AndreaBozzo/ceres-open-data-index huggingface dataset:
Snow Depth Mapping

The available datasets are snow depth maps with a spatial resolution of 2m generated from image matching of ADS 80/100 data. Image acquisition took place at peak of winter (time when the thickest snowpack is expected). The snow depth maps are the difference of a summer DSM from the winter DSM of the corresponding date . The summer DSM used is a product of image matching of ADS 80 data from summer 2013. In the available products buildings, vegetation and outliers were masked (set to NoData).
For the elimination of buildings the TLM layer (swisstopo) was used, because this layer might not represent exactly the
state of infrastructure at time of image acquisition, it is possible that mainly in dense settlement some buildings were not successfully masked. For the relevant area above treeline the masking of buildings showed good results. Vegetation got masked for a height above ground - 1m and was detected in a combination of summer and winter data sets. As Outliers were considered unrealistic snow depths caused by a failure of the image matching algorithm. Snow depths - 15m and smaller than - -15m were classified as outliers. Negative snow depth were kept, because of an uncertainty in image orientation accuracy. It is expected that in regions with negative snow depth also positive snow depth are underestimated by the same amount, which means that an estimation of snow volume should be carried out summing up the absolute values of snow depth (also the negative ones). For volume estimation in small regions the user has to take into account, that orientation accuracy of the images is roughly around 1-2 GSD (30cm), which propagates directly to the snow depth product. Areas which are not covered by snow got assigned a value of 0 as snow depth.
The work is published in: 
Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C., (2015). Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9 (1), 229-243. doi: 10.5194/tc-9-229-2015

Tags: aerial-imagery, avalanche, dsm, image-matching, snow-depth, snow-hydrology, snow-water-equivalent
Base cation dynamics in an Oriental beech forest

Throughfall, litterflow and soil solution were sampled during one whole year under five Oriental beech trees in a mixed Hyrcanian beech forest. The amounts of Ca2+, Mg2+, K+ and Na+ in these fluxes were calculated based on their concentrations and the sampled volumes, and subsequently compared with the respective fluxes in the rainfall and soil solution of an adjacent forest gap.
In addition six soil profiles, one close to every single tree and one in the forest gap, were analyzed for pH, CaCO3, organic matter and texture.

Tags: biogeochemical-cycling, calcium, fagus-orientalis-lipsky, magnesium, potassium
Translation between Checklist 2017 and Flora Indicativa

Landolt et al. (2010) indicator values are widely used in plant related ecological assessments. However, since the publication of the dataset, the national checklist of Switzerland (see Juillerat et al. 2017) has further evolved and the taxon names of the two are not congruent. Here, we present a translation between the two datasets. Translations were made by expert knowledge.
Juillerat, P., et al. 2017. _Flora Helvetica Checklist 2017: der Gefässpflanzen der Schweiz / de la flore vasculaire de la Suisse / della flora vascolare della Svizzera._ Info Flora, Genève.
Landolt, E., et al. 2010. _Flora indicativa: Ökologische Zeigerwerte und biologische Kennzeichen zur Flora der Schweiz und der Alpen._ Haupt,

Tags: indicator-values, switzerland, taxonomy, translation, vascular-plants
Sentinel-1 Synthetic Aperture Radar Composite Backscatter Time Series of Switzerland

The dataset contains a time series of countrywide Sentinel-1 synthetic aperture radar (SAR) composites for Switzerland and Liechtenstein starting in 2015. The temporal sampling step of the time series is 6 days and the compositing period 12 days resulting in 60 generated composites per year. Each composite contains the amplitude information of C-band backscatter and features a grid spacing of 10 m. The composites were generated according to the local resolution weighting (LRW) methodology described in Small et al. (2022, https://doi.org/10.1109/TGRS.2021.3055562). For the generation of each composite, backscatter information from all Sentinel-1 acquisitions of Switzerland and Liechtenstein during the compositing period was obtained.
The naming of each composite file follows the logic “S1_LRW_PD\-LRW compositing period in days\-\_SP\-Temporal sampling step in days\-_\-Start date and time for LRW composite generation\--\-End date and time for LRW composite generation\-.tif”, e.g. “S1_LRW_PD12_SP6_20150101000000-20150112235959.tif” for the first file. Each file contains four raster layers: 1) Vertically submitted and horizontally received (VH) and 2) vertically submitted and vertically received (VV) polarisation backscatter in the logarithmic dB scale, 3) composite local resolution, which is a measure for the quality of the pixel (for details, see Small et al. (2022, https://doi.org/10.1109/TGRS.2021.3055562), and 4) the number of contributing observations.
Contains modified Copernicus Sentinel data.

Tags: c-band, earth-observation, radar, remote-sensing, sar, sentinel-1, switzerland, time-series
Light-quality responses of photosynthetic, stomatal, and mesophyll traits of Alnus incana and Quercus ilex

Gas exchange, online isotope discrimination, and chlorophyll fluorescence measurements were conducted on fully expanded leaves of grey alder (*Alnus incana*) and holm oak (*Quercus ilex*) tree saplings under different fractions of blue light (0–100%). Blue light was supplemented with red light to maintain a constant total light intensity. A detailed description of the measurements is provided in Diao *et al.* (2025) (https://doi.org/10.1093/jxb/eraf305). These measurements generated a dataset describing the responses of key leaf physiological parameters to varying blue/red light fractions, including net photosynthetic rate, stomatal conductance, mesophyll conductance, the maximum carboxylation rate of RuBP, non-photochemical quenching, etc. The dataset was further used for photosynthetic limitation analysis to disentangle the relative biochemical, mesophyll, and stomatal limitations on photosynthesis under different light-quality conditions. The results of the photosynthetic limitation analysis are also provided here.

Tags: fluorescence, gas-exchange, light-quality, photosynthesis, stomata
Greater observer expertise leads to higher liverwort species richness in bryophyte surveys

This dataset contains bryophyte species count data and information about the observers bryophyte expertise for 2950 relevés conducted from 2011 to 2023 on 10-m2 plots in a long-term monitoring program in Switzerland. Plots were situated in raised bogs and fens of national importance, which were distributed across the whole country. The majority of the plots is represented by two relevés as sites are revisited every six years. The dataset was used in the paper mentioned below to test if species richness estimates differed among categories of observer expertise.
Moser T, Boch S, Bedolla A, Ecker KT, Graf UH, Holderegger R, Küchler H, Pichon
NA, Bergamini A (2025) Greater observer expertise leads to higher liverwort species richness in bryophyte surveys. _Journal of Vegetation Science_.

Tags: biodiversity-monitoring, cover, fen, liverworts, mosses, observer-bias, raised-bog, sphagnum, vegetation-survey
Swiss electricity system modeling -- HV grid - hydropower topology and inflows - renewable productions - past and forecast meteorological data

This dataset contains several useful components for **Swiss Electricity system modeling**:
1. **High-voltage Swiss grid**: 2019 snapshot of the high-voltage (-150kV) grid composed of : 
- Nodes: names, voltage, position. 
- Lines: ends nodes, resistance, power capacity. 
- Transformers: ends nodes, power capacity, resistance, tap ratio.
2. **Hydropower topology** : Representative description of Swiss reservoirs and plants (2019) composed of: 
- Plants: Lower reservoir, Upper reservoir, pump/turbine, debit, power capacity. 
- Reservoirs: Volume, altitude, position, canton. 
3. **Inflows** into all the reservoirs: hourly time series post-processed from PREVAH model outputs from 2009 to 2019.
4. **Wind production per node**: COSMO-1 data processed and scaled to match SFOE annual production. 
5. **Solar irradiance maps projected onto tilted surfaces**: hourly time series for 35° and 65° tilts, azimuth 180°. (same method as [Frischholz, Y. (2025)](https://www.doi.org/10.16904/envidat.632))
6. **Processed ERA5 (historical), ECMWF SEAS5 (seasonal forecast) and ECMWF TIGGE (short-term forecast)**:
- ERA5 Land: For inflow forecast model: historical runoff, snow depth, temperature and total precipitation per catchment (hourly, 2009-2019). For residual demand forecast model: historical temperature, u-v wind, ssrd per country (CH, AT, DE, FR, IT, hourly 2015-2019)
- ECMWF SEAS5: For inflow forecast model: same variables as ERA5 (yearly forecast starting from every 1st day of every month in 2019). For residual demand forecast model: same variables as ERA5 (yearly forecast starting from every 1st day of every month in 2019).
- ECMWF TIGGE: For inflow forecast model: same variables as ERA5 (two weeks forecast starting from every 1st day of every week in 2019). For residual demand forecast model: same variables as ERA5 (two weeks forecast starting from every 1st day of every week in 2019).
7. **Run-of-river production per electricity node**: 15-min resolution run-of-river production time-series (15min, 2009-2019). Raw data and documentation can be found on [https://data.sccer-jasm.ch/runofriver_production/2017-10-16/]. 
\
More details can be found on *README.txt*.

Tags: electricity-grid, forecast-models, hydropower, meteorological-data, renewable-energy, reservoir-inflow, solar-irradiance
TopoCLIM v1.0 code

Model code and documentation for the downscaling model TopoCLIM which provides methods to downscale climate timeseries from CORDEX RCM data. This scheme specifically addresses the need for hillslope scale atmospheric forcing timeseries for modeling the local impact of regional climate change projections on the land surface in complex terrain. The method has a global scope and is able to generate the full suite of model forcing variables required for hydrological and land surface modeling at hourly timesteps.
A working example is provided in this code archive but for full running of the scheme TopoSCALE is required https://doi.org/10.5194/gmd-7-387-2014 with code available at https://github.com/joelfiddes/tscaleV2. Standard library dependencies are given in the python requirements.txt of the archive with installation instructions in the README.md.
License GPL v.3

Tags: cordex, cryosphere, downscaling, rcm, toposcale
Seilaplan Tutorial: Load WMS layers as background maps

In order to digitally plan a cable line using the QGIS plugin ‘Seilaplan’, maps with various background information are helpful. In this tutorial we show you how to obtain maps that are helpful for cable line planning, for example a national map of Switzerland at different scales,  the NFI vegetation height model or the NFI forest mix rate. For this we explain what WMS datasets are and how to integrate them into QGIS. No download of large data is needed for this, only a good internet connection. Please note that the tutorial language is German!
Link for the integration of WMS data: https://wms.geo.admin.ch/
Link to the description on the Swisstopo website:
https://www.geo.admin.ch/en/geo-services/geo-services/portrayal-services-web-mapping/web-map-services-wms.html
Link to the Seilaplan website: https://seilaplan.wsl.ch
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Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung sind verschiedene Hintergrundkarten hilfreich. In diesem Tutorialvideo zeigen wir, was WMS Daten sind und wie man diese in QGIS einbinden kann. Dafür müssen die Daten nicht heruntergeladen werden. Es braucht lediglich eine gute Internetverbindung. Für die Seillinienplanung hilfreiche Karten sind bspw. die Landeskarte der Schweiz in verschiedenen Massstäben, das Vegetationshöhenmodell LFI oder der Waldmischungsgrad LFI. 
Link zur Einbindung der WMS Daten: https://wms.geo.admin.ch/
Link zur Beschreibung auf der Swisstopo Webseite: https://www.geo.admin.ch/de/geo-dienstleistungen/geodienste/darstellungsdienste-webmapping-webgis-anwendungen/web-map-services-wms.html
Link zur Seilaplan-Website: https://seilaplan.wsl.ch

Tags: cable-yarding, digital-elevation-model, digital-planning, geoinformation-system, open-source, qgis-plugin, seilaplan, swiss-geodata, wms-data
Seilaplan Tutorial: DTM download from swisstopo website

In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. As an alternative to using the ‘Swiss Geo Downloader’ plugin, the DTM can be obtained directly from Swisstopo. In this tutorial we explain step by step how to download the necessary DTM from the Swisstopo Website, and how to use it in QGIS for the digital planning of a cable line using the plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to the elevation model on the swisstopo website: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details
Link to the rope map website: https://seilaplan.wsl.ch
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Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Als Alternative zum Swiss Geo Downloader erklären wir in diesem Tutorial Schritt für Schritt, wie man das nötige Höhenmodell von der Swisstopo Webseite herunterladen und in QGIS zur Seillinienplanung verwenden kann. 
Link zum Höhenmodell auf der swisstopo Webseite: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details
Link zur Seilaplan-Website: https://seilaplan.wsl.ch

Tags: cable-yarding, digital-elevation-model, digital-planning, geoinformation-software, open-source, qgis-plugin, seilaplan, swiss-geodata, swisstopo
Seilaplan Tutorial: DTM download with SwissGeoDownloader

In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader
Link to Seilaplan website: https://seilaplan.wsl.ch
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Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.
Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader
Link zur Seilaplan-Webseite: https://seilaplan.wsl.ch

Tags: cable-yarding, digital-elevation-model, digital-planning, geoinformation-system, open-source, qgis-plugin, seilaplan, swiss-geo-downloader, swiss-geodata
Ramerenwald Close Range Remote Sensing Benchmark

Close Range Remote Sensing Benchmark for different LiDAR and photogrammetric Sensors in a mixed temperate forest.
Benchmarks are needed to evaluate the performance of different close-range remote sensing devices and approaches, both in terms of efficiency as well as accuracy. In this study we evaluate the performance of two terrestrial (TLS), one handheld mobile (PLS) and two drone based (UAVLS) laser scanning systems to detect trees and extract the diameter at breast height (DBH) in three plots with a steep gradient in tree and understorey vegetation density. As a novelty, we also tested the acquisition of 3D point-clouds using a low-cost action camera (GoPro) in conjunction with the Structure from Motion (SfM) technique and compared its performance with those of the more costly LiDAR devices.

Tags: 3d-point-cloud, forest-inventory, lidar, mobile-laser-scanning, structure-from-motion, terrestrial-laser-scanning, terrestrial-photogrammetry, unmanned-aerial-vehicle-laser-scanning
Seilaplan Tutorial: Merge DTM tiles

In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to Seilaplan website: https://seilaplan.wsl.ch
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Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.
Link zur Seilaplan-Website: https://seilaplan.wsl.ch

Tags: cable-yarding, digital-elevation-model, digital-planning, geodata-processing, geoinformation-system, open-source, qgis-plugin, raster-processing, seilaplan, swiss-geodata
Global species distributions for mammals, reptiles, and amphibians

We modelled the global distribution of 730 amphibian, 1276 reptile, and 1961 mammal species globally as a function of current climate at a 0.5° spatial resolution using four different predictor groups composed of different combinations of input variables: mean climatic conditions, spatial climatic variability, and temporal (interannual) climatic variability.

Tags: amphibians, chelsa, climate-variablity, generalized-additive-models, generalized-linear-models, interannual-climate-variability, iucn, mammals, niche-models, random-forests, range-maps, reptiles, sdm, species-distribution-models
Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples

For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles. 
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

Tags: 3d-ct-images, discrete-element-modelling, microstructure, snow-mechanics, spherical-model-snow, unconfined-compression-experiments
Compressive stick slip and snow-micro-quakes

When snow is compressed with a certain speed, micro-snowquakes are triggered in the porous structure of bonded crystals. The present dataset covers uniaxial compression experiments of snow at different strain rates and concurrent X-ray tomography imaging documenting this feature. 
The experiments were conducted in a micro-compression stage operated in the X-ray tomography scanner in the SLF cold laboratory. The dataset comprises the compression force data of 17 compression experiments, the 3D image data from 4 X-ray tomography scans and the results of numerical simulations.

Tags: compression-experiments, microstructure, snow, snow-mechanics, x-ray-tomography
Meteorological Time Series Aligned with Projected Temperature Changes

This dataset provides 50 years of seasonal synthetic hourly time series for five meteorological variables: incoming shortwave radiation, total precipitation, relative humidity, 2-meter air temperature and wind speed.
The data are generated from observational records (1990–present) from nine MeteoSwiss stations (ABO, BAS, BER, LUG, PUY, SCU, SIO, STG, WFJ). We use a sampling approach that preserves both the temporal structure and inter-variable dependencies. Specifically, the time series are constructed by drawing 7-day blocks from historical observations, ensuring realistic short-term variability and maintaining the physical coherence between variables.
The synthetic sequences are constrained to follow daily temperature change trajectories corresponding to three future climate scenarios for the period 2040–2070: RCP2.6, RCP8.5 and RCP0: a counterfactual scenario with no long-term warming trend, but with temperature variability consistent with the RCP2.6 one.
The temperature constraints are derived from projections downscaled at the staiton level, available at: https://www.envidat.ch//metadata/climate-change-scenarios-at-hourly-resolution

Tags: air-temperature, climate-change, meteo-station, precipitation, relative-humidity, shortwave-radiation, speed2zero, time-series, wind-speed
Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings. FORECOMON 2021 - the 9th forest ecosystem monitoring conference. 7–9 June 2021, Birmensdorf, Switzerland

Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings.
FORECOMON 2021 - the 9th forest ecosystem monitoring conference.
7-9 June 2021, WSL, Birmensdorf, Switzerland
The goal of FORECOMON 2021 is to highlight the extensive ICP Forests data series on forest growth, phenology and leaf area index, biodiversity and ground vegetation, foliage and litter fall, ambient air quality, deposition, meteorology, soil and crown condition. We combine novel modeling and assessment approaches and integrate long-term trends to assess air pollution and climate effects on European forests and related ecosystem services. Latest results and conclusions from local scale to European scale studies will be presented and discussed.
Copyright © 2021 by WSL, Birmensdorf
The authors are responsible for the content of their contribution.

Tags: air-pollution, forest, long-term-forest-ecosystem-research, long-term-monitoring, monitoring
Stand inventory data from the 10‐ha forest research plot in Uholka, Ukraine

In 2000, a permanent forest plot of 10 ha has been established in the core zone of the primeval beech forest of Uholka.
 All living and dead trees with a diameter at breast height (DBH) ≥ 60 mm were identified to species, DBH measured, stems tagged and mapped. 
Since then, the plot has been remeasured in 2005, 2010, and 2015. In total, 4,820 individual trees were measured with 14,116 individual measurements throughout all four inventories. 
In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka‐Shyrokyi Luh forest. This data set allows us to derive a high‐resolution digital elevation model (DEM) of the plot area.
The data set allows for important insights into the development and the spatial and temporal dynamics of primeval beech forests. 
The detailed dataset description can be found in Stillhard et. al (2019): https://doi.org/10.1002/ecy.2845

Tags: carpathian-biosphere-reserve, dem, fagus-sylvatica, forest, forest-dynamics, forest-structure, long-term-data-sets, permanent-forest-plot-data, primeval-beech-forest, stand-inventory-data