A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset

A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset

The analysis is based on a dataset of post-fire restoration interventions conducted on deciduous oak forests in Portugal between 2017 and 2018. The dataset includes data on 1314 restored sites and on 1699 control sites. We used a Generalized Additive Mixed Model (GAMM) to analyse how vegetation indi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Lopes, Luis Filipe, Dias, Filipe S., M. Fernandes, Paulo, Acácio, Vanda
Format: Dataset
Sprache:eng
Schlagworte:
Fire ecology
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Lopes, Luis Filipe
Dias, Filipe S.
M. Fernandes, Paulo
Acácio, Vanda
description The analysis is based on a dataset of post-fire restoration interventions conducted on deciduous oak forests in Portugal between 2017 and 2018. The dataset includes data on 1314 restored sites and on 1699 control sites. We used a Generalized Additive Mixed Model (GAMM) to analyse how vegetation indices such as NDVI and MSAVI changed over time as a function of post-fire restoration and topography and climate variables.
doi_str_mv 10.6084/m9.figshare.22012688
format Dataset
fullrecord <record><control><sourceid>datacite_PQ8</sourceid><recordid>TN_cdi_datacite_primary_10_6084_m9_figshare_22012688</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_6084_m9_figshare_22012688</sourcerecordid><originalsourceid>FETCH-LOGICAL-d918-d09d90b1e803c572d63d2430a6f87999abab791df2a307159071cd71d8d30e03</originalsourceid><addsrcrecordid>eNo1j8tOwzAURL1hgQp_wMI_kOBHmtjLqjylSiyKxNK6ia-LBY4rXwupf08q6GZmMaMZHcbupGh7Ybr7ZNsQD_QJBVulhFS9MdfsY8MLplyxIZwpzgcOREiUcK48B57hi4dckOrSm_IPlhOHULHwY6YaYkF-DnOBGvPMG_4AFQjrDbsK8E14--8rtn96fN--NLu359ftZtd4K03jhfVWjBKN0NN6UL7XXnVaQB_MYK2FEcbBSh8UaDHItV1k8oP0xmuBQq9Y97fql9cpVnTHEhOUk5PCnaldsu5C7S7U-he7r1SF</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>dataset</recordtype></control><display><type>dataset</type><title>A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset</title><source>DataCite</source><creator>Lopes, Luis Filipe ; Dias, Filipe S. ; M. Fernandes, Paulo ; Acácio, Vanda</creator><creatorcontrib>Lopes, Luis Filipe ; Dias, Filipe S. ; M. Fernandes, Paulo ; Acácio, Vanda</creatorcontrib><description>The analysis is based on a dataset of post-fire restoration interventions conducted on deciduous oak forests in Portugal between 2017 and 2018. The dataset includes data on 1314 restored sites and on 1699 control sites. We used a Generalized Additive Mixed Model (GAMM) to analyse how vegetation indices such as NDVI and MSAVI changed over time as a function of post-fire restoration and topography and climate variables.</description><identifier>DOI: 10.6084/m9.figshare.22012688</identifier><language>eng</language><publisher>figshare</publisher><subject>Fire ecology</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-5132-9258</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,1894</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.6084/m9.figshare.22012688$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Lopes, Luis Filipe</creatorcontrib><creatorcontrib>Dias, Filipe S.</creatorcontrib><creatorcontrib>M. Fernandes, Paulo</creatorcontrib><creatorcontrib>Acácio, Vanda</creatorcontrib><title>A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset</title><description>The analysis is based on a dataset of post-fire restoration interventions conducted on deciduous oak forests in Portugal between 2017 and 2018. The dataset includes data on 1314 restored sites and on 1699 control sites. We used a Generalized Additive Mixed Model (GAMM) to analyse how vegetation indices such as NDVI and MSAVI changed over time as a function of post-fire restoration and topography and climate variables.</description><subject>Fire ecology</subject><fulltext>true</fulltext><rsrctype>dataset</rsrctype><creationdate>2023</creationdate><recordtype>dataset</recordtype><sourceid>PQ8</sourceid><recordid>eNo1j8tOwzAURL1hgQp_wMI_kOBHmtjLqjylSiyKxNK6ia-LBY4rXwupf08q6GZmMaMZHcbupGh7Ybr7ZNsQD_QJBVulhFS9MdfsY8MLplyxIZwpzgcOREiUcK48B57hi4dckOrSm_IPlhOHULHwY6YaYkF-DnOBGvPMG_4AFQjrDbsK8E14--8rtn96fN--NLu359ftZtd4K03jhfVWjBKN0NN6UL7XXnVaQB_MYK2FEcbBSh8UaDHItV1k8oP0xmuBQq9Y97fql9cpVnTHEhOUk5PCnaldsu5C7S7U-he7r1SF</recordid><startdate>20230205</startdate><enddate>20230205</enddate><creator>Lopes, Luis Filipe</creator><creator>Dias, Filipe S.</creator><creator>M. Fernandes, Paulo</creator><creator>Acácio, Vanda</creator><general>figshare</general><scope>DYCCY</scope><scope>PQ8</scope><orcidid>https://orcid.org/0000-0002-5132-9258</orcidid></search><sort><creationdate>20230205</creationdate><title>A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset</title><author>Lopes, Luis Filipe ; Dias, Filipe S. ; M. Fernandes, Paulo ; Acácio, Vanda</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-d918-d09d90b1e803c572d63d2430a6f87999abab791df2a307159071cd71d8d30e03</frbrgroupid><rsrctype>datasets</rsrctype><prefilter>datasets</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Fire ecology</topic><toplevel>online_resources</toplevel><creatorcontrib>Lopes, Luis Filipe</creatorcontrib><creatorcontrib>Dias, Filipe S.</creatorcontrib><creatorcontrib>M. Fernandes, Paulo</creatorcontrib><creatorcontrib>Acácio, Vanda</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lopes, Luis Filipe</au><au>Dias, Filipe S.</au><au>M. Fernandes, Paulo</au><au>Acácio, Vanda</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset</title><date>2023-02-05</date><risdate>2023</risdate><abstract>The analysis is based on a dataset of post-fire restoration interventions conducted on deciduous oak forests in Portugal between 2017 and 2018. The dataset includes data on 1314 restored sites and on 1699 control sites. We used a Generalized Additive Mixed Model (GAMM) to analyse how vegetation indices such as NDVI and MSAVI changed over time as a function of post-fire restoration and topography and climate variables.</abstract><pub>figshare</pub><doi>10.6084/m9.figshare.22012688</doi><orcidid>https://orcid.org/0000-0002-5132-9258</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier DOI: 10.6084/m9.figshare.22012688
ispartof
issn
language eng
recordid cdi_datacite_primary_10_6084_m9_figshare_22012688
source DataCite
subjects Fire ecology
title A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T11%3A57%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-datacite_PQ8&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=unknown&rft.au=Lopes,%20Luis%20Filipe&rft.date=2023-02-05&rft_id=info:doi/10.6084/m9.figshare.22012688&rft_dat=%3Cdatacite_PQ8%3E10_6084_m9_figshare_22012688%3C/datacite_PQ8%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true