Published January 13, 2026 | Version v1.0.0

RESSAIG – Renewable Energy Site Selection using Artificial Intelligence and Geographic Information System: Dataset 1 – GIS layers inputs for PV/green-hydrogen suitability mapping (Algeria)

  • 1. Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
  • 2. Unité de Recherche Appliquée en Energies Renouvelables, URAER, Centre de Développement des Energies Renouvelables, CDER, Ghardaïa, Algeria
  • 3. Department of Earth Sciences, University of Florence, Florence, Italy.

Description

This dataset contains the core input data used to develop GIS-based suitability mapping for utility-scale photovoltaic (PV) deployment and subsequent green-hydrogen (PtX) assessments in Algeria. It combines harmonised geospatial layers (resource availability, land-use constraints, and infrastructure/connection proxies) with time-series inputs used in the modelling workflow and in the generation/validation of derived techno-economic and environmental indicators, including LCOE (Levelized Cost of Electricity), LCOH (Levelized Cost of Hydrogen), PV suitability outputs, and natural gas saving (as a proxy for avoided emissions/energy substitution) maps.

 
 
 

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RESSAIG_Dataset1_InputData_v1.0.0.zip

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Additional details

Funding

European Commission
RESSAIG – Renewable Energy Site Selection using Artificial Intelligence and Geographic Information System 101197884

Dates

Created
2026-01-13
First public release