Weed detection for site-specific weed management: mapping and real-time approaches.

摘要

This work describes the current status of remote and proximal (on-ground) weed detection systems for site-specific weed management and discusses the limitations and opportunities of these technologies. Remote sensing based on multispectral aerial imagery can provide accurate weed maps, especially at late weed phenological stages, whereas images from high spatial resolution satellite and unmanned aerial vehicles must still be analysed. Hyperspectral images produce highly accurate maps at early and late phenological stages at a farm scale or medium spatial scale. However, this technology is not profitable, because of current operating costs, which are prohibitive. In studies of on-ground weed seedling detection, accurate results can be obtained at a medium farm scale. Despite numerous efforts, a powerful and flexible classifier of soil, weeds and crops in a number of situations, remains the greatest challenge of this technology. The main limitations of remote and proximal sensing may be summarised in the following two points: (i) the time and education required for applying new technological advances and (ii) the high cost of the technology and the lack of compatibility of the machinery. Possible solutions might include: (i) offering an advisory service that provides technical support, agronomic knowledge and specific training courses, (ii) the development and implementation of uniform and cheaper standards, (iii) increased research of both high resolution satellite imagery exploring object-based image analysis and pan-sharpened imagery and unmanned aerial vehicles (UAV) and (iv) enabling the development of current prototypes of robotic weeding into commercial products. The general lack of multidisciplinary research groups can be a disadvantage when comparing the economic feasibility of site-specific weed management with conventional systems.Digital Object Identifier http://dx.doi.org/10.1111/j.1365-3180.2010.00829.x