ANALYSIS OF THE SPECTRAL PROPERTIES OF WHEAT GROWTH IN DIFFERENT VEGETATION PERIODS
Yerzhanova A. Kassymova A. Abdikerimova G. Abdimomynova M. Tashenova Z. Nurlybaeva E.
2021Technology Center
Eastern-European Journal of Enterprise Technologies
2021#6Issue 2-11496 - 102 pp.
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
atmospheric correction , cadastral number , Landsat-8 , multispectral images , range , spectral brightness coefficient , wavelength
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Department of Information Systems, L. N. Gumilyov Eurasian National University, Satpayev str., 2, Nur-Sultan, 010008, Kazakhstan
S. Seifullin Kazakh Agrotechnical University, Pobeda ave., 62, Nur-Sultan, 010000, Kazakhstan
Department of Information Systems, Zhangir Khan University, Zhugirkhan str., 51, Uralsk, 090009, Kazakhstan
Department of Information Systems, L. N. Gumilyov Eurasian National University, Satpayev str., 2, Nur-Sultan, 010008, Kazakhstan
Department of Informatics, Dulaty University, Suleimenova str., 7, Taraz, 080000, Kazakhstan
Department of Information Systems, T. K. Zhurgenov Kazak National Academy of Arts, Panfilova str., 127, Almaty, 050000, Kazakhstan
Department of Information Systems
S. Seifullin Kazakh Agrotechnical University
Department of Information Systems
Department of Information Systems
Department of Informatics
Department of Information Systems
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