Aerial multispectral imagery for site specific weed management

AGROSUPSPEEAGESTADCT1DOCT; In an agroecological context (French Law on the Future of Agriculture), the reduction of herbicide uses become a crucial issue. It requires developing new technologies allowing a better knowledge of the field. The company AIRINOV, specialized in use of Unmanned Aerial Vehicle (UAV) dedicated to precision agriculture wants to explore a new approach by UAV to localize weed infestation areas. This work aims to develop a method analyzing images acquired by UAV to detect and map weeds in a field. The study is carried out on crops widely grown in France and requiring weed control at a young state of the plant : maize, sunflower and sugar beet. With its on-board sensors …

Weed detection by aerial imagery : toward weed management by UAV

The agricultural framework aims to reduce pesticide use on fields. Weed management, which is highly herbicide consuming, became a great issue. In order to develop a weed management service using UAV, this PhD dissertation studies how to adapt the acquisition system (UAV + multispectral camera) developed by AIRINOV to detect weeds in row crops. The acquisition chain was modeled to assess some of its parameters (optical filters and spatial resolution) impact on weed detection quality. Orthoimages and orthorectified images were created using a multispectral camera (4 to 8 filters) with 6 mm to 6 cm spatial resolutions. Several weed location methods were specifically developed to study multispe…

Proxi-détection des adventices par imagerie aérienne

Détection non supervisée des adventices par drone : résultats et limites

Dans un cadre de diminution des produits phytosanitaires, l'agriculture de précision est une solution technique pour diminuer l'impact environnemental de l'agriculture sans transformer les systèmes de production actuels. La démocratisation des drones aériens pour l'agriculture permet leur utilisation afin de discriminer culture et adventices au sein de parcelles cultivées. Nous avons développé et testé des algorithmes non supervisés (ne nécessitant pas l’intervention d’un humain) combinant l'information spatiale et spectrale pour réaliser cette discrimination. Cette présentation sera l'occasion de revenir sur les résultats de ces algorithmes et de présenter également les limites rencontrées…

Aerial imagery for site specific weed management

National audience

Weed detection by aerial imaging: impact of soil, crop and weed spectral mixing

International audience; This study aims to evaluate spectral information potential of images captured with a UAV, for site specific weed management. The image acquisition chain was modeled in order to compute the digital values of image pixels, according to the field conditions and objects lying on the ground surface projected in the pixels. The object spectra are mixed in the same pixel to estimate the impact of the spatial resolution of the image. The classification potential into crop, weed and soil classes was studied usinf simulations based on the present multispectral sensor characteristics and according to different mixing rates.