Organization:
Occitanie Region (Region)

Brief description of the Organization launching the Challenge:
One of the sixteen regions of France, Occitanie is the second largest region with 72 000 km2. This area is recognised as a hotspot for biodiversity in France 

Region:
Occitanie / Pyrénées-Méditerranée (France)

Description of the Challenge:

Light pollution represents a major environmental pressure for biodiversity. Artificial light at night contributes to habitat loss and fragmentation for many species whose life cycles depend on natural day-night light cycles. By disrupting dark ecological networks, it compromises ecological connectivity for nocturnal, crepuscular, and dawn-active species. 
In this context, public authorities need reliable spatial data on light pollution to integrate nighttime darkness into ecological network conservation and land-use planning.
The Occitanie Regional Authority (France) has already taken a step in this direction by producing two editions (2020 and 2023) of a regional light pollution map. These maps provide a valuable basis for identifying light pollution hotspots and supporting the implementation of a dark ecological network. However, ensuring their long-term operational sustainability raises several challenges:

• Data sovereignty: The current light pollution maps rely on non-European satellite data (notably VIIRS/NOAA), creating a dependency that undermines digital sovereignty and may affect the long-term continuity of the service.
• Cost-efficient updates: Producing regular regional light pollution maps requires substantial processing resources, making annual updates difficult to sustain operationally.
• Operational decision support: Local authorities lack simulation tools to evaluate the ecological consequences of partial or complete public lighting switch-off scenarios before implementing them.

What we expect from the B2G initiative

• Identify and mobilise European Earth observation data sources (e.g. Copernicus, ESA, EUMETSAT) capable of supporting annual regional monitoring of light pollution, with appropriate spatial and temporal resolution. 
• Develop automated, scalable and cost-efficient workflows for regularly updating the regional light pollution map, ensuring its long-term operational sustainability. 
• Develop AI-powered simulations and decision-support tools enabling local authorities to assess the ecological effects of public lighting management scenarios (e.g. partial or complete switch-off), compare before/after situations, and identify interventions that maximise ecological connectivity while minimising implementation costs.

ADDITIONAL INPUT:

Bennie J, Duffy JP, Davies TW, Correa-Cano ME & Gaston KJ (2015) Global Trends in Exposure to Light Pollution in Natural Terrestrial Ecosystems. Remote Sensing, 7(3), 2715-2730. https://doi.org/10.3390/rs70302715 
Sanders D, Frago E, Kehoe R et al. (2021) A meta-analysis of biological impacts of artificial light at night. Nature Ecology & Evolution 5, 74-81. https://doi.org/10.1038/s41559-020-01322-x 
Sordello R (2017) Les conséquences de la lumière artificielle nocturne sur les déplacements de la faune et la fragmentation des habitats: une revue. Bulletin de la Société des naturalistes luxembourgeois, 119, 39-54. https://www.snl.lu/publications/bulletin/SNL_2017_119_039_054.pdf

Your Challenge in just one question:
How can data satellite and AI provide tools to study the dark infrastructure in Occitanie? 

Topics:

• Earth Observation (EO)
• AI & Data Analytics
• Biodiversity & Ecosystems 

Expected role of Service Provider:

• Data Supply & Processing
• Consultancy & Feasibility Study