An improved estimate of leaf area index based on the histogram analysis of hemispherical photographs
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
19/10/2012
19/10/2012
2009
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Resumo |
Leaf area index (LAI) is a key parameter that affects the surface fluxes of energy, mass, and momentum over vegetated lands, but observational measurements are scarce, especially in remote areas with complex canopy structure. In this paper we present an indirect method to calculate the LAI based on the analyses of histograms of hemispherical photographs. The optimal threshold value (OTV), the gray-level required to separate the background (sky) and the foreground (leaves), was analytically calculated using the entropy crossover method (Sahoo, P.K., Slaaf, D.W., Albert, T.A., 1997. Threshold selection using a minimal histogram entropy difference. Optical Engineering 36(7) 1976-1981). The OTV was used to calculate the LAI using the well-known gap fraction method. This methodology was tested in two different ecosystems, including Amazon forest and pasturelands in Brazil. In general, the error between observed and calculated LAI was similar to 6%. The methodology presented is suitable for the calculation of LAI since it is responsive to sky conditions, automatic, easy to implement, faster than commercially available software, and requires less data storage. (C) 2008 Elsevier B.V. All rights reserved. |
Identificador |
AGRICULTURAL AND FOREST METEOROLOGY, v.149, n.6/Jul, p.920-928, 2009 0168-1923 http://producao.usp.br/handle/BDPI/26982 10.1016/j.agrformet.2008.11.012 |
Idioma(s) |
eng |
Publicador |
ELSEVIER SCIENCE BV |
Relação |
Agricultural and Forest Meteorology |
Direitos |
restrictedAccess Copyright ELSEVIER SCIENCE BV |
Palavras-Chave | #Hemispherical photography #Histogram #Optimal threshold value #Gap fraction #Litterfall #Leaf area index (LAI) #TROPICAL FOREST #PLANT CANOPIES #AMAZONIA #FLUXES #STANDS #WATER #GAPS #Agronomy #Forestry #Meteorology & Atmospheric Sciences |
Tipo |
article original article publishedVersion |