کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
84605 | 158893 | 2011 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Software to quantify and map vegetative cover in fallow fields for weed management decisions Software to quantify and map vegetative cover in fallow fields for weed management decisions](/preview/png/84605.png)
Mapping weed cover during the fallow period of dryland crop rotations would be valuable for weed management in subsequent crops and could be done with low cost color digital cameras, however most managers lack the specialized software and expertise needed to create a map from the images. A system of software was developed to quantify weed cover in fallow fields in digital images and to simplify and automate the most challenging tasks that non-GIS professionals confront in creating and using maps derived from a large number of images. A GIS file of image locations is created with inexpensive consumer software. Images are classified, a GIS file is generated and the map is displayed in a simple GIS viewer with free software we developed. A map can be generated from 1000 images and 5000 GPS coordinates in 30 min, including image classification. The classified and original images for all locations can be viewed together easily from the map application. The accuracy of estimating weed cover was evaluated using images collected in 15 fields under natural light with a consumer grade camera mounted on an ATV driving 8–11 km h−1. Weed cover was estimated with 96% accuracy for images, regardless of the amount of crop residue, unless part of the image was shaded by the camera. In those images, accuracy was 90% or better. This system will work with many professional and consumer digital cameras and GPS units and the classification algorithm can be easily modified for other applications.
Figure optionsDownload as PowerPoint slideHighlights
► Weed cover is mapped with a color digital camera and GPS unit on a moving vehicle.
► No GIS or image analysis software or expertise is needed to map a set of images.
► Cover in an image is estimated in less than 1 s by classifying pixels by color.
► The classification accuracy is 96% for most images even with crop residue present.
► Original and classified images can be viewed by selecting a location on the map.
Journal: Computers and Electronics in Agriculture - Volume 78, Issue 1, August 2011, Pages 106–115