Mapping Climate Risk for Education Planning in the Caribbean

A project by CDEMA, OpenDevEd and UNOSAT

Overview

Within the education sector, geospatial data offers planners a way to visualize and monitor education-related fields. Geospatial data can contribute to ensuring that educational programmes and services consider geographic constraints, social challenges, and local economic realities.

Develop and Implement A Regional Model Safe Education Sector Plan and National Adaptation Guide is a project where  UNOSAT ,  OpenDevEd  and  CDEMA  are collaborating to strengthen education planning through the use of geospatial data in 6 countries of the Caribbean.

Small Island Developing States (SIDs) are some of the most disaster-prone countries in the world and often suffer damage to infrastructures. The use of geospatial data and applications and hazard risk can be analysed for better planning and mitigation of disasters' impact, including on education infrastructure. For example, location-based data can play a large role in mapping and identifying potential education facilities located in hazard-risk areas, and pinpoint locations that are vulnerable or pose a potential risk. 


Mapping School Locations

Accurate and up-to-date data and locations on education facilities are essential for education-related geospatial analyses. In this project, UNOSAT analysts obtained open-source datasets and found that several of these datasets were incomplete.

Since precise geospatial coordinates provided by Government/ National datasets were limited, the analysts used enhanced geocoding methods to fill gaps and map additional school locations. These included additional information such as school type and name. Improving these datasets helped to ensure a more accurate geospatial analysis.

Case Study: Antigua and Barbuda

The case study of Antigua and Barbuda shows the UNOSAT geocoding enhanced method which was used to map additional schools not included in open-source data.

On Antigua Island, data from open data sources only showed a few education facilities mapped, with limited information.

UNOSAT mapped 77 additional schools across, varying from primary, secondary and tertiary.

 All maps in this StoryMap are interactive. Zoom in and pan around the islands to interact with the map, and click on different schools for more information on their name and education levels.  

Antigua

By adding additional open-source data, such as roads, waterways and population density, it can give an overall picture of where people and infrastructures are located.

 Data sources: roads (OSM), waterways (OSM), population density (Meta). 


Geospatial Data Model

The geospatial model,  Multi-criteria decision analysis for site classification of educational facilities   is an open-source tool developed by UNOSAT and UNESCO IIEP. It allows users to leverage geospatial data to create data-driven outputs for education planning and policy making. See below how it was used for this project.

Part A: Multi-hazard risk index

Part A of the geospatial model calculated a multi-hazard risk index by creating a normalized risk index score (1-10) and combining several different hazard layers. Once calculated, this hazard risk index is then assigned to existing school/education facilities to provide them with an individual risk index.

Part A: Multi-hazard risk index process

The below case study shows the multi-hazard risk assessment output from Part A of the geospatial model for Dominica. Click on each school for more information about the school and the risk index.

Part A Output. Data Source: GeoCRIS, 2006.

Part B: Multi-Criteria Decision Analysis/ Suitability Study

The second step of the model adds social, economic, and environmental parameters to the outputs of Part A. Here, the model is a multi-criteria decision analysis that determines the suitability of the land to host new infrastructure, and provides insights into the maintenance of the existing infrastructure.

Part B: Multi-Criteria Decision Analysis/ Suitability Study process

Suitability Analysis

The multi-hazard criteria decision analysis output (map seen here) has been calculated by combining the outputs obtained from running the three criteria models (social, economic and environmental).

This output gives a land suitability rating, from low to high, which can help inform policy and planning activities within the country.

 Data sources: Hazard layers (GeoCRIS), roads (OSM), waterways (OSM), population density (Meta), forest classification (Copernicus), DEM SRTM (USGS). 

Conclusion

The results of this model are preliminary and provide several outputs, using a combination of national and global data sets. The model outputs demonstrate how geospatial data can be used at the national level to run different hazard risk scenarios and suitability studies for the potential new locations of education facilities or the relocation of at-risk existing facilities. 

After analysing existing research and data available, as well as school surveys and interviews undertaken with country representatives, it showed that the importance of geospatial data across the Caribbean is recognized. However, the use of this data within the Caribbean context is low and has the potential to be significantly increased for better education planning, in particular in the context of disaster risk reduction, mitigation and response. These maps and data can be used in combination with national data and statistics to help make data-driven decisions in planning and contribute to sustainable development across several sectors. 

Additional Project Links

This StoryMap and all analysis and maps have been produced by the United Nations Satellite Centre - UNOSAT. The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations.

Please note that all data shown throughout this StoryMap is preliminary and has not been verified on the ground.

Project information

CDEMA, OpenDevEd, UNOSAT

Analysis and StoryMap Production

United Nations Satellite Centre (UNOSAT)

Part A: Multi-hazard risk index process

Part B: Multi-Criteria Decision Analysis/ Suitability Study process