IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002 
  
SUGAR BEET YIELD PREDICTION USING ERS SAR DATA {PRIVATE } 
S.P. Vyas'", M.D. Steven! , K.W. Jaggard? and R. Werker 
1. Department of Geography, University of Nottingham, University Park, Nottingham NG7 2RD 
E-mail: Michael.Steven ? geography.nottingham.ac.uk Tel. +44 115 9515442 Fax. +44 115 9515249 
2. IACR Brooms Barn, Higham, Bury St Edmunds, Suffolk IP28 6NP 
, E-mail: Keith Jaggard@bbsrc.ac.uk Tel. +44 1284 812216 Fax. +44 1284 811191 
1*. Presently at CMD/ARG/RESA, Space Applications Centre (ISRO), Ahmedabad - 380 015 
Email: sp vyasQ yahoo.com Tel: 00 91 79 675 4037 Fax: 00 91 79 674 8813/676 2735 
KEY WORDS: ERS SAR, water cloud model, LAI, canopy cover, SPOT 
ABSTRACT : 
Radar remote sensing systems can penetrate cloud and provide regular data for persistently cloudy periods. In sugar beet, previous 
studies have shown that forecasts of potential sugar yield can be provided through the growing season, based on satellite 
observations of crop canopy cover at various stages of development. These observations are used in conjunction with corresponding 
regional weather information, crop sowing dates and soil types to provide successively refined yield forecasts as harvest time 
approaches. Field data were collected from June to August in 1995 and 1996 covering a study area around the IACR-Broom's Barn 
sugar beet research institute (UK). An independently fitted version of the water cloud model was inverted to calculate Leaf Area 
Index (LAI) from values of ERS-1 and ERS-2 SAR backscatter and estimates of soil moisture content. LAI estimates were in good 
agreement with measured values. Canopy cover was then estimated from the radar-estimated LAI values, using a standard 
exponential relationship that has a well established coefficient for sugar beet. Good correlation was found between observed and 
SAR predicted yield. The study shows that radar data can provide useful estimates of canopy cover for crop production modelling, 
especially in areas where optical data is difficult to obtain because of cloud. 
1. INTRODUCTION 
Radar data are not as well established for monitoring vegetation 
as optical data. However, the prime interaction of microwave 
radiation with the surface environment is with water. Leaves 
are essentially water-containing structures suspended above the 
soil surface and strongly affect radar backscatter. The volume 
of water in the canopy and the degree of backscattering depend 
primarily on the LAI In crops such as sugar beet, this 
parameter has well established relationships with the fraction f 
of photosynthetically active solar radiation intercepted and 
absorbed by leaves in the crop canopy. Sugar beet yield 
estimation using satellite data employs estimates of this 
fraction because it is directly proportional to the rate of 
biomass production by the canopy (Steven et al., 1986). The 
integral f and irradiance intercepted solar radiation, projected 
forward to harvest, corresponds to the seasonal biomass 
production of the crop. 
Compared with optical remote sensing, radar has a more 
ambiguous relationship with crop canopy variables, but the 
relationship with leaf area in sugar beet is significant and 
strong enough to provide reasonable estimates of crop cover 
(Xu et al., 1996). However, the radar model used by Xu ef al. 
(1996) was calibrated and fitted to agronomic field data from a 
single date in 1994. This paper describes an independant study 
to evaluate the reliability of radar estimates of crop cover in 
sugar beet. 
2. AIMS 
The specific objectives were as follows: 
1. To determine the relationship of radar backscatter, measured 
by ERS-1 and ERS-2 SAR, with LAI and soil moisture. 
2. To validate this relationship on an independent data set. 
3. To apply crop canopy cover indices derived from ERS SAR 
in yield prediction model. 
4. To compare the accuracies of yield estimates derived using 
optical and SAR data 
To test the robustness of this model over time, ERS-1 and ERS- 
2 SAR data were related to ground measurements of sugar beet 
for a sequence of dates through the growing season. This was 
then used to estimate crop cover (f) for incorporation into the 
sugar beet growth model. 
3. DATA SOURCES 
' 
3.1 Ground truth data 
The study area was chosen near IACR-Broom's Barn in 
Suffolk, UK (52? 16'N, 0? 35'E). The data were collected 
during the period from June to August, 1995 on ERS-1 
overpass dates, whereas in 1996 data were collected weekly 
from June to August. A Parkinson radiometer (P P Systems, 
Stotford, Beds, UK) with wavebands 2 bands (NIR and Red 
respectively at 650 and 850nm) and 2 heads (radiance for 30? 
FOV and irradiance) was used for radiometric measurements 
of the crop canopy. This served as a ground reference to the 
satellite data. In four fields, 5 areas each about minimum 12 m 
apart, were used to collect samples and  biophysical 
measurements as described by Xu et al. (1996). A larger set of 
sugar beet fields was identified for the extension of image 
analysis. 
32 ERS-1 and ERS-2 SAR data 
    
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