Weeds accurately mapped using DGPS and ground-based vision identification

Abstract

We describe a method for locating and identifying weeds, using cotton as the example crop. The system used a digital video camera for capturing images along the crop seedline while simultaneously capturing data from a global positioning system (GPS) receiver. Image time-stamps were synchronized with GPS time so that GPS coordinates could be overlaid onto selected images. The video system continuously mapped nutsedge weeds and crop plants within the seedline, allowing weed locations to be described with centimeter-scale accuracy when using a real-time kinematic GPS (RTK-GPS). This system may be used to develop maps of weed and crop populations as part of precision crop-management decisions.