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The goniometric platform with its (a) azimuth; (b) elevation and (c) rolling angle protractors. To be flattened, half adaxial and abaxial leaf faces are fixed with black strings.
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They are fixed (abaxial and adaxial side) on the goniometric platform with black painted strings (Figure 1) and are scanned within the hour after collection.
Part of a hemispherical projection of a TLS scan of 15 two years old pear trees (first row). The corrected intensity and angle of incidence relationship is tested on leaves of those trees. Trees are grouped by their distance to the beam aperture (red frames).
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In a second experiment, from each of the 15 pear trees of the first row (Figure 2) a second scan is made on June 24th 2010. Finally, the LSR is made on seven entire leaves for tree n 9 (Figure 2) to gain a more thorough understanding of the leaves geometry impact on the TLS point cloud and intensity data.
Analysis flowchart: (I) A semi-automatic and manual selection in the point cloud is proceeded. It takes into account a distance and an intensity threshold to limit unwanted point as ghost point or leaf curvature. (II) The average distance and average intensity are calculated from the selected point cloud. Their relationship is used to correct the distance effect by replacing the intensity value by a reference value (correction of the distance effect on the intensity). (III) The angle of incidence with the selected surface is calculated thanks to a LSR. (IV) The corrected intensities values of the selected points are averaged. The angle of incidence is then related to this averaged corrected intensity.
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A second sub-selection is made based on an intensity and distance threshold [Figure 3(I)]. Finally, as the value f(dref) is unknown, the distance effect on the intensity is corrected with the following formula [Figure 3(II)]: with c = f99% (d) - I (d). To obtain the angle of incidence with a surface (flat by assumption) represented by a selection from the point cloud, a Least Square Regression (LSR) is proceed on the sub-selection (Figure 3.III). Knowing the angle of incidence provided by the LSR, it can finally be related to the intensity averaged over the cloud of points selected (Figure 3.IV).