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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 5, pp. 176-193

Monitoring and prediction of land cover dynamics in the Middle Volga using satellite data with QGIS MOLUSCE

O.N. Vorobyev 1 , E.A. Kurbanov 1 , J. Sha 2 , S.A. Lezhnin 1 , J. Wang 3 , D.M. Dergunov 1 
1 Volga State University of Technology, Yoshkar-Ola, Russia
2 College of Geography, Fujian Normal University, Fuzhou, China
3 Faculty of Geography, Yunnan Normal University, Kunming, China
Accepted: 26.09.2023
DOI: 10.21046/2070-7401-2023-20-5-176-193
Operational remote monitoring and land cover models are essential components for decision making on how to manage territories in a sustainable way. In this research, a predictive analysis of the spatio-temporal dynamics for seven land cover classes in the Middle Volga region was carried out until 2041 with the use of local thematic maps and Landsat images acquired in 2001–2021. The dynamics of these classes were modelled using the cellular automata and artificial neural network (CA-ANN) methods with the MOLUSCE (Modules for Land-Use Change Simulation) plugin in the Quantum GIS software, subject to the trends in land and forest management over the past 20 years, as well as natural disturbances in the study region. The intensity and probability of spatio-temporal transitions between the examined classes of land cover have been analysed over the simulated time period. As a result, a set of thematic maps was created in ArcGIS and matrices for the transition probability and intensity of changes in the land cover of the Middle Volga region. The predictive spatiotemporal analysis made it possible to determine future trends in dynamics of land cover until 2041. The research findings indicate that the majority of the land cover classes will have changes in area between 2021–2041. This will have an impact on the areas of the Russian Federation located in the Middle Volga region, particularly Republic of Mari El, Kirov and Nizhny Novgorod Regions, all of which have extensive forested areas. According to the predictive analysis, the study area’s forest cover might increase by 23.8 % between 2001 and 2041. The “young forest” class, whose annual increase in area may equal 1.6 % each year, serves as a good example of the maximum intensity of changes until 2041. As much as 0.31 million hectares of coniferous plantations can be converted to mixed forest, while 0.357 million hectares of coniferous plantations can be converted to deciduous forest. The findings may be used in predictive monitoring of land cover using satellite images, taking into account other variables such as changing climate and socioeconomic activities at the regional and local levels.
Keywords: LUCC, CA-ANN, Middle Volga, forest cover, Landsat, MOLUSCE
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