then be combined with a hazard model using the GEM OpenQuake engine to compute a risk model.

The free/open framework we will provide can be used on commodity hardware for local to regional exposure capturing and for communities to understand their earthquake risk.