Article information

2022 , Volume 27, ¹ 3, p.95-111

Mamash E.A., Pestunov I.A., Sinyavskiy Y.N.

Analysis of patterns in the distribution of the temperature fields for large industrial cities of Siberia according to Landsat-8 data

Currently, one of the most rapidly developing and popular directions in remote sensing data processing and application is the analysis of longwave infrared (8–15 𝜇m) data. These data are widely used to analyze the underlying surface temperature (LST) for both natural and urban areas. Analysis of temperature fields of large cities allows identifying the thermal anomalies, its sources, intensity and character of distribution, defining the boundaries of surface urban heat island, and revealing patterns in temperature distribution within the city territory. It is important for rational planning and development of urban infrastructure, prevention and resolving of environmental problems, and creating a comfortable area for living.

This paper addresses the estimation and analysis of the temperature field of the territories of major industrial Siberian cities by satellite data. The temperature maps of urban areas of Barnaul, Kemerovo, Krasnoyarsk, Novosibirsk, and Omsk for the snow-free period of 2013–2021 were constructed from Landsat-8 multitemporal data with Google Earth Engine system. The resulting maps allow us to identify patterns in the distribution of temperature fields, which, in turn, could provide information for evaluating the industrial development of cities, the degree of urbanization and the ecological state of the territory. An approach to qualitative assessment of the spatial differentiation of urban green areas, characterizing the level of comfort of the living and recreation environment, based on the analysis of histograms constructed by multi-year Landsat-8 LST data, is proposed.

The analysis of constructed histograms showed the fundamental opportunity of its use for the integral evaluation of the urban environment comfort indices. For Siberian cities, the strong correlation between the Landsat-8 LST and the NDBI building index is also confirmed, which agrees with the results of different authors for other cities. In addition, the value of Landsat-8 LST data can be used as an additional informative feature for the classification of urban areas.

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Keywords: underlying surface temperature, LST, Landsat-8, heat island, Google Earth Engine, major Siberian cities

doi: 10.25743/ICT.2022.27.3.008

Author(s):
Mamash Elena Alexandrovna
PhD.
Position: Senior Research Scientist
Office: Institute of Computational Technologies of SB RAS
Address: 630090, Russia, Novosibirsk, prospect Akademika Lavrentjeva, 6
Phone Office: (383) 330 78 26
E-mail: elenamamash@gmail.com
SPIN-code: 3961-1369

Pestunov Igor Alekseevich
PhD. , Associate Professor
Position: Leading research officer
Office: Federal Research Center for Information and Computational Technologies
Address: 630090, Russia, Novosibirsk, Ac. Lavrentiev ave., 6
Phone Office: (383) 334-91-55
E-mail: pestunov@ict.nsc.ru
SPIN-code: 9159-3765

Sinyavskiy Yuriy Nikolaevich
Position: Research Scientist
Office: Institute of Computational Technologies SB RAS
Address: 630090, Russia, Novosibirsk, Ac. Lavrentiev ave., 6
E-mail: yorikmail@gmail.com

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Bibliography link:
Mamash E.A., Pestunov I.A., Sinyavskiy Y.N. Analysis of patterns in the distribution of the temperature fields for large industrial cities of Siberia according to Landsat-8 data // Computational technologies. 2022. V. 27. ¹ 3. P. 95-111
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