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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3U5UM6B
Repositorysid.inpe.br/mtc-m21c/2019/09.30.12.42
Metadata Repositorysid.inpe.br/mtc-m21c/2019/09.30.12.42.19
Metadata Last Update2020:01.06.11.42.22 (UTC) administrator
Secondary KeyINPE--PRE/
Citation KeyBeuchleSLVCJLA:2019:LaMoBa
TitleForest disturbances in the Brazilian Amazon - Large-scale monitoring based on cloud-computed remote sensing analysis
Year2019
Access Date2024, May 18
Secondary TypePRE CI
2. Context
Author1 Beuchle, René
2 Shimabukuro, Yosio Edemir
3 Langner, Andreas Johannes
4 Vogt, Peter
5 Carboni, Silvia
6 Janouskova, Klara
7 Lima, Thais Almeida
8 Achard, Frédéric
Resume Identifier1
2 8JMKD3MGP5W/3C9JJCQ
Group1
2 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
Affiliation1 European Commission, Joint Research Centre (JRC)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 European Commission, Joint Research Centre (JRC)
4 European Commission, Joint Research Centre (JRC)
5 GFT ITALIA Srl.
6 ARHS Developments S.A.
7 University of British Columbia
8 European Commission, Joint Research Centre (JRC)
Author e-Mail Address1
2 yosio.shimabukuro@inpe.br
Conference NameCongresso Mundial da IUFRO
Conference LocationCuritiba, PR
Date29 set. - 05 out.
History (UTC)2019-09-30 12:42:19 :: simone -> administrator ::
2020-01-06 11:42:22 :: administrator -> simone :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Abstracthe disturbances of forest cover by processes like selective logging and forest fires are very common in tropical forest. These disturbances heavily affect forest functionalities, lead to a decrease of forest biomass and contribute to greenhouse gas emissions. However, the quantification of the disturbance extend remains a challenging task because disturbed forest areas do not consist in a long-term conversion to another land use, but often undergo fast regrowth and thus are easily detectable only for a limited amount of time. We have applied a novel approach based on the ∆rNBR index, which maps the loss of forest canopy on a yearly basis by a multi-image analysis with cloud computing on Google Earth Engine. We have analysed 12 years of forest disturbances (2000-2011) over large area of interest (ca. 414,000 km2), defined by the intersection of the Mato Grosso State border and the Brazilian Amazon biome. We assessed the logging and fire intensity by applying a grid of 300 m × 300 m spatial resolution over the mapped disturbance pixels. In 2016, more than 220,000 km2 (53,3%) were covered by forest within the area of interest, thereof more than 38,000 km2 (17,3%) were disturbed by selective logging within the 12 years analysed, ranging from 1,819 km2 (2009) to 6,984 km2 (2005). The burned forest added up to 18,711 km2 (8,4%) during this period, the smallest forest area burned in 2001 (68 km2) the larges area in 2007 (10,258 km2).
AreaSRE
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4. Conditions of access and use
Languageen
User Groupsimone
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ER446E
Citing Item List
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6. Notes
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