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The modeling of the yielding capacity of winter cereals due to satellite monitoring data of agricultural lands in Ukraine

    Roman Stupen Affiliation
    ; Zoriana Ryzhok   Affiliation
    ; Nazar Stupen   Affiliation
    ; Oksana Stupen   Affiliation

Abstract

The paper reveals the method of work in the geoinformation system Crop Monitoring on the basis of satellite monitoring data on the example of comparison of two neighboring land uses outside Bortkiv village council of Zolochiv district of Lviv region. One has determined the size of the areas of crops of winter cereals and deduced the dependence between the index of the vegetative index NDVI and their yield capacity on the basis of the estimation of the state of land use by the processing of space information. One has suggested to take into account the value of NDVI when calculating the yield of winter cereals using mathematical modeling. The results obtained from the satellite monitoring data are proposed to be used for the planning of winter cerels yields, determining the area of their sowing and optimizing the harvesting time.

Keyword : geoinformation systems, satellite monitoring, vegetation index, yielding capacity, Cauchy method, agricultural land use

How to Cite
Stupen, R., Ryzhok, Z., Stupen, N., & Stupen, O. (2021). The modeling of the yielding capacity of winter cereals due to satellite monitoring data of agricultural lands in Ukraine. Geodesy and Cartography, 47(1), 1-9. https://doi.org/10.3846/gac.2021.11740
Published in Issue
Mar 31, 2021
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

An official website of the European Union. (2019). Monitoring Agricultural ResourceS (MARS). https://ec.europa.eu/jrc/en/mars

Babych, S. (1998). Methodical aspects of analytical processing of information in aerospace monitoring of sowing. System research and modeling in agriculture. Nyva.

Bidyuk, P., Terentiev, O., Prosyankina-Zharova, T., & Efendiev, V. (2017). Prediction modeling of nonlinear non-stationary processes in crop production using tools of SAS Enterprise Miner. Scientific news of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”: International Scientific and Technical Journal, 1(111), 24–36. https://doi.org/10.20535/1810-0546.2017.1.87423

Dovhyi, S. (2013). Environmental monitoring using NOAA satellite survey. National Aerospace University M.E., Zhukovsky “Kharkiv Aviation Institute”.

Dovhyi, S., Krasovskyi, H., Radchuk, V., & Trofymchuk, O. (2018). Geomodels in tasks of ecological and economic land estimations. Yuston.

Earth Observing System. (2019). Crop Monitoring. https://eos.com/products/crop-monitoring/

Kohan, S. (2011). Investigation of the dynamics of vegetation indices for the estimation of the state of crops based on IRS1D LISS-III data. Bulletin of Geodesy and Cartography, 4, 20–24.

Lialko, V., Sakhatskyi, O., & Zholobak, H. (2006). Features of prediction of gcereals yields according to multispectral data. In Multispectral methods of remote sensing of the earth in environmental problems (pp. 276–191). Scientific Thought.

Statistical Office in Lviv region. (2019). Agriculture, forestry and fisheries. http://database.ukrcensus.gov.ua/statbank_lviv/Database/04SILGOSP/databasetree_uk.asp

Stupen, M., Stupen, N., Ryzhok, Z., & Stupen, O. (2020). Application of satellite monitoring data for winter cereals growing in the Lviv region. Geomatics and Environmental Engineering, 14(4), 69–80. https://doi.org/10.7494/geom.2020.14.4.69

Stupen, N., Bohira, M., Stupen, O., & Ryzhok Z. (2019a). Prospects of the application of European practice on efficient agricultural lands use in Ukraine. Scientific Papers Series “Management, Economic Engineering in Agriculture and Rural Development”, 19(3), 563–569. https://doi.org/10.31734/agrarecon2019.03.090

Stupen, N., Stupen, M., & Stupen, O. (2018). Electronic agricultural maps formation on the basis of GIS and earth remote sensing. Scientific Papers Series “Management, Economic Engineering in Agriculture and Rural Development”, 18(4), 347–353.

Stupen, R., Stupen, M., Ryzhok, Z., & Stuppen, O. (2019b). Modeling of the effective functioning of the agricultural lands market in Ukraine. Geodesy and Cartography, 45(2), 96–101. https://doi.org/10.3846/gac.2019.7438

Tarariko, O., Sirotenko, O., Ilienko, T., & Kuchma, T. (2019). Agro-environmental satellite monitoring. Agrarian Science.

United States Department of Agriculture. Foreign Agricultural Service. (2019). International Production Assessment Division. https://ipad.fas.usda.gov

Voitenko, A. (2005). Mathematical processing of geodetic measurements. Least-squares method: teaching manual. Kyiv National University of Construction and Architecture.

Zatserkovnyi, V., Kryvoborets, S., & Serhienko, V. (2011). The use of GIS and remote sensing for agricultural land monitoring. Chernihiv Scientific Journal of Chernihiv State Institute of Economics and Management: Engineering and Nature, 2, 40–48.