ACROSS: Autonomous spatial-temporal crop and soil surveying

    Project Details

    Description

    The general vision is effective precision farming, which in harmony with the environment utilises resources optimally. This requires continuous selective and adaptive control of growth, weeds, diseases and pest. In turn such control is conditioned on corresponding continuous monitoring in the field using appropriate methods of measuring the current conditions of and for the plant growth. The objective of this project is to develop methods of measuring and managing such information to support the above vision in a way that invites also new innovative approaches to precision farming by providing the necessary information on demand and in time for planning and decision making. More concretely the project will develop methods and technology for: 1) Computer vision and laser range methods for on-site and real-time monitoring of information of the crop growth (nutrients, diseases, etc.). The methods will allow diagnostics of crop condition based on reflection patterns (e.g. miscoloured areas) down to single leaf scale. 2) Implementation and integration of the above methods on an autonomous platform with a suite of existing crop and soil measuring facilities for on-site operation. 3) Repeated test and evaluation for development and proof of concept: "Autonomous Crop and Soil Surveillance". Hence, the project through new research and practical development will contribute to a new scope precision agriculture, which until now has not been seen in its full perspectives, due to the lack of precise and timely information. The project is carried out by a consortium comprising CVMT and three departments of the Danish Institute of Agricultural Science: Agricultural Engineering (Bygholm), Agricultural Systems / Crop Physiology and Soil Science (Foulum), and Plant Biology (Flakkebjerg). Funded by: The Danish Technical Research and Agricultural and Veterinary Research Councils and the Danish Ministry of Food, Agriculture and Fisheries. (Erik Granum, Hans J. Andersen, Michael Nielsen, Kristian Kirk)
    StatusFinished
    Effective start/end date01/08/200301/08/2006

    Research Output

    • 1 Ph.D. thesis

    Automatic Plant Annotation Using 3D Computer Vision

    Nielsen, M., Mar 2011, Aalborg: Institut for Arkitektur og Medieteknologi. 175 p.

    Research output: Book/ReportPh.D. thesisResearch

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