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Mapping Climate Risk for Education Planning in the Caribbean
A project by CDEMA, OpenDevEd and UNOSAT
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Overview
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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.
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.
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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.
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
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.