Identification of Thermokarst Objects from Satellite Graphical Data Using a Neural Network

Abstract

The paper presents the results of a numerical experiment on the identification of thermokarst objects formed as a result of climatic changes in the regions of the cryolithozone, based on satellite graphical data. An applied computer program has been developed designed to identify satellite graphical data implementing a three-layer neural network. The dependence of the object identification efficiency on various initial parameters of the neural network, such as the learning rate, the number of neurons in the hidden layer and the number of learning epochs, has been studied. The optimal values of the above parameters have been identified, providing the highest efficiency indicators of the neural network. The results obtained were compared with the data of other researchers.