Agrivoltaics and artificial intelligence. New geographies of power
アグリボルタイクスと人工知能：新たな権力の地理 (AI 翻訳)
Simona Epasto, Maria Lúcia, Masiel Melissa Pereira
🤖 gxceed AI 要約
日本語
本論文は、営農型太陽光発電（アグリボルタイクス）におけるAI活用を、農村景観の社会・領土的影響の観点から考察する。欧州SYMBIOSYSTプロジェクトやGIS・UAVを用いた地理空間モニタリングの事例を通じ、予測モデルや3Dデジタルツイン、センサー統合型アグリテックが計画・ガバナンス・視覚表現を再形成する様を分析。AIは効率向上に寄与する一方、空間的不平等やアルゴリズムによる土地収奪、データ主権のリスクを生むと指摘し、参加型で場所に敏感な技術ガバナンスを提唱する。
English
This paper examines AI integration in agrivoltaic systems, focusing on socio-territorial implications for rural landscapes. Through case studies including the European SYMBIOSYST project and GIS/UAV geospatial monitoring, it analyzes how predictive modeling, 3D digital twins, and sensor-integrated agritech reshape planning, governance, and visual representation. While AI enhances operational efficiency, it introduces spatial asymmetries, risks of algorithmic land grabbing, and data sovereignty challenges. The authors advocate for a geography-informed framework promoting equity, transparency, and territorial justice.
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
日本では農地転用や地域共生が課題となる営農型太陽光の導入に、AI活用のガバナンス視点を提供。SSBJ開示や再エネ拡大政策と関連し、地域コミュニティ参加やデータ主権の考慮が求められる。
In the global GX context
Globally, this paper contributes to the discourse on AI in energy transitions, highlighting socio-territorial risks and governance needs. It complements ISSB/CSRD disclosure frameworks by emphasizing equity and transparency in renewable energy projects, relevant for just transition considerations.
👥 読者別の含意
🔬研究者:Critical geography perspective on AI in agrivoltaics, offering a framework to analyze power relations and territorial justice in energy transitions.
🏢実務担当者:Insights for agrivoltaic project developers on participatory governance and avoiding algorithmic land grabbing.
🏛政策担当者:Considerations for regulating AI in renewable energy to ensure equity, transparency, and community participation.
📄 Abstract（原文）
This paper explores the integration of Artificial Intelligence (AI) in agrivoltaic systems as a critical lens for understanding the socio-territorial implications of digital innovation in rural landscapes. Agrivoltaics, which combine agricultural production and solar energy generation on the same land, have emerged as a promising solution to the crises of energy transition and food security. However, their implementation raises significant questions about land use, community participation, and environmental justice. Through a series of case studies – including the European SYMBIOSYST project and two geospatial monitoring experiments using GIS and UAV technologies – the study investigates how AI-based tools such as predictive modelling, 3D digital twins, and sensor-integrated agritech platforms are reshaping the planning, governance, and visual representation of rural energy landscapes. While AI enhances the operational efficiency of agrivoltaic infrastructures and supports site-specific optimisation, it also introduces new spatial asymmetries, risks of algorithmic land grabbing, and challenges to data sovereignty. The analysis draws on critical geography to argue that AI should not be viewed merely as a technical enhancer but as a socio-technical actor that reconfigures power relations and decision-making in energy transitions. The cases discussed illustrate both the risks of centralised and extractive AI models and the opportunities for participatory and place-sensitive technological governance. The paper advocates for a geography-informed framework of AI adoption in the energy sector that promotes equity, transparency, and territorial justice.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.36253/jep-20879first seen 2026-08-08 04:45:41
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