MULTICRITERIA SELECTION OF A METHOD FOR PROCESSING MULTISPECTRAL EARTH REMOTE SENSING DATA

Viacheslav Zelentsov; Yuriy Andrianov; Victor Mochalov

doi:10.5937/jaes0-47477

Viacheslav Zelentsov St. Petersburg Federal Research Center of the Russian Academy of Science, St. Petersburg, Russia
Yuriy Andrianov Volga State University of Technology, Yoshkar-Ola, Russia
Victor Mochalov St. Petersburg Federal Research Center of the Russian Academy of Science, St. Petersburg, Russia

DOI: https://doi.org/10.5937/jaes0-47477

Keywords: qualimetry of models and polymodel complexes, multi-criteria selection, natural and technical systems, Earth remote sensing data, sustainability of forest vegetation

Abstract

The article is devoted to the use of qualimetry methods for models and polymodel complexes in order to solve one of the relevant engineering problems - automation of selecting methods for calculating Earth remote sensing (ERS) data processing when analysing the state of complex natural and technical systems. The proposed approach was discussed using the example of choosing methods for calculating forest sustainability indicators. A typical situation was considered when alternative methods and models can be applied at each stage of data processing. The essence of the proposed approach is to formulate and solve the task on multicriteria comparative analysis of processing methods based on a set of indicators, which include costs, required for implementation one or another method, efficiency, which refers to calculation duration of the analysed sustainability indicator, and an indicator reflecting the quality of the solution - accuracy of calculations result. The solution algorithm was illustrated within an example of choosing the method for assessing consequences of the forest fire. The selection results were presented in the form of a table, which allows the user to evaluate losses and gains in the values of partial indicators when moving from applying one method to another. The proposed algorithmization of the selection task determines possibility for its automation and, thereby, simplifying application of complex methods for processing ERS data for the end user. In addition, the possibilities and degree of validity for scaling the results of processing ERS data from individual areas to large forest areas are expanding.

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