A technique for high-accuracy ground-based continuous weed mapping at field scale.

摘要

Site-specific weed management was proven beneficial on both economic and environmental aspects. Little scientific literature exists about weed spatial distribution in corn fields because manual data acquisition is tedious and time-consuming. Airborne and satellite imagery resolution is too low to provide sound data to answer important questions about weed spatial distribution during the critical weed control period (weed seedlings). This article describes a technique to acquire high-resolution ground-based imagery data to quantify weed cover after crop emergence. The technique is based on a mobile platform traveling at a slow walking speed, controlling ambient light, and triggering a camera at fixed intervals. Vegetation is segmented from non-vegetation pixels using principal component analysis, and weed vegetation is distinguished from crop vegetation by location. Automatic image segmentation resulted in more than 99% detection accuracy, and crop-weed distinction resulted in 0.37% error. The technique enabled the creation of 19 one-hectare maps of weed cover with more than 3000 points per map. These high-definition weed maps can be used to analyze the spatial distribution of weeds and the cost-effectiveness of site-specific weed management.