Based on GIS technologies, a decision support system (GIDSS) has been developed to remediate agricultural lands in the Bryansk region (Russia) contaminated by 137Cs after the accident at the Chernobyl nuclear power plant. GIDSS is a multilevel system consisting of basic, information and computational layers. GIDSS allows justifying a targeted approach for the remediation of agricultural lands belonging to agricultural enterprises for the production that meets the established radiological requirements for the content of radionuclides. Evaluation of the effectiveness of alternative remediation technologies and the selection of optimal measures were carried out at the level of elementary plots using radiological criteria. The introduction of GIDSS will enable agricultural producers in the south-western districts of the Bryansk region to conduct radiation-safe agro-industrial production in radioactively contaminated areas, which will help improve the socio-economic situation of the region and return it to normal living conditions.
In this paper, introduction presents the problem statement. The second chapter gives a brief description of the Smart Farming system. The third chapter provides an overview of ontologies. The fourth chapter describes implementation of the knowledge base in the Smart...
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the...
Climate smart agriculture (CSA) technologies are innovations meant to reduce the risks in agricultural production among smallholder farmers. Among the factors that influence farmer adoption of agricultural technologies are farmers' risk attitudes and household livelihood diversification. This study, focused on...
The spatial and temporal variability of soil properties (fluid composition, structure, and water content) and hydrogeological properties employed for sustainable precision agriculture can be obtained from geoelectrical resistivity methods. For sustainable precision agricultural practices, site-specific information is paramount, especially during...
The digital transformation in agriculture introduces new challenges in terms of data, knowledge and technology adoption due to critical interoperability issues, and also challenges regarding the identification of the most suitable data sources to be exploited and the information models...
