The goal of proposed project is to improve methods of data access and statistical data analysis in process of precision farming. Precision farming is new agriculture technology designed to monitor, analyse and control plant production with the aim to optimise expenses and ecological effects. The basic principle of technology is exactly positional controlling of fertilisation with accuracy of few meters. For all process is collected big amount of data, which help to controlling all process. Among the parts exist data's from measuring provided in past ten years. For better understanding to all this process is necessary to improve access to this data and make analysis of this data. Mathematical analysis of this data can bring new quality to all process of precision farming. The real end-user of all technology are farmers and agriculture managers.
Precision farming is new agriculture technology designed to monitor, analyse and control plant production with the aim to optimise expenses and ecological effects. The basic principle of technology is exactly positional controlling of fertilisation with accuracy of few meters. The main focus of the proposed project will be data access data analysis and education of the farmers
The presently used methods of data analysis are mostly based on empirical methods of data analysis and agrochemical models. There don't exist real mathematical analysis of different data sources, which can influence on all process. This process can understand us cyclic optimisation process, with some control points. This control points are the measure of quantity and quality of the process. The different models of optimisation are used - maximum economy, minimum cost, optimisation of expenses and ecological effects, etc. The controlling of the process is provided by fertilisation.
To main goal is improve a methodology of data access, data collection and data analysis for precision farming, and costs optimalisation of measurement method. It will be made trough comparison of different method of data collections (including financial comparison and evaluation of dependence between each other with goals optimalisation of costs). The new tools for mathematical (statistic and theory of information) evaluation of new soil, fertilisation and crop data in connection with spatial information's (GIS, Remote Sensing) will be developed. The one from principal problems of precision farming is to know, what kind of incoming information can influenced crop production. There are different types of incoming data - soil parameters and content of nutrients, aerial photos, satellite imagery, applications maps, yields map (which are simultaneously incoming and outcoming data). The tolls for combination of spatial, quantitative and qualitative data will be developed. Evaluation of spatial and temporal changes will be carried out
The new mathematical evaluation methods will be implemented as an application for standard GIS tools. New methods of modelling based on multicriterial analysis and further development prediction will be implemented. The procedures will be built on standardized database in order to allow their easy implementation in potential future case studies The results will be collected in GIS environment and together with other data will be made accessible through the Internet
Until now there was very difficult to take into the account in praxis the influence of terrain relief. There will be followed this influence and will be tasted 3D modelling methods for chemical elements and organic matter. The results of this will be to create dynamic mass of nutrients level, and other soil parameters. In the time and space.
The system for distance learning of farmers will be implemented.
Project homepage M1,
Process model M6,
Metadata Implementation M6,
GIS implementation M10,
Database implementation M12,
PF 3D tools implementation M12,
Annual evaluation report M12,
Mathematical tools implementation M15,
Internet data access M15,
Business plan preparation M15,
Distance learning system implementation M17,
Final evaluation report M18
Funding SchemeACM - Preparatory, accompanying and support measures
147 00 Praha 4
256 01 Benesov U Prahy
382 03 Kremze
784 01 Litovel
33078 San Vito Al Tagliamento