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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/449CP82
Repositorysid.inpe.br/mtc-m21c/2021/03.02.17.33
Last Update2021:03.02.17.33.06 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2021/03.02.17.33.06
Metadata Last Update2022:04.03.22.39.35 (UTC) administrator
DOI10.3390/rs13030367
ISSN2072-4292
Citation KeySanoRKWASBF:2021:CaStBr
TitleComparative analysis of the global forest/non‐forest maps derived from sar and optical sensors. Case studies from brazilian amazon and cerrado biomes
Year2021
MonthFeb.
Access Date2024, May 13
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size12793 KiB
2. Context
Author1 Sano, Edson E.
2 Rizzoli, Paola
3 Koyama, Christian N.
4 Watanabe, Manabu
5 Adami, Marcos
6 Shimabukuro, Yosio Edemir
7 Bayma, Gustavo
8 Freitas, Daniel M.
Resume Identifier1
2
3
4
5
6 8JMKD3MGP5W/3C9JJCQ
ORCID1
2
3
4
5 0000-0003-4247-4477
6
7 0000-0001-5312-6609
Group1
2
3
4
5 COEAM-CGGO-INPE-MCTI-GOV-BR
6 DIOTG-CGCT-INPE-MCTI-GOV-BR
Affiliation1 Instituto Brasileiro de Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA)
2 German Aerospace Center
3 Tokyo Denki University
4 Tokyo Denki University
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Instituto Nacional de Pesquisas Espaciais (INPE)
7 Empresa Brasileira de Pesquisa Agropecuária - EMBRAPA
8 Instituto Brasileiro de Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA)
Author e-Mail Address1 edson.sano@ibama.gov.br
2 paola.rizzoli@dlr.de
3 16hz010@ms.dendai.ac.jp
4 16hz001@ms.dendai.ac.jp
5 marcos.adami@inpe.br
6 yosio.shimabukuro@inpe.br
7 gustavo.bayma@embrapa.br
8 daniel-moraes.freitas@ibama.gov.br
JournalRemote Sensing
Volume13
Number3
Pages1-25
Secondary MarkB3_GEOGRAFIA B3_ENGENHARIAS_I B4_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS B5_CIÊNCIAS_AGRÁRIAS_I
History (UTC)2021-03-02 17:33:06 :: simone -> administrator ::
2021-03-02 17:33:19 :: administrator -> simone :: 2021
2021-03-02 17:36:17 :: simone -> administrator :: 2021
2021-07-02 02:27:10 :: administrator -> simone :: 2021
2021-12-16 18:56:58 :: simone -> administrator :: 2021
2022-04-03 22:39:35 :: administrator -> simone :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractGlobal‐scale forest/non‐forest (FNF) maps are of crucial importance for applications like biomass estimation and deforestation monitoring. Global FNF maps based on optical remote sensing data have been produced by the wall‐to‐wall satellite image analyses or sampling strategies. The German Aerospace Center (DLR) and the Japan Aerospace Exploration Agency (JAXA) also made available their global FNF maps based on synthetic aperture radar (SAR) data. This paper attempted to answer the following scientific question: how comparable are the FNF products derived from optical and SAR data? As test sites we selected the Amazon (tropical rainforest) and Cerrado (tropical savanna) biomes, the two largest Brazilian biomes. Forest estimations from 2015 derived from TanDEM‐X (X band; HH polarization) and ALOS‐2 (L band; HV polarization) SAR data, as well as forest cover information derived from Landsat 8 optical data were compared with each other at the municipality and image sampling levels. The optical‐based forest estimations considered in this study were derived from the MapBiomas project, a Brazilian multi‐institutional project to map land use and land cover (LULC) classes of an entire country based on historical time series of Landsat data. In addition to the existing forest maps, a set of 1619 Landsat 8 RGB color composites was used to generate new independent comparison data composed of circular areas with 5‐km diameter, which were visually interpreted after image segmentation. The Spearman rank correlation estimated the correlation among the data sets and the paired MannWhitneyWilcoxon tested the hypothesis that the data sets are statistically equal. Results showed that forest maps derived from SAR and optical satellites are statistically different regardless of biome or scale of study (municipality or image sampling), except for the Cerrado´s forest estimations derived from TanDEM‐X and ALOS‐2. Nevertheless, the percentage of pixels classified as forest or non‐forest by both SAR sensors were 90% and 80% for the Amazon and Cerrado biome, respectively, indicating an overall good agreement.
AreaSRE
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data URLhttp://urlib.net/ibi/8JMKD3MGP3W34R/449CP82
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W34R/449CP82
Languageen
Target Filesano_comparative.pdf
User Groupsimone
Reader Groupadministrator
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Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/46KUATE
8JMKD3MGPCW/46KUBT5
Citing Item Listsid.inpe.br/bibdigital/2022/04.03.22.35 6
DisseminationWEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS.
Host Collectionurlib.net/www/2017/11.22.19.04
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