Scholarlink

Morocco's ambitious renewable energy goals necessitate an advanced, data-driven approach to urban planning, wherein a big data-enabled and AI-supported solar cadaster can play a pivotal role (Elhassan et al. in Proceedings of the 4th edition of international conference on Geo-IT and water resources 2020, Geo-IT and water resources 2020. ACM, Al-Hoceima Morocco, pp 1–5, 2020). By integrating large-scale geospatial datasets and applying AI-driven analytics, this cadaster can optimize land-use planning, enhance regulatory transparency, and foster investment readiness. However, its potential is hindered by fragmented data systems, outdated technological infrastructure, and limited cross-agency collaboration. This study examines these challenges through stakeholder insights from land tenure specialists, policymakers, spatial planners, and investors. Employing big data and AI tools, the research highlights critical inefficiencies in data governance and regulatory alignment. It proposes a comprehensive strategy combining centralized data repositories, predictive analytics, and AI-driven site assessments to unlock the solar cadaster's transformative capabilities.

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Geospatial Data-Driven Cadaster for Moroccan Land-Use Planning: Solar Cadaster Case Study

  • 章节

  • 发表日期：

    2025年

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  • Youssef Rissouni,
  • Elhassan Jamal,
  • Hicham Jamil,
  • Rachid El Ansari,
  • Bouabid El Mansouri,
  • Jamal Chao,
  • Aniss Moumen

摘要

Morocco's ambitious renewable energy goals necessitate an advanced, data-driven approach to urban planning, wherein a big data-enabled and AI-supported solar cadaster can play a pivotal role (Elhassan et al. in Proceedings of the 4th edition of international conference on Geo-IT and water resources 2020, Geo-IT and water resources 2020. ACM, Al-Hoceima Morocco, pp 1–5, 2020). By integrating large-scale geospatial datasets and applying AI-driven analytics, this cadaster can optimize land-use planning, enhance regulatory transparency, and foster investment readiness. However, its potential is hindered by fragmented data systems, outdated technological infrastructure, and limited cross-agency collaboration. This study examines these challenges through stakeholder insights from land tenure specialists, policymakers, spatial planners, and investors. Employing big data and AI tools, the research highlights critical inefficiencies in data governance and regulatory alignment. It proposes a comprehensive strategy combining centralized data repositories, predictive analytics, and AI-driven site assessments to unlock the solar cadaster's transformative capabilities.