|Waltermire, R. - USGS|
|Giles, T. - ARTIC SLOPE REGION CORPOR|
Submitted to: Weed Science Society of America Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: October 15, 2006
Publication Date: February 5, 2007
Citation: Wiles, L., Waltermire, R., Giles, T. 2007. "Digital Sampling": Mapping Weed Presence in Fallow Fields. 2007 Annual Meeting of the Weed Science Society of America : February 5-10, 2007, San Antonio Texas Technical Abstract: Growers need maps of the distribution of weeds in their fields to reduce herbicide use with site-specific weed management (SSWM). Remote sensing is key to successful weed mapping and sophisticated hyper- and multi-spectral image-based systems appear promising for detecting weed patches and identifying species. However, methods of varying cost and complexity are needed for the widest adoption of SSWM. Our objective is to develop a system for mapping weed presence in dryland cropping that is low cost, easy to use, and does not require expensive GIS, GPS, and image analysis software. The premise of our design is based on the following: (1) growers typically make 3 to 5 trips across a fallow field to control multiple flushes of weeds with tillage or herbicides; (2) these flushes include most weed species of the crop rotation; and (3) weed patches are spatially stable. A field is mapped during fallow to avoid the difficulty of distinguishing crop and weed cover. The system includes a consumer digital camera and GPS unit to be mounted on a tractor, commercial software to map locations of images and view the image at each location, and image analysis and map viewing software that we developed. Image locations are mapped by matching GPS and camera time. Weed cover is calculated as the percent green weed pixels in an image. Locations are displayed using a color legend for percent weed cover and are linked for viewing original and analyzed images. Locations can also be mapped on aerial photographs, topographical maps, or shape files portraying information such as crop yield. Cost of the system should be less than $5000. We are currently investigating image resolution and field of view to achieve the best balance between the value of the map for weed management and time required for the analysis.