WP5 Multi-scale dynamic vulnerability framework for recovery planning and monitoring

Lead: UCAM

The overall objective in this work package is the integration of multi-scale dynamic vulnerability information extraction, using remotely sensed data and other geospatial tools, into early recovery planning, monitoring and evaluation methodologies.

This WP will focus on the application of remotely sensed data and geospatial tools, including ground data collection tools and sampling methodologies developed in the other WPs of the project, as well as other existing tools, for the planning, monitoring and evaluation of early recovery following natural disasters. Recovery planning, monitoring and evaluation is usually carried out sector by sector (e.g., housing, logistics), independent of the disaster that has caused the disruption to the population. It is expected that the new tools this WP develops can promote collaboration between the different sectors in a positive and efficient manner.

This WP will use the collaborative opportunities of the project to create an innovative approach suitable for rapid large scale application thorough the use of semi-automated methods of collecting, analysing and presenting data for planning, monitoring and evaluation of recovery and reconstruction in a systematic way. Global urban datasets produced by the partners of this project, as well as existing ones, will be tested for their suitability for recovery planning and monitoring. The semi-automated urban data extraction methodologies to be produced during WPs 2, 3 and 4 will also be incorporated into the framework. Geo spatial sampling methodologies will be developed for ground data collection where the outputs will consist of sampling strategies and the associated uncertainty measures.

Mainly focusing on the data needs of the national and local civil protection agencies, differentiation will be made between data rich and data poor countries, by developing guidelines for planning, monitoring and evaluating reconstruction and recovery using remotely sensed data and other geo spatial tools for both situations. Another key output from this work package is to demonstrate the return in investment of creating pre-event datasets (e.g, inventory datasets), which can be used throughout the entire disaster cycle, making the entire process streamlined and more efficient.

The key objectives of this WP are therefore:

  • Develop a new approach to support the process of post-disaster recovery by considering newly available urban datasets (WP2) and semi-automated methods (WP2 and WP3 and WP6).
  • Develop separate recovery planning and monitoring/evaluation methodologies for both data rich countries and data poor countries.
  • Focus on the buildings, transportation, population, services, environment and livelihoods sectors, building on previous work carried out by the ReBuilDD group.
  • Streamline the entire process starting from preparedness mapping, to damage mapping and reconstruction planning, monitoring and evaluation. Assess the cost-effectiveness of streamlining the entire process.