Forest canopy structure data for radiation and snow modelling (CH/FIN) ...
This dataset contains forest canopy structure data acquired in a spruce forest at Laret, Switzerland, and a pine forest at Sodankylä, Finland. Data include: * Hemispherical photographs taken at transect intersection points of 13 experimental plots (40x40m each) * a Canopy Height Model (tree height m...
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Online Access: | https://dx.doi.org/10.16904/envidat.220 https://envidat.ch/#/metadata/chm-hp-4rtm |
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ftdatacite:10.16904/envidat.220 2023-06-11T04:16:40+02:00 Forest canopy structure data for radiation and snow modelling (CH/FIN) ... Mazzotti, Giulia Webster, Clare Jonas, Tobias 2020 .zip ascii x, y, z https://dx.doi.org/10.16904/envidat.220 https://envidat.ch/#/metadata/chm-hp-4rtm en eng EnviDat https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/5d071a02-e48e-4719-bce4-2e662d452dfe/download/hemisphericalphotos.zip https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/1b4aaf5f-545f-4afc-a045-73ccd4885747/download/chm_cropped.asc https://dx.doi.org/10.1029/2020wr029064 https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/5d071a02-e48e-4719-bce4-2e662d452dfe/download/hemisphericalphotos.zip https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/1b4aaf5f-545f-4afc-a045-73ccd4885747/download/chm_cropped.asc WSL Data Policy https://www.wsl.ch/en/about-wsl/programmes-and-initiatives/envidat.html ENERGY BALANCE FOREST CANOPY MASS BALANCE SNOW MODELLING UPSCALING Dataset dataset 2020 ftdatacite https://doi.org/10.16904/envidat.22010.1029/2020wr029064 2023-05-02T10:28:31Z This dataset contains forest canopy structure data acquired in a spruce forest at Laret, Switzerland, and a pine forest at Sodankylä, Finland. Data include: * Hemispherical photographs taken at transect intersection points of 13 experimental plots (40x40m each) * a Canopy Height Model (tree height map) derived by rasterizing airborne LiDAR data, encompassing the entire simulation domain at Laret (150'000 m2) These data provide the necessary basis for creating canopy structure datasets to be used as input to the forest snow snow model FSM2. These datasets, the model input derivatives and the radiation and snow modelling are described in detail in the following publication: _Mazzotti, G., Webster, C., Essery, R., and Jonas, T. (2021) Improving the physical representation of forest snow processes in coarse-resolution models: lessons learned from upscaling hyper-resolution simulations. Water Resources Research 57, e2020WR029064. [doi: 10.1029/2020WR029064](https://doi.org/10.1029/2020WR029064)_ This publication ... Dataset Sodankylä DataCite Metadata Store (German National Library of Science and Technology) Sodankylä ENVELOPE(26.600,26.600,67.417,67.417) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
ENERGY BALANCE FOREST CANOPY MASS BALANCE SNOW MODELLING UPSCALING |
spellingShingle |
ENERGY BALANCE FOREST CANOPY MASS BALANCE SNOW MODELLING UPSCALING Mazzotti, Giulia Webster, Clare Jonas, Tobias Forest canopy structure data for radiation and snow modelling (CH/FIN) ... |
topic_facet |
ENERGY BALANCE FOREST CANOPY MASS BALANCE SNOW MODELLING UPSCALING |
description |
This dataset contains forest canopy structure data acquired in a spruce forest at Laret, Switzerland, and a pine forest at Sodankylä, Finland. Data include: * Hemispherical photographs taken at transect intersection points of 13 experimental plots (40x40m each) * a Canopy Height Model (tree height map) derived by rasterizing airborne LiDAR data, encompassing the entire simulation domain at Laret (150'000 m2) These data provide the necessary basis for creating canopy structure datasets to be used as input to the forest snow snow model FSM2. These datasets, the model input derivatives and the radiation and snow modelling are described in detail in the following publication: _Mazzotti, G., Webster, C., Essery, R., and Jonas, T. (2021) Improving the physical representation of forest snow processes in coarse-resolution models: lessons learned from upscaling hyper-resolution simulations. Water Resources Research 57, e2020WR029064. [doi: 10.1029/2020WR029064](https://doi.org/10.1029/2020WR029064)_ This publication ... |
format |
Dataset |
author |
Mazzotti, Giulia Webster, Clare Jonas, Tobias |
author_facet |
Mazzotti, Giulia Webster, Clare Jonas, Tobias |
author_sort |
Mazzotti, Giulia |
title |
Forest canopy structure data for radiation and snow modelling (CH/FIN) ... |
title_short |
Forest canopy structure data for radiation and snow modelling (CH/FIN) ... |
title_full |
Forest canopy structure data for radiation and snow modelling (CH/FIN) ... |
title_fullStr |
Forest canopy structure data for radiation and snow modelling (CH/FIN) ... |
title_full_unstemmed |
Forest canopy structure data for radiation and snow modelling (CH/FIN) ... |
title_sort |
forest canopy structure data for radiation and snow modelling (ch/fin) ... |
publisher |
EnviDat |
publishDate |
2020 |
url |
https://dx.doi.org/10.16904/envidat.220 https://envidat.ch/#/metadata/chm-hp-4rtm |
long_lat |
ENVELOPE(26.600,26.600,67.417,67.417) |
geographic |
Sodankylä |
geographic_facet |
Sodankylä |
genre |
Sodankylä |
genre_facet |
Sodankylä |
op_relation |
https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/5d071a02-e48e-4719-bce4-2e662d452dfe/download/hemisphericalphotos.zip https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/1b4aaf5f-545f-4afc-a045-73ccd4885747/download/chm_cropped.asc https://dx.doi.org/10.1029/2020wr029064 https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/5d071a02-e48e-4719-bce4-2e662d452dfe/download/hemisphericalphotos.zip https://www.envidat.ch/dataset/117187b4-59b9-403c-a493-d2a6e1c97631/resource/1b4aaf5f-545f-4afc-a045-73ccd4885747/download/chm_cropped.asc |
op_rights |
WSL Data Policy https://www.wsl.ch/en/about-wsl/programmes-and-initiatives/envidat.html |
op_doi |
https://doi.org/10.16904/envidat.22010.1029/2020wr029064 |
_version_ |
1768375125584904192 |