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A method for computing leaf area of isolated trees from perspective photographs was developed. The method is based on gap fraction inversion. Photographs are discretized into picture zones where gap fraction is computed from image processing. Canopy volume and leaf area density associated with each picture zone are computed from geometrical considerations and inversion of gap fraction equations. Total leaf area and the vertical profile of leaf area are computed from the product of associated volume and its density. The method has been implemented in software called Tree Analyser, written in C++. The method has been tested by comparison with direct estimation of leaf area of three-dimensional (3D) digitized trees of walnut, peach, mango, olive and rubber. Estimated leaf area was sensitive to picture discretization, individual leaf size and leaf inclination distribution. Optimal size of picture discretization was 17 times projected leaf size. Total leaf area was estimated by using a set of eight photographs taken around the tree in the main horizontal directions: deviation ranged from -11% in peach tree to +5% in rubber tree. The method allows fast and nondestructive monitoring of leaf area of individual tree canopies. The next version of the method will include the estimation of 3D leaf area distribution within the canopy.

A photographic gap fraction method for estimating leaf area of isolated trees: assessment with 3D digitized plants