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| Registros recuperados : 33 | |
| 21. |  | ARVOR, D.; MEIRELLES, M.; MARTORANO, L. G.; JONATHAN, M.; DUBREUIL, V.; HERLIN, I.; BERROIR, J.-P. Séries temporais de EVI/MODIS na identificação da dinâmica da soja em sistema plantio direto no Mato Grosso, Brasil. In: REUNIÃO BRASILEIRA DE MANEJO E CONSERVAÇÃO DO SOLO E DA ÁGUA, 17., 2008, Rio de Janeiro. Manejo e conservação do solo e da água no contexto das mudanças ambientais. Rio de Janeiro: Embrapa Solos, 2008. 1 CD-ROM. (Embrapa Solos. Documentos, 101).| Biblioteca(s): Embrapa Solos. |
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| 26. | | ARVOR, D.; MEIRELLES, M. S. P.; VARGAS, R.; SKORUPA, L. A.; FIDALGO, E. C. C.; DUBREUIL, V.; BERROIR, J.-P. Monitoring land use changes around the indigenous lands of the Xingu basin in Mato Grosso, Brasil. In: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, Honolulu, HI. Proceedings... Danvers, MA: IEEE, 2010. p. 3190-3193.| Biblioteca(s): Embrapa Solos. |
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| 27. | | ARVOR, D.; DAHER, F. R. G.; BRIAND, D.; DUFOUR, S.; ROLLET, A.-J.; SIMÕES, M.; FERRAZ, R. P. D. Monitoring thirty years of small water reservoirs proliferation in the southern Brazilian Amazon with Landsat time series. ISPRS Journal of Photogrammetry and Remote Sensing, v. 145, pt. B, p. 225-237, Nov. 2018.| Biblioteca(s): Embrapa Solos. |
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| 28. | | KUCHLER, P. C.; SIMÕES, M.; FERRAZ, R. P. D.; ARVOR, D.; MACHADO, P. L. O. de A.; ROSA, M.; GAETANO, R.; BÉGUÉ, A. Monitoring complex integrated crop-livestock systems at regional scale in Brazil: a big earth observation data approach. Remote Sensing, v. 14, n. 7, 1648, 2022.| Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Solos. |
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| 29. | | ARVOR, D.; MEIRELLES, M. S. P.; VARGAS, R.; SKORUPA, L. A.; FIDALGO, E. C. C.; DUBREUIL, V.; HERLIN, I.; BERROIR, J. Monitoring land use changes around the indigenous lands of the Xingu basin in Mato Grosso, Brazil. INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, Honolulu. Remote sensing: global vision for local action. Honolulu, 2010. Havaí, EUA, Nº TH3.L05.2, 4 p.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 30. | | BÉGUÉ, A.; ARVOR, D.; BELLON, B.; BETBEDER, J.; ABELLEYRA, D. de; FERRAZ, R. P. D.; LEBOURGEOIS, V.; LELONG, C.; SIMÕES, M.; VERÓN, S. R. Remote sensing and cropping practices: a review. Remote Sensing, v. 10, n. 1, Jan. 2018.| Biblioteca(s): Embrapa Solos. |
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| 31. | | SIMÕES, M.; FIDALGO, E. C. C.; PEDREIRA, B. da C. C. G.; MONTEIRO, R. R.; ARVOR, D.; SKORUPA, L. A.; CASTANHEIRA, M. V. e S. Evolução do desmatamento na região dos formadores do Rio Xingu, no Estado de Mato Grosso. Rio de Janeiro: Embrapa Solos, 2010. 30 p. il. color. (Embrapa Solos. Boletim de pesquisa e desenvolvimento, 170).| Biblioteca(s): Embrapa Solos. |
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| 32. | | BOURGOIN, C.; BETBEDER, J.; LE ROUX, R.; GOND, V.; OSZWALD, J.; ARVOR, D.; BAUDRY, J.; BOUSSARD, H.; LE CLECH, S.; FREITAS, L. J. M. de; DESSARD, H.; LÄDERACH, P.; REYMONDIN, L.; BLANC, L. Looking beyond forest cover: an analysis of landscape-scale predictors of forest degradation in the Brazilian Amazon. Environmental Research Letters, v. 16, n. 11, 114045, Nov. 2021.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 33. | | PICOLI, M. C. A.; CAMARA, G.; SANCHES, I.; SIMÕES, R.; CARVALHO, A.; MACIEL, A.; COUTINHO, A. C.; ESQUERDO, J. C. D. M.; ANTUNES, J. F. G.; BEGOTTI, R. A.; ARVOR, D.; ALMEIDA, C. Big earth observation time series analysis for monitoring Brazilian agriculture. ISPRS Journal of Photogrammetry and Remote Sensing, v. 145, part B, p. 328-339, Nov. 2018. Na publicação: Alexandre Coutinho, Julio Esquerdo, João Antunes.| Biblioteca(s): Embrapa Agricultura Digital. |
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| Registros recuperados : 33 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
10/11/2021 |
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Data da última atualização: |
10/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
BOURGOIN, C.; BETBEDER, J.; LE ROUX, R.; GOND, V.; OSZWALD, J.; ARVOR, D.; BAUDRY, J.; BOUSSARD, H.; LE CLECH, S.; FREITAS, L. J. M. de; DESSARD, H.; LÄDERACH, P.; REYMONDIN, L.; BLANC, L. |
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Afiliação: |
CLÉMENT BOURGOIN, CIRAD / CIAT; JULIE BETBEDER, CIRAD / CATIE; RENAN LE ROUX, CIRAD; VALÉRY GOND, CIRAD; JOHAN OSZWALD, Université Rennes 2; DAMIEN ARVOR, Université Rennes 2; JACQUES BAUDRY, BAGAP, INRAE, Institut Agro; HUGUES BOUSSARD, BAGAP, INRAE, Institut Agro; SOLEN LE CLECH, Wageningen University and Research; LUCAS JOSE MAZZEI DE FREITAS, CPATU; HÉLÈNE DESSARD, CIRAD; PETER LÄDERACH, CIAT; LOUIS REYMONDIN, CIAT; LILIAN BLANC, CIRAD. |
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Título: |
Looking beyond forest cover: an analysis of landscape-scale predictors of forest degradation in the Brazilian Amazon. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Environmental Research Letters, v. 16, n. 11, 114045, Nov. 2021. |
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DOI: |
https://doi.org/10.1088/1748-9326/ac31eb |
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Idioma: |
Inglês |
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Conteúdo: |
While forest degradation rates and extent exceed deforestation in the Brazilian Amazon, less attention is given to the factors controlling its spatial distribution. No quantified correlation exists between changes of forest structure due to anthropogenic disturbances and dynamics of land use and cover change occurring at broader spatial levels. This study examines the influence of multi-scale landscape structure factors (i.e. spatial composition, configuration and dynamic of land use/cover) on primary forest's aboveground biomass (AGB), spanning from low to highly degraded, in Paragominas municipality (Pará state). We used random forest models to identify the most important landscape predictors of degradation and clustering methods to analyze their distribution and interactions. We found that 58% of the variance of AGB could be explained by metrics reflecting land use practices and agricultural dynamics around primary forest patches and that their spatial patterns were not randomly distributed. Forest degradation is mainly driven by fragmentation effects resulting from old deforestation and colonization events linked with cropland expansion (e.g. soybean and maize) coupled with high accessibility to market. To a lesser extent, degradation is driven by recent and ongoing (1985?2015) deforestation and fragmentation in slash-and-burn agricultural areas, characterized by heterogeneous mosaics of pastures and fallow lands combined with high use of fire. Our findings highlight the potential of landscape-level framework and remotely sensed land cover data for a thorough understanding of the distribution of forest degradation across human-modified landscapes. Addressing these spatial determinants by looking at agricultural dynamics beyond forest cover is necessary to improve forest management which has major implications for biodiversity, carbon and other ecosystem services. MenosWhile forest degradation rates and extent exceed deforestation in the Brazilian Amazon, less attention is given to the factors controlling its spatial distribution. No quantified correlation exists between changes of forest structure due to anthropogenic disturbances and dynamics of land use and cover change occurring at broader spatial levels. This study examines the influence of multi-scale landscape structure factors (i.e. spatial composition, configuration and dynamic of land use/cover) on primary forest's aboveground biomass (AGB), spanning from low to highly degraded, in Paragominas municipality (Pará state). We used random forest models to identify the most important landscape predictors of degradation and clustering methods to analyze their distribution and interactions. We found that 58% of the variance of AGB could be explained by metrics reflecting land use practices and agricultural dynamics around primary forest patches and that their spatial patterns were not randomly distributed. Forest degradation is mainly driven by fragmentation effects resulting from old deforestation and colonization events linked with cropland expansion (e.g. soybean and maize) coupled with high accessibility to market. To a lesser extent, degradation is driven by recent and ongoing (1985?2015) deforestation and fragmentation in slash-and-burn agricultural areas, characterized by heterogeneous mosaics of pastures and fallow lands combined with high use of fire. Our findings highlight the... Mostrar Tudo |
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Thesagro: |
Degradação Ambiental; Sensoriamento Remoto; Uso da Terra. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/227627/1/Bourgoin-2021-Environ.-Res.-Lett.-16-114045.pdf
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Marc: |
LEADER 02866naa a2200325 a 4500
001 2135995
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008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1088/1748-9326/ac31eb$2DOI
100 1 $aBOURGOIN, C.
245 $aLooking beyond forest cover$ban analysis of landscape-scale predictors of forest degradation in the Brazilian Amazon.$h[electronic resource]
260 $c2021
520 $aWhile forest degradation rates and extent exceed deforestation in the Brazilian Amazon, less attention is given to the factors controlling its spatial distribution. No quantified correlation exists between changes of forest structure due to anthropogenic disturbances and dynamics of land use and cover change occurring at broader spatial levels. This study examines the influence of multi-scale landscape structure factors (i.e. spatial composition, configuration and dynamic of land use/cover) on primary forest's aboveground biomass (AGB), spanning from low to highly degraded, in Paragominas municipality (Pará state). We used random forest models to identify the most important landscape predictors of degradation and clustering methods to analyze their distribution and interactions. We found that 58% of the variance of AGB could be explained by metrics reflecting land use practices and agricultural dynamics around primary forest patches and that their spatial patterns were not randomly distributed. Forest degradation is mainly driven by fragmentation effects resulting from old deforestation and colonization events linked with cropland expansion (e.g. soybean and maize) coupled with high accessibility to market. To a lesser extent, degradation is driven by recent and ongoing (1985?2015) deforestation and fragmentation in slash-and-burn agricultural areas, characterized by heterogeneous mosaics of pastures and fallow lands combined with high use of fire. Our findings highlight the potential of landscape-level framework and remotely sensed land cover data for a thorough understanding of the distribution of forest degradation across human-modified landscapes. Addressing these spatial determinants by looking at agricultural dynamics beyond forest cover is necessary to improve forest management which has major implications for biodiversity, carbon and other ecosystem services.
650 $aDegradação Ambiental
650 $aSensoriamento Remoto
650 $aUso da Terra
700 1 $aBETBEDER, J.
700 1 $aLE ROUX, R.
700 1 $aGOND, V.
700 1 $aOSZWALD, J.
700 1 $aARVOR, D.
700 1 $aBAUDRY, J.
700 1 $aBOUSSARD, H.
700 1 $aLE CLECH, S.
700 1 $aFREITAS, L. J. M. de
700 1 $aDESSARD, H.
700 1 $aLÄDERACH, P.
700 1 $aREYMONDIN, L.
700 1 $aBLANC, L.
773 $tEnvironmental Research Letters$gv. 16, n. 11, 114045, Nov. 2021.
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Embrapa Amazônia Oriental (CPATU) |
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