Spectral-spatial neural network classification of hyperspectral vegetation images

Abstract

The paper presents the results of a study of the method of classification of vegetation types based on hyperspectral survey data. A hyperspectrometer based on the Offner scheme was used as a shooting equipment. The spatial-spectral architecture of a convolutional neural network is used as a classifier. The experiments performed show the effectiveness of the proposed approach for the classification of vegetation types.