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REVIEW article
Front. Clim.
Sec. Climate Action
Volume 7 - 2025 | doi: 10.3389/fclim.2025.1514423
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We sincerely thank you and all the anonymous reviewers for your valuable input on our manuscript. We are pleased that the reviewers "appreciate the 'positionality' of our work (R1) and that our use of advanced analytical techniques 'provides a robust methodological foundation' for our conclusions (R2). It is gratifying to see that our review has been acknowledged for addressing "a highly relevant topic, specifically exploring how satellite-based solutions, combined with artificial intelligence (AI), can significantly accelerate climate action at scale, from local to global levels" (R3). Additionally, we appreciate the recognition that our review "effectively identifies gaps in the field and offers well-grounded recommendations for improving satellitebased climate resilience strategies" (R4).We would like to thank you for your thoughtful feedback during this review, incorporating these valuable suggestions strengthens the review.In response, we have now prepared a revised version which addresses the reviewers' concerns. Our responses to these points are itemised below (in red text).We hope that this revised manuscript will be considered suitable for publication. Yours sincerely.
Keywords: environmental informatics1, remote sensing2, climate resilience3, emergency preparedness4, machine learning5, satellite development6, LMIC7, Climate action8
Received: 20 Oct 2024; Accepted: 27 Mar 2025.
Copyright: © 2025 Codyre, Murphy, Ó Fionnagáin, O'Farrell, Tessema, Golden, Spillane and Geever. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Patricia Codyre, Ryan Institute, University of Galway, Galway, Ireland
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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