January 2024 – December 2024

 

Intended to support the ICRC to precisely map local populations to improve effective planning of humanitarian action, the results of this Humanitarian Action Challenges (HAC) research project were published in Nature in November 2022. Machine learning-based methodologies were used to estimate fine-grained population maps using open-source geodata in developing countries – the outcome of the model was gridded population estimates at a spatial resolution of 100 x 100m for Tanzania and Zambia.

The implementation and scale-up project is progressing well, with a consultant working on it until the end of 2024. The focus here is to implement and promote the use of gridded population datasets, particularly the Popcorn datasets, within the institution. These datasets are being refined and prepared for external cloud computing to allow ICRC to generate population estimates using open-source sentinel images.

The project’s goals are:

  • Centralization: Consolidate various gridded population datasets into a single platform.
  • Valorization: Make these datasets easily accessible to ICRC stakeholders.
  • Sustainability and Innovation: Create a platform that supports future developments and new data.
  • Methodological Application: Provide clear guidance on using these datasets.

The project is structured in phases:

  1. Analysis: Compare and analyze existing gridded population datasets.
  2. Diagnostic Assessment: Evaluate various applications within ICRC.
  3. Platform Development: Develop a hub platform to address identified gaps.
  4. Application: Ensure proper use of datasets with guidelines and examples.
  5. Promotion: Encourage the use of the hub within the institution.

ICRC focal point: Thao Ton That Whelan

Field evaluation of the Agilis foot
Country/Region : CONGO (DEMOCRATIC REPUBLIC OF THE CONGO) Caption : Kinshasa, Military Staff School. Militaries of the Congolese army during a training session given by the ICRC on international humanitarian law (IHL). Photographer : KAELA, Kevin Copyright : ICRC Confidentiality level : public Publication restrictions : publication without restrictionsCHITCHAT ArCHitectures for Interpretable & Transparent Continuous Humanitarian Alignment in chatbot Technologies