rorcc

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

en: design-discharge hydropower climate-change environmental-flow run-of-river-power-plants

en: RoRCC

title_for_slug: rorcc

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


$oid: OBSOLETE

en:
Based on the detailed tree stump inventory implemented in the Swiss NFI5 (https://www.lfi.ch/lfi/lfi.php), a study was conducted to obtain an accurate assessment of the stumps pool in the Swiss NFI over the last 30 years and to identify its significance for the total dead wood (DW) pool. The NFI5 includes a detailed stump inventory to improve accuracy and completeness of the above-ground DW- pool. Based on available data, stump volume estimates were derived at different accuracies to evaluate the contribution to the total DW-pool over time.
The study found that in Swiss Forests the contribution of stumps to total DW-pool is approximately 25%, and that applying simplifying assumptions to estimate stump volume can result in a significant underestimation of the true size of this pool. This study demonstrates that stumps can be a significant proportion of DW in forests, which should be accounted for in order to improve accuracy and completeness of NFI estimates and derived data such as C stocks for greenhouse gas reporting.
The study is published in Annals of Forest Science (2022) 79:34, https://doi.org/10.1186/s13595-022-01155-7 (open access).
The data can be obtained from the authors upon reasonable request.

en: protection-forest volume biodiversity carbon national-forest-inventory biomass

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: Stumps as a dead wood resource in forests - data based on the Swiss National Forest Inventory

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: ReadMe_Variables
    Size: 3109 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/82cad928-4741-415e-a3c7-f19ca4a0d72e/download/readme_variables.csv
    Description: Variable definitions for the datasets NFI1, NFI2, NFI3, NFI4 and NFI5

format: CSV

media_type: text/csv

en:
Resource Title: NFI3
    Size: 482387 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/f8dc0cfb-50f1-4f74-b428-27b8a690e406/download/nfi3.zip
    Description: Data on dead standing and downed trees, lying dead wood, and stumps for the NFI3

format: ZIP

media_type: application/zip

en:
Resource Title: NFI5
    Size: 488946 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/b27ae215-7eff-4546-9d08-b0c15d82a6e0/download/nfi5.zip
    Description: Data on dead standing and downed trees, lying dead wood, and stumps for the NFI5

en:
Resource Title: NFI2
    Size: 78643 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/69071e62-9dc2-4b61-91c1-322b0c340a60/download/nfi2.zip
    Description: Data on dead standing and downed trees for the NFI2

en:
Resource Title: Lanz 2014
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    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/72f417d6-3d19-4790-831c-9511f2169b8d/download/international_de.pdf
    Description: A short overview over stump assessment (field protocol) in some European NFIs

format: PDF

media_type: application/pdf

en:
Resource Title: Site Description
    Size: 510752 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/723bfcc7-f2b5-4030-94d5-86bac0f52250/download/sites_2022-03-09.csv
    Description: information on NFI sites throughout the five NFIs considered in this study

en:
Resource Title: NFI1
    Size: 42999 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/9f931dea-8d9b-4d16-b8bd-d933a98e8d9e/download/nfi1.zip
    Description: Data on dead standing and downed trees for the NFI1

en:
Resource Title: NFI4
    Size: 526483 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/94d92a0e-4b3a-43e0-9c1b-1293acda5938/download/nfi4.zip
    Description: Data on dead standing and downed trees, lying dead wood, and stumps for the NFI4

en:
Resource Title: Artikel - Annals of Forest Science
    Size: 1673213 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/dd13b5a9-758e-4416-ac74-446370307374/download/didionabegg2022.pdf
    Description:

en:
Resource Title: ReadMe_Files
    Size: 1278 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d7ccc56-42e8-4005-9cd1-648e0205a82b/resource/8de64d6a-4d7a-4233-a5ab-c4485b1f40a6/download/readme_files.csv
    Description: Files and contents

biodiversity

display_name: biodiversity

biomass

display_name: biomass

carbon

display_name: carbon

national-forest-inventory

display_name: national-forest-inventory

protection-forest

display_name: protection-forest

volume

display_name: volume


en: SnowMicroPen (SMP) measurements and manual snowpits from Dronning Maud Land, East Antarctica. Measurements were taken in the vicinity of the Belgium Princess Elisabeth Station (PEA), in a transect towards the coast, and on the Lokeryggen and Hammarryggen Ice Rises near the coast. Measurements were taken during 3 individual campaigns in the 2016-2017, 2018-2019 and 2019-2020 field seasons.

en: antarctica snow-density snow-density-profile microstructure snowmicropen

en: SnowMicroPen measurements and manual snowpits from Dronning Maud Land, East Antarctica

en:
Resource Title: Python code exported from the Jupyter notebook for processing the SnowMicroPen files
    Size: 5439 bytes
    Format: text/x-python
    URL: https://www.envidat.ch/dataset/02867726-da8e-4e54-ada7-058649af366b/resource/80f9bd9a-ba5f-461d-87ad-b0d65b0bb7ed/download/smp.py
    Description: Python code exported from the Jupyter notebook for processing the SnowMicroPen files

en:
Resource Title: Documentation SnowMicroPen measurements
    Size: 94028379 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/02867726-da8e-4e54-ada7-058649af366b/resource/4c1ab2e9-cfad-463b-bf94-b9d55794371a/download/documentation.zip
    Description: This *.zip archive contains all available documentation of the SnowMicroPen measurements, including the mapping of the SMP measurements in the terrestrial laser scan field at PEA (see documentation for 20161220) and at the Hammarryggen Ice Rise (see documentation for 20190104 and 20190111).

en:
Resource Title: Jupyter notebook for processing the SnowMicroPen files
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    URL: https://www.envidat.ch/dataset/02867726-da8e-4e54-ada7-058649af366b/resource/b18e5359-0134-47d6-aaf9-9f5a04a71543/download/smp.ipynb
    Description: Jupyter notebook for processing the SnowMicroPen files.

en:
Resource Title: List of SnowMicroPen measurements
    Size: 182060 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/02867726-da8e-4e54-ada7-058649af366b/resource/f993bafd-41b1-4978-884b-ee7e721a7f95/download/smp_list.txt
    Description: List of all SnowMicroPen measurements, including date and location, and processing status. This list has been generated by the python code (see other resources in this dataset).

format: TXT

media_type: text/plain

en:
Resource Title: SnowMicroPen pts files and processed txt files
    Size: 579091098 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/02867726-da8e-4e54-ada7-058649af366b/resource/3072110f-5284-4b7c-84c7-81ed98d3e6ee/download/smp_files.zip
    Description: Zip archive containing the acquired *.pts files (binary files recorded by the SnowMicroPen), and the converted *.txt files using the SMP.ipynb jupyter notebook (see the python code in the other resources in this dataset)

en:
Resource Title: Manual snow pits and other snow density measurements
    Size: 30761 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/02867726-da8e-4e54-ada7-058649af366b/resource/b234793d-1a5f-47f8-a7e2-c9e6099dbb7a/download/snowpits.txt
    Description: Manual snow pits and other snow density measurements

antarctica

display_name: antarctica

microstructure

display_name: microstructure

snow-density

display_name: snow-density

snow-density-profile

display_name: snow-density-profile

snowmicropen

display_name: snowmicropen


en: This questionnaire survey was conducted as an online survey and aimed at investigating the relationship between physical forest characteristics, visual attractiveness of forest and the perception of ecological and cultural ecosystem services in urban forests. Each participant was shown 6 photos out of a pool of 50 photos taken from the Swiss National Forest Inventory (NFI) database. Physical forest characteristics were derived from the photos. The study was conducted as part of the "WaMos meets LFI" (WML) project.

en: perception-of-ecosystem-services adults-and-teenagers visual-attractiveness nfi-photos online-questionnaire-survey

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: Relationship between physical forest characteristics, visual attractiveness and perception of ecosystem services in urban forests

envi

en: Environment

en:
Resource Title: Questionnaire French
    Size: 16449968 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4b2ca666-a329-4445-98c1-8d7ce3bca5a5/resource/ee508ecd-8d0f-4be5-b985-69acfdc3fb24/download/umfrageerwachsenefranzosisch.pdf
    Description:

en:
Resource Title: Questionnaire Italian
    Size: 10955256 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4b2ca666-a329-4445-98c1-8d7ce3bca5a5/resource/f4fe792f-05dc-4896-8b1e-541611d9f21c/download/umfrageerwachseneitalienisch.pdf
    Description:

en:
Resource Title: SPSS-Dataset
    Size: 9307772 bytes
    Format: application/x-spss-sav
    URL: https://www.envidat.ch/dataset/4b2ca666-a329-4445-98c1-8d7ce3bca5a5/resource/795a1d55-ec18-4153-9c93-e93109a67bd5/download/umfrage_mitlfi2_2.sav
    Description:

en:
Resource Title: Questionnaire German
    Size: 15478868 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4b2ca666-a329-4445-98c1-8d7ce3bca5a5/resource/31a62f4f-08ae-4baa-98af-f742ea96bc1d/download/umfrageerwachsenedeutsch.pdf
    Description:

en:
Resource Title: Dataset in csv-format
    Size: 5628069 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/4b2ca666-a329-4445-98c1-8d7ce3bca5a5/resource/ced93b4f-1424-4a54-ad92-753d96133fab/download/umfrage_mitlfi2_2.csv
    Description:

en:
Resource Title: Codebook to SPSS-file
    Size: 325674 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4b2ca666-a329-4445-98c1-8d7ce3bca5a5/resource/8a7f9645-ca1b-4fb3-8d9c-94240c0e235e/download/codebookwmlbilderstudie.pdf
    Description:

adults-and-teenagers

display_name: adults-and-teenagers

nfi-photos

display_name: nfi-photos

online-questionnaire-survey

display_name: online-questionnaire-survey

perception-of-ecosystem-services

display_name: perception-of-ecosystem-services

visual-attractiveness

display_name: visual-attractiveness


en:
The wind-driven saltation of sand and snow shapes dunes and ripples, generates dust emission, and erodes the surface of the Antarctic ice sheet. Here, we use a model based on the discrete element method to simulate grain-flow interactions and study the effect of particle cohesion on saltation dynamics.
The data contains the model output of granular splash simulations and saltation simulations. Granular splash, the main particle entrainment process in saltation, occurs upon impact of saltating particles with the granular bed. We performed Monte Carlo simulations of granular splash for loose sand grains and for cohesive ice grains. The analysis indicate that different values of cohesion have significant effects not on the number of splashed grains, on the ejection velocity, and the rebound velocity.
In our saltation simulations, we trigger particle movement with a single splash event at the inlet section section and let the system evolve until steady state. Our results show that saltation over cohesive surfaces is difficult to initiate but easy to sustain at low wind speed. The occurrence of transport thus depends on the history of the wind speed, a phenomenon known as hysteresis. We also show that saltation over cohesive surfaces presents higher mass fluxes but requires longer distances to saturate, which increases the size of the smallest stable surface ripples. Our model results have implications for large-scale aeolian processes on Earth and Titan, where sand grains are thought to be very cohesive.

en: wind sand sediment cohesion snow saltation

en: Saltation of cohesive granular materials

cohesion

display_name: cohesion

saltation

display_name: saltation

sand

display_name: sand

sediment

display_name: sediment

snow

display_name: snow

wind

display_name: wind


disdrometer-data-laret

en:
A laser optical disdrometer (Parsivel&178; , OTT Hydromet) was used to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms.
The dataset contains information on precipitation amount and type for the period of February 7 to March 29 2019 in Laret.

en: disdrometer precipitation raclets visibility hydrometeors

en: Disdrometer Data Laret

title_for_slug: disdrometer-data-laret

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility


disdrometer-data-gotschnagrat

en: A laser optical disdrometer (Parsivel² , OTT Hydromet) was deployed at Gotschnagrat (LON: 9.849, LAT: 46.859) to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms. The dataset contains information on precipitation amount and type for the period of February 11 to March 27 2019 at Gotschnagrat.

en: visibility hydrometeors disdrometer precipitation raclets

en: Disdrometer Data Gotschnagrat

title_for_slug: disdrometer-data-gotschnagrat


en:
This repository contains the source code of the analysis presented in the related paper. The code can be found in the following github repository: https://github.com/Chelmy88/temporal_downscaling
This code can be used to perform temporal downscaling of meteorological time series from daily to hourly time steps and to perform the quality assessment described in the paper.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

en: climate-change-scenarios quantile-mapping alpine-regions delta-change meteoswiss switzerland temporal-downscaling imis python r-script

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: Source code for: Climate change scenarios at hourly time-step over Switzerland from an enhanced temporal downscaling approach

en:
Resource Title: 1_downscaling
    Size: 13945 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73aa91a9-61b6-473c-9962-8d4c28016191/resource/3aa56f6a-4e60-4ba7-866a-e27b06315bea/download/1_downscaling.zip
    Description: Python scripts to perform the temporal downscaling

en:
Resource Title: README
    Size: 2098 bytes
    Format: text/markdown
    URL: https://www.envidat.ch/dataset/73aa91a9-61b6-473c-9962-8d4c28016191/resource/0ebfca71-d997-4586-93fe-7b6fcce8bc0f/download/readme.md
    Description:

format: markdown

en:
Resource Title: LICENSE
    Size: 35149 bytes
    Format: No Info
    URL: https://www.envidat.ch/dataset/73aa91a9-61b6-473c-9962-8d4c28016191/resource/f8e60185-27c1-4abf-ba3e-e272d86c52c8/download/license
    Description:

en:
Resource Title: 2_assessment
    Size: 12817 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73aa91a9-61b6-473c-9962-8d4c28016191/resource/8990361d-87b0-4320-9d79-7788832ffa1d/download/2_assessment.zip
    Description: Python and R scripts to perform the data quality analysis

alpine-regions

display_name: alpine-regions

climate-change-scenarios

display_name: climate-change-scenarios

delta-change

display_name: delta-change

imis

display_name: imis

meteoswiss

display_name: meteoswiss

python

display_name: python

quantile-mapping

display_name: quantile-mapping

r-script

display_name: r-script

switzerland

display_name: switzerland

temporal-downscaling

display_name: temporal-downscaling


en:
Dataset description-br /-
This dataset is a recalculation of the Copernicus 2015 high resolution layer (HRL) of imperviousness density data (IMD) at different spatial/territorial scales for the case studies of Barcelona and Milan. The selected spatial/territorial scales are the following:
 * a)	Barcelona city boundaries
 * b)	Barcelona metropolitan area, Àrea Metropolitana de Barcelona (AMB)
 * c)	Barcelona greater city (Urban Atlas)
 * d)	Barcelona functional urban area (Urban Atlas)
 * e)	Milan city boundaries
 * f)	Milan metropolitan area, Piano Intercomunale Milanese (PIM)
 * g)	Milan greater city (Urban Atlas)
 * h)	Milan functional urban area (Urban Atlas)-br /-
In each of the spatial/territorial scales listed above, the number of 20x20mt cells corresponding to each of the 101 values of imperviousness (0-100% soil sealing: 0% means fully non-sealed area; 100% means fully sealed area) is provided, as well as the converted measure into squared kilometres (km2). -br /- -br /-
-br /- Dataset composition-br /-
The dataset is provided in .csv format and is composed of: -br /-
_IMD15_BCN_MI_Sources.csv_: Information on data sources -br /-
 _IMD15_BCN.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Barcelona:
 * a)	Barcelona city boundaries (label: bcn_city)
 * b)	Barcelona metropolitan area, Àrea metropolitana de Barcelona (AMB) (label: bcn_amb)
 * c)	Barcelona greater city (Urban Atlas) (label: bcn_grc)
 * d)	Barcelona functional urban area (Urban Atlas) (label: bcn_fua)-br /-
 _IMD15_MI.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Milan:
 * e)	Milan city boundaries (label: mi_city)
 * f)	Milan metropolitan area, Piano intercomunale milanese (PIM) (label: mi_pim)
 * g)	Milan greater city (Urban Atlas) (label: mi_grc)
 * h)	Milan functional urban area (Urban Atlas) (label: mi_fua)-br /-
_IMD15_BCN_MI.mpk_: the shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h). -br /-
Regarding the territorial scale as per letter f), the list of municipalities included in the Milan metropolitan area in 2016 was provided to me in 2016 from a person working at the PIM. -br /-
In the IMD15_BCN.csv and IMD15_MI.csv, the following columns are included:
 * Level: the territorial level as defined above (a)-d) for Barcelona and e)-h) for Milan);
 * Value: the 101 values of imperviousness density expressed as a percentage of soil sealing (0-100%: 0% means fully non-sealed area; 100% means fully sealed area);
 * Count: the number of 20x20mt cells corresponding to a certain percentage of soil sealing or imperviousness;
 * Km2: the conversion of the 20x20mt cells into squared kilometres (km2) to facilitate the use of the dataset.-br /- -br /-
-br /- Further information on the Dataset-br /-
This dataset is the result of a combination between different databases of different types and that have been downloaded from different sources. Below, I describe the main steps in data management that resulted in the production of the dataset in an Esri ArcGIS (ArcMap, Version 10.7) project.-br /-
 1. The high resolution layer (HRL) of the imperviousness density data (IMD) for 2015 has been downloaded from the official website of Copernicus. At the time of producing the dataset (April/May 2021), the 2018 version of the IMD HRL database was not yet validated, so the 2015 version was chosen instead. The type of this dataset is raster.
 2. For both Barcelona and Milan, shapefiles of their administrative boundaries have been downloaded from official sources, i.e. the ISTAT (Italian National Statistical Institute) and the ICGC (Catalan Institute for Cartography and Geology). These files have been reprojected to match the IMD HRL projection, i.e. ETRS 1989 LAEA.
 3. Urban Atlas (UA) boundaries for the Greater Cities (GRC) and Functional Urban Areas (FUA) of Barcelona and Milan have been checked and reconstructed in Esri ArcGIS from the administrative boundaries files by using a Eurostat correspondence table. This is because at the time of the dataset creation (April/May 2021), the 2018 Urban Atlas shapefiles for these two cities were not fully updated or validated on the Copernicus Urban Atlas website. Therefore, I had to re-create the GRC and FUA boundaries by using the Eurostat correspondence table as an alternative (but still official) data source. The use of the Eurostat correspondence table with the codes and names of municipalities was also useful to detect discrepancies, basically stemming from changes in municipality names and codes and that created inconsistent spatial features. When detected, these discrepancies have been checked with the ISTAT and ICGC offices in charge of producing Urban Atlas data before the final GRC and FUA boundaries were defined.-br /-
Steps 2) and 3) were the most time consuming, because they required other tools to be used in Esri ArcGIS, like spatial joins and geoprocessing tools for shapefiles (in particular dissolve and area re-calculator in editing sessions) for each of the spatial/territorial scales as indicated in letters a)-h). -br /-
Once the databases for both Barcelona and Milan as described in points 2) and 3) were ready (uploaded in Esri ArcGIS, reprojected and their correctness checked), they have been ‘crossed’ (i.e. clipped) with the IMD HRL as described in point 1) and a specific raster for each territorial level has been calculated. The procedure in Esri ArcGIS was the following:
 * Clipping: Arctoolbox - Data management tools - Raster - Raster Processing - Clip. The ‘input’ file is the HRL IMD raster file as described in point 1) and the ‘output’ file is each of the spatial/territorial files. The option "Use Input Features for Clipping Geometry (optional)” was selected for each of the clipping.
 * Delete and create raster attribute table: Once the clipping has been done, the raster has to be recalculated first through Arctoolbox - Data management tools - Raster - Raster properties - Delete Raster Attribute Table and then through Arctoolbox - Data management tools - Raster - Raster properties - Build Raster Attribute Table; the "overwrite" option has been selected. -br /-
-br /- Other tools used for the raster files in Esri ArcGIS have been the spatial analyst tools (in particular, Zonal - Zonal Statistics). As an additional check, the colour scheme of each of the newly created raster for each of the spatial/territorial attributes as per letters a)-h) above has been changed to check the consistency of its overlay with the original HRL IMD file. However, a perfect match between the shapefiles as per letters a)-h) and the raster files could not be achieved since the raster files are composed of 20x20mt cells.-br /-
The newly created attribute tables of each of the raster files have been exported and saved as .txt files. These .txt files have then been copied in the excel corresponding to the final published dataset.

en: milan urban-atlas barcelona imperviousness soil-sealing copernicus

en: Soil sealing Barcelona and Milan different territorial levels

envi

en: Environment

en:
Resource Title: IMD15_MI
    Size: 9229 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/e4750d6b-e92c-4266-8d15-a04a673ba248/download/imd15_mi.csv
    Description: 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Milan

en:
Resource Title: IMD15_BCN_MI_Sources
    Size: 2730 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/d023c81b-4318-492a-abbf-44e429e9855d/download/imd15_bcn_mi_sources.csv
    Description: Information on data sources

en:
Resource Title: IMD15_BCN_MI
    Size: 9649908 bytes
    Format: .mpk
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/feb17f6a-9d3d-49d7-b072-654e3d210975/download/imd15_bcn_mi.mpk
    Description: Shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h), see Dataset description

en:
Resource Title: IMD15_BCN
    Size: 9402 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/34fc9c0c-1c90-4f87-b3a9-76cc0e888eda/resource/b49ab377-1058-44b0-9db3-eae5af4bb518/download/imd15_bcn.csv
    Description: 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Barcelona

barcelona

display_name: barcelona

copernicus

display_name: copernicus

imperviousness

display_name: imperviousness

milan

display_name: milan

soil-sealing

display_name: soil-sealing

urban-atlas

display_name: urban-atlas


en:
This data set provides estimates of annual fresh water fluxes related to sea-ice formation from ocean freezing and snow-ice formation, sea-ice melting, lateral transport of sea ice in the Southern Ocean over the period 1982 to 2008.It is derived from a mass balance calculation of local sea-ice volume change and divergence from satellite data and sea-ice reconstructions. The mass balance is calculated on a daily basis and fluxes are then integrated over the entire year, where a year is defined from March to February of the next year (i.e. from March 1982 to February 2009). This approach combines multiple products of sea-ice concentration (Cavalieri & Parkinson, 2008;Comiso, 1986; Meier et al., 2013), sea-ice thickness (Kurtz & Markus, 2012; Massonnet et al., 2013; Worby et al., 2008), and sea-ice drift (Fowler et al., 2013; Kwok 2005; Schwegmann et al., 2011). For a detailed description of the method see Haumann et al. (2016). The data set is derived to estimate large-scale (regional to basin-scale) fluxes on an annual basis. Our confidence is reduced on a grid cell basis, such as for single coastal polynyas, where the method and underlying data induce large, unknown uncertainties.
_Disclaimer: This data set is free to use for any non-commercial purpose at the risk of the user and the authors do not take any liability on the use of the data set. The authors assembled the data set carefully and assessed accuracy, errors, and uncertainties. Please contact the authors if you find any issues._
Related publication: http://www.nature.com/nature/journal/v537/n7618/full/nature19101.html (doi:10.1038/nature19101)
Disclaimer: This data set is free to use for any non-commercial purpose at the risk of the user and the authors do not take any liability on the use of the data set. The authors assembled the data set carefully and assessed accuracy, errors, and uncertainties. Please contact the authors if you find any issues.

en: polar salinity forcing sea-ice-divergence satellite melting salt freezing sea-ice physical-oceanography mass-balance transport antartic freshwater-flux sea-ice-volume climate-change cryospheric-science southern-ocean

en: Antarctic sea-ice freshwater fluxes associated with freezing, transport, and melting

en:
Resource Title: AnIceFlux_v01_annual_1982-2008.nc
    Size: 1493303 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/b16a0901-3abe-4da0-b61e-cdb80c59ba63/resource/5de37dd3-e6a7-41b4-b97a-21b14734b861/download/aniceflux_v01_annual_1982-2008.nc
    Description: Data in NetCDF4 CF-1.6 format

en:
Resource Title: Explanatory Document
    Size: 379128 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b16a0901-3abe-4da0-b61e-cdb80c59ba63/resource/a2d8430f-dc92-4a03-b3d6-6661b553bdd1/download/aniceflux_v01.pdf
    Description:

en:
Resource Title:  AnIceFlux_v01_clim_mean_1982-2008.nc
    Size: 260945 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/b16a0901-3abe-4da0-b61e-cdb80c59ba63/resource/6a315e6d-4c92-4f85-b131-92fd87853b65/download/aniceflux_v01_clim_mean_1982-2008.nc
    Description: Data in NetCDF4 CF-1.6 format

en:
Resource Title: Link to Related Publication
    Size: 1 bytes
    Format: application/pdf
    URL: http://www.nature.com/articles/nature19101.epdf?author_access_token=dtLqMQ3Ss6p16tymoagae9RgN0jAjWel9jnR3ZoTv0PH2BR1NrVw3zxcEnl7ViU5pKp8iHAlc_ntQx82EiRMqFRuGOR0VueOUVoGWzy8lSzML6YUBUMMZ5f4LYCdK8Ca
    Description:

antartic

display_name: antartic

climate-change

display_name: climate-change

cryospheric-science

display_name: cryospheric-science

forcing

display_name: forcing

freezing

display_name: freezing

freshwater-flux

display_name: freshwater-flux

mass-balance

display_name: mass-balance

melting

display_name: melting

physical-oceanography

display_name: physical-oceanography

polar

display_name: polar

salinity

display_name: salinity

salt

display_name: salt

satellite

display_name: satellite

sea-ice

display_name: sea-ice

sea-ice-divergence

display_name: sea-ice-divergence

sea-ice-volume

display_name: sea-ice-volume

southern-ocean

display_name: southern-ocean

transport

display_name: transport


en:
The R script IRFnnhs.R, which efficiently estimates impulse response functions for environmental systems that are nonlinear, nonstationary, or heterogeneous, based on their input and output time series.
Scripts and results for a series of benchmark tests are also provided, to accompany Kirchner, J.W., Impulse response functions for heterogeneous, nonstationary, and nonlinear systems, estimated by deconvolution and demixing of noisy time series, _Sensors_, 22(9), 3291, https://doi.org/10.3390/s22093291, 2022.

en: transfer-function greens-function arma-noise deconvolution irf de-mixing system-identification nonlinear-deconvolution time-series-analysis impulse-response-function irfnnhsr

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: Impulse response functions for nonlinear nonstationary and heterogeneous systems

en:
Resource Title: Benchmark demonstration scripts and results
    Size: 27341717 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c093641a-874e-4f8e-a04d-62a07d3855e1/resource/b2a57bb7-8466-4b71-9837-d500e8fa0226/download/benchmark-demonstration-scripts-and-results.zip
    Description:

en:
Resource Title: README file for IRFnnhs.R and benchmark demonstration scripts
    Size: 1315 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/c093641a-874e-4f8e-a04d-62a07d3855e1/resource/de609e80-41d7-41d8-8c73-a58d2c2fdc83/download/irf-code-folder-readme.txt
    Description:

en:
Resource Title: Impulse Response Function script
    Size: 123160 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/c093641a-874e-4f8e-a04d-62a07d3855e1/resource/7fb322da-6bd9-4e68-a8e7-33383b1db36c/download/irfnnhs.r
    Description:

arma-noise

display_name: arma-noise

de-mixing

display_name: de-mixing

deconvolution

display_name: deconvolution

greens-function

display_name: greens-function

impulse-response-function

display_name: impulse-response-function

irf

display_name: irf

irfnnhsr

display_name: irfnnhsr

nonlinear-deconvolution

display_name: nonlinear-deconvolution

system-identification

display_name: system-identification

time-series-analysis

display_name: time-series-analysis

transfer-function

display_name: transfer-function


modeling-snow-failure-with-dem

en: This data set includes the modeling results described in the research article by Bobiller et al. (2020). All the figures in the article can be reproduced with the data provided.

en: snow-failure snow-micro-mechanics discrete-element-modelling snow-avalanche snow

en: Modeling snow failure with DEM

title_for_slug: modeling-snow-failure-with-dem

envi

en: Environment

en:
Resource Title: Read-me
    Size: 174785 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/a3ace234-0794-4b75-bf17-3790744ed665/resource/8142e5f2-74cd-49ae-b64f-87d9600b8b53/download/read_me.pdf
    Description: The read-me file contains a description of all the data provided in the zip file.

en:
Resource Title: Dataset
    Size: 268629 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a3ace234-0794-4b75-bf17-3790744ed665/resource/73b649d7-b035-4815-b97a-bd8ecdf97a27/download/data.zip
    Description: The zip file contains the data underlying the figures presented in Bobillier et al. (2019). The figures can be reproduced with the python file, which is also provided.

en:
Resource Title: Python file
    Size: 32003 bytes
    Format: text/x-python
    URL: https://www.envidat.ch/dataset/a3ace234-0794-4b75-bf17-3790744ed665/resource/bcd1cf92-6c73-4bf4-83fb-96b8fc7c93b9/download/plot_figures.py
    Description: Python file to reproduce the figures in Bobillier et al. (2019)

discrete-element-modelling

display_name: discrete-element-modelling

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-micro-mechanics

display_name: snow-micro-mechanics


en:
This dataset includes discharge and rainfall measurements and deuterium compositions of streamflow, rainfall and groundwater, for four rainfall events and three baseflow snapshot campaigns in the Studibach (Alptal, Switzerland). More specifically, we present the following data:
- Specific discharge at the catchment outlet at 5-minute resolution (mm per hour);
- Rainfall at 5-minute resolution (mm per hour);
- Rainfall deuterium composition (‰);
- Stormflow deuterium composition (‰);
- Groundwater and baseflow deuterium compositions (‰).
For the files containing rainfall and discharge timeseries (QP), and rainfall and streamwater deuterium compositions ("Deuterium_Rainfall" and "Deuterium_Streamwater"), we added the corresponding event identifier (A, B, C or extra) to the file names. For the files containing the groundwater and baseflow deuterium values ("Deuterium_Snapshot") we added the sample collection date to the file name. We included the X and Y coordinates for each data point (coordinate system: CH1903 LV3) as well as the date and time (UTC).
More information on the data collection and preparation can be found in Kiewiet et al. (in review). A detailed description of the baseflow snapshot campaigns can also be found in Kiewiet et al., 2019.

en: alptal groundwater stable-water-isotopes streamflow runoff

en: Discharge, rainfall, and deuterium compositions of streamwater, rainwater and groundwater, for four rainfall events in the Studibach, Alptal, Switzerland

en:
Resource Title: Deuterium streamwater extra event
    Size: 1907 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/c09c3cd0-6a4b-4e3d-aa6e-7541241be20a/download/deuterium_streamwater_extraevent.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

en:
Resource Title: Deuterium groundwater and baseflow August 2017
    Size: 2022 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/287f9bcc-b876-4170-bce7-1e508982c8b9/download/deuterium_snapshot_aug2017.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

en:
Resource Title: Deuterium rainfall extra event
    Size: 2228 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2f6feb1a-ccfa-4aac-bacd-335760905550/download/deuterium_rainfall_extraevent.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

en:
Resource Title: Precipitation and discharge extra event
    Size: 45996 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/6983ae41-90ad-4000-9b13-d6a4942e38cb/download/qp_extraevent.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

en:
Resource Title: Deuterium groundwater and baseflow October 2016
    Size: 2170 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/73fc4834-881f-4547-9b7b-52ca2be61f71/download/deuterium_snapshot_oct2016.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

en:
Resource Title: Deuterium streamwater event B
    Size: 1300 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2e8bed6f-98be-47ef-8976-2df51703db3f/download/deuterium_streamwater_eventb.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

en:
Resource Title: Deuterium rainfall event C
    Size: 1044 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/993b5d45-b0aa-4bf8-a9b9-1a8fc950ba7a/download/deuterium_rainfall_eventc.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

en:
Resource Title: Precipitation and discharge event A
    Size: 13862 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2d765186-0ae0-4b43-bc34-cbad9edba879/download/qp_eventa.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

en:
Resource Title: Deuterium rainfall event A
    Size: 960 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/712f8d2e-129c-4ed4-ae19-eab3d2836511/download/deuterium_rainfall_eventa.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

en:
Resource Title: Precipitation and discharge event B
    Size: 9733 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/51bf0d6f-a68c-4e75-b5a1-1c81bbc7a9ea/download/qp_eventb.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

en:
Resource Title: Deuterium streamwater event A
    Size: 1273 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2add59a1-5621-4b0b-949e-e144e66de9e8/download/deuterium_streamwater_eventa.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

en:
Resource Title: Deuterium streamwater event C
    Size: 1246 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/2b90dbcd-8fd7-440d-b0e0-4b724d688dc5/download/deuterium_streamwater_eventc.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

en:
Resource Title: Precipitation and discharge event C
    Size: 8146 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/684ec1fc-df96-42ab-ba3c-0b4f981776ad/download/qp_eventc.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

en:
Resource Title: Deuterium groundwater and baseflow October 2017
    Size: 2208 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/cc4b2f2b-537d-49e2-ac0a-c82216ad99d9/download/deuterium_snapshot_oct2017.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

en:
Resource Title: Deuterium rainfall event B
    Size: 880 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/dd1a478e-23f4-49e5-a240-c1985147bf27/resource/98b1bd86-e4a4-46f9-a75a-e871cab67aad/download/deuterium_rainfall_eventb.csv
    Description: This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

alptal

display_name: alptal

groundwater

display_name: groundwater

runoff

display_name: runoff

stable-water-isotopes

display_name: stable-water-isotopes

streamflow

display_name: streamflow


en:
This database contains 1957 distribution maps of species from Fagales and Pinales constructed based on a method integrating polygon mapping and SDMs (Lyu et al., 2022).
To construct the maps, we first collected occurrence data from 48 different sources. According to the number of occurrences after data cleaning, three kinds of maps are constructed: (1) For species with more than 20 occurrences, we performed SDM and polygon mapping described in Lyu et al. (2022) and select the integration of the two layers as the distribution range; (2) For species with more than 4 but less than 20 occurrences, we only use polygon mapping to draw the distribution range; (3) For species with less than 4 occurrences, a 20-km buffer was generated around the occurrences as the distribution range. The maps were manually checked and evaluated (see Note S3 and Table S9 in Lyu et al., 2022 for details).

en: pinales species-richness species-range-map species-distribution-model fagales species-occurrence

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: Species distribution maps of Fagales and Pinales (GDPlants)

envi

en: Environment

en:
Resource Title: Species range maps of species in Fagales and Pinales (with enough occurrences)
    Size: 37517772 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/aee8c2bd-ca0b-4de0-a41f-940dc11984e6/resource/6c946cd2-e08b-44e0-8fda-4ab01b6b43b9/download/species_maps.zip
    Description: species_map.zip includes species 1690 range maps generated based on the integrated method described in Lyu et al., (2022). File names with (polygon) indicate that this map is only generated by polygon mapping, as there are not enough occurrences for SDMs.

en:
Resource Title: Occurrence maps for species of Fagales and Pinales with few records
    Size: 32315283 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/aee8c2bd-ca0b-4de0-a41f-940dc11984e6/resource/9239265c-dba9-413d-9fc6-40beb3cb7368/download/point_buffers.zip
    Description: Point_buffer.zip includes 267 occurrence maps of species that do not have enough occurrence data for polygon mapping.

fagales

display_name: fagales

pinales

display_name: pinales

species-distribution-model

display_name: species-distribution-model

species-occurrence

display_name: species-occurrence

species-range-map

display_name: species-range-map

species-richness

display_name: species-richness


en:
These data include all avalanches that were mapped in the region of Davos, Switzerland during the winters 1998-1999 to 2018-2019 (21 years), in total 13,918 avalanches, and the corresponding forecast danger level valid on the day of avalanche occurrence, 3533 days and danger ratings in total.
This avalanche activity data set was analysed and results published by Schweizer et al. (2020). They found that the
number of avalanches per day strongly increased with increasing danger level, but avalanche size was poorly related  to avalanche danger level.
The data are provided in two files: the first includes the avalanche data (13,918 records); the second includes the avalanche activity per day (3533 records).
Please refer to the Read-me file for further details on the data.
These data are the basis of the following publication:
Schweizer, J., Mitterer, C., Techel, F., Stoffel, A. and Reuter, B., 2020. On the relation between avalanche occurrence and avalanche danger level. The Cryosphere, 14, 737-750, https://doi.org/10.5194/tc-14-737-2020.

en: avalanche-activity snow-avalanche avalanche-size danger-level avalanche-forcasting

en: Snow avalanche data Davos, Switzerland, 1999-2019

en:
Resource Title: Snow avalanche data
    Size: 936455 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ce11efbe-4dac-4ff5-9a3d-f01e2c573292/resource/4c2b7c38-a874-45fc-9833-fdf83823067b/download/data_set_1_avalanche_observations_wi9899_to_wi1819_davos.csv
    Description: This data file includes data on the avalanches mapped in the region of Davos.

en:
Resource Title: Avalanche activity data
    Size: 929518 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ce11efbe-4dac-4ff5-9a3d-f01e2c573292/resource/39e6dd9e-9b52-439e-a4d1-5e17a8e18eca/download/data_set_2_danger_avalanches.csv
    Description: This data file includes data on the avalanche activity per day aggregated from the avalanche data.

en:
Resource Title: Readme
    Size: 159745 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ce11efbe-4dac-4ff5-9a3d-f01e2c573292/resource/f8d6835f-3ef6-4fe6-94a2-6b7f7b5827ce/download/read_me.pdf
    Description: The Readme file contains the description of the two data files.

avalanche-activity

display_name: avalanche-activity

avalanche-forcasting

display_name: avalanche-forcasting

avalanche-size

display_name: avalanche-size

danger-level

display_name: danger-level


en:
This is the source code to compute rainfall thresholds for debris flows or landslides following Hirschberg et al. (2021).
 How to install and run the example
Pyhton has to be installed to run the codes. To make sure it works correctly, it is easiest to install Anaconda and create an environment with the right packages from the yml-file. To this end, in a command-line interpreter, change the working directory to where you saved this project and run the following:
`$ conda env create -f environment.yml`
`$ conda activate thresholds` or `$ source activate thresholds`
To run an example:
`$ python run_example()`
It will save a dat-file and a figure as Fig. 7 in Hirschberg et al. (2021), where more information can be found.
 License
GNU General Public License v3.0

en: landslide rainfall-thresholds debris-flow random-forest illgraben python

en: Source code for: Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment

debris-flow

display_name: debris-flow

illgraben

display_name: illgraben

landslide

display_name: landslide

python

display_name: python

rainfall-thresholds

display_name: rainfall-thresholds

random-forest

display_name: random-forest


aerosol-data-weissfluhjoch

en:
Aerosol properties were measured between February 8 and March 31 2019  at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (- 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.
Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 &956;m) and GT-526S (0.3 – 5 &956;m), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM&8321;, PM&8322;,&8325; and PM&8321;&8320; (assumptions: particle density: 1.65 g cm&713;&179;, refractive index: 1.5+i0).
Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 &956;m and ~20 &956;m by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cm&713;&179;).
Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cm&713;&179;).
Coriolis &956; and LINDA: A microbial air sampler (Coriolis &956;, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 &956;m were drawn with an air flow rate of up to 300 l min&8254;&185; into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

en: raclets ice-nucleation linda aerosol inp particles

en: Aerosol Data Weissfluhjoch

title_for_slug: aerosol-data-weissfluhjoch

en:
Resource Title: OPC-N3 Dataset Weissfluhjoch
    Size: 54387041 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/3932aae8-fa08-4dd7-bb1c-35cdfe3859bf/download/opc-n3_weissfluhjoch.csv
    Description: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

en:
Resource Title: OPC-GT526S Dataset Weissfluhjoch
    Size: 11552644 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/6e0ab260-4ec2-4b08-b485-63bbed6b4433/download/opc-gt526s_weissfluhjoch.csv
    Description: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

en:
Resource Title: LINDA Dataset Weissfluhjoch
    Size: 191898 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/6451c23d-b1ec-4100-8f78-ba35611e540f/download/raclets_inp_wfj.nc
    Description: The LINDA file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en:
Resource Title: SMPS Dataset Weissfluhjoch
    Size: 32316159 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/585a81d2-1d89-4453-b9b0-49176e48359d/download/smps_weissfluhjoch.nc
    Description: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity) in a temporal resolution of 2 minutes, with time in UTC, measured at Weissfluhjoch.

en:
Resource Title: APS Dataset Weissfluhjoch
    Size: 98624420 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/67ab6458-99fd-4f2e-b707-20c8dcf52109/resource/c7846a5d-4a0f-462b-bddc-594bfb6a578b/download/aps_weissfluhjoch.nc
    Description: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Weissfluhjoch.

aerosol

display_name: aerosol

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

linda

display_name: linda

particles

display_name: particles

raclets

display_name: raclets


aerosol-data-davos-wolfgang

en:
Aerosol properties were measured between February 8 and March 31 2019  at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (- 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.
Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 &956;m) and GT-526S (0.3 – 5 &956;m), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM&8321;, PM&8322;,&8325; and PM&8321;&8320; (assumptions: particle density: 1.65 g cm&713;&179;, refractive index: 1.5+i0).
Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 &956;m and ~20 &956;m by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cm&713;&179;).
Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cm&713;&179;).
Coriolis &956; and DRINCZ: A microbial air sampler (Coriolis &956;, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 &956;m were drawn with an air flow rate of up to 300 l min&713;&185; into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

en: drincz inp aerosol particles raclets ice-nucleation

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: Aerosol Data Davos Wolfgang

title_for_slug: aerosol-data-davos-wolfgang

envi

en: Environment

en:
Resource Title: DRINCZ Dataset Davos Wolfgang
    Size: 181636 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/03a2914e-d0c6-438a-b4c0-5f576db641da/resource/6c39beac-0605-4915-9f93-ef22ff5b29f4/download/raclets_inp_wop.nc
    Description: The DRINCZ file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en:
Resource Title: APS Dataset Davos Wolfgang
    Size: 100296188 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/03a2914e-d0c6-438a-b4c0-5f576db641da/resource/1b62d21e-674c-4fa4-884b-cce7f18801e6/download/aps_wolfgang.nc
    Description: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Davos Wolfgang.

en:
Resource Title: SMPS Dataset Davos Wolfgang
    Size: 32383567 bytes
    Format: application/x-netcdf
    URL: https://www.envidat.ch/dataset/03a2914e-d0c6-438a-b4c0-5f576db641da/resource/1135c794-6c1c-49cb-9189-4d0a67f15b0d/download/smps_wolfgang.nc
    Description: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity), in a temporal resolution of 2 minutes, with time in UTC, measured at Davos Wolfgang.

en:
Resource Title: OPC-N3 Dataset Davos Wolfgang
    Size: 30756674 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/03a2914e-d0c6-438a-b4c0-5f576db641da/resource/2632179e-3c62-45f8-9454-c3d946ccf430/download/opc-n3_wolfgang.csv
    Description: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

en:
Resource Title: OPC GT-526S Dataset Davos Wolfgang
    Size: 14718206 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/03a2914e-d0c6-438a-b4c0-5f576db641da/resource/a0a29389-e885-4e4d-bc5f-a65913a0ba46/download/opc-gt526s_wolfgang.csv
    Description: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

drincz

display_name: drincz


en:
This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format.
The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication:
_Schürholt, K., Kowalski, J., Löwe, H.; Elements of future snowpack modeling - Part 1: A physical
instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_
The code and potential updates can be accessed directly through git via:
https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics

en: numerical-model pattern-formation vapor-transport python snow

en: A numerical solver for heat and mass transport in snow based on FEniCS

numerical-model

display_name: numerical-model

pattern-formation

display_name: pattern-formation

snow

display_name: snow

vapor-transport

display_name: vapor-transport


causal-effect-of-mfoz

en:
Title: Closer to causality: How effective is spatial planning in governing built-up land expansion in Fujian Province, China?
Research objective: The Major Function Oriented Zone (MFOZ), the first strategic spatial plan in China, is developed to achieve a coordinated regional development, through spatial regulation and zoning of development. The MFOZ he MFOZ divided land into four major function-oriented zones: The development-optimized zone, the development-prioritised zone, the development-restricted zone, and the development-prohibited zone. We used propensity score marching to evaluate the effect of the MFOZ on built-up land expansion in Fujian Province over three time intervals (2013–2015, 2013–2018 and 2013–2020).
Data: Data.xlsx contains the variables of 954 towns in Fujian Province.
Town_ID is the town unique ID;
County_ID is the county unique ID;
City_ID is the city unique ID;
MFOZ is the the development-prioritised zone and the development-restricted zone (The development-optimized zone and the development-prohibited zone are excluded);
Builtup_13_15 is the built-up land expansion from 2013 to 2015;
Builtup_13_18 is the built-up land expansion from 2013 to 2018;
Builtup_13_20 is the built-up land expansion from 2013 to 2020;
Dis2water is the Euclidean distance from the town to the nearest waterbody;
Slope is the the average slope within the town;
GDP is the average GDP in 2010 within the town;
Pop is the average population in 2010 within the town;
Road is the average population in 2010 within the town;
Dis2city is the Euclidean distance from the town to the nearest prefectural city centre;
Nei_Arable, Nei_Forest, and Nei_Built.up are the area of arable land, forest land, and built-up land neighbouring town i in 2010.
Method: we used the propensity score matching to compare the changes in the amount of built-up land in the towns of the development-prioritised zone with the matched towns of the development-restricted zone. Additionally, we used three evaluation intervals (2013–2015, 2013–2018 and 2013–2020) to evaluate temporal variation in the causal effect of the MFOZ on built-up land expansion.

en: fujian-province causality the-major-function-oriented-zone propensity-score-matching built-up-land-change selection-bias

en: Causal effect of MFOZ

title_for_slug: causal-effect-of-mfoz

built-up-land-change

display_name: built-up-land-change

causality

display_name: causality

fujian-province

display_name: fujian-province

propensity-score-matching

display_name: propensity-score-matching

selection-bias

display_name: selection-bias

the-major-function-oriented-zone

display_name: the-major-function-oriented-zone


causal-effect-of-lup

en:
Title: Does zoning contain built-up land expansion? Causal evidence from Zhangzhou City, China.
Research objective: Built-up land zoning is an imporatant policy measure of land use planning (LUP) to contain built-up land expansion in China. We used a difference-indifference model with propensity score matching to estimate the average and annual effect of built-up land zoning on built-up land expansion in Zhangzhou City, China between 2010 and 2020.
Data: Data.dbf contains the varibles of 1662 villages in Zhangzhou Cities in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020.
XZQDM2 is villages' unique administrative ID;
Area is the land area of village i;
Dis2water is the Euclidean distance from village i to the nearest waterbody;
Dis2coastl is the Euclidean distance from village i to the nearest coastline;
Dis2city is the the Euclidean distance from village i to the city center;
Dis2county is the the Euclidean distance from village i to the nearest county center;
Elevation is the the average elevation within village i;
Dis2road is the the Euclidean distance from village i to the nearest road;
Nei_Built_ is the the area of built-up land (Nei Built.upit) in the neighboring villages of village i in year t;
Treated is a binary variable, Treated = 1 to the villages that were partially or entirely located inside the development-permitted zones, and Treated = 0 to the villages that were entirely located outside the development-permitted zones;
Intensity is the percentage of land that was assigned to the development-permitted zones in village i;
Year represent the year in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020;
BuLE is the dependent variable, representing built-up land expansion in village i in year t;
Town is town' unique administrative ID.
Method: First, we employed propensity score matching to overcome the selection bias and satisfy the parallel trend
assumption. Second, we built four Difference-in-Difference models to estimate the average and annual effect.

en: land-use-change land-use-planning plan-evaluation annual-effect psm-did

en: Causal effect of LUP

title_for_slug: causal-effect-of-lup

annual-effect

display_name: annual-effect

land-use-change

display_name: land-use-change

land-use-planning

display_name: land-use-planning

plan-evaluation

display_name: plan-evaluation

psm-did

display_name: psm-did


en: The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

en: land-use urban-morphology landscape austin land-dynamics

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: Land use/cover dynamics in Austin metropolitan area since 1992

austin

display_name: austin

land-dynamics

display_name: land-dynamics

land-use

display_name: land-use

landscape

display_name: landscape

urban-morphology

display_name: urban-morphology


en: The data results from a questionnaire survey conducted at 8 schools in the cantons Zurich, Aargau and St. Gallen. Respondents aged 13-22 years. The aim of the survey was to gain insight into teenagers' relationship to the forest, reasons for visiting or not visiting the forest and activities in the forest.

en: childhood forest adolescents recreational-activities teenagers

en: Factors influencing teenagers' forest visit frequency

envi

en: Environment

en:
Resource Title: Questionnaire school survey
    Size: 141278 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/c7f5fdd3-361e-44bf-ba4c-fa97f6164bf0/download/fragebogenv2.pdf
    Description: The questionnaire used in the survey at 8 schools aimed at teenagers in German.

en:
Resource Title: Dataset comments
    Size: 32680 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/29308f48-7be2-4afb-9b4d-829c5618e50a/download/datensatz-kommentar.xlsx
    Description: The codebook to the dataset

format: XLS

en:
Resource Title: Dataset survey at schools
    Size: 844175 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/9b9bee0b-a041-4870-b845-1115c5deed6d/download/datensatz-umfrage-schulen.xlsx
    Description: The dataset of the questionnaire survey at schools in excel format.

en:
Resource Title: Survey at schools 2017
    Size: 638125 bytes
    Format: application/x-spss-sav
    URL: https://www.envidat.ch/dataset/04ecf3b8-76aa-4b45-af4e-e06da88a8fcd/resource/fe6746a6-96c4-484e-99c4-8f8556d76d86/download/datensatz-umfrage-schulen.sav
    Description: The dataset of the questionnaire survey at schools in SPSS-format.

adolescents

display_name: adolescents

childhood

display_name: childhood

forest

display_name: forest

recreational-activities

display_name: recreational-activities

teenagers

display_name: teenagers


en: The data includes (1) amphibian occurrence data (2017-2019) for ten species across the cantons of Aargau and Zürich gathered from the Coordination Center for the Protection of Amphibians and Reptiles of Switzerland (http://www.karch.ch), (2) amphibian whole-life cycle environmental predictors (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related), and (3) local urban "green" and "grey" landcover data which can be used to identify opportunities for Blue-Green Infrastructure (through green or grey transitions) in support of regional landscape connectivity.

en: integrated-modelling human-dominated-landscapes ecological-corridors biodiversity circuit-theory urban-spatial-planning

en: Amphibian and urban-rural landscape data Swiss Lowlands

en:
Resource Title: Amphibian monitoring data
    Size: 310101 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/ce42d731-4b85-4da0-b356-35deb8f80607/download/amphibian_presence_2017_2019.csv
    Description: Processed amphibian occurrence data (2017-2019) in the cantons of Aargau and Zürich. The dataset includes information for the following species:  _Alytes obstetricans_,_Bombina variegata_, _Bufo bufo_, _Hyla arborea_, _Ichtyosaura alpestris_, _Lissotriton helveticus_, _Lissotriton vulgaris_, _Rana temporaria_, _Salamandra salamandra_, and _Triturus cristatus_.

en:
Resource Title: Amphibian species specific landscape resistance maps.
    Size: 51864736 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/acaac64b-3ebe-4e97-ae24-a35736dfa1d5/download/resistance.zip
    Description: For each amphibian species we used the weighted average Ensemble model suitability map and converted it to a resistance map using an exponential decay function following (Duflot et al., 2018) using the species-specific mpa threshold previously computed (Preau et al., 2020). The function assigns a resistance value of 1,000 when habitat suitability equals zero, and a value of one when habitat suitability is greater than or equal to the binarization threshold. The exponential shape strengthens the barrier effect of less favorable areas.

en:
Resource Title: Amphibian breeding sites of national importance - cantons of Aargau and Zürich
    Size: 39808424 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/fd5b1fe3-bdf9-4095-816a-edaf22178df2/download/breeding_sites_raster_30m.asc
    Description: Amphibian breeding sites of national importance (focal nodes) in the cantons of Aargau and Zürich, 30x30 m resolution, binarised ascii format.

format: pgp-keys

en:
Resource Title: Binarized "green" and "grey" landcover data (Cantons of Aargau and Zürich)
    Size: 531399 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/5752ef42-b6cc-4365-bb61-288dfa3d5d95/download/urban_green_grey.zip
    Description: "Green" landcover refers to lawns and vegetated urban surfaces such as, for example private gardens, public parks, cemeteries, green stripes along roadsides, etc. While "grey" landcover refers to impervious grounds such as roads, troittoirs, other impervious. Binarized maps, 30x30m resolution.

en:
Resource Title: Amphibian whole life cycle predictors - 10m resolution
    Size: 734915785 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/26ceef50-633c-469b-970d-cd6e453e9500/download/amphibian_predictors_sdms.zip
    Description: Amphibian whole life cycle predictors include 6 variable types:
(1)	Topographic – slope [°]: derived from the Swiss Topographical Landscape model (swissTLM 3D 2015) at 2 m resolution (elevation uncertainty ± 0.5m) and, subsequently, aggregated to a median value;
(2)	Hydrologic: two predictors including nearest distance to water [m] (all water-related objects and rasterized lotic, lentic and reedbeds from the regional cadastral maps – AV: Daten der Amtliche Vermessung) and runoff coefficient [C] (between 0 and 1 relating amount of runoff to amount of precipitation, mapped AV: Daten der Amtliche Vermessung data against literature values for different land covers);
(3)	Edaphic – soil moisture variability (not available): can gathered from the spatial modelling of Ecological Indicator Values in Switzerland (Descombes et al., 2020) and resampled from 100m to 10m;
(4)	Vegetation: we calculated the median and standard deviation of the Normalized Difference Vegetation Index (NDVI) from all available cloud free Sentinel-2 pixels available between April and October for the years 2016 to 2019 (Drusch et al., 2012) and the median vegetation height [m] (not available) can gathered from Ginzler and Hobi (2015);
(5)	Land-use derived: includes three predictors, grassland density [grassland/cell] (not available) - can be gathered from Pazur et al. (2021), total grasslands area evaluated using a spatial weight matrix and a 250m neighborhood radius around each cell; urbanization [buildings/cell] – average building density for a 250m neighborhood around each cell based on the AV: Daten der Amtliche Vermessung ; and traffic intensity [vehicles/day] – average daily vehicle count (Nationales Personenverkehrsmodells);
(6)	Movement-ecology related: includes three predictors of proximity – nearest forest distance [m]; nearest rock-gravel and sandy area (RGS) distance [m] and nearest road distance [m] (considering any road type) – all calculated based on the AV: Daten der Amtliche Vermessung maps.

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

human-dominated-landscapes

display_name: human-dominated-landscapes

integrated-modelling

display_name: integrated-modelling

urban-spatial-planning

display_name: urban-spatial-planning


biogas-aus-hofdunger-in-der-schweiz

en: Ziel dieses Whitepapers ist es, Entscheidungsträgern, Verwaltungen und Stakeholdern die aktuellsten Forschungsergebnisse zur Verfügung zu stellen, um die optimale Nutzung von Bioenergie aus Hofdünger in der Schweizer Energiewende zu fördern. Zu diesem Zweck werden die Ergebnisse des Schweizer Kompetenzzentrums für Bioenergieforschung - SCCER BIOSWEET - zusammengefasst und in einem breiteren Kontext dargestellt. Wenn nichts anderes erwähnt wird, beziehen sich die Ergebnisse auf die Schweiz und im Falle der Ressourcen auf die heimischen Biomassepotenziale.

en: biogas bioenergy manure switzerland review

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: Biogas aus Hofdünger in der Schweiz

title_for_slug: biogas-aus-hofdunger-in-der-schweiz

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland


en: L'objectif de ce livre blanc est de fournir aux décideurs, aux administrations et aux parties prenantes les résultats de recherche les plus récents afin de promouvoir l'utilisation optimale de la bioénergie issue des engrais de ferme dans la transition énergétique suisse. A cette fin, les résultats du centre de compétence suisse pour la recherche en bioénergie - SCCER BIOSWEET - sont résumés et présentés dans un contexte plus large. Si rien d'autre n'est mentionné, les résultats se réfèrent à la Suisse et, dans le cas de la matière première, aux potentiels nationaux de biomasse.

en: review biogas bioenergy manure switzerland

en: Production de biogaz à partir d’engrais de ferme en Suisse

envi

en: Environment


en: Aim of this white paper is to provide decision-makers, administrations and stakeholders with the most current research findings in order to promote the optimal use of bioenergy from manure in the Swiss energy transition. For this purpose, the results of the Swiss competence center for bioenergy research - SCCER BIOSWEET - are summarized and presented in a broader context. If nothing else is mentioned, the results refer to Switzerland and in case of the feedstock to the domestic biomass potentials.

en: switzerland review biogas bioenergy manure

en: Biogas from animal manure in Switzerland