Full text: XVIIIth Congress (Part B7)

  
  
nethods, 
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1ded road 
A Monte Carlo radiative transfer simulation 
of rice canopy based on digital stereo photogrammetry 
Keiji KUSHIDA and Kunihiko YOSHINO 
Department of Agricultural Engineering 
Faculty of Agriculture, 
University of Tokyo 
1-1-1 Yayoi, Bunkyo-ku, Tokyo 113, JAPAN 
Phone: *81-3-3812-2111 (ext. 5345), Fax: *81-3-5684-3632 
Commission VI, Working Group 1 
KEY WORDS: 
Vegetation, Radiation, Simulation, Agriculture, Matching, 
Digital, Three-dimensional, Measurement 
ABSTRACT: 
NIR (Near Infra Red) bidirectional reflectance distributions of thirteen kinds of rice canopies are simulated 
using the 3-D Monte Carlo method and measured in an experimental field. The simulation is carried out under two 
different field conditions. One is similar to the condition of the experimental field (condition A) and the other is the 
wide spread field condition under the parallel solar beam (condition B). 
The framework of the simulation model is 1cm x 1cm x 1cm sized rectangular solid cell. Each cell has an 
information on leaf area, inclination, and direction that are calculated using a 3-D digital stereo measurement 
method. Other than the structural information, the sensitivity of individual leaf reflectance is accounted. 
The sensitivity is decided by measuring some kinds of individual leaf reflectance. From the measurement, 
NIR reflectance and transmittance of rice leaves have low coefficient of variation. On the other hand, VIS (Visible) 
reflectance and transmittance have high coefficient of variation. 
The simulated bidirectional reflectance fit the measured one well under condition A in NIR region. As the 
result of the simulation, the ratio of the reflectance factors (view zenith: 45deg. to 0 deg. ) in NIR region from wide 
spread field is suggested to give average inclination of rice canopy. 
1. INTRODUCTION 
Radiative transfer simulation of plant canopy is 
basic to remote sensing of plant canopy state. A 
complex scene is hard to model with analytical models. 
With the simulation models such as Monte Carlo 
method, one can consider canopy structure that is hard 
to model with analytical models. Therefore, the 
simulation has been carried out using the Monte Carlo 
method. 
Ross et al. (1988) modeled plant elements (leaf, 
stem) as simple geometrical shapes. Round or elliptic 
leaves are assumed and the difference of bidirectional 
reflectance factor is estimated under the conditions of 
different variance of leaf inclination, different deg. of 
ellipticity, the row effect, and the influence of stems. 
Kimes et al. (1982) represented information on 
Plant canopy physical state as 3-D cell matrix and 
developed a simulation model. A size of one cell is 
about 10cm. Each cell that corresponds to leaf has 
Information on leaf inclination distribution function and 
leaf area index. Each cell has the same theoretical or 
389 
empirical leaf inclination distribution. Simulation is 
carried out with homogeneous dense canopy (Kimes, 
1984), homogeneous sparse canopy (Kimes et al., 
1985), and inhomogeneous canopy (Kimes et al., 
1986). The results of the simulation are compared with 
measured value, and bidirectional reflectance 
characteristics of various vegetation canopy are 
explained. 
‘However, simulations and validation of their 
result have hardly carried out from the viewpoint of 
estimate of canopy physical state of a fixed crop 
canopy. One of the reasons is thought to be that the 
structural measurement of canopy has been hardly 
carried out so that the cells are small enough to 
correspond to a minute region of an individual leaf. 
G.V.Menzhulin et al. (1991) also pointed out this as a 
shortcoming of the simulation model. 
Therefore, NIR bidirectional reflectance 
distribution of thirteen kinds of rice canopy is simulated 
using the 3-D Monte Carlo method based on cell 
information given from 3-D structure obtained by the 
leaf edge matching method (Kushida et al, 1993; 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996 
 
	        
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