Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072023
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dc.contributor.authorOLIVEIRA, M. V. N. d'pt_BR
dc.contributor.authorOLIVEIRA, L. C. dept_BR
dc.date.accessioned2017-07-05T11:11:11Zpt_BR
dc.date.available2017-07-05T11:11:11Zpt_BR
dc.date.created2017-07-05pt_BR
dc.date.issued2017pt_BR
dc.identifier.citationIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1072023pt_BR
dc.descriptionLidar data has been largely used to produce estimative on biomass and timber stocks in tropical forests. A major problem is the lidar flights costs, and the exhaustive and expensive ground plot data acquisition necessary to calibrate lidar data metrics. The use of ground information from previously established plots and the generalization of existent models to structurally similar forests should be a way to minimize these costs. In this work we study six forest in Acre state with similar structure and different disturbance history covered by lidar flights and forest inventories. We investigate whether the use of plots with different sizes violate the null hypothesis of the variance equality of the lidar metrics and tested the use of a lidar general model to estimate the biomass on the studied sites. We generated regression models to estimate above ground biomass for each area and compared them to a general model elaborated with the ground and lidar information of all areas together. The results showed that the null hypotheses of the variance was not violated to the variable selected to compose the models and no significant differences were found among the local and general models suggesting that in the absence of forest inventories, when forest were structurally similar, a general lidar model can be used to assess biomass stocks.pt_BR
dc.language.isoporpt_BR
dc.rightsopenAccesspt_BR
dc.subjectGeotécnicapt_BR
dc.subjectTerra Indígena Kaxinawá de Nova Olinda (AC)pt_BR
dc.subjectFeijó (AC)pt_BR
dc.subjectFloresta Estadual do Antimary (AC)pt_BR
dc.subjectBujari (AC)pt_BR
dc.subjectSena Madureira (AC)pt_BR
dc.subjectProjeto de Assentamento Dirigido Humaita (AC)pt_BR
dc.subjectPorto Acre (AC)pt_BR
dc.subjectFazenda Bonalpt_BR
dc.subjectSenador Guiomard (AC)pt_BR
dc.subjectEmbrapa Acrept_BR
dc.subjectRio Branco (AC)pt_BR
dc.subjectAcrept_BR
dc.subjectAmazônia Ocidentalpt_BR
dc.subjectWestern Amazonpt_BR
dc.subjectAmazonia Occidentalpt_BR
dc.subjectAnálisis estadísticopt_BR
dc.subjectAnálisis de regresiónpt_BR
dc.subjectBiomasa aéreapt_BR
dc.subjectTeledetecciónpt_BR
dc.titleComparação de modelos lidar para a estimativa de biomassa seca acima do solo de florestas com diferentes históricos de perturbação natural ou antrópica no Estado do Acre.pt_BR
dc.typeArtigo em anais e proceedingspt_BR
dc.date.updated2017-11-08T11:11:11Zpt_BR
dc.subject.thesagroBiomassapt_BR
dc.subject.thesagroParte aéreapt_BR
dc.subject.thesagroEstimativapt_BR
dc.subject.thesagroSensoriamento remotopt_BR
dc.subject.thesagroRaio laserpt_BR
dc.subject.thesagroAnálise estatísticapt_BR
dc.subject.thesagroRegressão linearpt_BR
dc.subject.nalthesaurusAboveground biomasspt_BR
dc.subject.nalthesaurusRemote sensingpt_BR
dc.subject.nalthesaurusLidarpt_BR
dc.subject.nalthesaurusStatistical analysispt_BR
dc.subject.nalthesaurusRegression analysispt_BR
dc.subject.nalthesaurusLáserspt_BR
dc.format.extent28 p.pt_BR
riaa.ainfo.id1072023pt_BR
riaa.ainfo.lastupdate2017-11-08 -02:00:00pt_BR
dc.contributor.institutionMARCUS VINICIO NEVES D OLIVEIRA, CPAF-Acre; LUIS CLAUDIO DE OLIVEIRA, CPAF-Acre.pt_BR
Aparece nas coleções:Artigo em anais de congresso (CPAF-AC)

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