Библиографическое описание:Variation in Spectral Indices in the Context of Natural and Technogenic Transformations of Landscapes : научное издание / N. D. Yakimov, E. I. Ponomarev, T. V. Ponomareva. - Текст : непосредственный // Cosmic Research. - 2025. - Т. 63, № S1. -S282-S288. - The work was supported by a grant of the Russian Science Foundation (no. 23-14-20007, https://rscf.ru/project/23-14-20007/) and the Krasnoyarsk Regional Science Foundation. Satellite data were processed at the Center for Collective Use of the Krasnoyarsk Scientific Center, Siberian Branch, Russian Academy of Sciences (KSC SB RAS), within the framework of state assignment no. FWES-2024-0023 (Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences) and FWES-2024-0027 (FRC KSC SB RAS). - ISSN 0010-9525. - ISSN 1608-3075, DOI 10.1134/S0010952525602208.
Аннотация:We investigated the variability of spectral indices calculated from <i>Landsat</i> data for areas with signs of natural and technogenic transformations of vegetation and ground cover. An analysis of relative deviation of the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) indicators from the background values due to changes in the condition of the underlying surface covers was carried out. A classification of significant type-factors of transformation was produced for the territory of the Olimpiada mining and processing plant (North Yenisei Region, Krasnoyarsk krai), which is characterized by signs of natural (wildfires) and man-made (mining) impacts for the period of 2000–2023. The degree of transformation of vegetation and ground cover under the influence of both natural and technogenic factors was described in terms of relative anomalies of the spectral indices ΔLST and ΔNDVI, calculated as the average for each cell of a regular network in the study area. A linear relationship was recorded between the anomalies of the ΔLST and ΔNDVI and the degree of natural/technogenic transformation of the vegetation and ground cover with a reliability of 0.31–0.81 for the thermal anomalies ΔLST and at the level of 0.28–0.85 for the vegetation anomalies ΔNDVI. It has been established that the degree of generalization of the initial data, depending on the size of the regular network cells used, does not affect critically the result of analyzing the state of the territory using the proposed method.
Держатель оригинала документа:Krasnoyarsk Science Center, Siberian Branch, Russian Academy of Sciences, Siberian Federal University, Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences
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