Digital hemispherical photographing for LAI estimation


 

An example of digital hemispherical photograph (left) and a digital camera (Nikon CoolPix 4500) with a fisheye lens

Hemispherical or fisheye photography is an indirect means for measuring LAI as well as studying the canopy architecture and light regime. Hemispherical photographs have the advantage of spatial discrimination, and are particularly useful for acquiring canopy structure and light penetration such as foliage angular distributions, and gap fractions at different zenith and azimuthal angles. Hemispherical photographs can capture the light obstruction/penetration patterns in the canopy, from which the canopy architecture and foliage area can be quantified. Gap fraction can be calculated from the photographs to quantify the canopy openness and architecture. By measuring gap fractions at several zenith angles, the plant area index and the leaf inclination angle distribution can be simultaneously calculated (Chen et al., 1991).

A correct exposure is of crucial importance for collecting digital hemispherical photographs to accurately retrieve effective LAI, clumping index and the actual LAI. A methodology of digital hemispherical photograph exposure was developed for estimation of canopy parameters (Zhang et al., 2005). The procedure for collection of digital hemispherical photographs is suitable for various sky brightness and canopies with different closure levels. Two stops of overexposure relative to the sky reference was proven theoretically and experimentally to be the optimum exposure for taking digital hemispherical photographs for the purposes of obtaining the mean canopy gap fraction and the effective LAI.

References:

Chen, J.M., Black, T.A. and Adams, R.S., 1991. Evaluation of hemispherical photography for determining plant area index and geometry of a forest stand. Agricultural and Forest Meteorology, 56: 129-143. Zhang, Yongqin., Jing M. Chen, John R. Miller, 2005b, Determining Digital Hemispherical Photograph Exposure for Leaf Area Index Estimation, Agricultural and Forest Meteorology (in review).


© Revised: Mar., 2005