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Frontiers in Climate
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Frontiers in Climate
Article . 2025
Data sources: DOAJ
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Measuring climate resilience in low- and middle-income countries using advanced analytical techniques and satellite data: a systematic review

Authors: Patricia Codyre; Patricia Codyre; Pearse C. Murphy; Pearse C. Murphy; Dúalta Ó Fionnagáin; Dúalta Ó Fionnagáin; Jemima O’Farrell; +11 Authors

Measuring climate resilience in low- and middle-income countries using advanced analytical techniques and satellite data: a systematic review

Abstract

Anthropogenic changes to our Earth’s climate system are amongst the most pressing challenges facing humankind. Advances in satellite systems for earth observation are revolutionizing our ability to monitor and assess environmental changes, manage natural resources and respond to global challenges, including climate change and disaster management. Here we review the potential for satellite Earth Observation and artificial intelligence solutions to accelerate climate action at scale. The satellite industry already has extensive expertise in emergency communication and is a critical element of any comprehensive global emergency warning and messaging infrastructure to support unserved populations in remote and rural regions. We review the literature demonstrating how current technologies and methodologies that have been developed to leverage satellite-based information and the critical role that satellite data plays to support vulnerable populations in Low-and middle-income countries. Whilst previous reviews focus on isolated climate indicators, our systematic review demonstrates how the fusion of remote sensing, AI-driven analytics and geospatial data can provide a more comprehensive, real-time assessment of climate vulnerabilities and adaptive capacities. We situate our review within established global frameworks, such as: the Sustainable Development Goals (SDGs) addressing goals related to climate action (SDG 13) and zero hunger (SDG 2). The Sendai Framework for Disaster Risk Reduction, the Paris Agreement: supporting Nationally Determined Contributions (NDCs) with data-driven strategies and the delivery of the Early Warnings for All initiative which calls for the implementation of early warning systems to protect all global populations by 2027.

Keywords

Environmental sciences, remote sensing, machine learning, climate resilience, emergency preparedness, GE1-350, environmental informatics, satellite development

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold
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