Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture
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...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Netherlands
2023
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| Online Access: | https://hdl.handle.net/1721.1/151065 |
| _version_ | 1811096671914819584 |
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| author | Noy, Ilan Blanc, Elodie Pundit, Madhavi Uher, Tomas |
| author2 | Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change |
| author_facet | Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change Noy, Ilan Blanc, Elodie Pundit, Madhavi Uher, Tomas |
| author_sort | Noy, Ilan |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T16:47:12Z |
| format | Article |
| id | mit-1721.1/151065 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:47:12Z |
| publishDate | 2023 |
| publisher | Springer Netherlands |
| record_format | dspace |
| spelling | mit-1721.1/1510652024-01-22T18:22:34Z Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture Noy, Ilan Blanc, Elodie Pundit, Madhavi Uher, Tomas Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change 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. 2023-07-10T18:37:36Z 2023-07-10T18:37:36Z 2023-07-04 2023-07-09T03:17:38Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/151065 Noy, Ilan, Blanc, Elodie, Pundit, Madhavi and Uher, Tomas. 2023. "Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture." PUBLISHER_CC en https://doi.org/10.1007/s11069-023-06080-0 Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer Netherlands Springer Netherlands |
| spellingShingle | Noy, Ilan Blanc, Elodie Pundit, Madhavi Uher, Tomas Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture |
| title | Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture |
| title_full | Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture |
| title_fullStr | Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture |
| title_full_unstemmed | Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture |
| title_short | Nowcasting from space: tropical cyclones’ impacts on Fiji’s agriculture |
| title_sort | nowcasting from space tropical cyclones impacts on fiji s agriculture |
| url | https://hdl.handle.net/1721.1/151065 |
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