TOAS - New remote sensing technologies for optimizing herbicide applications in weed-crop systems Completed Project uri icon

description

  • Agricultural production requires the use of herbicides as an essential tool to control weed infestations. Associated environmental and economic concerns have led to the creation of European policy that encourages farmers to optimize their use. These components are part of the agronomical basis of site-specific weed management (SSWM), whose efficient development somehow relies on the use of remote sensing technology for collecting and processing spatial data from sensors mounted in satellite or aerial platforms. Some limitations of this technology have been traditionally attributed to insufficient imagery resolution for mapping weed seedlings in early stages, just when the herbicide application is needed. Nowadays, these problems could be overcame by utilizing the new generation of remote platforms known as unmanned aerial vehicles (UAV), which can operate at low altitudes and, thus, capture images at the spatial resolution needed. This project involves the testing and applications of the UAV technology for effective weed management (or SSWM), mainly accomplished in two different crop systems: 1) Annual crops (i.e., sunflower, maize or tomato) and permanent woody crops (i.e., poplar or olive tree). The specific objectives will concentrate on the evaluation of the specifications (sensor type, imagery characteristics, crop-weed phenological stage) required for each type of crop and on the development of advanced algorithms for crop assessment and weed mapping using the captured remote images. The ultimate objective is to generate geo-referenced weed infestation maps for making in season site-specific herbicide treatments in early weed stages that, consequently, lead to a considerable decrease in the use of herbicide, a reduction in farm costs and an increase in agro-environmental benefits. Further, the potential and opportunities of this technology for other agricultural applications represent a new trend of evident relevance.

date/time interval

  • September 1, 2011 - August 31, 2015