Intro

By 2050, only in Africa, 113 million people are estimated to relocate within their country due to climate reasons, and many others will remain in place despite the growing risks. The Africa Climate Mobility Initiative’s platform (initiative coordinated by the Global Climate Change Mobility (GCCM)) was launched to forecast the impacts of climate change on the continent and show how climate change is already increasing forced migration and displacement, referred to as ‘climate mobility’.

The platform, launched for the 2022 UN Climate Change Conference in Sharm el-Sheikh (COP27), is meant to serve as an information source for climate mobility and ignite policy change. Provided with the data from the cutting-edge Africa Climate Mobility Model, it was essential to convert this complex concept into tangible and digestible insights to inform and encourage change. We took quite a hybrid approach in how we display the data on the platform, not settling on one solution but deciding on the best solution case by case, and making the Content Management System (CMS) a key feature that ensures the flexibility and scalability of the platform.

We worked alongside the GCCM team to understand the target users and their goals, and we developed technical strategies to address the users’ needs. In this article, we draw the three ways of using the core project data through different technologies to engage with users, inform them with detail, and allow them to explore the research outcomes further.

Image 2. A 3D map showing people leaving Ethiopia’s Adama Valley.

Engaging through powerful visuals

Users are first introduced to data through visually appealing representations on 3D maps. These 3D maps show localized insights exemplifying how the reality of people living there will be very different across geographies due to climate change.

Together with the GCCM team, we selected a location that would best convey the main message of each story. After, we used the model results and publicly available datasets to generate three different images for each location: the data layer, a grayscale elevation data layer, and a rendered 3D elevation model. These three images, when put together, result in a compelling 3D map.

We generated the data layer by researching and filtering the original dataset on QGIS to identify the metric that would best support the story insight. We transformed the data format and exported the layer as a vector together with contextual information (political boundaries, water bodies, etc). We used Python to fetch and process elevation data as grayscale images for all locations. The elevation data layer was then brought into Blender to create a realistic 3D render. These three files per location were stored in the platform CMS and used to display and animate the final visuals in the platform:

In the platform, the MapboxGL library renders the basemap, which provides geographical context and allows overlaying information on top of it. The topographic map and data layer are superimposed on the map in the same WebGL context as Mapbox, which leads to optimal runtime performance, and smaller bundle size. The grayscale elevation layer, although not visible, is used to generate the map reveal animation. By including the MapboxGL flyover between story maps and reveal animations, we ensured that these data snippets attracted users’ attention and encouraged them to learn more about the topic.

Image 6: Graphs overview.

Informing through effective data visualization

More in-depth data insights are shared on each of the 11 stories on the platform. To better inform and aid understanding of the topic, these insights are backed by graphs which, in comparison to 3D maps, present a more detailed view of the project data — such as analytical maps, trends over time including uncertainty margins, possible scenarios, or demographic breakdowns.

Together with the GCCM team, we explored how the placement, content, and format of each graph would best support the narrative of the project. The goal here was to create simple and straightforward data visualizations that, in combination with text, shed light on complex data.

After extracting the data for all graphs, we automated the production of all figures and maps using Python and QGIS. We exported the rendered figures as vector images which were then manually adjusted to align with the platform’s visual design, creating unique visuals. The final figures are uploaded on the platform via the CMS, through which we could also create and update visual legends, textual insights, sources, and captions.

Exploring research data

The platform also hosts a map portal containing 108 unique data layers (accounting for the number of indicators, scenarios, timeframes, units, and resolutions) from the Africa Climate Mobility Model and is directed toward users looking to dive deeper into the topic. Users can explore data in different scenarios and timeframes with the map portal selectors, and the high-resolution data unfolds automatically when zooming in.

Image 9: Some of the datasets that make up the content of the map portal.

We worked with the researchers who developed the Africa Climate Mobility Model to understand the data, learn how it was generated, and how it could be used in the platform. Once selected the portal datasets, we built a pipeline that would convert source geospatial files to geoJSONs that could be uploaded as Mapbox source sets. We built each source set to contain data for all scenarios and time periods available for a single metric at a specific resolution. These source sets were then converted into tilesets that allow us to render vector or raster data on the web as users navigate maps in an efficient manner.

In the platform, the CMS controls the available dataset metadata (available scenarios, timeframes, units, resolutions) as well as the layer styling and legends, while the data is stored on Mapbox and fetched through MapboxGL. The hybrid approach of combining platform CMS and Mapbox allows for full flexibility.

Image 10: Navigation within the map portal.

Summary

Leveraging technology can be a powerful tool to not only unravel complex topics like climate mobility, but also to promote social change. Intuitive platforms such as Africa Climate Mobility Initiative’s platform are effective information hubs that can engage, inform, and help users explore knowledge more in-depth to develop plans that require urgent action.

Image 11: Project overview.

Visit the project “Voices from the Frontlines” to learn more about climate mobility in Africa.

Acknowledgements

Thanks to Pietro Lodi and Rugile Dunauskaite for their contributions to this article.