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Spatial planning is key to guiding the revitalization of rural territories like “España Vacía” towards sustainable development. However, current tools are insufficient to address the complexity of the Doughnut Economics framework. This research, following a Design Science Research (DSRM) approach, proposes a methodology and a geo-technological workflow prototype. This system integrates Artificial Intelligence (AI), adapted Explainable AI (XAI), and interactive visualization to support local technicians. The objective is to operationalize the Doughnut, enabling systemic analysis and informed decision-making while prioritizing usability and free/open-source software. We hypothesize that the integration of adapted XAI and interactive visualization will significantly enhance trust, understanding, and adoption of AI tools by non-expert users. The expected contribution is a validated, user-centred method connecting sustainability theory and advanced AI with local practice.

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Spatial Planning with Artificial Intelligence for Sustainable Development

  • 会议论文

  • 发表日期：

    2026年

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  • Alberto MP-Moneo,
  • Angélica González-Arrieta,
  • Javier Parra

摘要

Spatial planning is key to guiding the revitalization of rural territories like “España Vacía” towards sustainable development. However, current tools are insufficient to address the complexity of the Doughnut Economics framework. This research, following a Design Science Research (DSRM) approach, proposes a methodology and a geo-technological workflow prototype. This system integrates Artificial Intelligence (AI), adapted Explainable AI (XAI), and interactive visualization to support local technicians. The objective is to operationalize the Doughnut, enabling systemic analysis and informed decision-making while prioritizing usability and free/open-source software. We hypothesize that the integration of adapted XAI and interactive visualization will significantly enhance trust, understanding, and adoption of AI tools by non-expert users. The expected contribution is a validated, user-centred method connecting sustainability theory and advanced AI with local practice.