Numbers of wild Canada geese (Branta canadensis) have increased dramatically during the past 30 years in the lower Columbia and Willamette Valley systems. The damage they cause by grazing and trampling plants can be substantial.
The objectives of this research were to:
1) Develop methods that provide reliable estimates of goose impact on wheat yield and quality, and 2) Develop methods to separate goose damage from other factors that lower
yield such as poor soil or waterlogging.
To document grazing impacts, color aerial photography was combined with Global Positioning System (GPS) and precision farming technology. Field-scale color aerial photographs (1:14,000 scale) were acquired four times during each growing season: in January, March, April, and just prior to harvest in July. Each flight was coupled with ground truth data collection to verify exact cause of spectral signature variation or variations in wheat cover. Such data included wheat height, number of goose droppings, and a relative rating of goose grazing intensity. At each sampling point a platform photograph and a GPS location were taken.
Wheat yield impact varied considerably as field size, shape and proximity to road varied. Yield maps revealed that, goose grazing had reduced grain yield by 25% or more in heavily grazed areas. At harvest time during the first year, wheat grain in the heavily grazed areas had higher moisture content due to delayed maturity. Therefore those areas were harvested two weeks later. Heavily grazed areas also had more weeds than ungrazed portions of the field. Late-season (April) grazing was more damaging to wheat yield than was earlier season grazing, but early season grazing did have an impact on yield. Intensely hazed fields had lower levels of damage than did fields or portions of fields that were not as vigorously guarded.
Our results illustrate very practical ways to combine image analysis capability, spectral observations, global positioning systems, precision farming and ground truth data collection to map and quantify field condition or crop damage from depredation, standing water, or other adversities. Image analysis of geopositioned color platform photographs can be used to stratify winter wheat fields into impact units according to grazing intensity. Ground-truth data, when collected in conjunction with a GPS, provided the information needed to locate and establish the spectral properties of impacted areas. Once the spectral properties of a representative area were identified, information could be extrapolated to other areas with the same characteristics. In addition, this method could be used in conjunction with aerial photography to verify areas of grazing. The combination of two or more of these tools would provide farm managers and agricultural consultants with a cost-effective method to identify problem areas associated with vegetation stress due to heavy grazing by geese or other factors. / Graduation date: 1999
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/33615 |
| Date | 22 January 1999 |
| Creators | Louhaichi, Mounir |
| Contributors | Borman, Michael M. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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