The Convergence of High-Resolution Geospatial Analytics and Next-Generation Mitigation Technologies: A Framework for Climate Resilience in the 2020s
高解像度地理空間分析と次世代緩和技術の融合：2020年代の気候レジリエンスのためのフレームワーク (AI 翻訳)
Dr. Ch. Sudhakar
🤖 gxceed AI 要約
日本語
本論文は、AI駆動の高解像度地理空間分析とDAC、グリーン水素、ペロブスカイト太陽電池などの次世代緩和技術を統合したフレームワークを提案する。1.5℃目標達成に向け、AI・電化のパラドックスやグローバル・サウスの社会経済的影響を分析し、インドの2025年排出強度目標規則を参照。最終的に、データ駆動型監視と低炭素インフラを連携させる「システム・オブ・システムズ」アプローチの必要性を強調する。
English
This paper proposes a framework integrating AI-driven high-resolution geospatial analytics with next-generation mitigation technologies such as Direct Air Capture, green hydrogen, and perovskite photovoltaics. It addresses the 1.5°C target, analyzing the AI-electrification paradox and socio-economic implications for the Global South, citing India's 2025 emission intensity rules. It concludes that a system-of-systems approach is needed, linking data-driven monitoring with scalable low-carbon infrastructure.
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
日本はグリーン水素やDACなどの技術開発を進めており、本フレームワークはAIと物理技術の統合によるGX戦略の参考となる。特に、システム全体最適化の視点は、日本のカーボンニュートラル実現に向けた政策立案に示唆を与える。
In the global GX context
Globally, this paper addresses the need for an integrated approach combining digital intelligence and physical mitigation technologies. It highlights the equity dimension for the Global South, relevant for international climate finance and technology transfer discussions under the Paris Agreement.
👥 読者別の含意
🔬研究者:Provides a conceptual framework for integrating AI, geospatial analytics, and mitigation tech, suitable for further empirical research.
🏛政策担当者:Emphasizes the need for system-of-systems approaches and references India's GHG intensity rules, offering a policy model for emerging economies.
📄 Abstract（原文）
As the global community confronts the escalating volatility of the "critical decade," the integration of advanced environmental sciences with disruptive climate technologies has moved from a peripheral strategy to a foundational necessity. This paper explores the synergistic potential of digital intelligence and physical engineering in addressing the 1.5°C climate threshold. It first reviews the evolution of Advanced Environmental Monitoring, specifically focusing on how high-resolution geospatial analytics powered by AI and quantum-enhanced satellite telemetry provide the high-fidelity data required for real-time ecological interventions. It then transitions into an analysis of Next-Generation Mitigation Technologies, technical scaling of Direct Air Capture (DAC), Green Hydrogen value chains, and Perovskite-based photovoltaics. A significant portion of the study is dedicated to the "AI-Electrification Paradox," analyzing the tension between the energy demands of advanced computation and its role in optimizing smart grids. Furthermore, the paper evaluates the socio-economic implications of these technologies within the context of the Global South, citing frameworks like India’s Greenhouse Gas Emission Intensity Target Rules 2025 . By synthesizing technical data with policy analysis, this study concludes that climate resilience is no longer achievable through isolated innovations. Instead, it requires a "system-of-systems" approach. In this model, data-driven monitoring directly informs the deployment of scalable, low-carbon infrastructure. This holistic strategy ensures a scientifically rigorous and equitable transition toward a sustainable global economy, bridging the gap between technological potential and real-world impact.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/21312426first seen 2026-07-13 04:24:58
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