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Registro Completo |
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Biblioteca(s): |
Embrapa Meio-Norte. |
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Data corrente: |
10/08/2015 |
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Data da última atualização: |
25/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
GOLLANY, H. T.; TITUS, B. D.; SCOTT, D. A.; ASBJORNSEN, H.; RESH, S. C.; CHIMNER, R. A.; KACZMAREK, D. J.; LEITE, L. F. C.; FERREIRA, A. C. C.; ROD, K. A.; HILBERT, J.; GALDOS, M. V.; CISZ, M. E. |
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Afiliação: |
HERO T. GOLLANY, USDA - Agricultural Research Service; BRIAN D. TITUS, Natural Resources Canada, Canadian Forest Service.; D. ANDREW SCOTT, USDA Forest Service, Southern Research Station; HEIDI ASBJORNSEN, Department of Natural Resources and the Environment and the Earth Systems Research Center, Institute for Earth, Oceans and Space, University of New Hampshire, Durham, NH 03824, USA; SIGRID C. RESH, School of Forest Resources and Environmental Science, Michigan Technological University.; RODNEY A. CHIMNER, School of Forest Resources and Environmental Science, Michigan Technological University.; DONALD J. KACZMAREK, Oregon Department of Forestry, USA.; LUIZ FERNANDO CARVALHO LEITE, CPAMN; ANA C. C. FERREIRA, Climate Change Adaptation Consultant, Brazil.; KENTON A. ROD, School of the Environment, Washington State University, USA.; JORGE HILBERT, Centro de Investigacio´nes de Agroindustria (CIA), Instituto Nacional de Tecnologia agropecuaria (INTA); MARCELO V. GALDOS, Brazilian Bioethanol Science and Technology Laboratory (CTBE), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, SP.; MICHELLE E. CISZ, School of Forest Resources and Environmental Science, Michigan Technological University, USA. |
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Título: |
Biogeochemical research priorities for sustainable biofuel and bioenergy feedstock production in the Americas. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
Environmental Management, 2015. DOI 10.1007/s00267-015-0536-7. |
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Páginas: |
26 p. |
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DOI: |
10.1007/s00267-015-0536-7 |
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Idioma: |
Inglês |
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Palavras-Chave: |
Agroecossistema; Sustentabilidade. |
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Thesagro: |
Bioenergia; Silvicultura. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/127592/1/ArtigoLuizFernandoEnvironmentalManagement2015.pdf
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Marc: |
LEADER 00954naa a2200325 a 4500
001 2021598
005 2022-05-25
008 2015 bl uuuu u00u1 u #d
024 7 $a10.1007/s00267-015-0536-7$2DOI
100 1 $aGOLLANY, H. T.
245 $aBiogeochemical research priorities for sustainable biofuel and bioenergy feedstock production in the Americas.$h[electronic resource]
260 $c2015
300 $a26 p.
650 $aBioenergia
650 $aSilvicultura
653 $aAgroecossistema
653 $aSustentabilidade
700 1 $aTITUS, B. D.
700 1 $aSCOTT, D. A.
700 1 $aASBJORNSEN, H.
700 1 $aRESH, S. C.
700 1 $aCHIMNER, R. A.
700 1 $aKACZMAREK, D. J.
700 1 $aLEITE, L. F. C.
700 1 $aFERREIRA, A. C. C.
700 1 $aROD, K. A.
700 1 $aHILBERT, J.
700 1 $aGALDOS, M. V.
700 1 $aCISZ, M. E.
773 $tEnvironmental Management, 2015. DOI 10.1007/s00267-015-0536-7.
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Registro original: |
Embrapa Meio-Norte (CPAMN) |
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
27/11/2019 |
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Data da última atualização: |
27/11/2019 |
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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: |
BISPO, P. da C.; PARDINI, M.; PAPATHANASSIOU, K. P.; KUGLER, F.; BALZTER, H.; RAINS, D.; SANTOS, J. R. dos; RIZAEV, I. G.; TANSEY, K.; SILVA, M. F. da; ARAUJO, L. S. de. |
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Afiliação: |
POLYANNA DA CONCEICAO BISPO, University of Leicester; MATTEO PARDINI, German Aerospace Center; KONSTANTINUS P PAPATHANASSIOU, German Aerospace Center; FLORIAN KUGLER, German Aerospace Center; HEIKO BALTZER, Ghent University; DOMINIK RAINS, University of Leicester; JOAO ROBERTO DOS SANTOS, INPE; IGOR G RIZAEV, University of Bristol; KEVIN TANSEY, University of Leicester; MAIZA FERREIRA DA SILVA, SGE; LUCIANA SPINELLI DE ARAUJO, CNPMA. |
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Título: |
Mapping forest successional stages in the Brazilian Amazon using forest heights derived from TanDEM-X SAR interferometry. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Remote Sensing of Environment, v. 232, 2019. Article 111194. |
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DOI: |
https://doi.org/10.1016/j.rse.2019.05.013 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Knowledge of the spatial patterns of successional stages (i.e., primary and secondary forest) in tropical forests allows to monitor forest preservation, mortality and regeneration in relation to natural and anthropogenic disturbances. Different successional stages have also different capabilities of re-establishing carbon stocks. Therefore, a successful discrimination of successional stages over wide areas can lead to an improved quantification of above ground biomass and carbon stocks. The reduction of the mapping uncertainties is especially a challenge due to high heterogeneity of the tropical vegetation. In this framework, the development of innovative remote sensing approaches is required. Forests (top) height (and its spatial distribution) are an important structural parameter that can be used to differentiate between different successional stages, and can be provided by Interferometric Synthetic Aperture Radar (InSAR) acquisitions. In this context, this paper investigates the potential of forest heights estimated from TanDEM-X InSAR data and a LiDAR digital terrain model (DTM) for separating successional stages (primary or old growth and secondary forest at different stages of succession) by means of a maximum likelihood classification. The study was carried out in the region of the Tapajós National Forest (Pará, Brazil) in the Amazon biome. The forest heights for three years (2012, 2013 and 2016) were estimated from a single-polarization in bistatic mode using InSAR model-based inversion techniques aided by the LiDAR digital terrain model. The validation of the TanDEM-X forest heights with independent LiDAR H100 datasets was carried out in the location of seven field inventory plots (measuring 50?×?50?m, equivalent to 0.25?ha), also allowing for the validation of the LiDAR datasets against the field data. The validation of the estimated heights showed a high correlation (r?=?0.93) and a low uncertainty (RMSE?=?3?m). The information about the successional stages and forest heights from field datasets was used to select training samples in the LiDAR and TanDEM-X forest heights to classify successional stages with a maximum likelihood classifier. The identification of different stages of forest succession based on TanDEM-X forest heights was possible with an overall accuracy of about 80%. MenosAbstract: Knowledge of the spatial patterns of successional stages (i.e., primary and secondary forest) in tropical forests allows to monitor forest preservation, mortality and regeneration in relation to natural and anthropogenic disturbances. Different successional stages have also different capabilities of re-establishing carbon stocks. Therefore, a successful discrimination of successional stages over wide areas can lead to an improved quantification of above ground biomass and carbon stocks. The reduction of the mapping uncertainties is especially a challenge due to high heterogeneity of the tropical vegetation. In this framework, the development of innovative remote sensing approaches is required. Forests (top) height (and its spatial distribution) are an important structural parameter that can be used to differentiate between different successional stages, and can be provided by Interferometric Synthetic Aperture Radar (InSAR) acquisitions. In this context, this paper investigates the potential of forest heights estimated from TanDEM-X InSAR data and a LiDAR digital terrain model (DTM) for separating successional stages (primary or old growth and secondary forest at different stages of succession) by means of a maximum likelihood classification. The study was carried out in the region of the Tapajós National Forest (Pará, Brazil) in the Amazon biome. The forest heights for three years (2012, 2013 and 2016) were estimated from a single-polarization in bistatic mode usi... Mostrar Tudo |
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Palavras-Chave: |
Forest height; TanDEM-X. |
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Thesagro: |
Floresta Tropical; Mapa; Sensoriamento Remoto. |
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Thesaurus NAL: |
Forest succession; Height; Interferometry; synthetic aperture radar; Tropical forests. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/205662/1/ARAUJO-SPINELLI-Mapping-Forest-2019.pdf
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Marc: |
LEADER 03451naa a2200373 a 4500
001 2115303
005 2019-11-27
008 2019 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.rse.2019.05.013$2DOI
100 1 $aBISPO, P. da C.
245 $aMapping forest successional stages in the Brazilian Amazon using forest heights derived from TanDEM-X SAR interferometry.$h[electronic resource]
260 $c2019
520 $aAbstract: Knowledge of the spatial patterns of successional stages (i.e., primary and secondary forest) in tropical forests allows to monitor forest preservation, mortality and regeneration in relation to natural and anthropogenic disturbances. Different successional stages have also different capabilities of re-establishing carbon stocks. Therefore, a successful discrimination of successional stages over wide areas can lead to an improved quantification of above ground biomass and carbon stocks. The reduction of the mapping uncertainties is especially a challenge due to high heterogeneity of the tropical vegetation. In this framework, the development of innovative remote sensing approaches is required. Forests (top) height (and its spatial distribution) are an important structural parameter that can be used to differentiate between different successional stages, and can be provided by Interferometric Synthetic Aperture Radar (InSAR) acquisitions. In this context, this paper investigates the potential of forest heights estimated from TanDEM-X InSAR data and a LiDAR digital terrain model (DTM) for separating successional stages (primary or old growth and secondary forest at different stages of succession) by means of a maximum likelihood classification. The study was carried out in the region of the Tapajós National Forest (Pará, Brazil) in the Amazon biome. The forest heights for three years (2012, 2013 and 2016) were estimated from a single-polarization in bistatic mode using InSAR model-based inversion techniques aided by the LiDAR digital terrain model. The validation of the TanDEM-X forest heights with independent LiDAR H100 datasets was carried out in the location of seven field inventory plots (measuring 50?×?50?m, equivalent to 0.25?ha), also allowing for the validation of the LiDAR datasets against the field data. The validation of the estimated heights showed a high correlation (r?=?0.93) and a low uncertainty (RMSE?=?3?m). The information about the successional stages and forest heights from field datasets was used to select training samples in the LiDAR and TanDEM-X forest heights to classify successional stages with a maximum likelihood classifier. The identification of different stages of forest succession based on TanDEM-X forest heights was possible with an overall accuracy of about 80%.
650 $aForest succession
650 $aHeight
650 $aInterferometry
650 $asynthetic aperture radar
650 $aTropical forests
650 $aFloresta Tropical
650 $aMapa
650 $aSensoriamento Remoto
653 $aForest height
653 $aTanDEM-X
700 1 $aPARDINI, M.
700 1 $aPAPATHANASSIOU, K. P.
700 1 $aKUGLER, F.
700 1 $aBALZTER, H.
700 1 $aRAINS, D.
700 1 $aSANTOS, J. R. dos
700 1 $aRIZAEV, I. G.
700 1 $aTANSEY, K.
700 1 $aSILVA, M. F. da
700 1 $aARAUJO, L. S. de
773 $tRemote Sensing of Environment$gv. 232, 2019. Article 111194.
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Embrapa Meio Ambiente (CNPMA) |
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