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Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture

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Author(s)
Noy, Ilan
•
Blanc, Elodie
•
Pundit, Madhavi
•
Uher, Tomas
Date Issued
July 4, 2023
Publisher
Springer Netherlands
Citation
Noy, Ilan, Blanc, Elodie, Pundit, Madhavi and Uher, Tomas. 2023. "Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture."
Version
Final published version
Abstract
Abstract Ground-based disaster damage assessments typically take the form of a team of experts being sent to the affected areas to conduct a survey. This approach is time-consuming, difficult, and costly. An alternative to this is an assessment based on satellite data, which can provide faster, cheaper, and possibly accurate insights into disaster’s specific impacts. An even timelier option of disaster ‘nowcasting’ is supposed to inform on impacts during or very shortly after the event. Typically, this has been done using risk models, but these usually do not account for compounding and cascading effects. We propose a novel nowcasting approach for tropical cyclones employing pre-existing socio-economic and demographic data and calibrated with satellite data. The method could be used to assess cyclone impacts based only on its known trajectory, and even before post-event satellite imagery is available. We investigate the feasibility of this approach focusing on Fiji and its agricultural sector. We link remote sensing data with available household surveys and the agricultural census data to identify potential correlates of vegetation damage from cyclones. If robust enough, these correlates could later be used for nowcasting cyclone impacts. We show that remote sensing data, when combined with pre-event socio-economic and demographic data, can be used for both nowcasting and post-disaster damage assessments.
MIT Department
Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change
Terms of Use
Creative Commons Attribution
http://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/151065
DOI of Published Version
https://doi.org/10.1007/s11069-023-06080-0
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