The Li-Strahler Geometry Optical Mutual Shadow（GOMS）model is a simple

yet efficient mechanism for modeling forest canopies as arrays of three-dimensional objects. In GOMS model

the signal received by the sensor is modeled as consisting of reflected light from tree crowns

their shadows and the background within the field of view of the sensor. The model is intrinsically bound to the influence of variation in viewing and illumination geometry

and may be inverted to recover biophysical parameters. However

because the GOMS model is a nonlinear model

difficulties exist to invert it. In this paper

a Modified Genetic Algorithm（MGA） are introduced for the inversion. Compared with the deterministic search method-Sequential Quadratic Programming（SQP）

MGA can quickly find promising regions of the search space

but may take a relatively long time to reach the optimal solution. In contrary

SQP can converge to an extreme value quickly

but whether the result is optimal or not depends greatly on the initial value. For this reason

a mixed method is used to invert GOMS model in some cases. The result obtained by MGA is inputted to SQP as initial value. This method significantly increases the power of MGA in terms of solution quality and speed of convergence to the optimal.