FATIMA Czech pilot

In FATIMA project, a pilot site in Czechia was established to demonstrate how precision agriculture may serve for optimizing crop yields as well as for protection of water quality, since the pilot is located in Czech largest drinking water reservoir catchment. The pilot site Dehtáře is situated in the south-west Bohemo-Moravian Highland. The site contains tile drainage and is of very heterogeneous soil conditions; from shallow, light and stony Haplic Cambisols to heavy Haplic Gleysols, with profoundly different water regimes. For the field trial (spring barley in 2016), crop yield potential was determined from crop statuses as captured by satellite images) eight years back, assessed by Enhanced Vegetation Index. Based on this, as well as on a detailed soil survey and repeated soil sampling, variable fertilizer application zones (70 – 120%) were delineated and mineral fertilizers distributed accordingly with GPS operated spreader three times from late April to late May. The rest of the site was fertilized uniformly. Soil water regime (soil moisture, soil water potential) was monitored continuously on eight spots and real-time broadcasted by wireless sensor network to WEB GIS interface via SensLog solution, adopted from FOODIE project. In the same spots, soil water was sampled by gravitational soil lysimeters. Precise harvest showed a general agreement with the delineated application zones and yield potential, however, some ambiguities were revealed, most probably due to changeable soil water regime, as documented by the sensors, as well as due to variable soil chemical properties (low soil pH). Nevertheless, precisely applied fertilizer doses in the application zones brought about 10% higher crop yields with simultaneous better N crop efficiency. Soil water quality samples confirmed that heterogeneous doses of fertilizer in correctly delineated zones is a promising approach for improvement of groundwater quality especially in shallow soils with low water and nutrient retention abilit

Big Data in Agriculture – From FOODIE towards data bio

What’s the role of Big Data in the farming ecosystem? Farmers need to measure and understand the impact of a huge amount and variety of data which drive overall quality and yield of their fields. Among those are local weather data, GPS data, ortophotos, satellite imagery, soil specifics, soil conductivity, seed, fertilizer and crop protectant specifications and many more. Being able to leverage this data for running long and short term simulations in response to “events” like changed weather, market need or other parameters is indispensable for farmers in terms of maximizing their profits. IoT (Internet of Technology) including field sensors and machinery monitoring. The experimentation in FarmTelemetry project demonstrates that one average Czech farm (i.e. around 1’000 hectares) could generate daily 20 MegaBytes of data. This could be only for Czech Republic something between 30 and 50 GB per one day. We may easily reach Terabytes of data a day from agricultural basic monitoring by sensors in Europe. Together with satellite data agriculture will need to manage extremely large amount of data. On one side there is growing whole ecosystem with a strong need to secure Big Data from different repositories and heterogeneous sources. In some cases, sharing of data could be common interest, but on other side, there are also different interests and data could help to one part of value chain to take bigger part of profit. From this reason Big data are sensitive topics and trusting of producers about data security is essential. The producers of seeds and chemicals want to maximize their business with farmers. Our team stated implementation of Big Data technologies in frame of European 7FP project FOODIE. This work currently the work continue as part of DataBio project

Benefits of Using Traffic Volumes Described on Examples in the Open Transport Net Project Pilot Regions

The paper describes the goals of the Open Transport Net project in the pilot regions for regional development and the motivation to use traffic volumes in order to reach the project objectives. In the introduction, a short overview of the Open Transport Net project is provided. It is followed by descriptions of the identified problems in the pilot regions and incentives to use traffic volumes for achieving good quality results. The basics of traffic volumes as well as their visualisation are further described and demonstrated including several examples

MONITORING OF IN-FIELD VARIABILITY FOR SITE SPECIFIC CROP MANAGEMENT THROUGH OPEN GEOSPATIAL INFORMATION

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