Geospatial database for digitalization of agriculture of the Krasnoyarsk territory
URI (for links/citations):
https://iopscience.iop.org/article/10.1088/1755-1315/315/3/032022https://elib.sfu-kras.ru/handle/2311/128456
Author:
Ерунова, Марина Геннадьевна
Шпедт, Александр Артурович
Трубников, Юрий Николаевич
Якубайлик, Олег Эдуардович
Corporate Contributor:
Институт фундаментальной биологии и биотехнологии
Кафедра водных и наземных экосистем
Date:
2019Journal Name:
AGRITEH IOP. Conf. Series: Earth and Environmental Science (2019) 032022.Journal Quartile in Scopus:
без квартиляJournal Quartile in Web of Science:
без квартиляBibliographic Citation:
Ерунова, Марина Геннадьевна. Geospatial database for digitalization of agriculture of the Krasnoyarsk territory [Текст] / Марина Геннадьевна Ерунова, Александр Артурович Шпедт, Юрий Николаевич Трубников, Олег Эдуардович Якубайлик // AGRITEH IOP. Conf. Series: Earth and Environmental Science (2019) 032022.. — 2019. — Т. 315.Abstract:
The experience of implementation of GIS and web technologies for regional
agriculture of the Krasnoyarsk territory is considered. The experimental agricultural enterprise
"Minino", located near the city of Krasnoyarsk, was chosen as a pilot project. For this agricultural
enterprise, the comprehensive digital model using geographic information systems, remote
sensing and web mapping data processing techniques and software is created. A geospatial
database, which contains relevant and archival information about agricultural fields, varieties,
crops, soil, particle size distribution, soil-forming rocks, terrain features, has been developed. A
series of technological digital maps and cartograms have been created in which information on
crop rotations and cultivated crops is concentrated. Archives of available multispectral satellite
data of high spatial resolution on the considered territory are analyzed. As a result, a multi-layer
electronic map of the agricultural enterprise was created, which contains all available
information and can be used for modeling and forecasting crop yields, agricultural planning. The
developed methods and software and technological solutions can become a methodological basis
for a new generation of information and analytical systems and technologies to support
management decisions in the agricultural sector.