MONITORING OF IN-FIELD VARIABILITY FOR SITE SPECIFIC CROP MANAGEMENT THROUGH OPEN GEOSPATIAL INFORMATION
- 1Masaryk University, Faculty of Science, Department of Geography, Kotlářská 2, 61137 Brno, Czech Republic
- 2Mendel University, Faculty of Agronomy, Department of Agrosystems and Bioclimatology, Brno, Czech Republic
- 3Baltic Open Solutions Center, Krišjāņa Barona iela 32-7, Rīga, Latvia
- 4Wirelessinfo, Cholinská 19, Litovel, Czech Republic
Keywords: satellite images, location-based services, environmental monitoring, open data, cloud computing
Abstract. The agricultural sector is in a unique position due to its strategic importance around the world. It is crucial for both citizens (consumers) and the economy (both regional and global), which, ideally, should ensure that the whole sector is a network of interacting organisations. It is important to develop new tools, management methods, and applications to improve the management and logistic operations of agricultural producers (farms) and agricultural service providers. From a geospatial perspective, this involves identifying cost optimization pathways, reducing transport, reducing environmental loads, and improving the energy balance, while maintaining production levels, etc.
This paper describes the benefits of, and open issues arising from, the development of the Open Farm Management Information System. Emphasis is placed on descriptions of available remote sensing and other geospatial data, and their harmonization, processing, and presentation to users. At the same time, the FOODIE platform also offers a novel approach of yield potential estimations. Validation for one farm demonstrated 70% successful rate when comparing yield results at a farm counting 1’284 hectares on one hand and results of a theoretical model of yield potential on the other hand. The presented Open Farm Management Information System has already been successfully registered under Phase 8 of the Global Earth Observation System of Systems (GEOSS) Architecture Implementation Pilot in order to support the wide variety of demands that are primarily aimed at agriculture and water pollution monitoring by means of remote sensing.