Journal of Siberian Federal University. Engineering & Technologies / Software Development for Assessment of the Vegetation Cover Changes Using the Earth Remote Sensing Data

Full text (.pdf)
Issue
Journal of Siberian Federal University. Engineering & Technologies. 2018 11 (8)
Authors
Kovalev, Anton V.; Markov, Nikolay G.; Tokareva, Olga S.
Contact information
Kovalev, Anton V.: National Research Tomsk Polytechnic University 30 Lenin, Tomsk, 634050, Russia; ; Markov, Nikolay G.: National Research Tomsk Polytechnic University 30 Lenin, Tomsk, 634050, Russia; ; Tokareva, Olga S.: National Research Tomsk Polytechnic University 30 Lenin, Tomsk, 634050, Russia;
Keywords
Earth remote sensing; cellular automata; modeling and forecast of landscape changes; space images
Abstract

The article presents the results of software development for predictive maps modeling of the earth’s surface processes based on time-varying satellite data using the probabilistic and spatial characteristics of various types of the earth’s surface in the image. The analysis of existing methods for the assessment and modeling of the state of landscapes of various territories using satellite Earth monitoring data is presented. The review of existing systems of the earth’s surface dynamics analysis and their main advantages and disadvantages is given. The cellular automata method was used to implement the forecast. This method allows complex systems modeling using a simple set of rules and is the most convenient and accurate method for working with a space images. Algorithms and basic modeling parameters for using this method are described. The developed software makes it possible to forecast the state of the surface of the territories under consideration based on a series of time-varying data, and also to specify various modeling parameters in order to improve the accuracy of forecast maps. The results of the developed software testing with MODIS and Landsat data are presented, the accuracy of the forecast and the influence of simulation parameters on the result were estimated

Pages
922-933
Paper at repository of SibFU
https://elib.sfu-kras.ru/handle/2311/109195

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