Water is a major factor limiting cotton production and farmers must aim to
optimise crop water use through timely irrigation scheduling decisions. Airborne
video imagery when calibrated with a low density of ground based observations, offers
the potential for near real time monitoring of crop condition, through sequential
coverages of entire cotton fields. Using commercially available video equipment
mounted on a light aircraft images were acquired of field experiments that were
established in commercial cotton fields to test if the imagery could monitor changes in
crop condition. Ground data collected from these experiments were used to evaluate
green, red, near infrared and thermal band imagery for irrigated crop management.
Prior to acquiring imagery, a ground radiometer study was conducted to
investigate if canopy reflectance changed with the onset of crop water stress. Canopy
reflectance decreased in the near infrared and green bands during the five day period
prior to the crop's normal irrigation date. Red reflectance increased only after the crop
irrigation was due, when the crop was suffering from water stress. The greatest
change in canopy reflectance was in the near infrared region, attributable in part to a
decrease in ground cover caused by canopy architectural changes including leaf
wilting. The results of this experiment were used to select spectral filters for the video cameras.
A range of crop conditions were identified in the imagery including; crop
waterlogging, wheeltrack soil compaction, crop nitrogen status, different varieties,
crop maturity, canopy development, soil moisture status, cotton yield and nutgrass
weeds. Thermal imagery was the most successful for distinguishing differences in the
crop soil moisture status. Near infrared imagery was most closely related to crop
canopy development and is recommended for monitoring crop growth.
Linear relationships were found between spectral responses in the imagery,
crop reflectance (%) and crop temperature measured on the ground. Near infrared
reflectance linearly increased, while spectral responses in the green, red and thermal
bands exhibited an inverse relationship with plant height and ground cover. Imagery
collected early in the season was affected by the soil background. Final lint yield was
related to imagery in the red band. As the soil moisture level declined, crop
temperature increased while reflectance in the green band decreased. To ensure an
accurate relationship between soil moisture and thermal imagery, separate calibration
equations are recommended for different stages in the season.
Green, red and near infrared imagery were affected by the sun angle that
caused one side of the imagery to appear brighter than the other. This problem was
greatest in the green and red bands, but was not evident in the thermal imagery.
Changes in solar radiation and air temperature on some occasions caused greater
variation to the imagery between flights, than changes in crop condition per se.
Therefore, it is not aIways possible to directly determine the soil moisture status from
canopy temperature. Further research is required to correct imagery for environmental
variables such as solar radiation, air temperature and vapour pressure deficit.
Thermal imagery offers many improvements to current irrigation scheduling
techniques including the facilitation of locating more representative ground sampling
points. Thermal imagery also enables cotton fields on a farm to be ranked according to
their soil moisture status. This then provides farmers with a visual picture of the crop
water status across the whole farm, which is not possible using conventional ground
scheduling techniques. At this stage, airborne video imagery will not replace soil
moisture data collected for irrigation scheduling, however offers potential to enhance
irrigation scheduling methods by addressing the problem of crop variability within
cotton fields.
| Identifer | oai:union.ndltd.org:ADTP/218661 |
| Date | January 1993 |
| Creators | Roth, Guy W, n/a |
| Publisher | University of Canberra. Resource and Environmental Sciences |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | ), Copyright Guy W Roth |
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