Journal of Geo-information Science >
Indirect Measurement of Forest LAI to Deal with the Underestimation Problem Based on Beer-Lambert Law
Received date: 2011-10-27
Revised date: 2012-05-06
Online published: 2012-06-25
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Leaf area index (LAI) defined as one half of the total green leaf area per unit ground surface area. It is an important parameter of canopy structure, because it relates to many biophysical and physiological processes of canopy, including photosynthesis, respiration, transpiration, carbon cycling, net primary productivity, precipitation interception, and energy exchange, etc. Accurate measurement of forest leaf area index by means of remote sensing has been an important task in remote sensing research. The direct method of LAI measurement is time-consuming, labor-intensive and may destroy plants. Compared to the direct method, indirect methods by means of optical methods are quicker and more efficient. These methods are all based on the Beer-Lambert law. As an important means to validate remote sensing LAI products, indirect LAI ground measurement is the basis and standard of remote sensing inversion. However, indirect ground measurement method based on Beer-Lambert law has serious underestimation problem in forest. The derivation of Beer's law was originally in uniform gas medium, when applied to discrete vegetation measurement on a pixel scale. Its applicability has not got enough attention and validation. In this paper, by theory analysis, we find that the underestimation of leaf area index comes from the spatial heterogeneity of foliage area volume density, extinction depth and leaf angle projection function G if Beer-Lambert law is applied to LAI measurements in forest. Quantitative assessment of impact on LAI measurement from non-random distribution of canopy was made. It was shown that non-random distribution of canopy may bring 20-40% measurement error of LAI. An important conclusion is that the simple correction of Beer-Lambert law has significant limitations on the in situ forest LAI measurement. This method is not a fundamental solution to this underestimation problem, and the theories and methods for LAI indirect measurement need to be changed.
Key words： clumping effects; LAI measurement; Beer-Lambert law; underestimation; remote sensing
HU Ronghai, YAN Guangjian . Indirect Measurement of Forest LAI to Deal with the Underestimation Problem Based on Beer-Lambert Law[J]. Journal of Geo-information Science, 2012 , 14(3) : 366 -375 . DOI: 10.3724/SP.J.1047.2012.00366
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