03037nam a2200529 a 450000100080000000500110000800800410001910000260006024502040008626001010029030000090039152013560040065000240175665000120178065000100179265000240180265000190182665000250184565000260187065000130189665000150190965000170192465000150194165000220195665000250197865300090200365300240201265300240203665300280206065300270208865300190211565300160213465300170215065300180216765300160218565300390220165300160224065300200225665300500227665300200232665300240234665300260237065300190239665300500241565300190246570000230248420720232023-11-16       2017    bl uuuu     u00u1 u    #d1 aOLIVEIRA, M. V. N. d'  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]  aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpec2017  a8 p.  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.  aAboveground biomass  aLásers  aLidar  aRegression analysis  aRemote sensing  aStatistical analysis  aAnálise estatística  aBiomassa  aEstimativa  aParte aérea  aRaio laser  aRegressão linear  aSensoriamento remoto  aAcre  aAmazonia Occidental  aAmazônia Ocidental  aAnálisis de regresión  aAnálisis estadístico  aBiomasa aérea  aBujari (AC)  aEmbrapa Acre  aFazenda Bonal  aFeijó (AC)  aFloresta Estadual do Antimary (AC)  aGeotécnica  aPorto Acre (AC)  aProjeto de Assentamento Dirigido Humaita (AC)  aRio Branco (AC)  aSena Madureira (AC)  aSenador Guiomard (AC)  aTeledetección  aTerra Indígena Kaxinawá de Nova Olinda (AC)  aWestern Amazon1 aOLIVEIRA, L. C. de