Applications: This approach enables planners to identify specific buildings at scale that need improvements or strengthening. It holds promise for use as a proxy for social vulnerability. Related work can inform region-wide infrastructure management decisions and scan for buildings’ structural vulnerabilities in earthquake-prone areas. It has been successfully applied in nine countries and 18 areas of interest. Typical areas of interest span 15-25 sq km, though it has been implemented in locations up to 80 sq km, making it suitable for small island states. Future developments might pinpoint roofs that could generate solar power or identify emergency routes and shelters.
Data requirement: None - data collected locally
Final deliverables: The resulting georeferenced datasets hold enormous potential to help create resilient, healthy communities. That includes unprecedented opportunities for spatial planning, disaster and climate risk management and reduction. Results are navigable in a password-protected portal that supports basic queries and geospatial analysis, allowing users to easily obtain an overview of the data, while also examining specific results at the unit level. Results can be exported from the portal in a variety of formats (CSV, Shapefile, GeoJSON, GeoPackage).
Geographic scope: City- and neighborhood level
Hazards covered: Earthquakes, floods, and hurricanes; landslides to a limited extent
Indicative Cost / working time: $100k-250k
Methodology peer-reviewed, cleared (date)?: Yes, methodology was peer reviewed and published in a few journals.
Time Required for delivery: 3-6 months, depending on location, size, and terrain of area of interest
Access detailed datasets characterizing the built environment more efficiently than traditional survey methods. By applying machine learning algorithms to high-resolution imagery taken above the city (aerial imagery) and at ground level (street view imagery), we can make comprehensive, multi-view urban observations from the sky and street.
Using this data, one can analyze built components to gather insights about blocks, neighborhoods, and cities through access to a wide-ranging overview of specific urban characteristics, such as each unit’s:
Size (area, height, and volume of building)
Use (residential, commercial, critical infrastructure, or mixed)
Masonry (unreinforced, reinforced, or unknown)
Roof condition (good, fair, poor, under construction or vacant)
Roof material (concrete, metal, mixed, tile, other)
Wall condition (good, fair, poor)
Wall material (typically: brick or concrete block, plaster, mix/unclear/other; can include: wood – polished, wood - crude/plank, adobe, corrugated metal, stone with mud/ashlar with lime or cement, container/trailer, plant material)
Total condition (composite estimation based on roof and wall conditions).
Vintage (for example, pre-1940, 1941-1974, 1975-1999, and 2000-present. These are locally determined based on field surveys conducted by structural engineers.)