A spatially-explicit harmonized global dataset of critical infrastructure

Sadhana Nirandjan; Elco E. Koks; Philip J. Ward; Jeroen C.J.H. Aerts

doi:10.1038/s41597-022-01218-4

A spatially-explicit harmonized global dataset of critical infrastructure

Sadhana Nirandjan^*, Elco E. Koks, Philip J. Ward, Jeroen C.J.H. Aerts

^*Corresponding author for this work

Water and Climate Risk

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments.

Original language	English
Article number	150
Pages (from-to)	1-13
Number of pages	13
Journal	Scientific Data
Volume	9
Early online date	1 Apr 2022
DOIs	https://doi.org/10.1038/s41597-022-01218-4
Publication status	Published - 2022

Bibliographical note

Funding Information:
The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union’s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442.

Funding Information:
The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union?s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442.

Funding Information:
Natural hazards are a large source of potential damage, and therefore pose a major threat to CI. Climate change and the associated intensification and increased frequency of hazards will increase the impacts of natural hazards on CI, while socio-economic development will lead to an increase in the amount and value of CI exposed to hazards. Given these challenges it is no surprise that Building resilient infrastructure is an explicit part of Goal 9 of the Sustainable Development Goals (SDGs), with the aim of reducing the risks of natural hazards and climate change on society. This is supported by the UN Sendai Framework for Disaster Risk Reduction (SFDRR), which calls for assessing CI risk, and the development of open access databases on CI exposure to support risk assessment. ,,, ,– ,–

Publisher Copyright:
© 2022, The Author(s).

Funding

The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union’s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442. The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union?s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442. Natural hazards are a large source of potential damage, and therefore pose a major threat to CI. Climate change and the associated intensification and increased frequency of hazards will increase the impacts of natural hazards on CI, while socio-economic development will lead to an increase in the amount and value of CI exposed to hazards. Given these challenges it is no surprise that Building resilient infrastructure is an explicit part of Goal 9 of the Sustainable Development Goals (SDGs), with the aim of reducing the risks of natural hazards and climate change on society. This is supported by the UN Sendai Framework for Disaster Risk Reduction (SFDRR), which calls for assessing CI risk, and the development of open access databases on CI exposure to support risk assessment. ,,, ,– ,–

Funders	Funder number
SFDRR
UN Sendai Framework for Disaster Risk Reduction
VICI
European Research Council
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	VI.Veni.194.033, VI.Vidi.016.161.324, 453-13-006
EU-H2020 CoCliCo	101003598
Horizon 2020 Framework Programme	884442, 820712

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41597-022-01218-4

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Cite this

@article{7f21fbdc3f484cce9b3e77629cb71154,

title = "A spatially-explicit harmonized global dataset of critical infrastructure",

abstract = "Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world{\textquoteright}s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments.",

author = "Sadhana Nirandjan and Koks, \{Elco E.\} and Ward, \{Philip J.\} and Aerts, \{Jeroen C.J.H.\}",

note = "Funding Information: The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union{\textquoteright}s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442. Funding Information: The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union?s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442. Funding Information: Natural hazards are a large source of potential damage, and therefore pose a major threat to CI. Climate change and the associated intensification and increased frequency of hazards will increase the impacts of natural hazards on CI, while socio-economic development will lead to an increase in the amount and value of CI exposed to hazards. Given these challenges it is no surprise that Building resilient infrastructure is an explicit part of Goal 9 of the Sustainable Development Goals (SDGs), with the aim of reducing the risks of natural hazards and climate change on society. This is supported by the UN Sendai Framework for Disaster Risk Reduction (SFDRR), which calls for assessing CI risk, and the development of open access databases on CI exposure to support risk assessment. ,,, ,– ,– Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

doi = "10.1038/s41597-022-01218-4",

language = "English",

volume = "9",

pages = "1--13",

journal = "Scientific Data",

issn = "2052-4463",

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T1 - A spatially-explicit harmonized global dataset of critical infrastructure

AU - Nirandjan, Sadhana

AU - Koks, Elco E.

AU - Ward, Philip J.

AU - Aerts, Jeroen C.J.H.

N1 - Funding Information: The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union’s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442. Funding Information: The authors would like to thank the OpenStreetMap community for their contributions. The work was financially supported by the European Union?s Horizon 2020 Research and Innovation Programme. This research is part of the project Remote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT), grant number 820712. E.E.K. and P.J.W. were further supported by the Dutch Research Council (NWO) (Grant Nos. VI.Veni.194.033 and VI.Vidi.016.161.324) and the EU-H2020 CoCliCo project (grant number 101003598). J.C.J.H.A. was supported by the VICI grant nr. 453-13-006, and ERC advanced grant 884442. Funding Information: Natural hazards are a large source of potential damage, and therefore pose a major threat to CI. Climate change and the associated intensification and increased frequency of hazards will increase the impacts of natural hazards on CI, while socio-economic development will lead to an increase in the amount and value of CI exposed to hazards. Given these challenges it is no surprise that Building resilient infrastructure is an explicit part of Goal 9 of the Sustainable Development Goals (SDGs), with the aim of reducing the risks of natural hazards and climate change on society. This is supported by the UN Sendai Framework for Disaster Risk Reduction (SFDRR), which calls for assessing CI risk, and the development of open access databases on CI exposure to support risk assessment. ,,, ,– ,– Publisher Copyright: © 2022, The Author(s).

PY - 2022

Y1 - 2022

N2 - Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments.

AB - Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments.

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ER -

A spatially-explicit harmonized global dataset of critical infrastructure

Abstract

Bibliographical note

Funding

UN SDGs

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