Journal of Siberian Federal University. Engineering & Technologies / Classification of Agricultural Crops from Middle-Resolution Satellite Images Using Gaussian Processes Based Method

Full text (.pdf)
Issue
Journal of Siberian Federal University. Engineering & Technologies. 2018 11 (8)
Authors
Safonova, Anastasiia N.; Dmitriev, Yegor V.
Contact information
Safonova, Anastasiia N.: Siberian Federal University 79 Svobodny, Krasnoyarsk, 660041, Russia; ; Dmitriev, Yegor V.: Institute of Numerical Mathematics RAS 8 Gubkina Str., Moscow, 119333, Russia; M.V. Lomonosov Moscow State University 1 Leninskiye Gory, Moscow, 119991, Russia;
Keywords
Gaussian processes; classification; regression; agricultural crops; Landsat images; remote sensing; NDVI; NDVI
Abstract

Agricultural applications of the Gaussian process (GP) based techniques is considered. A method of classifying crops from multi-temporal Landsat 8 satellite imagery is proposed. The method uses the model of spectral features based on GP regression with constant expectation and square exponential covariance functions. Main steps of the classification procedure and examples of recognition of culture species are represented. The ground based data are used for quantitative validation of the proposed classification method. The highest overall classification accuracy in three classes of crops is 77.78%

Pages
909-921
Paper at repository of SibFU
https://elib.sfu-kras.ru/handle/2311/109194

Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).