Using the Power of Geospatial Intelligence to Build Trust for the Renewable Energy Transition
再生可能エネルギー移行の信頼構築における地理空間情報の活用 (AI 翻訳)
Alice Kesminas
🤖 gxceed AI 要約
日本語
本稿は、再生可能エネルギープロジェクトの選定・計画・運用における地理空間データとAIの役割を考察する。これらのツールは、自然保護や地域社会の価値とのバランスを取る可能性を持つが、不透明なデータやアクセス障壁が不信感を深めるリスクもある。責任ある実装のためには、トレーサビリティ、公平なデータ、包摂的な意思決定が不可欠であり、信頼構築と公正なエネルギー移行に貢献できると論じる。
English
This chapter examines how geospatial data and AI can support renewable energy site selection and planning while balancing nature conservation and community values. It warns that poorly implemented tools risk deepening mistrust due to biased data and lack of transparency. The authors argue for traceable, fair, and inclusive design to rebuild trust and ensure an equitable energy transition.
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
日本では再生可能エネルギーの導入拡大に伴い、地域コミュニティとの軋轢が課題となっている。地理空間情報を活用した合意形成プロセスの透明性向上は、日本のRE政策にも示唆を与える。
In the global GX context
The paper addresses global challenges of social licence for renewable energy projects. Its emphasis on transparency, accountability, and inclusive decision-making aligns with growing demands for just transitions in international climate policy.
👥 読者別の含意
🔬研究者:Provides a critical framework for studying the social and ethical dimensions of geospatial AI in energy transitions.
🏢実務担当者:Highlights pitfalls and best practices for using geospatial tools in RE project planning to maintain community trust.
🏛政策担当者:Offers principles for regulatory frameworks that ensure geospatial and AI technologies support equitable energy transition outcomes.
📄 Abstract（原文）
This chapter discusses the role of geospatial data and tools in supporting successful renewable energy (RE) site selection, planning, design, and operations. With the growth in integration of technologies, such as artificial intelligence (AI), 3D modelling, and near real-time environmental data, geospatial intelligence has the potential to better balance RE project targets with nature conservation, community values, and competing land-use priorities. However, this potential is emerging amid community opposition and loss of social licence for RE projects. If not implemented responsibly, geospatial and AI-driven tools risk deepening mistrust, particularly when they rely on low-quality or biased data, lack transparency, are inaccessible to non-experts, or reinforce existing social and environmental inequities through flawed optimisation processes. To avoid undermining the transition to RE, this chapter argues that geospatial and AI technologies must be traceable, grounded in fair and high-quality data, and designed for transparency, accountability, and accessibility. Crucially, they must support inclusive, place-based decision-making. When developed and applied responsibly, these tools offer a powerful opportunity to rebuild trust and accelerate a just and equitable energy transition.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1201/9781003638308-6first seen 2026-06-04 04:40:02
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