Full text: Resource and environmental monitoring (A)

   
ined 
been 
ears. 
soil 
0.2 
dex, 
ed to 
nopy 
CM2 
s are 
nopy 
The 
y the 
d by 
ECT 
t al. 
This 
F the 
. The 
nany 
plied 
with 
f the 
ising 
table 
{OUD 
998). 
ich a 
sured 
999) 
1at is 
now, 
lance 
tions 
irical 
dels, 
* the 
sical 
sical 
KURZ 
, the 
vant 
four 
sical 
dry 
1cted 
gares 
Forward model 
IAPRS & SIS, Vol.34, Part 7, "Resource and Environmental Monitoring", Hyderabad, India,2002 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Output .- | Empirical model | E Input parameters 
SAIL Leaf area index 
o 
9 
2 Chlorophyll 
© content 
© 
(e 
Model- Linear fitting to A PROSPECT o 
predicted real data using | & phys-mod S Spec. dry matter 
Sensor grey | «| measurements at | — € © 
values ground control > Spec. water 
É model | points (GCP) SOLSPEC content 
i 
52 
zg 
Sensormodel ss 
O © 
© 
per point per data set per point 
Modelinversion 
Measured = : 
sensor grey odelinversion 
Values (Simulated annealing und "least squares" TES 
A > adjustment) > ; 
mas ; 
  
  
  
  
  
  
  
  
  
Figure 1. Overview of the applied physical and empirical models 
3. METHODOLOGY 
3.1 Overview 
Modelling of radiative transfer is usually established in the 
forward direction, i.e. the model follows the way of the photons 
from the sun to the observer to calculate sensor grey values 
given some information about the surface and atmosphere. The 
reverse direction is also referred to as model inversion with 
given sensor grey values to derive information about the surface 
and atmosphere. Figure 1. shows the combination of several 
physical and a linear empirical model in the forward and reverse 
mode. The model input is divided into constant and variable 
parameters. The variable parameters, leaf area index, 
chlorophyll content, specific dry matter and specific water 
content, are part of the input parameters as well as the target 
parameters of the model inversion. These parameters are chosen 
because they show the highest variability within single fields, 
whereas the other input parameters, e.g. the soil reflectance or 
the leaf angle distribution, are assumed to be known and 
constant. Output parameters of the physical models are sensor 
grey values Chiro , that have to be fitted to grey values gl. 
actually occurring at the test site. We use a linear empirical 
model to attain fitted model-predicted grey values g^ der * 
During the model inversion variable parameters are calculated 
given the measured grey values. The model inversion is 
conducted by a least-squares adjustment in combination with 
simulated annealing. 
In the following chapter a more detailed description of the 
applied physical and empirical models with all input parameters 
is given. 
3.2 Physical and Empirical Models 
3.2.1 The SAIL model 
The SAIL model (VERHOEF 1984) calculates the directional 
reflectance on top of the canopy as a function of structural and 
spectral properties of the vegetation/soil medium. A functional 
relation between vegetation- and soil parameters and directional 
reflectance ,* can be sketched by 
p^ - SAIl(LAL LAD, pj c, p? SKYE a, 2,2,,,) (1) 
The vegetation canopy is considered as a homogeneous layer 
characterised by leaf area index LAI, leaf angle distribution 
LAD, as well as reflectance Pi and transmittance 7 / of the 
leaves. Other input parameters of the SAJL model are soil 
reflectance E diffuse percentage SKYL^ of the incoming 
radiation, azimuth angle «a of the observer with respect to the 
azimuth angle of the sun, zenith angle z of the observer, and 
zenith angle z,,, of the sun. 
3.2.2 The PROSPECT model 
The PROSPECT model (JACQUEMOUD and BARET 1990) 
provides hemispherical reflectance P and hemispherical 
A A . 
transmittance 7, of fresh leaves over the whole solar domain 
given only four parameters 
(p, 7?) - PROSPECT (chl,,,c,,.c,. N) (2) 
The variables are the content of chlorophyll a and b chl,, the 
specific dry matter c,, the specific water content c,, and a 
structure parameter .N. The reflectance and transmittance of 
   
   
    
  
   
   
    
    
   
  
   
   
    
   
   
  
   
  
   
   
    
   
    
  
   
   
   
  
  
     
  
  
   
  
   
   
   
   
   
   
    
   
  
   
  
   
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.