IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002
the results using the model to simulate fractional soil moisture
for soil layer 1 and fractional crop canopy moisture.
o o
to o >
o > o
Simulated fractional soil moisture
e
o
0.25 +
0.25 0.3 0.35 0.4 0.45 0.5
Measured fractional soil moisture
Figure 4. Measured fractional soil moisture versus simulated
fractional soil moisture for soil layer 1 (0-10 cm depth). The
1:1 line is also shown.
Simulated fractional canopy moisture
0 0.2 0.4 0.6 0.8 1
Measured fractional canopy moisture
Figure 5. Plot of measured crop canopy moisture versus
simulated crop canopy moisture. The 1:1 line is also shown.
3.3 Irrigation
The CHIPS model provides satisfactory results for the test
fields examined. It can be used to assess the moisture status of a
field by using SAR data as an input. Where farmers are using
water legally for irrigation then the SAR data can be used to
confirm this. Where farmers are using water illegally then the
SAR data can be used to identify those fields that have
unexpectedly high crop and soil moisture levels, and this can be
followed by further action. In this way SAR data can be used in
the CHIPS model to combat fraud.
In addition, the CHIPS model can also be used for scheduling
irrigation and therefore making better use of existing water.
The data noted above were also examined for their use in
irrigation scheduling and it was found that the most effective
irrigation water application during the 1999 simulation period
would use 25 mm of water when a soil moisture deficit of 30
mm is reached. This would have required less water application
than was actually applied in the field and so would have
achieved water savings (Graham and Harris 2002).
4 CONCLUSIONS
Can radar data provide a reliable method to detect agricultural
fraud? Certainly radar data can be provided regularly from a
variety of sources. This paper has shown that for field
identification radar data can produce useful results and when
used in the CHIPS model the data can be used to give good
estimates of crop and soil moisture status.
The emphasis of this paper has been on fraud detection because
of the need to use land and water resources effectively, which
in turn means monitoring the uses that are legal and those that
are not legal. Radar data can also be used in a more pro-active
way to improve efficiencies by:
1. measuring crop areas planted to particular crops, so
allowing advice on what new crops to plant, and
2. providing advice on the actual water needs of crops
so that irrigation water can be scheduled more
effectively.
Both in a fraud detection sense and in a pro-active sense, radar
data can be useful to sustainable agriculture by providing data
and related methods to assist better uses of land and water
resources.
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ACKNOWLEDGEMENTS
We acknowledge the support, comments, advice and assistance
provided by the University of London Intercollegiate Research
Services, the British National Space Centre, the UK
Environment Agency, Logica UK Ltd, the UK Environment
Agency and Richard Turner Associates.
