RECEIPT’s researchers have just published a paper in Nature Scientific Data that presents a dataset for the spatial distribution of critical infrastructure (CI) around the world. The study, “A spatially-explicit harmonized global dataset of critical infrastructure”, carried out by Sadhana Nirandjan, includes the development of the first-of-its-kind index to express the spatial density of CI: the Critical Infrastructure Spatial Index (CISI). This dataset can be used to perform risk analyses, for example to identify areas where floods or earthquakes are likely to occur, and to assess which types of infrastructure would be at risk in case of a natural disaster.
Critical infrastructure at risk
Critical infrastructure (CI) is essential for the functioning of our daily lives and for the socio-economic development. Our societies are extremely dependent on telecommunications, transport or energy infrastructures to cover our basic needs.
Natural hazards, however, like earthquakes or flooding represent a serious threat for CI. Climate change is exacerbating the intensity and frequency of those hazardous events which can damage and destroy CI. These events can also trigger causal chains of disruptions affecting interconnected infrastructures and amplifying the consequences of those events worldwide.
The development of the dataset and applications
Information on the geospatial location for different types of infrastructure is extracted from OpenStreetMap. The study shows that this data can be successfully used to create an index for CI at the global scale. The index represents the spatial density of global CI on a scale of 0 to 1. Areas without CI were assigned a 0, and areas with the highest density of CI were given a 1.
As RECEIPT’s researchers expose on the coastal infrastructure’s storyline, there is a need to find ways to adapt and predict the impact of this kind of disruptive events. That is why this study is key for the risk assessment of CI. The global dataset can help identify vulnerable areas that need to adapt their infrastructures to climate threats as well as evaluate the risk of different types of infrastructures.
Our researchers conclude that the global dataset published on Nature’s journal Scientific Data “…will be a very valuable starting point for policymakers, planners, and researchers in several fields.” Next to risk assessments for natural hazards, the dataset can also be used, for instance, to evaluate various Sustainable Development Goals.
Nirandjan’s spatial dataset is freely accessible at Zenodo. The dataset’s code is also open source, meaning it can be freely accessed. This allows users to create their own datasets for different infrastructure types, spatial scales and resolutions, while also ensuring that the model can be further developed. The code is available via Github.
Nirandjan, S., Koks, E.E., Ward, P.J. et al. A spatially-explicit harmonized global dataset of critical infrastructure. Sci Data 9, 150 (2022). https://doi.org/10.1038/s41597-022-01218-4
Published on : 19 April 2022