Remote sensing technology can be used to prepare maps of crop type
and acreage. The use of satellites is advantageous as it can generate a
systematic and repetitive coverage of a large area and provide
information about the health of the vegetation.
Through scaling procedures it is possible to compare less frequent
high resolution data with daily deliveries of inexpensive data with a
lower resolution. Interpretations from remotely sensed data can be input
into a Geographic Information System (GIS) and combined with ancillary
data to provide information about ownership, management practices, crop
rotation systems etc.
When using optical data the spectral
reflection of a field will vary with respect to changes in the
phenology (growth), stage type, and crop health, and these paramters can
thus be measured and monitored by multispectral sensors. Water stress
indicators and vegetations greenness provide information about the
status of vegetation. The biomass of crops (crop yield) can be estimated
based on light-use efficiency relations.
In contrast, radar data are sensitive to the
structure, alignment, and moisture content of the crop and can thus
provide complementary information to the optical data. Biomass can also
be assessed. Combining the information from radar and optical sensors
increases the information available for distinguishing each target class
and its respective signature, and thus there is a better chance of
performing a more accurate classification.
In countries where agricultural
statistics are reliable, the main use of remote sensing is for
monitoring purposes. During the growing season, the status of crops can
be inspected using satellite images and the need for irrigation and
fetilisation can be monitored on an operational basis.
In countries with less reliable agricultural statistics remote
sensing is both relevant for monitoring and for updating agricultural
database statistics. Through classifications of crop types, the acreage
of each crop can be computed with high accuracies. Crop yield can in
most cases be estimated with app. 85% accuracy which is adequate in many