Clevers, Jan 
  
A SEMI-EMPIRICAL APPROACH FOR ESTIMATING PLANT PARAMETERS WITHIN THE 
RESEDA-PROJECT 
J.G.P-W. CLEVERS', O.W. VONDER', R.E.E. JONGSCHAAP", J.F. DESPRATS™, C. KING™, 
L. PRÉVOT""", N. BRUGUIER"* 
" Centre for Geo-Information, Wageningen-UR, The Netherlands 
jan.clevers Q staff. girs.wag-ur.nl 
"Plant Research International, Wageningen-UR, The Netherlands 
""BRGM, Orléans, France 
SO oo, 
INRA, Avignon, France 
Working Group VII/1 
KEY WORDS: Multi-spectral data, Multi-temporal, Modelling, Monitoring, Agriculture 
ABSTRACT 
Monitoring the growth of agricultural crops during the whole growing season is important for observing anomalies in 
growth and development in order to be able (1) to adjust the growth of the crops, and (2) to obtain yield predictions well 
before harvest time. More and more use is being made of crop growth simulation models for this purpose. Remote 
sensing data can be used for calibrating dynamic crop growth models for actual field conditions, thus rendering the 
combination of growth models and remote sensing data a valuable tool for growth monitoring. This paper describes the 
use of SPOT satellite data for deriving crop biophysical parameters at various dates during the growing season. In 
particular, the leaf area index is estimated by using the semi-empirical CLAIR model. Subsequently, these leaf area 
index estimates are used for calibrating the mechanistic crop growth model ROTASK. This study is based on 
measurements obtained during the ReSeDA experiment at the Alpilles test site in Southern France from October 1996 
to November 1997. The methodology is applied to a number of wheat fields in the area. A total of four SPOT images 
during the growing season were used. Results show that crop variables such as leaf area index can be monitored well 
using SPOT data. Also the calibration of a wheat growth model yields good results. Correspondence with field 
measurements was satisfactory. 
1 INTRODUCTION 
1.1 The ReSeDA Project 
Remote sensing information in potential is very important for the estimation of net primary production, 
evapotranspiration and yield of agricultural crops. In order to study this potential, the ReSeDA project was initiated 
within the EU fourth framework programme. The main objective of the ReSeDA project was “the use of multisensor 
and multitemporal observations for the monitoring of soil and vegetation processes, in relation with the atmospheric 
boundary layer at local and regional scales by assimilation of remote sensing data into canopy and soil functioning 
models” (Prévot et al, 1998). 
The project was decomposed into 3 main tasks: 
l. The experiment. The ReSeDA experiment covered the whole growing season of winter and summer crops from 
October 1996 to November 1997. It included field measurements, airborne and satellite remote sensing 
measurements. The experimental site (Alpilles) was located near Avignon (SE of France) in the Rhone valley. Its 
size was about 4 km x 5 km. It is a very flat area with large enough fields (200 m x 200 m) to extract pure pixels 
from high spatial resolution satellites. Main crops were wheat, corn, sunflower and alfalfa. 
2. Evaluation of inverse methods. Canopy and soil biophysical variables were retrieved from remote sensing 
observations using mainly the spectral, directional and polarisation signatures. Analytical approaches using 
radiative transfer and surface reflectivity models as well as semi-empirical approaches were used. Biophysical 
variables retrieved through these inverse methods were compared to the values measured in the fields. 
3. Evaluation of assimilation methods. Canopy functioning models and SVAT (Soil- Vegetation- Atmospheric 
Transfer) models were tuned so that the simulated temporal, spectral, directional and polarisation signature 
matched the observed remote sensing signals as close as possible. Several approaches of data assimilation were 
evaluated with emphasis on the use of all remote sensing data available and knowledge of the physical and 
physiological processes governing soil and vegetation functioning. 
  
272 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000.