Enhanced LC-product for Fennoscandia

New forest classification scheme was developed to better represent the key forest structural variables, which have direct influence on vegetation-climate interactions, in different land models. Forest management affects the distribution of tree species and the age class of a forest, shaping its over...

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Bibliographic Details
Main Author: Majasalmi, Titta
Format: Dataset
Language:English
Published: Norsk institutt for bioøkonomi (NIBIO) 2017
Subjects:
NFI
PFT
Online Access:https://dx.doi.org/10.21350/7zzey5w3
https://bird.unit.no/resources/3be2d461-b01b-418e-90cd-03f3cbc8ee37
id ftdatacite:10.21350/7zzey5w3
record_format openpolar
spelling ftdatacite:10.21350/7zzey5w3 2023-05-15T16:11:42+02:00 Enhanced LC-product for Fennoscandia Majasalmi, Titta 2017 https://dx.doi.org/10.21350/7zzey5w3 https://bird.unit.no/resources/3be2d461-b01b-418e-90cd-03f3cbc8ee37 en eng Norsk institutt for bioøkonomi (NIBIO) Creative Commons - Attribution 4.0 International https://creativecommons.org/licenses/by/4.0 CC-BY land use land use change forest management LULCC NFI PFT SVAT CCI LC-product MS-NFI dataset Dataset 2017 ftdatacite https://doi.org/10.21350/7zzey5w3 2021-11-05T12:55:41Z New forest classification scheme was developed to better represent the key forest structural variables, which have direct influence on vegetation-climate interactions, in different land models. Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning, and in turn, surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related Look-Up Table (LUT) of key forest structural attributes (i.e. maximum growing season leaf area index (LAImax), basal area weighted mean tree height, tree crown length and total stem volume) was developed, and the classification was applied for Multi-Source NFI (MS-NFI) maps from Norway, Sweden and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Intiative’s Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Dataset Fennoscandia DataCite Metadata Store (German National Library of Science and Technology) Norway
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic land use
land use change
forest management
LULCC
NFI
PFT
SVAT
CCI LC-product
MS-NFI
spellingShingle land use
land use change
forest management
LULCC
NFI
PFT
SVAT
CCI LC-product
MS-NFI
Majasalmi, Titta
Enhanced LC-product for Fennoscandia
topic_facet land use
land use change
forest management
LULCC
NFI
PFT
SVAT
CCI LC-product
MS-NFI
description New forest classification scheme was developed to better represent the key forest structural variables, which have direct influence on vegetation-climate interactions, in different land models. Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning, and in turn, surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related Look-Up Table (LUT) of key forest structural attributes (i.e. maximum growing season leaf area index (LAImax), basal area weighted mean tree height, tree crown length and total stem volume) was developed, and the classification was applied for Multi-Source NFI (MS-NFI) maps from Norway, Sweden and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Intiative’s Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7).
format Dataset
author Majasalmi, Titta
author_facet Majasalmi, Titta
author_sort Majasalmi, Titta
title Enhanced LC-product for Fennoscandia
title_short Enhanced LC-product for Fennoscandia
title_full Enhanced LC-product for Fennoscandia
title_fullStr Enhanced LC-product for Fennoscandia
title_full_unstemmed Enhanced LC-product for Fennoscandia
title_sort enhanced lc-product for fennoscandia
publisher Norsk institutt for bioøkonomi (NIBIO)
publishDate 2017
url https://dx.doi.org/10.21350/7zzey5w3
https://bird.unit.no/resources/3be2d461-b01b-418e-90cd-03f3cbc8ee37
geographic Norway
geographic_facet Norway
genre Fennoscandia
genre_facet Fennoscandia
op_rights Creative Commons - Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.21350/7zzey5w3
_version_ 1765996856241815552