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Harnessing Artificial Intelligence, Machine Learning, and Drone Technologies for Climate Change Monitoring and Mitigation

気候変動の監視と緩和のための人工知能、機械学習、ドローン技術の活用 (AI 翻訳)

Dr. Mala. C. Patil, Dr. A. M. Nageswara Yogi

Zenodo (CERN European Organization for Nuclear Research)📚 査読済 / ジャーナル2026-05-04#気候科学
DOI: 10.5281/zenodo.20025981
原典: https://doi.org/10.5281/zenodo.20025981

🤖 gxceed AI 要約

日本語

本稿は、気候変動監視・緩和におけるAI、機械学習、ドローンの相乗的活用を探る。ドローンによる高解像度リアルタイムデータをAIで解析し、森林伐採や温室効果ガス排出追跡などの応用を提示。気候科学の変革的ツールとしての可能性を論じる。

English

This review explores the synergistic use of AI, ML, and drone technology for climate change monitoring and mitigation. Drones provide high-resolution real-time data from remote areas, which AI/ML analyze for pattern detection and prediction. Applications include deforestation monitoring, GHG tracking, and disaster impact assessment.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

本稿は特定の日本事例を含まないが、日本企業・研究機関が進めるAI・ドローンによる環境モニタリング（森林管理、災害監視など）の文脈で参考になる。

In the global GX context

This paper provides a broad overview of AI/drone applications in climate monitoring, relevant globally. It does not address disclosure or transition finance, but underscores technology's role in climate data collection and modeling.

👥 読者別の含意

🔬研究者:A useful overview of current AI/drone applications in climate monitoring, highlighting methodological synergies.

📄 Abstract（原文）

The accelerating pace of climate change necessitates innovative tools and technologies to enhance our understanding, monitoring, and mitigation strategies. Artificial Intelligence (AI), Machine Learning (ML), and Unmanned Aerial Vehicles (UAVs), commonly known as drones, are emerging as powerful allies in climate research. This ABSTRACT explores the synergistic use of AI and ML algorithms with drone technology to collect, analyze, and interpret vast and complex environmental data. Drones provide high-resolution, real-time data from hard-to-reach or hazardous regions, such as glaciers, forests, and oceans. When combined with AI and ML, this data can be processed to detect patterns, predict environmental changes, and improve the accuracy of climate models. Applications include monitoring deforestation, tracking greenhouse gas emissions, studying atmospheric conditions, and assessing the impact of natural disasters. The integration of these technologies represents a transformative shift in climate science, offering scalable, cost-effective, and precise solutions for global environmental monitoring and decision-making.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。