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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
05/07/2017 |
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Data da última atualização: |
16/11/2023 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
OLIVEIRA, M. V. N. d'; OLIVEIRA, L. C. de. |
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Afiliação: |
MARCUS VINICIO NEVES D OLIVEIRA, CPAF-Acre; LUIS CLAUDIO DE OLIVEIRA, CPAF-Acre. |
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Título: |
Comparação 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. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017. |
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Páginas: |
8 p. |
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Idioma: |
Português |
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Conteúdo: |
Lidar 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. |
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Palavras-Chave: |
Acre; Amazonia Occidental; Amazônia Ocidental; Análisis de regresión; Análisis estadístico; Biomasa aérea; Bujari (AC); Embrapa Acre; Fazenda Bonal; Feijó (AC); Floresta Estadual do Antimary (AC); Geotécnica; Porto Acre (AC); Projeto de Assentamento Dirigido Humaita (AC); Rio Branco (AC); Sena Madureira (AC); Senador Guiomard (AC); Teledetección; Terra Indígena Kaxinawá de Nova Olinda (AC); Western Amazon. |
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Thesagro: |
Análise estatística; Biomassa; Estimativa; Parte aérea; Raio laser; Regressão linear; Sensoriamento remoto. |
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Thesaurus Nal: |
Aboveground biomass; Lásers; Lidar; Regression analysis; Remote sensing; Statistical analysis. |
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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/161401/1/26343.pdf
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Marc: |
LEADER 03037nam a2200529 a 4500
001 2072023
005 2023-11-16
008 2017 bl uuuu u00u1 u #d
100 1 $aOLIVEIRA, M. V. N. d'
245 $aComparação de modelos lidar para a estimativa de biomassa seca acima do solo de florestas com diferentes históricos de perturbação natural ou antrópica no Estado do Acre.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe$c2017
300 $a8 p.
520 $aLidar 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.
650 $aAboveground biomass
650 $aLásers
650 $aLidar
650 $aRegression analysis
650 $aRemote sensing
650 $aStatistical analysis
650 $aAnálise estatística
650 $aBiomassa
650 $aEstimativa
650 $aParte aérea
650 $aRaio laser
650 $aRegressão linear
650 $aSensoriamento remoto
653 $aAcre
653 $aAmazonia Occidental
653 $aAmazônia Ocidental
653 $aAnálisis de regresión
653 $aAnálisis estadístico
653 $aBiomasa aérea
653 $aBujari (AC)
653 $aEmbrapa Acre
653 $aFazenda Bonal
653 $aFeijó (AC)
653 $aFloresta Estadual do Antimary (AC)
653 $aGeotécnica
653 $aPorto Acre (AC)
653 $aProjeto de Assentamento Dirigido Humaita (AC)
653 $aRio Branco (AC)
653 $aSena Madureira (AC)
653 $aSenador Guiomard (AC)
653 $aTeledetección
653 $aTerra Indígena Kaxinawá de Nova Olinda (AC)
653 $aWestern Amazon
700 1 $aOLIVEIRA, L. C. de
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Registro original: |
Embrapa Acre (CPAF-AC) |
