Agriculture Reference
In-Depth Information
as Ag Leader's SMS Basic software use a constant time lag to compensate for the
effect of the flow delay. However, it is difficult to objectively determine a correct or
optimum time lag for a whole field or for each area of the field. Chung et al. (2001)
used geostatistical and data segmentation methods for determining yield monitoring
time lag with objective criteria. Beal and Tian (2001) used the ratio of the surface
area of a three-dimensional yield map to its projected area for determining yield
monitoring time lag. Correct time delays were determined based on minimum area
ratio values. Yang et al. (2002) developed a method for determining the optimum
time lag for yield monitoring based on remotely sensed imagery taken during the
growing season. The underlying assumption for the method is that there exist statis-
tically significant correlations between crop yield and remotely sensed imagery and
that incorrect time lags will cause a reduction in the correlations. Therefore, a time
lag that maximizes the correlation can be considered the correct or optimum time
lag.
4.2.6 R
EMOTE
S
ENSING
Remote sensing is the science and technology of acquiring information about the
earth's surface without physically touching it. It uses sensors to measure and record
the reflected and emitted electromagnetic radiation from the target area in the field
of view of the sensor instrument. The detecting and recording instruments are gen-
erally referred to as remote sensors. Remote sensors are typically carried on air-
craft and Earth-orbiting satellites, but some sensors can be handheld or mounted on
ground-based vehicles. Remote sensing applications in precision agriculture have
been steadily increasing in recent years because of improvements in spatial, spectral,
and temporal resolutions of both airborne and satellite remote sensors. Airborne
or satellite imagery allows a farmer to have a bird's-eye view of the crops grow-
ing on the entire field or entire farm. This section will provide a brief overview of
the remote sensing systems that have been used for precision agriculture, including
ground-based spectroradiometers, airborne digital multispectral and hyperspectral
imaging systems, and high-resolution satellite imaging systems.
4.2.6.1 RemoteSensors
Remote sensors include all the instruments that detect and measure reflected and
emitted electromagnetic radiation from a distance. These instruments fall into two
broad categories: non-imaging (i.e., spectroradiometers) and imaging (i.e., cameras).
According to the types of sensor-carrying platforms, remote sensors can be ground-
based, airborne, and spaceborne. Both non-imaging and imaging sensors can be car-
ried in all three types of platforms, although non-imaging sensors are primarily used
for ground-based applications.
Portable non-imaging remote sensing instruments include radiometers and spec-
troradiometers. The types of radiometers can be single-band radiometers, which
measure radiation intensity integrated through one broad waveband, and multispec-
tral radiometers, which measure radiation intensity in more than one broad wave-
band. Spectroradiometers measure radiation intensity over a continuous range of
wavelengths by simultaneously sampling a large number of narrow spectral bands.
