The context​

The extreme low-lying nature of the country’s topography makes the effects of climate change potentially devastating to a population dispersed sparsely across over 180 inhabited islands. Further, the economic and human impacts of climate change, including both, sudden disasters such as storms, floods and heatwaves, and slow-onset disasters such as erosion, water and soil salinity and crop losses, are already being felt. As it stands, these effects are unfortunately on course to increase exponentially and seriously threaten the livelihoods of those working in sectors including tourism, fisheries and farming – the primary industries of the islands.

The dispersed geography and the uniqueness of each island necessitates a hyperlocal approach to risk reduction and adaptation. Hyperlocal action requires hyperlocal data. However, the data ecosystem around DRR and CCA is particularly weak. The National Disasters Management Authority (NDMA) works with local councils to plan for disasters at the national level, but granular data about vulnerable building infrastructure and community assets is not always available, particularly at the island level. Improving data at this level requires real-time and granular data that goes beyond broad land use features. Geo-referenced data that includes both the conditions of the built environment and a mechanism to continually document changes over time are extremely important.

Approach

The UNDP Accelerator Lab in the Maldives prototyped a participatory mapping approach to try to fill this data gap. Participatory mapping allows people to contribute spatial data based on their local knowledge and ground observation through free and easily available digital tools.

The Lab set up our experiment on the island of Maafaru on the Noonu Atoll, partnering with the local council and gathering a group of volunteers from the local community. After the delivery of a brief training, the entire island was captured on a free street view imaging application. Using existing satellite imagery, drone imagery and this new street-level imagery, participants mapped the island’s building footprint, road network and critical infrastructure onto Open Street Map. While some worked on smartphones and laptops, digitally drawing lines and polygons, others pinned locations on paper maps. Using a mix of digital and analogue activities helped get the most out of all volunteers. The real intelligence accrued was the participants’ innate knowledge of their island and its neighbourhoods; this was well demonstrated as volunteers confidently identified various structures, points of interest and vulnerable buildings on the maps.

Incredibly, the Accelerator Lab was able to clean the data and generate a GIS base map of the island within a single day. This map then only needed a few volunteers to go out onto the streets and further validate the information and fill any gaps to bring this data up to a sufficient standard. Over the next two days, with a bigger group of volunteers, the Accelerator Lab further generated aHVCA map of Maafaru, mapping vulnerable infrastructure and areas prone to flooding and erosion.

How did data contribute to better policy?

The experiment demonstrated that citizen-generated data is very useful in bridging local data gaps, and can strengthen approaches to local planning. Based on the HVCA, the Accelerator Lab facilitated a co-creation workshop with the council and the volunteer mappers, to formulate the island's disaster management and disaster risk reduction plan.

The GIS base map is not only beneficial in strengthening the HVCA and formulating disaster management plans at the local level. Having a detailed map also helps establish important baseline data that can be used for more accurate risk modelling, as well as enabling loss and damage assessments to monitor and adapt to slow effects of climate change.

Where do we go from here?

In addition to local planning, the data generated at the local level needs to be interoperable with, and used for, centralized decision-making. This is why, beyond sharing the data for local action, the Lab actively explored how to integrate this data with national data systems on climate change and disaster risk reduction.

The Climate and Resilience unit of UNDP and UNESCAP were supporting the NDMA to develop a data portal for aggregating data on risks and using it for impact-based forecasting. The Lab worked with these teams to upload these data layers within the portal to be used with existing data.. If these functionality can be built on this portal, councils would be able to feed data generated through participatory mapping to the portal themselves. This will allow two things: firstly, local councils will be able to layer this data with other national datasets (such as meteorological data) for more informed planning; and secondly, national level stakeholders can make use of this localized data in their planning and decision making.