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Hourly potential light availability maps at 10 m resolution over Switzerland.

Clare Webster1,2,3, Christian Ginzler4, Mauro Marty4

  • 1WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland. clare.webster@slf.ch.

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|November 28, 2025
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Summary
This summary is machine-generated.

The SwissRad10 dataset provides nationwide light availability maps at 10m resolution, crucial for understanding forest microhabitats and ecosystem dynamics. This detailed data reveals light patterns influenced by terrain and tree canopies throughout the year.

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Area of Science:

  • Ecology
  • Environmental Science
  • Forestry

Background:

  • Accurate light availability data is essential for ecological studies, microclimate modeling, and ecosystem research.
  • Existing datasets often lack the high resolution and comprehensive coverage needed to capture fine-scale light variations within forest environments.

Purpose of the Study:

  • To introduce the SwissRad10 dataset, a novel nationwide resource for light availability mapping in Switzerland.
  • To provide hourly light availability data at 10m resolution across a full annual solar cycle, incorporating detailed canopy and terrain information.

Main Methods:

  • Utilized the Canopy Radiation Model (CanRad) with high-resolution airborne lidar and terrain data (swissSURFACE3D).
  • Calculated sky-view factor and direct-beam transmissivity to estimate direct and diffuse light at the ground surface.
  • Modeled light availability for leaf-on, leaf-off, and terrain-only scenarios for all pixels.

Main Results:

  • Generated nationwide light availability maps at 10m and hourly resolution for Switzerland.
  • The dataset resolves shadows cast by individual trees, offering unprecedented detail.
  • Light availability was calculated considering both canopy structure (leaf-on/leaf-off) and terrain.

Conclusions:

  • The SwissRad10 dataset offers valuable insights into light availability dynamics and drivers across Switzerland.
  • It serves as a critical resource for research in forest microhabitat suitability, biogeochemistry, snow modeling, and carbon/water flux studies.
  • This data supports researchers, practitioners, and decision-makers in ecology and environmental sciences.