Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование
DETECTION of FERTILE SOILS BASED on SATELLITE IMAGERY PROCESSING. / Grishkin, Valery; Zhivulin, Evgeniy; Khokhriakova, Anastasiia; Karimov, Sardor.
в: CEUR Workshop Proceedings, Том 3041, 2021, стр. 251-255.Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование
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TY - JOUR
T1 - DETECTION of FERTILE SOILS BASED on SATELLITE IMAGERY PROCESSING
AU - Grishkin, Valery
AU - Zhivulin, Evgeniy
AU - Khokhriakova, Anastasiia
AU - Karimov, Sardor
N1 - Conference code: 9
PY - 2021
Y1 - 2021
N2 - The paper proposes a method for detecting fertile soils based on the processing of satellite images. As a result of its application, a map of the location of fertile and infertile soils for a given region of the earth's surface is formed and the corresponding areas are calculated. The method for detecting fertile soils is based on the fact that fertile soil includes areas covered with vegetation in the spring-summer period. Therefore, by measuring the spectral characteristics of these areas in the late autumn period, when there is no vegetation on them, it is possible to obtain objective parameters of fertile soils. For detection, a number of classifiers are being built that recognize two classes - fertile soil and sand, which is especially important when monitoring areas prone to desertification. The feature vector used for classification is a set of indices similar to the well-known NDVI index. This set of indices is calculated for each pixel of the image by its values in different spectral channels. Classifiers are implemented using CUDA parallel computing technology on a GPU. Based on the results of the experimental study, a classifier is selected that has shown the best characteristics of the recognition quality.
AB - The paper proposes a method for detecting fertile soils based on the processing of satellite images. As a result of its application, a map of the location of fertile and infertile soils for a given region of the earth's surface is formed and the corresponding areas are calculated. The method for detecting fertile soils is based on the fact that fertile soil includes areas covered with vegetation in the spring-summer period. Therefore, by measuring the spectral characteristics of these areas in the late autumn period, when there is no vegetation on them, it is possible to obtain objective parameters of fertile soils. For detection, a number of classifiers are being built that recognize two classes - fertile soil and sand, which is especially important when monitoring areas prone to desertification. The feature vector used for classification is a set of indices similar to the well-known NDVI index. This set of indices is calculated for each pixel of the image by its values in different spectral channels. Classifiers are implemented using CUDA parallel computing technology on a GPU. Based on the results of the experimental study, a classifier is selected that has shown the best characteristics of the recognition quality.
KW - Cene classification
KW - Multispectral images
KW - Satellite image segmentation
UR - http://www.scopus.com/inward/record.url?scp=85121656817&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85121656817
VL - 3041
SP - 251
EP - 255
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
SN - 1613-0073
T2 - 9th International Conference "Distributed Computing and Grid Technologies in Science and Education", GRID 2021
Y2 - 5 July 2021 through 9 July 2021
ER -
ID: 91657138