Open AccessMethodology for automated classification of farmland based on Earth remote sensing data
Author(s) -
Oleslav Antamoshkin,
О. И. Антамошкина,
E. R. Bryukhanova,
Artem Stupin,
N. V. Kamenskaya
Publication year - 2022
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/981/3/032015
Subject(s) - remote sensing , satellite , geographic information system , agricultural land , field (mathematics) , geography , agriculture , sample (material) , earth remote sensing , earth observation , cartography , computer science , environmental science , engineering , mathematics , chemistry , archaeology , chromatography , aerospace engineering , pure mathematics , high resolution
The analysis of spectral characteristics from satellite images of the earth for different periods of the growing season is carried out. Using a geographic information system, a training sample was obtained for identifying agricultural land based on satellite monitoring data for the Krasnoyarsk region. The classification is carried out on the basis of spectral characteristics of agricultural land according to the data of remote sensing of the earth. Field studies were carried out to verify the classification results. Based on the results of the work, modules of a geographic information system were created, containing a cartographic database of agricultural land in the Sukhobuzimsky district of the Krasnoyarsk Territory.