Zemleustrìj, Kadastr ì Monìtorìng Zemelʹ (Nov 2024)
Composition and sources of information and analytical support for agricultural land valuation
Abstract
It is determined that in order to form a model for agricultural land valuation, it is necessary to use modern methods and tools, in particular, remote sensing, machine learning and artificial intelligence, big data analysis, geographic information systems (GIS), and agroscouting. It is established that the composition and sources of information and analytical support for such a model are crucial. We have determined that among the factors affecting the price and value of agricultural land, we should consider such indicators as environmental sustainability, crop yields, infrastructure development, cultivation technologies, production organisation, logistics, etc. The analysis of these factors and the results of the studies conducted indicate the need to use a large amount of data to ensure an accurate valuation of agricultural land. Taking into account these factors and the indicators presented in the study will make the assessment more comprehensive and objective, which, in turn, will facilitate informed decision-making in the field of land relations. It is established that the data available in the state registers do not allow for an objective determination of the value of agricultural land plots. It is also noted that the sources of information for obtaining quantitative and qualitative indicators should ensure their relevance, completeness, reliability and timeliness. The author provides a dynamic list of geoportals that are recommended to be used to obtain such information. Key words: assessment of agricultural land, land market, geographic information systems, remote sensing, crop yields, environmental sustainability, soil fertility, soil productivity for crops
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