en: Data obtained in the free-air CO2 enrichment (FACE) experiment at Hofstetten, NW Switzerland, between 2009 and 2016. This dataset contains analyses of the soil solution throughout the experiment, especially for nitrate, as well as different analyses done at the end of the experiment: ammonium and nitrate captured by ion-exchange resin bags and extracted from soil cores, gross N mineralisation and nitrification measured by isotope dilution.

en: soil picea-abies forest co2 face nitrogen

en: Nitrogen availability under trees exposed to CO2 enrichment (FACE)

en:
Resource Title: Resin bags
    Size: 1237 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/594288d3-95ff-4ad6-914e-d3e9c1d0ea42/download/resin-bags.csv
    Description: Ammonium, nitrate and their 15N in resin bags

en:
Resource Title: Gross N mineralisation and nitrification
    Size: 1183 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/f6a9e85f-187b-4a55-9f57-e243d14906ab/download/mineralisation-nitrification.csv
    Description: Gross rates of N mineralisation and nitrification (15N dilution)

en:
Resource Title: Water analyses
    Size: 65553 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/50749920-cf85-4140-8802-54beffcf490e/download/water-analyses.csv
    Description: Analyses of water, especially soil solution

en:
Resource Title: Collection points
    Size: 453 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/1e7dfaf0-d504-4bab-ae3b-8f96181b4e84/download/points.csv
    Description: Collection points under the trees

en:
Resource Title: Collection of soil solution
    Size: 33840 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/3cfe06e1-c280-4b18-903a-321ceef6044a/download/soil-solution.csv
    Description: Soil solution collected by suction cups

en:
Resource Title: Soil C and N
    Size: 1298 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/dc99385c-0ab8-4c7f-88cd-cf53ba0aea41/download/soil-c-n.csv
    Description: Analyses of C, N and their stable isotopes in the soil, and soil pH

face

display_name: face

picea-abies

display_name: picea-abies


$oid: OBSOLETE

en:
Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010).
The calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX  for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below:
- ICHEC-EC-EARTH	DMI-HIRHAM5	2.6	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	4.5	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	8.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	2.6	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	4.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	8.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	4.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	8.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	4.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	8.5	EUR-11
*References*:
-	Köplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010.
-	National Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich.
-	Schäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825.
-	Viviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH.  Part II - Physical model description_, Geographica Bernensia, 40, 1-89.
-	Viviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001.
-	Viviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation  for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022.

en: precipitation discharge soil-moisture climate-change hydrology snowmelt

envidat

approval_status: approved

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Simulated future discharge and climatological variables for medium-sized catchments in Switzerland

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: Shapefile of 307 catchments in Switzerland
    Size: 103266 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/05c1a038-40c2-423a-8ad9-f11b43689cf1/download/catchment_shapes.zip
    Description: Shapefile of the 307 medium-sized catchments in Switzerland. The "gridcode" provides the ID of the catchment used in the datafiles.

format: ZIP

media_type: application/zip

en:
Resource Title: Daily simulated data for the reference period
    Size: 31447784 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/a67b4308-25ca-47ea-9aed-f529b8dc7f4d/download/reference.zip
    Description: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the reference period 1981-2017 in mm.

en:
Resource Title: Daily simulated data for the future period
    Size: 1010416415 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/be17bcca-3f34-414f-960e-bcbdd855ba81/download/climate_simulations.zip
    Description: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the period 1981-2100 in mm for the 307 catchments.

climate-change

display_name: climate-change

discharge

display_name: discharge

hydrology

display_name: hydrology

precipitation

display_name: precipitation

snowmelt

display_name: snowmelt

soil-moisture

display_name: soil-moisture


snow-depth-mapping

en:
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

en: avalanche snow-hydrology snow-depth snow-water-equivalent aerial-imagery image-matching dsm

en: Snow Depth Mapping

title_for_slug: snow-depth-mapping

en:
Resource Title: Snow depth map 20160126
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/9229984f-b417-45e5-8dbe-031f295d0406/download/snowmap_20160126_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m
Because of very diffuse light conditions at time of image acquisition the quality of the resulting snow depth values are in some regions quite poor.

format: TIFF

media_type: image/tiff

en:
Resource Title: Snow depth map 20130415
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/da3ca703-c629-45c0-8dac-e78645b0fa5e/download/snowmap_2013_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20160309
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/ceae68a6-28f9-43f4-8ff5-9715588ade57/download/snowmap_20160309_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20150415
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/578e95ce-ffa0-4fc6-8109-d9653b2c622a/download/snowmap_2015_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20140417
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/5cf5d3a5-555d-429e-9819-6c93ccce6dfc/download/snowmap_2014_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.18 m

en:
Resource Title: Snow depth mapping in high-alpine catchments using digital photogrammetry
    Size: 8122296 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/3b711e29-cea1-48e8-8de6-a008850c4f94/download/snow-depth-mapping-in-high-alpine-catchments.pdf
    Description:

format: PDF

media_type: application/pdf

en:
Resource Title: Snow depth map 20100416
    Size: 412324171 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/4ba96052-9e3e-4b7a-9968-2dcc58fc96c0/download/snowmap_2010_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20120320
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/aff41055-8e6e-4287-b52d-2c2fb61633c2/download/snowmap_2012_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20160420
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/bc035833-3193-4394-af92-f8d195d5e034/download/snowmap_20160420_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent


en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).
 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

en: erosion sediment-transport mars model snow

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation

en:
Resource Title:
    Size: 3587 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/1f30b883-fc62-4bbf-a8f5-88f716008097/download/figure2.txt
    Description: Datasets of Figure 2

format: TXT

media_type: text/plain

en:
Resource Title:
    Size: 2190 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/82479779-1b20-486f-b4bc-414c6024c25d/download/figure3b.txt
    Description: Datasets of Figure 3b

en:
Resource Title:
    Size: 1434 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/8ab9bafb-62f5-4420-80da-a2a96d22be74/download/figure3a.txt
    Description: Datasets of Figure 3a

en:
Resource Title:
    Size: 3626 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/6ee21796-08ad-4069-a4cb-da6c35ffede7/download/figure4a.txt
    Description: Datasets of Figure 4a

en:
Resource Title:
    Size: 2904 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/709f4330-9a35-4685-aac8-347067a5e483/download/figure4b.txt
    Description: Datasets of Figure 4b

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow


seilaplan

en:
Cable-based technologies have been a backbone for harvesting on steep slopes. The layout of a single cable road is challenging because one must identify intermediate support locations and heights that guarantee structural safety and operational efficiency while minimizing set-up and dismantling costs. Seilaplan optimizes the layout of a cable road by
Seilaplan stands for Cable Road Layout Planner. Seilaplan is able to calculate the optimal rope line layout (position and height of the supports) between defined start and end coordinates on the basis of a digital elevation model (DEM).
The program is designed for Central European conditions and is designed on the basis of a fixed suspension rope anchored at both ends. For the calculation of the properties of the load path curve an iterative method is used, which was described by Zweifel (1960) and was developed especially for standing skylines. When testing the feasibility of the cable line, care is taken that 1) the maximum permissible stresses in the skyline are not exceeded, 2) there is a minimum distance between the load path and the ground and 3) when using a gravitational system, there is a minimum inclination in the load path. The solution is selected which has a minimum number of supports in the first priority and minimizes the support height in the second priority.
The newly developed method calculates the load path curve and the forces occurring in it more accurately than tools available on the market to date (status 2019) and is able to determine the optimum position and height of the intermediate supports.
The reason for the more accurate results of the new tool is the assumption that the skyline is anchored at both end points. Forest cable yarders used in Europe have a skyline that is fixed at both ends. The behaviour of fixed-anchored suspension ropes is very difficult to describe mathematically and cannot be solved analytically. For this reason, simplified linearized assumptions have so far been used in the forestry sector, which corresponds to the behaviour of a weight-tensioned suspension rope and is known as the Pestal method (1961). Weight-tensioned suspension ropes are used for passenger transport.
For the calculation of the load path curve we use an iterative method, which was described by Zweifel (1960) and developed especially for fixed anchored suspension ropes. This makes mathematics much more demanding, but leads to more accurate and realistic results. Since there are no current models which describe the installation costs with adequate accuracy, the solution sought is the one which has a minimum number of supports in the first priority and minimises the support height in the second priority (Figure 2). The presented method is the first one, which starts from a fixed anchored supporting rope and identifies the mathematically optimal column layout at the same time. In contrast to methods that assume a weight-tensioned suspension rope, this approach achieves more realistic solutions with longer spans and lower support heights, which ultimately leads to lower installation costs. Background information on rope mechanics and calculation methods is documented in Bont and Heinimann (2012).
License: GNU, General Public License, Version 2 or newer.
Literature:
Bont, L., & Heinimann, H. R. (2012). Optimum geometric layout of a single cable road. European journal of forest research, 131(5), 1439-1448.

en: cable-yarding catenary-load-path qgis cable-planning software python steep-terrain-harvesting

en: Seilaplan

title_for_slug: seilaplan

envi

en: Environment

cable-planning

display_name: cable-planning

cable-yarding

display_name: cable-yarding

catenary-load-path

display_name: catenary-load-path

python

display_name: python

qgis

display_name: qgis

software

display_name: software

steep-terrain-harvesting

display_name: steep-terrain-harvesting


en:
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.

en: fagus-orientalis-lipsky magnesium biogeochemical-cycling potassium calcium

en: Base cation dynamics in an Oriental beech forest

format: XLS

biogeochemical-cycling

display_name: biogeochemical-cycling

calcium

display_name: calcium

fagus-orientalis-lipsky

display_name: fagus-orientalis-lipsky

magnesium

display_name: magnesium

potassium

display_name: potassium


en:
**CH-POA300** is a dataset of hourly solar irradiance maps projected onto tilted surfaces (analogous to monofacial solar panels).
- **Spatial resolution:** 300 m
- **Coverage:** Switzerland
Two temporal extents are available, depending on the number of surface orientations (azimuth–tilt combinations):
 1. Long-term
- **Period:** 2004–2020
- **Orientations:**
  - Azimuth: 180° (South)
  - Tilts: 0°, 35°, 60°, 90°
 2. Typical year
- **Period:** 2016
- **Orientations:**
  - Azimuths: 0° (North), 90° (East), 135°, 180° (South), 225°, 270° (West)
  - Tilts: 0°, 3°, 8°, 15°, 25°, 35°, 45°, 60°, 80°, 90°
 Notes
- Azimuth angles: 0° = North, 90° = East, 180° = South, 270° = West
- Tilt angles: 0° = horizontal, 90° = vertical
 Additional data
- Seasonal and annual statistics derived from the maps are included.
- Methodology and quality assessment are documented in *CH-POA300-v-specs.pdf*.

en: agri-pv plane-of-array alpine-pv sweet-edge rooftop-pv speed2zero solar-irradiance

en: CH-POA300 -- Hourly Plane-of-Array Solar Irradiance at High Resolution for Switzerland

en:
Resource Title: CH-POA300_v1_statistics
    Size: 1445061901 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ea36025c-c855-488d-857d-f658bace53e2/download/chpoa300_statistics.zip
    Description: Contains seasonal and annual statistics (mean, sum) of the CH-POA300 dataset.

- "yyyy_agg_period_hourly_stat.nc": statistic <stat> for the period <agg_period> of the year <yyyy>
- "all_agg_period_stat_mean.nc": statistic <stat> for the period <agg_period> reduced on the entire dataset (all years).
\
yyyy: [2004, 2020]
agg_period: [winter, summer, annual]
stat: [mean, sum]

en:
Resource Title: Data 2016
    Size: 751619276800 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300%2F&prefix=2016
    Description:

en:
Resource Title: CH-POA300-v2-specs
    Size: 11473219 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/c184fb33-6751-47cd-a936-2f04de24c760/download/ch-poa300-v2-specs.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: CH-POA300_v1_specs
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    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/7146fc4a-df12-44a8-923f-69476b147a55/download/chpoa300_specs_v1.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: CH-POA300-v2-statistics
    Size: 1889349528 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ed1238d2-b8c0-42f1-9b65-b837ac2dd259/download/stats.zip
    Description: Contains seasonal and annual statistics (mean and sum) derived from the CH-POA300 dataset.
File naming conventions:
yyyy_agg_period_hourly_stat.nc : statistic <stat> for aggregation period <agg_period> in year <yyyy>
all_agg_period_stat_mean.nc : statistic <stat> for aggregation period <agg_period> computed over the entire dataset (all years)
Definitions:
yyyy = year (2004–2020)
agg_period = winter, summer, annual
stat = mean, sum

en:
Resource Title: Data 2004-2020
    Size: 858993459200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300/&prefix=2004-2020
    Description:

agri-pv

display_name: agri-pv

alpine-pv

display_name: alpine-pv

plane-of-array

display_name: plane-of-array

rooftop-pv

display_name: rooftop-pv

solar-irradiance

display_name: solar-irradiance

sweet-edge

display_name: sweet-edge


en:
Background information
Climate change-induced range expansion of treeline populations depends on their successful recruitment, which requires dispersal of viable seeds followed by successful establishment of individual propagules. The Global Treeline Range Expansion Experiment (G-TREE) is a global initiative involving researchers from Europe, North America, Australia and New Zealand (Brown et al., 2013). At 15 alpine and Arctic treeline sites worldwide the mechanisms determining the elevational and latitudinal distribution of tree populations are studied using a standardized experimental approach. In summer 2013, a multifactorial seedling recruitment experiment has been established at the Stillberg ecological treeline research site. The aim of this experiment, is to quantify the effect of multiple abiotic and biotic drivers on emergence, survival, and growth of *Larix decidua* and *Picea abies* seedlings in replicated plots along an elevation gradient with three sites below (1930 m a.s.l.), at (2090 m a.s.l.), and above treeline (2410 m a.s.l.; Frei et al., 2018). All plots have been surveyed annually to count seedlings and to measure their total height. Additional environmental factors, such as soil temperature, have been recorded.
 Experimental design
The Stillberg research area is located in the Eastern Swiss Alps near Davos, Switzerland. The site has been used for several long-term monitoring as well as experimental studies for the last four decades. Our G-TREE experiment consists of a lowest site located in a subalpine Larch-Spruce forest (*Larici-Picetum*) dominated by *Larix decidua* and *Picea abies* (1930 m a.s.l.), a transition zone site dominated by alpine shrubs (2100 m a.s.l.), and an uppermost site in an alpine meadow with some dwarf shrubs (2390 m a.s.l.). The three experimental sites were set up following the standard protocol of the global G-TREE initiative (Brown et al., 2013). In a split-plot design, 20 plots (224 cm × 45 cm) were established at each site, which were randomly assigned to the 2 × 2 treatment combinations of the main factors seeding and scarification (i.e. seeding and scarification, seeding only, scarification only, and full control), resulting in five replications per main treatment combination. Each plot was divided into 16 split-plots (22.5 cm × 28 cm), to which treatment combinations of four additional two-level factors species (larch and spruce), provenance (low- and high-elevation), herbivore exclosure (with and without exclosure), and seeding year (2013, 2014) were randomly assigned, which resulted in a total of 960 split-plots (Details see Frei et al. 2018).
 Data description
All plots have been surveyed annually to count seedlings and to measure their total height. Seedling height was assessed with a hand ruler as the total length from the original emerging point to the apical meristem (Details see Frei et al. 2018). Additionally, soil temperature at each site, has been continuously recorded since 2013. Here, we present data from eight years (2013–2021).

en: g-tree climate-change larix-decidua forest stillberg seedling-recruitment swiss-alps treeline picea-abies

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en: G-TREE: Global Treeline Range Expansion Experiment Davos, Switzerland

climate-change

display_name: climate-change

forest

display_name: forest

g-tree

display_name: g-tree

larix-decidua

display_name: larix-decidua

picea-abies

display_name: picea-abies

seedling-recruitment

display_name: seedling-recruitment

stillberg

display_name: stillberg

swiss-alps

display_name: swiss-alps

treeline

display_name: treeline


en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Jussy in Switzerland where one station is located within a natural broad-leaved forest stand (JUB) with sessile oak (_Quercus petrea_; 90 yrs), aspen (_Populus tremula_; 60 yrs) and European hornbeam (_Carpinus betulus_; 60 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, JUF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Jussy is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

en: temperature wind-speed swiss-forest-lab long-term climate-change meteorology relative-humidity par precipitation meteo

en: Jussy, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards

envi

en: Environment

en:
Resource Title: Data plot of the field station (JUF)
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    Format: text/csv
    URL: https://www.envidat.ch/dataset/936684d9-ba55-49bb-b098-9ffbaf08261f/resource/a3786108-900a-4eed-a325-0277a5c7000f/download/juffield.csv
    Description: Data file.

format: CSV

media_type: text/csv

en:
Resource Title: Site photo of the field station (JUF)
    Size: 627860 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/936684d9-ba55-49bb-b098-9ffbaf08261f/resource/748cb54f-8eee-4777-b194-49903ae68da5/download/juf.jpg
    Description: Site photo of the field station from the side.

format: jpeg

en:
Resource Title: Data plot of the field station (JUF)
    Size: 281673 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/936684d9-ba55-49bb-b098-9ffbaf08261f/resource/a9f24dcd-7e4a-4b63-8dbe-29e136d81b4c/download/jufplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site photo of the forest station (JUB)
    Size: 5383408 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/936684d9-ba55-49bb-b098-9ffbaf08261f/resource/1bbb5ed2-481b-41fe-91c1-b2976b26b8c8/download/jub.jpg
    Description: Site photo of the forest station from the side.

en:
Resource Title: Forest station data (JUB)
    Size: 10879542 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/936684d9-ba55-49bb-b098-9ffbaf08261f/resource/d29d718d-5305-41ba-9d6d-811615b45586/download/jubforest.csv
    Description: Data file.

en:
Resource Title: Data plot of the forest station (JUB)
    Size: 238163 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/936684d9-ba55-49bb-b098-9ffbaf08261f/resource/7ee946ed-f2cd-4c63-8b28-41f5c804b1a9/download/jubplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site aerial photo (Jussy)
    Size: 9075365 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/936684d9-ba55-49bb-b098-9ffbaf08261f/resource/7081d2c5-f8df-4bcd-bddd-5d9e3ece1239/download/jufront.jpg
    Description: Site aerial photo from both Jussy stations. Source: Google. 2016. Site aerial photo from both Jussy stations. Retrieved November 11, 2016, from https://www.google.ch/maps

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed


en:
This dataset comprises a large array of ecological data for the European Alps:
    (1) Current soil and climate predictors at various resolutions.
    (2) GBIF observations of the European Alps Flora (~4,000 species).
    (3) Species habitat suitability maps (1,109 species; based on species observations filtered at 40x40-km)
    at various resolutions used in the study to generate (4); except 'expert'...
    (4) Expert, Taxonomic, phylogenetic and functional diversity of the study region at various resolutions
    (from 100-m to 40-km --- 100-m aggregated & mean to km + non-aggregated/predicted) for CLIM,
    SOIL and CLIM-SOIL models.
    (5) Ecological and altitudinal preferences of the European Alps Flora.
    (6) Data outputs of the related published article.
    (7) All scripts used for analyses.
    (8) Additional files used for analyses.
    (9) Improved set of species habitat suitability maps (~2,600 species; based on species observations
    filtered at 1x1-km) and related taxonomic diversity at 100-m resolution (aggregated to km +
    non-aggregated/predicted) for CLIM, SOIL and CLIM-SOIL models ---- not incorporated in the study.

en: phylogenetic-diversity taxonomic-diversity grain-size functional-diversity ecological-indicator-values climate soil

en: Resolution in species distribution models shapes spatial patterns of plant multifaceted diversity

climate

display_name: climate

ecological-indicator-values

display_name: ecological-indicator-values

functional-diversity

display_name: functional-diversity

grain-size

display_name: grain-size

phylogenetic-diversity

display_name: phylogenetic-diversity

soil

display_name: soil

taxonomic-diversity

display_name: taxonomic-diversity


en:
This data set includes GPS-derived snow water equivalent (SWE), snow depth (HS) and liquid water content (LWC) data for three entire snow-covered seasons (2015-2016, 2016-2017, 2017-2018) at the study plot Weissfluhjoch 2540 m a.s.l. (Davos, Switzerland). The procedure to derive these snow properties is described in Koch et al. (2019). The novel approach is based on a combination of GPS signal attenuation and time delay.
The dataset also includes corresponding validation data for SWE and HS measured at Weissfluhjoch, and some additional meteorological data used for interpretation of the snow cover evolution.
Please refer to the Read-me file for further details on the data.
These data are the basis of the following publication:
- Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M., Schweizer, J., and Mauser, W., 2019. Retrieval of snow water equivalent, liquid water content and snow height of dry and wet snow by combining GPS signal attenuation and time delay. Water Resources Research, 55(5), 4465-4487. https://doi.org/10.1029/2018WR024431

en: snow liquid-water-content snow-depth gps snow-cover

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: GPS-derived data of SWE, HS and LWC and corresponding validation data

en:
Resource Title: Read-me
    Size: 109310 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cd57ac77-a276-4783-88c9-f52f51552d2c/resource/d491aadc-0a43-4caa-8b32-09c988ec4841/download/readme.pdf
    Description: The read-me file contains the description of the data provided.

en:
Resource Title: Dataset with GPS-derived snow cover properties and validation data
    Size: 90714 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cd57ac77-a276-4783-88c9-f52f51552d2c/resource/01f4a113-7ad0-4993-9efa-f30bbe0f0474/download/gps-derived_snow_properties.csv
    Description: This file includes the data as described in the Read-me file.

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth


en:
Overview
The SUNWELL Modelling Environment is a combination of data and code that models electricity production from satellite-derived irradiance data and other spatial data sets for all of Switzerland. This ensemble accompanies the publication "The bright side of PV production in snow-covered mountains", published in the Proceedings of the National Academy of Science and reproduces all results and figures of. Code and resources are in their original form (with documentation). A new version with a more generalized application to PV modelling and with more flexibility in terms of input and output formats will be released in the coming months.
 Format
All code is written and has to be executed in Matlab. The input and output data sets are also in the Matlab-specific .mat format. Whenever publicly available, the original data is provided as geotif, .xlsx or other common format.
This is the case for:
- Digital Elevation Model (InputsFromMatlab/MSG/OriginalData/ASTERDEM),
- Landsurface cover type (InputsFromMatlab/MSG/OriginalData/CORINE),
- Population Density (InputsFromMatlab/MSG/OriginalData/popdensRaster,
- Electricity production from three of our validation sites (/Validation/WSL),
- Measured irradiance for two validation sites (/Validation/ASRB)
The ‘Metadata’ documents in the respective folders provide further information about the data sources and processing. Figures are produced either in .pdf or .png format.
 Structure
The central level of the SUNWELL environment holds the 5 Mains, which run the different modelling aspects of the paper; each code is documented separately. Additional code is located in the ‘DataProcessing’ and the ‘functions’ folder. Functions are called in the different Mains.
‘InputsFromMatlab’ contains the radiation and albedo input data sets in separate subfolders (SIS/SISDIR/ALB). The original data is not publicly available, but can be requested for research purposes free of charge. We provide a processed subset of the data set that was used to run the SUNWELL simulations. The MSG subfolder contains additional spatial input data sets.
‘Outputs’ contains the output files from the different mains (matching names, Main_CHallpixels.m  Prod_CHallpixels)
‘Publication_figures’ contains all individual figures from the PNAS publication, as well as the generating code (/code_plot) and the power point figures (/ppts) that provide the combined final figures.
‘Validation’ contains the data sets used in the model validation:
- Electricity production from three of our validation sites (/WSL),
- Measured irradiance for two validation sites (/ASRB)
Electricity production from a validation site at Lac des Toules in Wallis (/LDT), this data set was provided under an NDA and cannot be made publicly available.
Paper Citation:
 - _Annelen Kahl; Jérôme Dujardin; Michael Lehning (2018). Dataset on PV Production in Snow Covered Mountains. PNAS - Proceedings of the National Academy of Sciences. (in press)_

en: mountain albedo reflection photovoltaic irradiance energy snow

envidat

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: Dataset on PV Production in Snow Covered Mountains
    Size: 7462505677 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.47/pv.zip
    Description: __Windows users__ use the 7-zip app to extract the zip-file.

en:
Resource Title: PV Data
    Size: 2654822 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/90e36ede-4301-43f3-b0cb-b524d8c81f6b/resource/a2dd7f4f-b4dd-41c5-8ed9-1968af46bbcf/download/pv_daten_wsl_lehning_wfj_slf_laret_19.03.2018.xlsx
    Description:

albedo

display_name: albedo

energy

display_name: energy

irradiance

display_name: irradiance

mountain

display_name: mountain

photovoltaic

display_name: photovoltaic

reflection

display_name: reflection


en: The dataset provides simulated 1) precipitation, 2) discharge, 3) soil moisture, and 4) low-flow simulations for 307 medium-sized catchments in Switzerland for the period 1981-2018. The data were simulated using the hydrological model PREVAH in its gridded-version. The simulated time series are provided at daily resolution. A detailed description of the modeling approach can be found in Brunner et al. 2019 submitted to NHESS.

en: low-flow hydrological-simulations precipitation discharge soil-moisture prevah drought-2018

en: Hydro-meteorological simulations for the period 1981-2018 for Switzerland

en:
Resource Title: Precipitation
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/0f551cfd-804d-4f3a-80d9-c33562ea8b45/download/precipitation.txt
    Description: Simulated precipitation for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm/d.

en:
Resource Title: Shapefile of 307 catchments in Switzerland
    Size: 103266 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/7ebed8a1-98ce-4833-b1dd-64246bd07e5f/download/catchment_shapes.zip
    Description: Shapefile of 307 catchments for which simulations of precipitation, discharge, soil moisture, and low flow are provided. The OBJECTID entry corresponds to the data columns in the textfiles of the simulated data provided.

en:
Resource Title: Discharge
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/4c11fec4-0846-48a0-8dfe-9f7f5a4b574f/download/discharge.txt
    Description: Simulated discharge for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm/d.

en:
Resource Title: Soil moisture
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/0ad6127b-f7d6-4356-9ac4-283166385578/download/soil_moisture.txt
    Description: Simulated plant-available soil moisture for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm.

en:
Resource Title: Low-flow storage
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/a1338c95-09df-4bce-8d9c-7b059ae2f6a1/download/low_flow.txt
    Description: Simulated low-flow storage for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm.

discharge

display_name: discharge

hydrological-simulations

display_name: hydrological-simulations

low-flow

display_name: low-flow

precipitation

display_name: precipitation

prevah

display_name: prevah

soil-moisture

display_name: soil-moisture


en:
The present dataset is part of the published scientific paper entitled “The role of spatial planning in land change: An assessment of urban planning and nature conservation efficiency at the southeastern coast of Brazil” (Pierri Daunt, Inostroza and Hersperger, 2021). In this work, we evaluated the conformance of stated spatial planning goals and the outcomes in terms of urban compactness, basic services and housing provision, and nature conservation for different land-use strategies. We evaluate the 2005 Ecological-Economic Zoning (EEZ) and two municipal master plans from 2006 in a coastal region in São Paulo State, Brazil. We used Partial Least Squares Path Modelling (PLS-PM) to explain the relationship between the plan strategies and land-use change ten years after implementation in terms of urban compactness, basic services and housing increase, and nature conservation.
We acquired the data for the explanatory variables from different sources listed on Table 1. Since the model is spatially explicit, all input data were transformed to a 30 m resolution raster. Regarding the evaluated spatial plans, we acquired the zones limits from the São Paulo State Environmental Planning Division (CPLA-SP), Ilhabela and Ubatuba municipality.
1)	Land use and cover data: Urban persistence, Urban axial, Urban infill, Urban Isolates, Forest cover persistence, Forest cover gain, NDVI increase
We acquired two Landsat Collection 1 Higher-Level Surface Reflectance images distributed by the U.S. Geological Survey (USGS), covering the entire study area (paths 76 and 77, row 220, WRS-2 reference system, https://earthexplorer.usgs.gov/). We classified one image acquired by the Landsat 5 Thematic Mapper (TM) sensor on 2005-05-150, and one image from the Landsat 8 Operational Land Imager (OLI) sensor from 2015-08-15. We collected 100 samples for forest cover, 100 samples for built-up cover and 100 samples for other classes. We then classified these three classes of land cover at each image date using the Support Vector Machine (SVM) supervised algorithm (Hsu et al., 2003), using ENVI 5.0 software.
Land-use and land-cover changes from 2005 to 2015 were quantified using map algebra, by mathematically adding them together in pairs (10*LULC2015 + LULC2005). We reclassified the LULC data into forest gain (conversion of any 2005 LULC to forest cover in 2015); forest persistence (2005 forested pixels that remained forested in 2015); new built-up area (conversion of any 2005 LULC to built-up in 2015); and urban maintenance (2005 built-up pixels that remained built-up in 2015).
To describe the spatial configuration of the urban expansion, we classified the new built-up areas into axial, infill and isolated, following Inostroza et al. (2013) (For details, please refer to Supplementary Material I at the original publication).
The NDVI was obtained from the same source used for the LULC data. With the Google Engine platform, we used an annual average for the best pixels (without clouds) for 2005 and 2015, and we calculated the changes between dates. We used increases of - 0.2 NDVI to represent an improvement in forest quality.
2)	Federal Census data organization: Urban Basic Services and Housing indicator, socioeconomic and population:
The data used to infer the values of basic services provision, socioeconomic and population drivers was derived from the Brazilian National Census data (IBGE, 2000 and 2010). Population density, permanent housing unit density, mean income, basic education, and the percentage of houses receiving waste collection, sanitation and water provision services, called basic services in the context of this study, were calculated per 30 m pixel. The Human Development Index is only available at the municipality level. We attributed the HDI for the vector file with the municipality border, and we rasterized (30 m resolution) this file in QGIS. Annual rates of change were then calculated to allow comparability between LULC periods. To infer the BSH, we used only areas with an increase in permanent housing density and basic services provision (See Supplementary Material I at the original publication).
3)	Topographic drivers
To infer the values of the topographic driver, we used the slope data and the Topographic Index Position (TPI) based on the digital elevation model from SRTM (30 m resolution) produced by ALOS (freely available at eorc.jaxa.jp/ALOS/en/about/about_index.htm), and both variables were considered constant from 2005 to 2015 (See Supplementary Material I at the original publication).

en: urban-morphology basic-services built-up-classification urban-sprawl land-use-and-cover-change nature-conservation planning-outcome forest-gain urban-compactness spatial-modelling forest-persistence topography

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Spatially explicit data to evaluate spatial planning outcomes in a coastal region in São Paulo State, Brazil

en:
Resource Title: infill
    Size: 1337272 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/5b598ade-cb86-4f8b-aadc-c18e12814d15/download/infill.tif
    Description: New built-up pixels classified as infill

en:
Resource Title: TPI300
    Size: 11941205 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3a51f451-aa57-4d4e-b4a8-a07786d7a18b/download/tpi300.tif
    Description: Topographic Index Position (TPI)

en:
Resource Title: waste_inc_0010
    Size: 1528622 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/e50c4311-9521-4ec1-a177-cc9952a5cff3/download/waste_inc_0010.tif
    Description: Increase in waste collection service

en:
Resource Title: hdi_0010
    Size: 1672974 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/4e9794cf-e518-4b03-abe9-8c797b3a0562/download/hdi_0010.tif
    Description: Human Development Index (HDI) per municipality (change per year)

en:
Resource Title: alfa_0010
    Size: 2405447 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/b0604e68-15bf-4c85-a4ca-9bfe519fd03a/download/alfa_0010.tif
    Description: Basic education in % per census sector (change per
year)

en:
Resource Title: forest_persist_0515
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    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/a7d6f906-ee5d-4d64-a713-754764577b8a/download/forest_persist_0515.tif
    Description: Native forest cover persistence from 2005 to 2015

en:
Resource Title: water_inc_0010
    Size: 1464652 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/5f52216a-8f44-472b-b70d-6bb003968d1d/download/water_inc_0010.tif
    Description: Increase in clean water provision service

en:
Resource Title: isolated
    Size: 1365075 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/08978ae8-8980-446a-af9b-28b6e18b8dcb/download/isolated.tif
    Description: New built-up pixels classified as isolated

en:
Resource Title: Axial
    Size: 1360715 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/7dc6ab63-6a3b-4744-8b8e-b899427e95a5/download/axial.tif
    Description: New built-up pixels classified as axial

en:
Resource Title: ndvi_inc
    Size: 1552732 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3f14dfcc-668a-4321-9719-f0b58737deda/download/ndvi_inc.tif
    Description: Increase in Normalized Difference Vegetation Index

en:
Resource Title: income_0010
    Size: 2453471 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/d4800254-34c8-4699-ad14-78a32d90a8e8/download/income_0010.tif
    Description: Mean income in Reais (R$) per census sector (change per year)

en:
Resource Title: urban_persistence
    Size: 1412319 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/09b0444f-8dbd-4a8a-b5ac-26ba6d463401/download/urban_persistence.tif
    Description: Urban persistence: Built-up 2005 = Built-up 2015

en:
Resource Title: EEZ_2005
    Size: 755680 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/df399923-2f14-45df-bc12-707385ea2fe7/download/eez_2005.7z
    Description: Ecological-Economic Zoning (EEZ)

en:
Resource Title: Descricao dos dados em portiuguês
    Size: 93276 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3142ea4a-a5cf-41e9-b04e-3eea956e32af/download/tabela.pdf
    Description: Portugues description

en:
Resource Title: sanit_inc_0010
    Size: 1424839 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/a9a2d0d1-2de5-4a14-9b82-eb22e9dd2a8f/download/sanit_inc_0010.tif
    Description: Increase in sanitation service

en:
Resource Title: house_inc_0010
    Size: 1559472 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/309672b6-4fa2-411c-999a-5b119c72fbef/download/house_inc_0010.tif
    Description: Permanent housing density increase

en:
Resource Title: forest_gain_0515
    Size: 1359475 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/cc2499a2-e179-473d-ba04-ba7502d0e1ca/download/forest_gain_0515.tif
    Description: Native forest cover gains from 2005 to 2015

en:
Resource Title: pop_0010.
    Size: 2604307 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/21d0b38e-7066-4ac1-9c43-4c6fb732f337/download/pop_0010.tif
    Description: Population density per pixel (change per year)

en:
Resource Title: master_plan_Ilhabela
    Size: 92087 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/b3f65b7e-8f44-4cb1-8f3b-21e45da6ecd4/download/master_plan_ilhabela.7z
    Description: Master plan Ihabela (zones)

en:
Resource Title: slope
    Size: 10630454 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3ad576ef-181c-485a-b794-53381eed55d5/download/slope.tif
    Description: Slope °

en:
Resource Title: Variables description
    Size: 89561 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/8a4afdc9-9af4-4922-8856-6c0e67a1bcca/download/table.pdf
    Description: Table of content. Variables description, source, and other important information

en:
Resource Title: master_plan_Ubatuba
    Size: 458342 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/cdbd343b-fe3b-4404-a9ed-6a2516ec4610/resource/3c1e0ad8-fb01-447a-b325-a9574bdaeb06/download/master_plan_ubatuba.7z
    Description: Master plan Ubatuba (zones)

basic-services

display_name: basic-services

built-up-classification

display_name: built-up-classification

forest-gain

display_name: forest-gain

forest-persistence

display_name: forest-persistence

land-use-and-cover-change

display_name: land-use-and-cover-change

nature-conservation

display_name: nature-conservation

planning-outcome

display_name: planning-outcome


en:
General description
Data associated with the publication "CRISPR-Dx and metabarcoding perform similarly for monitoring mammals with eDNA on the catchment level in high-alpine ecosystems".  The data set contains the cleaned metabarcoding reads per site/catchment, the CRISPR-Dx detection per species and site, the site coordinates and a species checklist obtained from the Swiss National Park with the species known to occur at the sampling time point in the respective catchments.
 Authors
Flurin Leugger, Martina Lüthi, Michel Schmidlin, Sarah Marie-Antoine Turnheer, Zacharias Kontarakis and Loïc Pellissier
 Contact
flurinleugger@gmail.com
loic.pellissier@usys.ethz.ch
 Project description
We collected eDNA samples in the Swiss National Park in September 2022 using VigiDNA filters. We extracted the samples in the clean lab at ETH using a modified extraction protocol of Pont et al. (2018). We used the Mamm01 primer (Tabarlet et al. 2018) for metabarcoding and for CRISPR analysis. We applied CRISPR-Dx for eight species occurring in the Swiss National Park. Additionally, we compared the eDNA detections to species inventories per catchment obtained from the Swiss National Park. See publication for more details.
 Folders
 catchments
Shape file containing the catchments sampled in the Swiss National Park.
 metadata
Folder containing files with overview of site names and extract number. Second file with metadata per site (e..g., sampling date). Column called "EVS" (Environmental sample) is the key between the two files.
 data
Folder containing a folder for eDNA and species_inventory (traditional monitoring), respectively.
 eDNA folder
CRISPR_classifications.csv: CRISPR-Dx classifications per extract (and PCR pool).
metabarcoding_seqs_all_cleaned.csv: all DNA sequences from metabarcoding after removing all sequences found in the negative controls.
 species_inventory
Species per catchment reported by the Swiss National Park, based on traditional monitoring including. visual surveys and other opportunistic records. 2: known presence in 2022, 1: maybe present in 2022, 0: not recorded in 2022

en: catchment edna metabarcoding national-park dna-metabarcoding mammals crispr-dx

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en: Application of CRISPR-Dx and metabarcoding to catchment-level eDNA for terrestrial mammal detection

envi

en: Environment

en:
Resource Title: Readme.txt
    Size: 1811 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/7927cfd4-2861-434a-bdd3-0c3790fab6e4/resource/9aa5d934-729d-43a3-9c9f-7294dc8aa2b3/download/readme.txt
    Description: Read me file with information about files within this repository

en:
Resource Title: data.zip
    Size: 6818 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7927cfd4-2861-434a-bdd3-0c3790fab6e4/resource/658a31d4-24d1-40f3-8468-e605c56a5dda/download/data.zip
    Description: Folder containing a folder for eDNA and species_inventory (traditional monitoring), respectively.
eDNA folder:
CRISPR_classifications.csv: CRISPR-Dx classifications per extract (and PCR pool).
metabarcoding_seqs_all_cleaned.csv: all DNA sequences from metabarcoding after removing all sequences found in the negative controls.
species_inventory: species per catchment reported by the Swiss National Park, based on traditional monitoring including. visual surveys and other opportunistic records. 2: known presence in 2022, 1: maybe present in 2022, 0: not recorded in 2022

en:
Resource Title: catchments.zip
    Size: 6475 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7927cfd4-2861-434a-bdd3-0c3790fab6e4/resource/f7e73ace-23c5-486b-a93e-74fb19488032/download/catchments.zip
    Description: Shape file containing the catchments sampled in the Swiss National Park

en:
Resource Title: metadata.zip
    Size: 1102 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7927cfd4-2861-434a-bdd3-0c3790fab6e4/resource/3e9d98d5-8dcf-4531-bb15-04bf3863563e/download/metadata.zip
    Description: Folder containing files with overview of site names and extract number. Second file with metadata per site (e..g., sampling date). Column called "EVS" (Environmental sample) is the key between the two files.

catchment

display_name: catchment

crispr-dx

display_name: crispr-dx

dna-metabarcoding

display_name: dna-metabarcoding

edna

display_name: edna

mammals

display_name: mammals

metabarcoding

display_name: metabarcoding

national-park

display_name: national-park


en: With this study, our aim was to estimate the nutrient fluxes relevant for assessing nutrient sustainability as accurately as possible and to calculate nutrient balances for alternative forest management scenarios. Furthermore, we tested whether mapping units from existing geologic maps can serve as a basis for forest practitioners to estimate nutrient sustainability or whether more detailed data is needed. Positive fluxes include deposition and weathering, while negative fluxes include losses due to leaching and nutrient removal through timber harvesting in the balance. Weathering and leachate losses were modeled with a geochemical model. The SwissStandSim model was used to simulate the biomass growth under different harvesting and silvicultural strategies, allowing sustainability to be assessed for each nutrient at a given intensity of use. This assessment was made per rotation period of 100 years based on two criteria: i) nutrient supply; and ii) total stocking volume.

en: nutrient soil beech sustainability mass-balance

en: Nutrient sustainability in beech forests

en:
Resource Title: Soil_Properties_TabA2.xlsx
    Size: 50339 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/b938dd05-54ab-4dc0-b7d8-a106567322f4/resource/ba211033-8761-4d53-a1fd-6e741926f3d6/download/soil_properties_taba2.xlsx
    Description:

en:
Resource Title: Nutrient_tree_compartments.xlsx
    Size: 39892 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/b938dd05-54ab-4dc0-b7d8-a106567322f4/resource/59464da8-a4aa-4adf-86d1-df763223e9c4/download/nutrient_tree_compartments.xlsx
    Description:

en:
Resource Title: Nutrient_mass_balances.xlsx
    Size: 27714 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/b938dd05-54ab-4dc0-b7d8-a106567322f4/resource/23bb8222-159c-42b8-8e06-dd14b8469600/download/nutrient_mass_balances.xlsx
    Description:

en:
Resource Title: Nutrient_export_harvesting.xlsx
    Size: 15618 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/b938dd05-54ab-4dc0-b7d8-a106567322f4/resource/3f5aa362-7738-4a1e-8cce-9c0b60f0ef71/download/nutrient_export_harvesting.xlsx
    Description:

beech

display_name: beech

mass-balance

display_name: mass-balance

nutrient

display_name: nutrient

soil

display_name: soil

sustainability

display_name: sustainability


en:
Preferential deposition of snow and dust over complex terrain is responsible for a wide range of environmental processes, and accounts for a significant source of uncertainty in surface mass balances of cold and arid regions. Despite the growing body of literature on the subject, previous studies reported contradictory results on the location and magnitude of deposition maxima and minima. This study aims at unraveling the  governing processes of preferential deposition in neutrally stable atmosphere and to reconcile seemingly inconsistent results of previous works. For this purpose, a comprehensive modeling approach is developed, based on large eddy simulations of the turbulent airflow, Lagrangian stochastic model of particle trajectories, and immersed-boundary method to represent the underlying topography. The model performance is tested against wind tunnel measurements of dust deposition around isolated and sequential hills. A scale analysis is then performed to investigate the dependence of snowfall deposition on the particle Froude and Stokes numbers, which fully account for the governing processes of inertia, flow advection, and gravity. Additional simulations are performed, to test whether the often used assumption of inertialess particles yields accurate deposition patterns. We finally show that our scale analysis provides qualitatively similar results for hills with different aspect ratios.
This dataset contains the results of the LES-LSM model. Each Matlab file contains a 2D array of deposition values (in kg/m2) in each surface node (ix, iy) of the Cartesian grid. The file names are consistent with the simulation numbers listed  in the original paper. For additional information, please refer to "Preferential deposition of snow and dust over hills: governing processes and relevant scales" by F. Comola, M. G. Giometto, S. T. Salesky, M. B. Parlange, and M. Lehning, Journal of Geophysical Research: Atmospheres, 2019.

en: dust deposition turbulence snow particles atmosphere hill

atmosphere

display_name: atmosphere

deposition

display_name: deposition

dust

display_name: dust

hill

display_name: hill

particles

display_name: particles

snow

display_name: snow

turbulence

display_name: turbulence


en:
Assessment of coarse woody debris on LWF plots using full count methods on defined subplots (applying ForestBiota protocoll)
 Purpose:
Assessing the amount of coarse woody debris
 Manual Citation:
 * Franziska Heinrich, 2005: Totholz-Aufnahme mit ForestBIOTA Protokoll. Langfristige Waldökosystem-Forschung LWF. Eidg. Forschungsanstalt WSL, Birmensdorf, 7 S.
 *  ForestBiota, 2005. Stand structure assessment including deadwood. EU/ICP Forests Biodiversity Test-Phase (ForestBIOTA). [---](http://www.forestbiota.org)
 *  Fischer, R., Fischer, R., Seidling, W., Granke, O., Meyer, P., Stofer, S., Travaglini, D., 2007. ForestBIOTA – Testphase zur Erfassung der biologischen Vielfalt. AFZ/Wald 62, 1070.
 Paper Citation:
 * Seidling, W., Travaglini, D., Meyer, P., Waldner, P., Fischer, R., Granke, O., Chirici, G., Corona, P., 2014. Dead wood and stand structure - relationships for forest plots across Europe. IForest - Biogeosciences and Forestry 7, 269-281.

en: coarse-woody-debris deadwood long-term-forest-ecosystem-research icp-forests swiss-forest-lab

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Deadwood survey LWF 2005 - subplot (Forets Biota)

format: HTML

coarse-woody-debris

display_name: coarse-woody-debris

deadwood

display_name: deadwood

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

swiss-forest-lab

display_name: swiss-forest-lab


en:
Measuring air pollutants in forests is important for evaluating the risk for vegetation in areas not covered by conventional air quality monitoring networks. Ozone-induced symptoms are being assessed at LWF, applying the harmonized methodologies from UNECE/ICP Forests and running under the 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone. Data are also collected on ozone concentrations and other ecosystem properties such as tree growth, nutrition, and biodiversity, as well as climate. This makes this long-term monitoring data series essential for impact assessment and air pollution modelling.
 Purpose:
Ozone risk assessment, i.e. to investigate relationships between ozone exposures and ozone-induced, visible symptoms
 Manual Citation:
 * Schaub  M,  Calatayud  V,  Ferretti  M,  Brunialti  G, Lövblad  G,  Krause  G,  Sanz  MJ,  2016:  Part  VIII:  Monitoring  of  Ozone  Injury.  In:  UNECE  ICP  Forests  Programme  Co-ordinating  Centre  (ed.):  Manual  on  methods  and  criteria  for  harmonized  sampling,  assessment,  monitoring  and  analysis  of  the  effects  of  air  pollution  on  forests.  Thünen  Institute  of  Forest  Ecosystems,  Eberswalde,  Germany, 14 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Schaub M, Häni M, Calatayud V, Ferretti M, Gottardini E (2018) ICP Forests Brief No 3 - Ozone concentrations are decreasing but exposure remains high in European forests. Programme Co-ordinating Centre of ICP Forests, Thu¨nen Institute of Forest Ecosystems. [doi: 10.3220/ICP1525258743000](https://icp-forests.org/pdf/ICPForestsBriefNo2.pdf)
 *  Schaub M and Calatayud V (2013) Assessment of Visible Foliar Injury Induced by Ozone. In: Marco Ferretti and Richard Fischer (Eds). Forest Monitoring: Methods for Terrestrial Investigations in Europe with an Overview of North America and Asia, Vol 12, DENS, UK: Elsevier, 2013, pp. 205-221. ISBN: 9780080982229. [doi: 10.1016/B978-0-08-098222-9.00011-X](https://doi.org/10.1016/B978-0-08-098222-9.00011-X)

en: ambient-air-quality long-term-forest-ecosystem-research icp-forests ozone ground-vegetation symptoms-of-visible-injuries swiss-forest-lab

envidat

en: EnviDat: the Environmental Data Portal

en: Symptoms of O3 injuries LWF

envi

en: Environment

ambient-air-quality

display_name: ambient-air-quality

ground-vegetation

display_name: ground-vegetation

ozone

display_name: ozone

symptoms-of-visible-injuries

display_name: symptoms-of-visible-injuries


en: This dataset contains the raw ring-width and climate data (1952-2020), as well as the R code to run the model and the model output used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".

en: beech fagus-sylvatica tree-ring dendroecology network-analysis dendrochronology

en: European Beech tree-ring dataset 1952-2020

en:
Resource Title: beech_rawtrw.txt
    Size: 332605512 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6b052bdb-9e18-4f00-92b6-e102347245ec/resource/f3bc670c-3474-4987-966e-c9a2e94bebd3/download/beech_rawtrw.txt
    Description: This dataset contains the raw ring-width and climate data (1952-2020) used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".

RW= ring width
Year= Calendar year
CN = core number
ID3= plot identifier
longitude = longitude (°)
latitude = latitude (°)
elevation = elevation (m)
age= estimated age in calendar year
radius= estimated radius in calendar year (mm)
MAT= mean annual temperature (°C)
MAP= mean annual precipitation (mm)
MCWB= mean climatic water balance (P-PET; mm)
amplitude= simple continentality measure (July - January mean maximum temperatures)
MATspline1 and 2, MCWBspline1 and 2, radiusspline4 and 5= natural spline transformed values of MAT, MCWB and radius #ns(x,2)
CWD_pMay_Jun= Climatic Water Balance of previous year May to June #!!!#please note CWD here is NOT Climatic Water Deficit, this was a labeling error in the creation of the dataset headers
CWD_May_Jun= Climatic Water Balance of current year May to June
Tmax_pMay_Jun= mean monthly maximum temperature of previous year May to June
Tmax_May_Jun= mean monthly maximum temperature of current year May to June
weight = site replication-based weighting input for model
SOM= membership of regional cluster 1-8 based on Supervised Organized Mapping

en:
Resource Title: final_cwb_model.R
    Size: 13781 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/6b052bdb-9e18-4f00-92b6-e102347245ec/resource/5d54048a-25a6-4861-89a3-6586b970177d/download/final_cwb_model.r
    Description: R code to run the model behind the results of the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".
Requires beech_rawtrw.txt.

format: OCTET

en:
Resource Title: Model output
    Size: 679105614 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/6b052bdb-9e18-4f00-92b6-e102347245ec/resource/c0117599-93c9-4ea0-8f12-753c711f003c/download/ebtrnplus_model_newcwbmean2
    Description: Output of the Mixed-effects model

beech

display_name: beech

dendrochronology

display_name: dendrochronology

dendroecology

display_name: dendroecology

fagus-sylvatica

display_name: fagus-sylvatica

network-analysis

display_name: network-analysis

tree-ring

display_name: tree-ring


en:
This repository contains extensive data for the European Alps:
   - Observations of ~3,500 plant species
   - Climate (1-km), soil (100-m) and land cover predictors (1km); current and future scenarios (28 CMIP6-GCMs, 2 land cover change and 3 dispersal scenarios i.e., unlimited, no and realistic vegetation dispersal)
   - Flora migration rates (categorical) and ecological preferences (continuous indicator values)
   - Regional maps of barriers to migration and water bodies at 100-m resolution
   - Sampling effort, distance to roads and cities predictors at 100-m resolution
   - Present and future abundances over the study region at 1-km resolution (~2,000 species)
   - Present and future multifaceted and uniqueness of the European Alps' Flora at  1-km resolution
   - Present and future conservation recommendations at 1-km resolution (26 current and future strategies)
   - Phylogenetic data and functional traits of ~2,000 plants (raw data and classification trees)
   - All scripts, data and plots used for the analyses, including a singularity container (mini-linux) to run them

en: beta-diversity zonation species-distribution-models migclim functional-diversity plants european-alps global-change phylogenetic-diversity land-use-change taxonomic-diversity conservation

en: Present and future multifaceted plant diversity, uniqueness and conservation in the European Alps

en:
Resource Title: Updated SDM outputs
    Size: 10242439935 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7b947fcf-73a0-46a7-be03-804797c9c3d7/resource/4838348a-6050-4774-83f1-cab5efe7b244/download/sdm_outputs_updated.zip
    Description: Refined scenarios of plants distribution in the European Alps

en:
Resource Title: Data Access
    Size: 85899345920 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.371%2F
    Description:

beta-diversity

display_name: beta-diversity

conservation

display_name: conservation

european-alps

display_name: european-alps

functional-diversity

display_name: functional-diversity

global-change

display_name: global-change

land-use-change

display_name: land-use-change

migclim

display_name: migclim

phylogenetic-diversity

display_name: phylogenetic-diversity

plants

display_name: plants

species-distribution-models

display_name: species-distribution-models

taxonomic-diversity

display_name: taxonomic-diversity

zonation

display_name: zonation


en:
Continuous measurement of soil water content at 15, 50 and 80 cm depth (3 replications) with ECH2O EC-5 soil moisture probes (Decagon Incorporation, Pullman, WA, USA).
 Purpose:
Improve the available data for the calibration or validation of the water cycle modells, i.e. the determination of the water flux needed for calculating the leaching fluxes.

en: icp-forests soil-water-content swiss-forest-lab lwf long-term-forest-ecosystem-research

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EC-5 soil water content measurement LWF

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

lwf

display_name: lwf

soil-water-content

display_name: soil-water-content

swiss-forest-lab

display_name: swiss-forest-lab


forest-canopy-layer

en: This dataset provides a LiDAR-based classification of the forest canopy layer for selected Swiss cantons. Combining an area-based and tree-centred approach, forest areas are categorised into four canopy layering classes that differentiate between single-layered and multi-layered canopies.

en: forest-structure forest-management lidar nfi forest-canopy mountain-forest

envidat

en: EnviDat: the Environmental Data Portal

en: Forest Canopy Layer

title_for_slug: forest-canopy-layer

en:
Resource Title: ForestCanopyLayer.qml
    Size: 8139 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/378dbed2-33a3-4398-8a41-5c341d27557d/download/forestcanopylayer.qml
    Description: QGIS QML file with stored layer style definitions for the ForestCanopyLayer.tif.

en:
Resource Title: ForestCanopyLayer.tif
    Size: 558505541 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/90bcde13-c71d-4618-a198-362ebccd0516/download/forestcanopylayer.tif
    Description: Forest Canopy Layer (class 1: single-layered; class 2: probably single-layered; class 3: probably multi-layered; class 4: multi-layered).

en:
Resource Title: IFA_Data.csv
    Size: 3837 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/a15b3bdb-c45e-4a8a-b526-8d43b265862c/download/ifa_data.csv
    Description: Validation data from the Independent Forester Assessment (IFA). x- /y-coordinate (CH1903+ LV03) and layer (1: single-layered; 2: multi-layered; -999: NA).

forest-canopy

display_name: forest-canopy

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

nfi

display_name: nfi


swiss-fluxnet-site-lageren

en:
The Swiss FluxNet Site Lägeren is a managed mixed deciduous mountain forest located on the steep Lägeren mountain (NW of Zurich, Swiss Plateau). The forest is highly diverse, dominated by beech, but also including ash, maple, spruce and fir trees. Eddy covariance flux measurements were started in April 2004. The site was part of the international CarboEurope IP network and the National Air Pollution Monitoring Network (NABEL). In addition to Swiss FluxNet, the site is part of the Long-term Forest Ecosystem Research (LWF) of WSL and the biological drought and growth indicator network (TreeNet) of WSL.
Measurements
- Ecosystem flux measurements of CO2, H2O vapour are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O), soil respiration campaigns
- Continuous CO2 profile measurements.
- Auxiliary micrometeorology and soil climate measurements.
Data availability
All data are available from the European Fluxes Database Cluster, but are also part of Fluxnet2015 dataset.
Data policy
ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)
Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae//](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae/)

en: meteorological-measurements greenhouse-gas forest flux swiss-forest-lab eddy-covariance swiss-fluxnet

en: Swiss FluxNet Site Lägeren

title_for_slug: swiss-fluxnet-site-lageren

envi

en: Environment

en:
Resource Title: Site description
    Size: 512219 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4666c33f-b2af-495c-ac49-4fdec3e26bd1/resource/3e9fc3ba-afc4-41f9-b8ca-488ca6810669/download/swissfluxnet_lae_sitedescription.pdf
    Description:

en:
Resource Title: Data access
    Size: 1024 bytes
    Format: No Info
    URL: http://www.europe-fluxdata.eu/home/site-details?id=CH-Lae
    Description: The flux and meteo data of the Swiss FluxNet site Lägeren are openly available from the European Fluxes Database Cluster.

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet


en:
One individual per species, vitality class (low and high) and height class (eight classes: 0–10, 11–20, 21–35, 36–60, 61–90, 91–130, 131–200 and 201–500 cm) was randomly selected and harvested in each of the six plots. This resulted in a sample of 82, 80 and 89 living individuals of A. platanoides, A. pseudoplatanus and F. sylvatica, respectively.
 Additionally stems of dead Acer spp. and F. sylvatica trees that had died within the last three years (2015–2018) were randomly harvested, matching the height classes of the harvested living trees wherever possible. In total, 179 dead young trees (60 A. platanoides, 72 A. pseudoplatanus and 47 F. sylvatica) were collected.
 Variables:
* species_code: a_pla - Acer platanoides, a_pse - Acer pseudoplatanus, f_syl - Fagus sylvatica
* species: as above
* dummy: 0 - living individual, 1 - dead individual
* LAR_cm2_g: leaf area ratio or ratio of leaf area to total plant biomass, [cm2/g]
* tree_age: in years
* avg_ring_micron: average width of the last 5 rings in tree life excluding the last ring
* dry_mass_g: aboveground and belowground biomass
* DLI: direct light index (measured only under living individuals)
* BLI: diffuse light index (measured only under living individuals)
* GLI: global light index

en: acer lar fagus dominance regeneration mortality-rate shade-tolerance

en: Mortality of regeneration: Acer spp. and Fagus sylvatica

en:
Resource Title: Mortality of regeneration
    Size: 60209 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8d9df0cd-f20c-423f-a4ab-71fc213871de/resource/37fb69d9-c553-4931-89ba-31857ac15c04/download/imputed.csv
    Description: Acer platanoides, Acer pseudoplatanus and Fagus sylvatica living and dead juveniles (0-500 cm in height) grown in the deep shade of a prime beech-dominated forest.

en:
Resource Title: Survival_AFT_R_script
    Size: 18015 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/8d9df0cd-f20c-423f-a4ab-71fc213871de/resource/6ff5b7a2-6662-41ab-8c2d-68f688cde189/download/survival_script.r
    Description: The R-script of survival analysis for accelerated failure time model

acer

display_name: acer

dominance

display_name: dominance

fagus

display_name: fagus

lar

display_name: lar

mortality-rate

display_name: mortality-rate

regeneration

display_name: regeneration

shade-tolerance

display_name: shade-tolerance


en:
This data was collected at Mizuho Station (44.315°E, 70.71°S, 2230 m a.s.l.), East Antarctica, from **30 September to 22 November 2000** during the 41st Japanese Antarctic research expedition. Vertical profiles of the horizontal mass flux and particle number size distribution of drifting and blowing snow were measured in the lowest 10 m of the atmosphere using four **snow particle counters** (SPCs). Three 3-dimensional **ultrasonic anemometers** were deployed in the lowest 25 m of the atmosphere to record the wind velocity components and sonic temperature at a high frequency of 100 Hz. Additionally, an **automatic weather station** provided air temperature, relative humidity, air pressure, shortwave and longwave downward and upward radiation fluxes, surface temperature, snow temperatures at depths of 0.1 and 0.4 m below the surface, wind speed, and wind direction. The data is complemented by **weather observations** performed twice to eleven times per day by the Japanese Meteorological Agency.
Most of the time, the lowest SPC was situated at a height of 0.05 or 0.1 m above the snow surface. During certain periods called profile runs, the height of the lowest SPC was systematically varied between 0.02 and 0.2 m to increase the vertical resolution of the measured profiles. The other SPC's were installed at fixed heights of 1.1, 3.1, and 9.6 m. During each profile run, the lowest SPC was kept at a specific height for approximately 10 min before changing the height. If the wind speed remained approximately constant throughout a profile run, the data was used to compute the average snow-transport profile in that period. In total, 24 of such average profiles were obtained. A part of these SPC measurements are discussed in Nishimura and Nemoto (2005).
The ultrasonic anemometers were placed at heights of 0.3, 1, and 25 m. However, the height of the lowest ultrasonic anemometer was changed several times in the measurement period and ranged from 0.05 to 0.32 m. On top of that, 19 short periods (each lasting 15 to 160 min) were used to systematically vary the height of the lowest ultrasonic anemometer and thus increase the vertical resolution of the measured wind speed profile. Occasionally, drifting and blowing snow particles perturbed the ultrasonic measurement signal and electrically-charged particles caused an electric charge of the anemometers, leading to artifacts such as spikes and dropouts in the measured time series. These artifacts were largely removed and replaced by NaN, using the statistical spike removal algorithm of Mauder et al. (2013). However,  the artifact removal was sometimes incomplete for the lowest anemometer because of very intense snow transport close to the surface. While temporal averages are barely affected by the artifacts, the high-frequency data of the lowest anemometer should be used carefully when computing turbulent fluxes using the eddy-covariance method. Further important explanations are provided in the file Readme.pdf in data resource '(a) Metadata'.
References
- Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H.P., Schmidt, M., Steinbrecher, R. (2013). A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements. Agric For Meteorol 169:122–135. https://doi.org/10.1016/j.agrformet.2012.09.006
- Nishimura, K., Nemoto M. (2005). Blowing snow at Mizuho station, Antarctica. Phil. Trans. R. Soc. A. 363: 1647–1662. https://doi.org/10.1098/rsta.2005.1599

en: antarctica meteorological-measurements drifting-snow blowing-snow atmospheric-turbulence

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Profile measurements of snow transport and micrometeorology at Mizuho Station in Antarctica

en:
Resource Title: (h) Sonic data 5
    Size: 1825361101 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/h_Sonic_data_5.zip
    Description: Ultrasonic anemometer data in the period from 6 to 13 November 2000.

en:
Resource Title: (m) Weather observations
    Size: 16589 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/m_Weather_observations.csv
    Description: Weather elements and phenomena observed by the Japanese Meteorological Agency.

en:
Resource Title: (a) Metadata
    Size: 113832 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/a_Metadata.zip
    Description: General and specific metadata for all files.

en:
Resource Title: (k) Wind speed profiles
    Size: 302490 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/k_Wind_speed_profiles.zip
    Description: Average vertical profiles of horizontal wind speed based on the ultrasonic anemometer data.

en:
Resource Title: (f) Sonic data 3
    Size: 1932735283 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/f_Sonic_data_3.zip
    Description: Ultrasonic anemometer data in the period from 21 to 30 October 2000.

en:
Resource Title: (e) Sonic data 2
    Size: 1932735283 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/e_Sonic_data_2.zip
    Description: Ultrasonic anemometer data in the period from 11 to 21 October 2000.

en:
Resource Title: (d) Sonic data 1
    Size: 1825361101 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/d_Sonic_data_1.zip
    Description: Ultrasonic anemometer data in the period from 30 September to 11 October 2000.

en:
Resource Title: (g) Sonic data 4
    Size: 1932735283 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/g_Sonic_data_4.zip
    Description: Ultrasonic anemometer data in the period from 30 October to 6 November 2000.

en:
Resource Title: (j) Spike percentage
    Size: 831078 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/j_Spike_percentage.csv
    Description: Percentage of spikes removed from the ultrasonic anemometer data per 5-min interval.

en:
Resource Title: (i) Sonic data 6
    Size: 1503238554 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/i_Sonic_data_6.zip
    Description: Ultrasonic anemometer data in the period from 13 to 18 November 2000.

en:
Resource Title: (b) SPC time series
    Size: 149946368 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/b_SPC_time_series.zip
    Description: Data from the snow particle counters with 1-s intervals.

en:
Resource Title: (l) AWS data
    Size: 736870 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/l_AWS_data.csv
    Description: Automatic weather station data with 10-min intervals.

en:
Resource Title: (c) SPC average profiles
    Size: 7235174 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.540/c_SPC_average_profiles.zip
    Description: Average vertical profiles of the horizontal snow mass flux, particle number size distribution, and mean and standard deviation of the particle diameter.

antarctica

display_name: antarctica

atmospheric-turbulence

display_name: atmospheric-turbulence

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow


en:
In 2013, the Institute for Applied Plant Biology (IAP) started a monitoring programme to study the development and the spatial variation of the ash dieback disease with the aim to find some partially resistant European ash trees (Fraxinus excelsior).
We collaborate as co-authors for the publication: Spread and Severity of Ash Dieback in Switzerland - Tree Characteristics and Landscape Features Explain Varying Mortality Probability (Klesse et al. 2021 in frontiers)

en: monitoring forest iap fraxinus ash-dieback

envidat

en: EnviDat: the Environmental Data Portal

en: Monitoring of ash trees as part of the Intercantonal Forest Observation Programme

envi

en: Environment

ash-dieback

display_name: ash-dieback

fraxinus

display_name: fraxinus

iap

display_name: iap

monitoring

display_name: monitoring