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About the Authors
Mikhail Yu. Grishchenko
119991, Russia, Moscow, Leninskiye Gory, 1,
E-mail: m.gri@geogr.msu.ru
Lev S. Kalitka
119991, Russia, Moscow, Leninskiye Gory, 1,
E-mail: lev@kalitka.me
Abstract
Among all major cities of Russia Krasnodar is in the most mild and warm climatic conditions. In this regard, it is interesting to study the features of the seasonal variability of the Krasnodar thermal field, as well as the internal structure of the surface heat island, detected by thermal infrared satellite images. For this purpose, Landsat 8 multiseasonal thermal infrared satellite images (TIRS sensor), characterized by a spatial resolution of 100 m, were used. An unsupervised classification of the multitemporal image was performed. Out of the variants of the unsupervised classification results, an optimal one has been chosen. There were identified 13 classes of objects, different in seasonal variability of the intensity of thermal radiation, and forming the thermal structure of the analyzed territory. To choose the optimal variant of the unsupervised classification result, the difference coefficient was developed. Based on the selected result of the unsupervised classification, the Krasnodar thermal structure map was compiled. The information visualized on this map can be used to assess the ecological state of the urban area, in urban planning, in assessing the bioclimatic comfort of the urban environment. The general characteristic features of the Krasnodar thermal field are revealed. It stands out against the backdrop of the adjacent territories due to the fact that on the one hand, industrial zones have a great influence on it, forming large positive thermal anomalies in the area; on the other hand, a large urban area with low greenery with active heat absorption and heat radiation. Contribution to the thermal structure of the city is made by large recreational green zones, creating negative thermal anomalies.
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References
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For citation: Grishchenko M.Yu., Kalitka L.S. Studying the seasonal variability of thermal field of Krasnodar using Landsat 8 satellite imagery. InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: Moscow University Press, 2019. V. 25. Part 2. P. 101–111. DOI: 10.35595/2414-9179-2019-2-25-101-111 (in Russian)