| Title | Hemispherical photography simulations with an architectural model to assess retrieval of leaf area index |
| Author | Leblanc, S G; Fournier, R A |
| Source | Agricultural and Forest Meteorology vol. 194, 2014 p. 64-76, https://doi.org/10.1016/j.agrformet.2014.03.016 |
| Year | 2014 |
| Alt Series | Earth Sciences Sector, Contribution Series 20130139 |
| Publisher | Elsevier |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing; vegetation; photography; space photography; computer simulations |
| Illustrations | photographs; histograms; plots; tables |
| |
| Program | Aquifer Assessment & support to mapping, Groundwater Geoscience |
| Abstract | Three-dimensional simulations of forest scenes rendered with the freeware POV-Ray (www.povray.org)were used to assess retrievals of plant and leaf area index (PAI and LAI) from hemispherical
photography(HP). Ten HPs were simulated in 75 scenes with random, erectophile and planophile leaf angle distri-butions. PAI retrieved using Beer's law near 57.3?(55-60?) and with the truncated Miller integrationover zenith angles from 10?to 65?gave
similar results. The importance of clumping was also shown toobtain accurate PAI. Foliage density inside the crown was a major factor causing underestimates of thePAI because the clumping effect was underestimated. Moreover, best PAI retrievals were
found with theclumping index method using the Chen and Cihlar method combined with the Lang and Xiang method(relative RMSE of 23-24% and relative median absolute error of 12-14%) and was slightly less affected bythe averaging length when compared
with only using the Lang and Xiang. Previous error measurementsof 29% were reduced to 16-23% for a black spruce stand using updated input variables and the methodpresented here, and they were shown to fall within the errors of the simulation
framework. |
| Summary | (Plain Language Summary, not published)
Measurement errors of forest characteristics are not always well known. This paper uses virtual forests to assess forest measurements that are regularly
mapped in the Ground Water Program. The two parameters studied are the leaf area index (LAI), representing the amount of leaves in a forest, and the canopy closure (CC), representing the percentage of the ground covered by the forest canopy. LAI and
CC are used in ecological models to calculate the water and CO2 absorbed by vegetation and are used in aquifer assessments to estimate part of the ground water availability. Field measurements are typically used to validate LAI and CC map products.
In this study, LAI and CC are estimated using digital cameras with a fish-eye lens. Synthetic photographs from the virtual forests with known LAI and CC are analysed with the same software used in normal field measurements, to assess the error and
accuracy of the current estimation methods. Our results show that the current methods used have errors around 25% for LAI, and 9% for CC. |
| GEOSCAN ID | 292785 |
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