Increasing the resilience of countries to natural hazards through the integration of open exposure data derived through satellite imagery and open protocols.
The escalating impacts of natural hazards are caused mostly by increasing exposure of populations and assets. It is estimated that the world will see the construction of 1 billion new dwellings by 2050 and this growth may lead to rapid increase in risk.
.: UK Space Agency :.
HOT is working together with the British Geological Survey, ImageCat, and the Global Earthquake Model on a UK Space Agency International Partnership Programme, focused on developing innovative applications of earth observation (EO) technologies to improve understanding of exposure to help minimise these risks.
The project aims to build and strengthen local and global resilience through complete, up-to-date, accurate exposure data in order to better identify risk and enable more effective decision-making:
- Deliver exposure data for 46 of the least developed Official Development Assistance (ODA) countries
- Capacity-building of local decision makers to apply data and assess hazard exposure
- Create open protocols to develop critical exposure information from EO data
The country-wide datasets developed by ImageCat will be tested for their suitability of purpose against OSM data surveyed on the ground within the cities of Kathmandu and Dar es Salaam. Detailed attribute information following the GED4ALL taxonomy developed as part of the GFDRR Challenge Fund, will be collected for buildings randomly selected within homogenous zones by Kathmandu Living Labs and Ramani Huria for their cities.
METEOR is also working closely with the National Society for Earthquake Technology of Nepal and the Disaster Management Department of the United Republic of Tanzania to ensure that the project is effectively received by local partners.
Recent news from Modelling Exposure Through Earth Observation Routines: METEOR (View all news)
METEOR: Site Visits with Kathmandu Living Labs in Nepal
HOT and KLL set out on site visits across Kathmandu to assess the homogenous zones identified for mapping in OpenStreetMap. These seven zones have been identified as rural, residential, dense residential, urban, industrial, informal, high urban and new industrial. KLL will remotely digitise all the building footprints within the homogenous zones, before collecting detailed attribute information on the ground for a select sample of these buildings.