Published June 21, 2026 | Version v3

Bern Landscape Change Explorer Landscape Robustness Results

Description

GENERAL INFORMATION

1. Title of Dataset: Bern Landscape Change Explorer Landscape Robustness Results.    

2. Author Information

A. Principal Investigator Contact Information
Name: Benjamin Black
Institution:  Institute for Spatial and Landscape Development, Swiss Federal Institute of Technology (ETH) 
Address:  HIL H 52.1, Stefano-Franscini-Platz 5 CH-8093 Zürich, Switzerland
Email: bblack@ethz.ch

B. Additional researcher Contact Information
Name: Manuel Kurmann
Institution:  Institute for Spatial and Landscape Development, Swiss Federal Institute of Technology (ETH) 
Address:  HIL H 52.1, Stefano-Franscini-Platz 5 CH-8093 Zürich, Switzerland
Email: mankurma@ethz.ch

C. Additional researcher Contact Information
Name: Isabel Nicholson Thomas
    Institution:  Institute for Spatial and Landscape Development, Swiss Federal Institute of Technology (ETH)
    Address:  HIL H 52.1, Stefano-Franscini-Platz 5 CH-8093 Zürich, Switzerland
Email: inthomas@ethz.ch

3. Date of data collection: 2025-06-01 > 2026-01-1 

4. Geographic location of data: Switzerland 

SHARING/ACCESS INFORMATION
1. Licenses/restrictions placed on the data: Creative Commons Attribution 4.0 International 

2. Recommended citation for this dataset: Black, B., Kurmann, M., & Nicholson Thomas, I. (2026). Bern Landscape Change Explorer Landscape Robustness Results (Version 1.0.0) [Data set]. ETH Zurich. https://doi.org/10.5281/zenodo.18327228

DESCRIPTION/REPRODUCIBILITY: 
- This dataset contains rasters of landscape robustness for the Bern Landscape Change Explorer project.
- All rasters are projected in the CH1903+ / LV95 coordinate reference system and share the same extent and resolution (1 hectare).
For detailed descriptions of the data generation process, raster value interpretation and suggested colour scheme, please refer to the accompanying metadata files:
-  BeschreibungMetadatenRobustheit.pdf
- MetadataDescriptionRobustness.pdf
- DescriptionMetadonneesRobustesse.pdf

For the robustness evaluation, three continuous raster indicators are provided for each topic: level,
mean change, and certainty (also referred to as stability). The level indicator is stored in files with
the prefix robustness_mean_ and describes the value averaged across all scenarios in the year 2060.
The mean change indicator is stored in files with the prefix robustness_mean_difference_ and describes
the mean cumulative change between 2025 and 2060 across all scenarios and future points in time. The
certainty indicator is stored in files with the prefix robustness_UD_ and describes the agreement
between scenarios with regard to unfavourable deviations. All three indicators are available for
ecosystem services (ES), biodiversity (SDM), and the combination of ecosystem services and
biodiversity (ES_SDM). In addition, two pre-classified categorical rasters are provided for each topic,
one combining level and certainty (prefix robustness_class_mean_) and one combining mean change and
certainty (prefix robustness_class_mean_difference_); these contain the robustness classes shown on
the platform as ready-classified grid layers.

Included files:

  • BeschreibungMetadatenRobustheit.pdf
  • MetadataDescriptionRobustness.pdf
  • DescriptionMetadonneesRobustesse.pdf
  • robustness_mean_ES.tif
  • robustness_mean_SDM.tif
  • robustness_mean_ES_SDM.tif
  • robustness_mean_difference_ES.tif
  • robustness_mean_difference_SDM.tif
  • robustness_mean_difference_ES_SDM.tif
  • robustness_UD_ES.tif
  • robustness_UD_SDM.tif
  • robustness_UD_ES_SDM.tif
  • robustness_class_mean_ES.tif
  • robustness_class_mean_SDM.tif
  • robustness_class_mean_ES_SDM.tif
  • robustness_class_mean_difference_ES.tif
  • robustness_class_mean_difference_SDM.tif
  • robustness_class_mean_difference_ES_SDM.tif

 

Files

blce-robustness-data-archive.zip

Files (31.0 MB)

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Additional details

Funding

Wyss Academy for Nature

Dates

Updated
2026-06
Update to Data & Metadata-Files

Software

Repository URL
https://doi.org/10.5281/zenodo.18202087
Programming language
R , Python
Development Status
Active