Abstract
Aims There is increasing need for regional estimates of leaf area index (LAI) because it is an essential input for many eco-hydrological processes models; however,there has been a lack of effec-tive methods for its estimation. Picea crassifolia is the dominant species in the forest ecosystem of Qi-lian Mountains and is critical to the eco-hydrological processes of the ecosystem. Our objective is to compare methods for determining canopy LAI of this P. crassifolia forest. Methods We investigated canopy LAI with an LAI-2000 canopy analyzer,hemispherical photography and allometric regression on tree height and diameter at breast height (DBH). The value was underestimated by the two instruments because of clumping in the conifer forest. In order to adjust the LAI measured and obtain the spatial distribution of LAI,we first measured the clumping index by Tracing Radiation and Architecture of Canopies (TRAC). Then we calculated the adjusting coefficient by the clumping index,which was used to adjust the LAI value measured by hemispherical photography. Then,we determined the relationship between adjusted LAI and vegetation indexes retrieved by high resolution remote sensing data (QuickBird) and estimated the spatial distribution of canopy LAI. Important findings The values of canopy LAI were 1.03–3.70 by LAI-2000 canopy analyzer,0.48–2.26 by hemispherical photography,and 2.27–8.20 by allometric regression. LAI value by allometric regression on tree height and DBH was used for assessing the measurement accuracy by the other two indirect measurement techniques. We found the two instruments (LAI-2000 canopy analyzer and hemispherical photography) under estimated the canopy LAI of the forest by about 3.14–3.86 times. We built statistical models between adjusted LAI and vegetation indexes and selected the optimal model,i.e.,correlation between normalized difference vegetation index and LAI,through validating.
Published Version
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