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ANALYSIS OF THE SPECTRAL PROPERTIES OF WHEAT GROWTH IN DIFFERENT VEGETATION PERIODS

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dc.contributor.author Yerzhanova, Akbota
dc.contributor.author Kassymova, Akmaral
dc.contributor.author Abdikerimova, Gulzira
dc.contributor.author Abdimomynova, Manshuk
dc.contributor.author Tashenova, Zhuldyz
dc.contributor.author Nurlybaeva, Elmira
dc.date.accessioned 2024-09-19T09:13:16Z
dc.date.available 2024-09-19T09:13:16Z
dc.date.issued 2021
dc.identifier.citation Yerzhanova, A., Kassymova, A., Abdikerimova, G., Abdimomynova, M., Tashenova, Z., Nurlybaeva, E. (2021). Management of processes of technological transformation of food industry in the formation of sustainable development of agroecosystems. Eastern-European Journal of Enterprise Technologies, 6 (2 (114)), 96–102. doi: https://doi.org/10.15587/1729-4061.2021.249278 ru
dc.identifier.issn 1729-3774
dc.identifier.uri https://doi.org/10.15587/1729-4061.2021.249278
dc.identifier.uri http://rep.enu.kz/handle/enu/16657
dc.description.abstract The article presents a technique for studying space images based on the analysis of the spectral brightness coefficient (SBC) of space images of the earth’s surface. Recognition of plant species, soils, and territories using satellite images is an applied task that allows to implement many processes in agriculture and automate the activities of farmers and large farms. The main tool for analyzing satellite imagery data is the clustering of data that uniquely identifies the desired objects and changes associated with various reasons. Based on the data obtained in the course of experiments on obtaining numerical SBC values, the patterns of behavior of the processes of reflection of vegetation, factors that impede the normal growth of plants, and the proposed clustering of the spectral ranges of wave propagation, which can be used to determine the type of objects under consideration, are revealed. Recognition of these causes through the analysis of SBC satellite images will create an information system for monitoring the state of plants and events to eliminate negative causes. SBC data is divided into non-overlapping ranges, i.e. they form clusters reflecting the normal development of plant species and deviations associated with negative causes. If there are deviations, then there is an algorithm that determines the cause of the deviation and proposes an action plan to eliminate the defect. It should be noted that the distribution of the brightness spectra depends on the climatic and geographical conditions of the plant species and is unique for each region. This study refers to the Akmola region, where grain crops are grown. ru
dc.language.iso en ru
dc.publisher Eastern-European Journal of Enterprise Technologies ru
dc.relation.ispartofseries Volume 6, Issue 2-114;Pages 96 - 102
dc.subject atmospheric correction ru
dc.subject cadastral number ru
dc.subject Landsat-8 ru
dc.subject multispectral images ru
dc.subject range ru
dc.subject spectral brightness coefficient ru
dc.subject wavelength ru
dc.title ANALYSIS OF THE SPECTRAL PROPERTIES OF WHEAT GROWTH IN DIFFERENT VEGETATION PERIODS ru
dc.type Article ru


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