Forestry Inventory 2015
This dataset is based on the 6th National Forest Inventory published by ICNF - Instituto de Conservação da Natureza e das Florestas. The data collection for this National Forest Inventory was obtained through aerial photography and ground surveys in 2015, to supply updated statistical and basic cartographic information for the evaluation and monitoring of the abundance, state and condition of the portuguese forest resources and to enable a sustainable forest management.
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Identification
- Alternate Identifier
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0fe87daf-ed3c-4544-9d41-e187c408ee71
- Publication Date
- 2021-11-12
- Title
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Forestry Inventory 2015
- Abstract
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This dataset is based on the 6th National Forest Inventory published by ICNF - Instituto de Conservação da Natureza e das Florestas. The data collection for this National Forest Inventory was obtained through aerial photography and ground surveys in 2015, to supply updated statistical and basic cartographic information for the evaluation and monitoring of the abundance, state and condition of the portuguese forest resources and to enable a sustainable forest management.
- Dataset Language
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PORTUGUESE
- Dataset Creator
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- Dataset Creator
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- Dataset Creator
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- Metadata Provider
- Metadata Provider
- Dataset Contact
- Dataset Contact
- Dataset Contact
- Keywords (GBIF Dataset Type Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_type_2015-07-10.xml)
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occurrence
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event
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- Keywords (N/A)
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Forests
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Plants
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Portugal
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Geographic Coverage
- Geographic Description
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Mainland Portugal
Bounding Box
- West Bounding Coordinate
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-9.558
- East Bounding Coordinate
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-5.713
- North Bounding Coordinate
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42.423
- South Bounding Coordinate
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36.527
Temporal Coverage
Range of Dates
- Begin Date
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2015-01-01
- End Date
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2015-12-31
Taxonomic Coverage
- General Taxonomic Coverage
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This dataset includes 387859 records referring to plant specimens of 7 families, 9 genera (Acacia, Castanea, Ceratonia, Eucalyptus, Olea, Oryza, Pinus, Quercus, Vitis) and 8 species.
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Acacia
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Castanea
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Ceratonia
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Eucalyptus
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Olea
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Oryza
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Pinus
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Quercus
Taxonomic Classification
- Taxonomic Rank Name
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Genus
- Taxonomic Rank Value
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Vitis
License Information
- Intellectual Rights
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This work is licensed under a
Creative Commons Attribution (CC-BY) 4.0 License
.
Distribution
Additional Metadata
Metadata
GBIF Metadata Block
- Date Stamp
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2021-11-29T09:03:34Z
- Citation
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Uva J S, Onofre R, Moreira J, Faias S P, Barreiro S, Santos E, Capelo J, Corte-Real L, Martins J, Ribeiro J R, Cancela J, Rainha M, Amaral N, Santos C, Perpétua J, Pinho J, Araújo J M, Reis L, Canaveira P, Paulino J, Pina A, Binev Y, Coelho P (2021). Forestry Inventory 2015. ICNF - Instituto da Conservação da Natureza e das Florestas. Sampling event dataset https://doi.org/10.15468/33hvm4 accessed via GBIF.org on 2021-11-29.
- Bibliography
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ICNF, 2019. IFN6 – Termos e definições. [pdf], 22 pp, versão 1.0 Instituto da Conservação da Natureza e das Florestas.
- Logo URL
- http://www2.icnf.pt/portal/logo.png
Project
• Project
- Title
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6.º Inventário Florestal Nacional (IFN6)
Personnel
Individual Name
- Given Name
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Teresa
- Surname
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Pimenta
- Role
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ADMINISTRATIVE_POINT_OF_CONTACT
Personnel
Individual Name
- Given Name
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Mário
- Surname
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Reis
- Role
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ADMINISTRATIVE_POINT_OF_CONTACT
Personnel
Individual Name
- Given Name
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José Sousa
- Surname
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Uva
- Role
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ADMINISTRATIVE_POINT_OF_CONTACT
- Abstract
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The 6th National Forest Inventory was published by ICNF - Instituto de Conservação da Natureza e das Florestas and uses aerial and ground survey data collected in 2015 for the evaluation and monitoring of the portuguese forest resources.
- Funding
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The 6th National Forest Inventory was co-funded by the Portuguese Carbon Fund (FPC - Fundo Português de Carbono), by ICNF, I.P. and the European Union, through the Environment Operational Programme (application 1.1/00021– Documentos Estruturantes da Conservação da Natureza e da Biodiversidade).
The preparation of this resource for publication through GBIF was supported by Project PORBIOTA―Portuguese E-Infrastructure for Information and Research on Biodiversity (POCI-01-0145-FEDER-022127), under the Operational Thematic Program for Competitiveness and Internationalization (POCI), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) and FCT.
Study Area Description
- Descriptor
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The geographic area considered for the original study was Portugal Mainland.
Methods
• Method
Method Step
- Description
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Preparation of the dataset for GBIF publication used as source the geographic layer in shape file format obtained in:
https://sig.icnf.pt/portal/home/item.html?id=dc60bcef20b844b88c8a0638d0fe943b
Method Step
- Description
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convert of the the shape file to csv
Method Step
- Description
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create events and and occurrences omitting ones without described species.
DarwinCore "event" with "occurence" and "recourceRelationship" extensions were used
Sampling
- Study Extent
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This study is the 2015 National Forest Inventory for mainland Portugal.
- Sampling Description
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Data was collected through aerial ortho images, using grids that cover the whole continental Portugal, photo-points and points for field evaluation of vegetation parameters.
All data was inserted in a specific database build for the project.
qualityControl
- Description
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All initial data was inserted in a specific relational database built specifically for the project, which implemented several quality control methods. In the preparation of the dataset for GBIF publication, data consistency was verified using cluster algorithms using OpenRefine.