Urban climate and registration of thermal anomalies of territories using satellite imagery

A.D. Biryukov; V.D. Olenkov; A.О. Kolmogorova

doi:10.1051/e3sconf/202126608008

All issues

Volume 266 (2021)

E3S Web Conf., 266 (2021) 08008

References

Open Access

Issue		E3S Web Conf. Volume 266, 2021 Topical Issues of Rational Use of Natural Resources 2021


Article Number		08008
Number of page(s)		16
Section		Sustainable Development of Regions and Environmental Safety
DOI		https://doi.org/10.1051/e3sconf/202126608008
Published online		04 June 2021

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[1] N.E. Brusova, I.N. Kuznetsova, M.I. Nakhaev, Thermal agitation of a megalopolis against the background of regional heterogeneity of the surface temperature field. Proceedings of the Hydrometeorological Center of Russia. 365: 22–34. (2017). [Google Scholar]

[2] V.D. Olenkov, Urban safety (Moscow: LKI Publ., 2007). [Google Scholar]

[3] K. Thome, J. D'Amico, C. Hugon, Inter-comparison of Terra ASTER, MISR, and MODIS, and Landsat-7 ETM+, IEEE International Symposium on Geoscience and Remote Sensing, Denver, CO, 1772–1775 (2006). [Google Scholar]

[4] L.T. Matveev, E.A. Vershel, J.L. Matveev, Influence of anthropogenic factors on the climate of cities. Scientific notes of the RSUH, 17: 41–50 (2011). [Google Scholar]

[5] M.A. Lokoshchenko, I.A. Korneva, A.V. Kochin, et al., On the altitude of the urban heat island over Moscow. Reports of the Russian Academy of Sciences. 466(2): 213–217 (2016). [Google Scholar]

[6] A. Gosteva, A. Matuzko, O. Yakubailik, Remote methods in studying the temperature of the earth's surface in cities (on the example of the city of Krasnoyarsk, Russia). Proceedings of the International conference “InterCarto. InterGIS”, 24: 195–205 (2018). [Google Scholar]

[7] L. Klok, S. Zwart, H. Verhagen, E. Mauri, The surface heat island of Rotterdam and its relationship with urban surface characteristics. Resources, Conservation and Recy- cling, 64: 23–29 (2012). [Google Scholar]

[8] A.M. Kostin, S.A. Belov, I.V. Malev, Peculiar Features of Influence of the Modern Ecological State of the City of Chelyabinsk on Economic and Architectural Indexes of the Territory, Procedia Engineering, 150: 2025–2030 (2016). [Google Scholar]

[9] V.D. Olenkov, N.T. Tazeev, Urban Planning Problems of Agglomerations IOP Conference Series: Materials Science and Engineering, 262 (1): 012155 (2017). [Google Scholar]

[10] G. Grigoras, B. Uritescu, Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data. Annals of Valahia University of Targoviste. Geographical Series, 18(1): 14–22 (2018). [Google Scholar]

[11] E.A. Baldina, M.J. Grishchenko, Mapping of thermal anomalies of Moscow according to different seasonal thermal images. Geoecological Problems of New Moscow. 70–76 (2013) [Google Scholar]

[12] E.A. Baldina, M.J. Grishchenko, J.V. Fedorkova, Comparison of radiometric features of ETM + and ASTER shooting systems in thermal channels http://www.geogr.msu.ru/cafedra/karta/materials/heatimg/files/3/sravneniesnimkovasterietm.htm (2012). [Google Scholar]

[13] LP DAAC Change in Status Alert for the ASTER SWIR detector https://lpdaac.usgs.gov/news/change-status-alert-aster-swir-detector/ (2009) [Google Scholar]

[14] J.-C. Padró, F.-J. Muňoz, L. Avila, L. Pesquer, X. Pons, Radiometric Correction of Landsat-8 and Sentinel-2A Scenes Using Drone Imagery in Synergy with Field Spec-troradiometry. Remote Sensing. 10(11), 1687 (2018). [Google Scholar]

[15] C. Song, C.E. Woodcock, K.C. Seto, M.P. Lenney, S.A. Macomber, Classification and change detection using Landsat TM data: when and how to correct atmospheric effects. Remote Sensing of Environment, 75(2): 230–244 (2001). [Google Scholar]

[16] USGS Landsat Missions Using the USGS Landsat Level-1 Data Product https://www.usgs.gov/land-resources/nli/landsat/using-usgs-landsat-level-1-data-product (2019) [Google Scholar]

[17] National Physical Laboratory What is emissivity and why is it important? https://www.npl.co.uk/resources/q-a/why-is-emissivity-important (2020) [Google Scholar]

[18] GIS-Lab and authors. NDVI - Theory and Practice https://gis-lab.info/qa/ndvi.html (2002-2018). [Google Scholar]

[19] L. Zhao-Liang, W. Hua, W. Ning, Q. Shi, A. S. José, W. Zhengming, T. Bo-Hui, Y. Guangjian, Land surface emissivity retrieval from satellite data, International Journal of Remote Sensing, 34(9-10), 3084–3127 (2013). [Google Scholar]

[20] Congedo, Luca. Semi-Automatic Classification Plugin User Manual. Technical Report (2016). [Google Scholar]

[21] GIS-Lab and authors. Estimating the surface temperature from a Landsat-8 image using the Land Surface Temperature QGIS Plugin https://wiki.gis-lab.info/w/OneHKaTCMncparvpbinoBepxHOCTnm3chmmku-Landsat-8-npn-noMomn-Land-Sur-face-Temperature-QGIS-Plugin (2018). [Google Scholar]

[22] H. Szu, I. Kopriva, Comparison of Lagrange constrained neural network with traditional ICA methods. Proceedings of the 2002 International Joint Conference on Neural Networks, 1, 466–471 (2002). [Google Scholar]