B53B-0545
On the accurate estimation of gap fraction during daytime with digital cover photography
Friday, 18 December 2015
Poster Hall (Moscone South)
Yo Rum Hwang1, Youngryel Ryu2, Hyungsuk Kimm1, Craig Macfarlane3, Mait Lang4 and Oliver Sonnentag5, (1)Seoul National University, Department of Landscape Architecture and Rural Systems Engineering, Seoul, South Korea, (2)Seoul National University, Seoul, South Korea, (3)CSIRO Land and Water Flagship, Private Bag No. 5, Wembley,WA6917, Australia, (4)Tartu Observatory, 61602 Tõravere, Tartu, Estonia, (5)University of Montreal, Montreal, QC, Canada
Abstract:
Digital cover photography (DCP) has emerged as an indirect method to obtain gap fraction accurately. Thus far, however, the intervention of subjectivity, such as determining the camera relative exposure value (REV) and threshold in the histogram, hindered computing accurate gap fraction. Here we propose a novel method that enables us to measure gap fraction accurately during daytime under various sky conditions by DCP. The novel method computes gap fraction using a single DCP unsaturated raw image which is corrected for scattering effects by canopies and a reconstructed sky image from the raw format image. To test the sensitivity of the novel method derived gap fraction to diverse REVs, solar zenith angles and canopy structures, we took photos in one hour interval between sunrise to midday under dense and sparse canopies with REV 0 to -5. The novel method showed little variation of gap fraction across different REVs in both dense and spares canopies across diverse range of solar zenith angles. The perforated panel experiment, which was used to test the accuracy of the estimated gap fraction, confirmed that the novel method resulted in the accurate and consistent gap fractions across different hole sizes, gap fractions and solar zenith angles. These findings highlight that the novel method opens new opportunities to estimate gap fraction accurately during daytime from sparse to dense canopies, which will be useful in monitoring LAI precisely and validating satellite remote sensing LAI products efficiently.