03384naa a2200589 a 450000100080000000500110000800800410001902400400006010000220010024501360012226000090025852016830026765000130195065000160196365000220197965000120200165000100201365000160202365000240203965000250206365000150208865000210210365000300212465000260215465000140218065000220219465000150221665000220223165300090225365300240226265300240228665300280231065300270233865300230236565300160238865300130240465300090241765300250242665300330245165300390248465300240252365300200254765300170256765300270258465300240261165300190263570000260265470000210268070000160270170000190271777300580273621091062019-05-17       2017    bl uuuu     u00u1 u    #d7 a10.1590/1806-908820170003000132DOI1 aFIGUEIREDO, E. O.  aEquations to estimate tree gaps in a precision forest management area the Amazon based on crown morphometry.h[electronic resource]  c2017  aThe precision forest management technique still has much to be improved with the incorporation of forest biometric techniques and forest profiling with airborne LIDAR. When planning the cutting of a tree in forest management, the volume to be produced for industry is estimated but not the area impacted by removal of the tree. The objective of the present study was to develop equations for the Amazon rainforest that are able to estimate the impact area of gaps from harvesting individual dominant and co-dominant trees based on the canopy morphology obtained through forest profiling. On two separate occasions profiles were made in an annual forest-production unit in the Antimary State Forest (FEA) in the state of Acre, Brazil. The first was done a few days before the start of logging in 2010 and the second was done after completion of harvest activities in 2011. With field measurements and processing of the cloud of LIDAR points, dendrometric and morphometric variables were obtained for the canopy in order to develop equations for estimating gap areas. After evaluation of the explanatory variables with the highest correlation with gap area, the method used considered all possible models and included 2-4 parameters. The explanatory variables that best represent the impact of clearings are volume of the crown (VCop) and crown-projection area (APC). Ten equations were selected, of which two were chosen for use; these had R2 aj &gt 75% and Syx &lt23%. The good fit of the equations demonstrates the potential use of LIDAR to obtain information for estimating in advance the gaps in the forest cover that will be created from harvesting trees of different sizes.  aBiometry  aCanopy gaps  aForest management  aLásers  aLidar  aMorphometry  aRegression analysis  aStatistical analysis  aTree crown  aTropical forests  aAdministração florestal  aAnálise estatística  aBiometria  aFloresta tropical  aRaio laser  aRegressão linear  aAcre  aAmazonia Occidental  aAmazônia Ocidental  aAnálisis de regresión  aAnálisis estadístico  aBosques tropicales  aBujari (AC)  aClareira  aCopa  aCopa de los árboles  aEspacios vacíos en el dosel  aFloresta Estadual do Antimary (AC)  aManejo de precisão  aManejo forestal  aMorfometría  aPerfilamento florestal  aSena Madureira (AC)  aWestern Amazon1 aOLIVEIRA, M. V. N. d'1 aFEARNSIDE, P. M.1 aBRAZ, E. M.1 aPAPA, D. de A.  tRevista Árvore, Viçosagv. 41, n. 3, e410313, 2017.