Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts)

The relevance of the study lies in the need for a scientific search for the possibilities of using new types of Big data in studies of the population vulnerability to solve practical problems of improving the safety of urban spaces from natural and man-made hazards. The object of the study is the ad...

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Published in:GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY
Main Authors: Roman A. Babkin, Svetlana V. Badina, Alexander N. Bereznyatsky
Format: Article in Journal/Newspaper
Language:English
Published: Russian Geographical Society 2023
Subjects:
Online Access:https://ges.rgo.ru/jour/article/view/2718
https://doi.org/10.24057/2071-9388-2022-116
id ftjges:oai:oai.gesj.elpub.ru:article/2718
record_format openpolar
institution Open Polar
collection Geography, Environment, Sustainability (E-Journal)
op_collection_id ftjges
language English
topic time-geography
vulnerability of the urban population
dynamic clustering
typology of urban districts
Moscow
intracity population mobility
social time
spellingShingle time-geography
vulnerability of the urban population
dynamic clustering
typology of urban districts
Moscow
intracity population mobility
social time
Roman A. Babkin
Svetlana V. Badina
Alexander N. Bereznyatsky
Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts)
topic_facet time-geography
vulnerability of the urban population
dynamic clustering
typology of urban districts
Moscow
intracity population mobility
social time
description The relevance of the study lies in the need for a scientific search for the possibilities of using new types of Big data in studies of the population vulnerability to solve practical problems of improving the safety of urban spaces from natural and man-made hazards. The object of the study is the administrative districts of Moscow; the subject is the temporal patterns of vulnerability of their population to potential natural and man-made hazards. The research question of the study is to develop a typology of Moscow districts and further assess this sustainability in terms of the population vulnerability to natural and man-made hazards. To achieve this research question, a set of tasks was solved: 1. Processing of the mobile operators’ data array and further construction of a continuous graph of the Moscow population dynamics in 2019 (with a time cycle of 30 minutes, over 36 million measurements in more than 7 thousand time slices); 2. Empirical justification of natural temporal boundaries of daily, weekly, seasonal cycles of population dynamics in Moscow districts; 3. Justification of key factors and parameters of urban population vulnerability; 4. Development and approbation of the dynamic clustering method of Moscow districts using selected variables and periods. The study is based on the impersonal mobile operators’ data on the locations of subscribers for 2019, provided by the Department of Information Technologies of the Moscow city. The method of dynamic cluster analysis is used. Four particular clusterings were obtained that characterize the “behavior” of the settlement system in the main intervals of social time (weekdays and weekends of the cold and warm seasons). Сluster stability matrix allows to identify which of the districts retain their properties during the period under review, and which are characterized by instability of considered indicators of population vulnerability. Depending on the stability of the position of the districts in a particular cluster, “stable”, “conditionally stable” and ...
format Article in Journal/Newspaper
author Roman A. Babkin
Svetlana V. Badina
Alexander N. Bereznyatsky
author_facet Roman A. Babkin
Svetlana V. Badina
Alexander N. Bereznyatsky
author_sort Roman A. Babkin
title Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts)
title_short Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts)
title_full Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts)
title_fullStr Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts)
title_full_unstemmed Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts)
title_sort assessment of temporal variability in the level of population vulnerability to natural and man-made hazards (the case of moscow districts)
publisher Russian Geographical Society
publishDate 2023
url https://ges.rgo.ru/jour/article/view/2718
https://doi.org/10.24057/2071-9388-2022-116
genre Arctic
genre_facet Arctic
op_source GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY; Vol 15, No 4 (2022); 90-101
2542-1565
2071-9388
op_relation https://ges.rgo.ru/jour/article/view/2718/667
Ahas R., Aasa A., Yuan Y., Raubal M., Smoreda Z., Liu Y., Ziemlicki C., Tiru M., Zook M. (2015). Everyday Space–Time Geographies: Using Mobile Phone-Based Sensor Data to Monitor Urban Activity in Harbin, Paris, and Tallinn. International Journal of Geographical Information Science, 29(11), 2017-2039.
Akimov V.A., Durnev R.A., Sokolov Y.I. (2009). Dangerous hydrometeorological phenomena on the territory of Russia. Moscow: FGU VNII GOChS (FC) (in Russian).
Aksha S.K., Juran L., Resler L.M., Zhang Y. (2019). An analysis of social vulnerability to natural hazards in Nepal using a modified social vulnerability index. International Journal of Disaster Risk Science, 10(1), 103-116.
Baburin V.L. (2011). Two-dimensional model of the territorial organization of society. Vestnik Moskovskogo Universiteta, Seriya 5: Geografiya, 1, 3-8 (in Russian).
Baburin V.L. and Baldina S.V. (2021). Forecasting of socio-economic damages from hazardous natural processes for the tourist cluster Resorts of the North Caucasus. Vestnik Moskovskogo Universiteta, Seriya 5: Geografiya, 2, 25-35 (in Russian).
Badina S.V. (2020). Prediction of socioeconomic risks in the cryolithic zone of the Russian Arctic in the context of upcoming climate changes. Studies on Russian Economic Development, 31(4), 396-403.
Badina S.V. and Babkin R.A. (2021). Assessment of Moscow population vulnerability to natural and technogenic hazards. InterCarto. InterGIS, 27(4), 184-201 (in Russian).
Badina S., Babkin R., Bereznyatsky A., Bobrovskiy R. (2022a). Spatial aspects of urban population vulnerability to natural and man-made hazards. City and Environment Interactions, 15, 100082.
Badina S., Babkin R., Mikhaylov A. (2022b). Approaches to assessing the vulnerability of large city population to natural and man-made hazards using mobile operators data (case study of moscow, russia). In: Wohlgemuth V., Naumann S., Behrens G., Arndt HK. (eds) Advances and New Trends in Environmental Informatics. ENVIROINFO 2021. Springer Cham, 171-186.
Baida S.E. (2019). Wave cycles of natural, human-made and social catastrophes. Civil Security Technology, vol. 16, No. 4 (62), 30–-36 (in Russian).
Cutter S.L., Boruff B.J., Shirley W.L. (2003). Social vulnerability to environmental hazards. Social science quarterly, 84(2), 242-261.
De Oliveira Mendes J.M. (2009). Social vulnerability indexes as planning tools: beyond the preparedness paradigm. Journal of Risk Research, 12(1), 43-58.
Flanagan B.E., Gregory E.W., Hallisey E.J., Heitgerd J.L., Lewis B. (2011). A social vulnerability index for disaster management. Journal of homeland security and emergency management, 8(1), article 3.
Froude M.J. and Petley D.N. (2018). Global fatal landslide occurrence from 2004 to 2016. Natural Hazards and Earth System Sciences, 18(8), 2161-2181.
Geyer H.S. and Kontuly T.A (1993). Theoretical foundation of the concept of differential urbanization. International Regional Science Review, 15(2), 157-177.
Gibbs J. (1963). The evolution of population concentration. Economic Geography, 2, 119-129.
Hägerstrand T. (1973). The domain of human geography. In: Chorley R.J. (ed.) Directions in Geography. London: Methuen.
Kaniewski D., Marriner N., Morhange C., Faivre S., Otto T., Van Campo E. (2016). Solar pacing of storm surges, coastal flooding and agricultural losses in the Central Mediterranean. Scientific reports, 6(1), 1-12.
Karachurina L.B. and Ivanova K.A. (2017). Migration of the elderly in Russia (according to the 2010 census). Regional studies, 3(57), 51-60 (in Russian).
Klaassen L.H. and Scimeni G. (1981). Theoretical issues in urban dynamics. In: L.H. Klaassen, W.T.M. Molle and J.H.P. Paelinck (ed.). Dynamics of Urban Development. Aldershot: Gower.
Knaub R.V., Ignateva A.V. (2022). The General Mechanism of the Origin of Natural Disasters in the Global Dimension. IOP Conference Series: Earth and Environmental Science, 988(2), 022068.
Kondratiev N.D. (2003). Large cycles of conjuncture and the theory of foreseeing. Selected Works. Voprosy Ekonomiki, 8, 153-154 (in Russian).
Luque-Espinar J.A., Mateos R.M., García-Moreno I., Pardo-Igúzquiza E., Herrera, G. (2017). Spectral analysis of climate cycles to predict rainfall induced landslides in the western Mediterranean (Majorca, Spain). Natural Hazards, 89(3), 985-1007.
Makhrova A.G. and Babkin R.A. (2018). Analysis of pulsations of the settlement system of the Moscow agglomeration with the use of cellular operator data. Regional studies, 2, (60), 68-78 (in Russian).
Makhrova A.G., Babkin R.A., Kirillov P.L., Starikova A.V., and Sheludkov A.V. (2022). Temporary mobility and population pulsations in space of post-Soviet Russia. Regional Research of Russia, 12(1), 36-60.
Makhrova A.G., Kirillov P.L. (2015). Seasonal pulsation of settlement in the Moscow agglomeration under the influence of dacha and labor pendulum migration: approaches to the study and assessment. Regional studies, 1(47), 117-125 (in Russian).
Makhrova A.G., Kirillov P.L., Bochkarev A.N. (2016). Pendulum labor migrations of the population in the Moscow agglomeration: experience of flow estimates using data from cellular operators. Regional studies, 3(53), 71-82 (in Russian).
Nefedova T.G. (2015). Seasonal work in the system migrations in post-Soviet Russia. Prerequisites. Demoscope Weekly, [online] Available at: http://demoscope.ru/weekly/2015/0641/demoscope641.pdf [Accessed 20 Apr. 2022] (in Russian).
Nelson K.S., Abkowitz M.D., Camp J.V. (2015). A method for creating high resolution maps of social vulnerability in the context of environmental hazards. Applied Geography, 63, 89-100.
Osipov V.I., Burova V.N., Zaikanov V.G. et al. (2011). Map of large-scale (detailed) engineeringgeological zoning of the territory of Moscow. Geoecology, 4, 306-318. (in Russian).
Petrov N.V. (1986). Spatial and temporal analysis in social geography: Main achievements and directions of research. Swedish. shk. [T. Hegerstrand]. Moscow: VINITI (in Russian).
Siagian T.H., Purhadi P., Suhartono S., Ritonga H. (2014). Social vulnerability to natural hazards in Indonesia: driving factors and policy implications. Natural hazards, 70(2), 1603-1617.
Sorokin P.A. and Merton R.K. (1937). Social Time: a methodological and functional analysis. The American Journal of Sociology, 42(5), 615-629.
Spielman S.E., Tuccillo J., Folch D.C., Schweikert A., Davies R., Wood N., Tate E. (2020). Evaluating social vulnerability indicators: criteria and their application to the Social Vulnerability Index. Natural Hazards, 100(1), 417-436.
United Nations, Department of Economic and Social Affairs, Population Division (2019). World Urbanization Prospects: The 2018 Revision (ST/ESA/SER.A/420). New York: United Nations.
Ward P.S. and Shively G.E. (2017). Disaster risk, social vulnerability, and economic development. Disasters, 41(2), 324-351.
Zemlyansky D.Y. (2011). An indicative approach to assessing the seasonal dynamics of population placement in Russia. Regional studies, 3, 83-92 (in Russian).
Zhang, Z., Tian, H., Cazelles, B., Kausrud, K. L., Bräuning, A., Guo, F., Stenseth, N. C. (2010). Periodic climate cooling enhanced natural disasters and wars in China during AD 10–1900. Proceedings of the Royal Society B: Biological Sciences, 277(1701), 3745-3753.
Zhongrui W., Feng S., Maocang T.A. (2003). Relationship between solar activity and frequency of natural disasters in China. Advances in Atmospheric Sciences, 20 (6), 934-939.
https://ges.rgo.ru/jour/article/view/2718
doi:10.24057/2071-9388-2022-116
op_rights Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).The information and opinions presented in the Journal reflect the views of the authors and not of the Journal or its Editorial Board or the Publisher. The GES Journal has used its best endeavors to ensure that the information is correct and current at the time of publication but takes no responsibility for any error, omission, or defect therein.
Авторы, публикующие в данном журнале, соглашаются со следующим:Авторы сохраняют за собой авторские права на работу и предоставляют журналу право первой публикации работы на условиях лицензии Creative Commons Attribution License, которая позволяет другим распространять данную работу с обязательным сохранением ссылок на авторов оригинальной работы и оригинальную публикацию в этом журнале.Авторы сохраняют право заключать отдельные контрактные договорённости, касающиеся не-эксклюзивного распространения версии работы в опубликованном здесь виде (например, размещение ее в институтском хранилище, публикацию в книге), со ссылкой на ее оригинальную публикацию в этом журнале.Авторы имеют право размещать их работу
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container_title GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY
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spelling ftjges:oai:oai.gesj.elpub.ru:article/2718 2023-05-15T14:28:26+02:00 Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts) Roman A. Babkin Svetlana V. Badina Alexander N. Bereznyatsky 2023-01-17 application/pdf https://ges.rgo.ru/jour/article/view/2718 https://doi.org/10.24057/2071-9388-2022-116 eng eng Russian Geographical Society https://ges.rgo.ru/jour/article/view/2718/667 Ahas R., Aasa A., Yuan Y., Raubal M., Smoreda Z., Liu Y., Ziemlicki C., Tiru M., Zook M. (2015). Everyday Space–Time Geographies: Using Mobile Phone-Based Sensor Data to Monitor Urban Activity in Harbin, Paris, and Tallinn. International Journal of Geographical Information Science, 29(11), 2017-2039. Akimov V.A., Durnev R.A., Sokolov Y.I. (2009). Dangerous hydrometeorological phenomena on the territory of Russia. Moscow: FGU VNII GOChS (FC) (in Russian). Aksha S.K., Juran L., Resler L.M., Zhang Y. (2019). An analysis of social vulnerability to natural hazards in Nepal using a modified social vulnerability index. International Journal of Disaster Risk Science, 10(1), 103-116. Baburin V.L. (2011). Two-dimensional model of the territorial organization of society. Vestnik Moskovskogo Universiteta, Seriya 5: Geografiya, 1, 3-8 (in Russian). Baburin V.L. and Baldina S.V. (2021). Forecasting of socio-economic damages from hazardous natural processes for the tourist cluster Resorts of the North Caucasus. Vestnik Moskovskogo Universiteta, Seriya 5: Geografiya, 2, 25-35 (in Russian). Badina S.V. (2020). Prediction of socioeconomic risks in the cryolithic zone of the Russian Arctic in the context of upcoming climate changes. Studies on Russian Economic Development, 31(4), 396-403. Badina S.V. and Babkin R.A. (2021). Assessment of Moscow population vulnerability to natural and technogenic hazards. InterCarto. InterGIS, 27(4), 184-201 (in Russian). Badina S., Babkin R., Bereznyatsky A., Bobrovskiy R. (2022a). Spatial aspects of urban population vulnerability to natural and man-made hazards. City and Environment Interactions, 15, 100082. Badina S., Babkin R., Mikhaylov A. (2022b). Approaches to assessing the vulnerability of large city population to natural and man-made hazards using mobile operators data (case study of moscow, russia). In: Wohlgemuth V., Naumann S., Behrens G., Arndt HK. (eds) Advances and New Trends in Environmental Informatics. ENVIROINFO 2021. Springer Cham, 171-186. Baida S.E. (2019). Wave cycles of natural, human-made and social catastrophes. Civil Security Technology, vol. 16, No. 4 (62), 30–-36 (in Russian). Cutter S.L., Boruff B.J., Shirley W.L. (2003). Social vulnerability to environmental hazards. Social science quarterly, 84(2), 242-261. De Oliveira Mendes J.M. (2009). Social vulnerability indexes as planning tools: beyond the preparedness paradigm. Journal of Risk Research, 12(1), 43-58. Flanagan B.E., Gregory E.W., Hallisey E.J., Heitgerd J.L., Lewis B. (2011). A social vulnerability index for disaster management. Journal of homeland security and emergency management, 8(1), article 3. Froude M.J. and Petley D.N. (2018). Global fatal landslide occurrence from 2004 to 2016. Natural Hazards and Earth System Sciences, 18(8), 2161-2181. Geyer H.S. and Kontuly T.A (1993). Theoretical foundation of the concept of differential urbanization. International Regional Science Review, 15(2), 157-177. Gibbs J. (1963). The evolution of population concentration. Economic Geography, 2, 119-129. Hägerstrand T. (1973). The domain of human geography. In: Chorley R.J. (ed.) Directions in Geography. London: Methuen. Kaniewski D., Marriner N., Morhange C., Faivre S., Otto T., Van Campo E. (2016). Solar pacing of storm surges, coastal flooding and agricultural losses in the Central Mediterranean. Scientific reports, 6(1), 1-12. Karachurina L.B. and Ivanova K.A. (2017). Migration of the elderly in Russia (according to the 2010 census). Regional studies, 3(57), 51-60 (in Russian). Klaassen L.H. and Scimeni G. (1981). Theoretical issues in urban dynamics. In: L.H. Klaassen, W.T.M. Molle and J.H.P. Paelinck (ed.). Dynamics of Urban Development. Aldershot: Gower. Knaub R.V., Ignateva A.V. (2022). The General Mechanism of the Origin of Natural Disasters in the Global Dimension. IOP Conference Series: Earth and Environmental Science, 988(2), 022068. Kondratiev N.D. (2003). Large cycles of conjuncture and the theory of foreseeing. Selected Works. Voprosy Ekonomiki, 8, 153-154 (in Russian). Luque-Espinar J.A., Mateos R.M., García-Moreno I., Pardo-Igúzquiza E., Herrera, G. (2017). Spectral analysis of climate cycles to predict rainfall induced landslides in the western Mediterranean (Majorca, Spain). Natural Hazards, 89(3), 985-1007. Makhrova A.G. and Babkin R.A. (2018). Analysis of pulsations of the settlement system of the Moscow agglomeration with the use of cellular operator data. Regional studies, 2, (60), 68-78 (in Russian). Makhrova A.G., Babkin R.A., Kirillov P.L., Starikova A.V., and Sheludkov A.V. (2022). Temporary mobility and population pulsations in space of post-Soviet Russia. Regional Research of Russia, 12(1), 36-60. Makhrova A.G., Kirillov P.L. (2015). Seasonal pulsation of settlement in the Moscow agglomeration under the influence of dacha and labor pendulum migration: approaches to the study and assessment. Regional studies, 1(47), 117-125 (in Russian). Makhrova A.G., Kirillov P.L., Bochkarev A.N. (2016). Pendulum labor migrations of the population in the Moscow agglomeration: experience of flow estimates using data from cellular operators. Regional studies, 3(53), 71-82 (in Russian). Nefedova T.G. (2015). Seasonal work in the system migrations in post-Soviet Russia. Prerequisites. Demoscope Weekly, [online] Available at: http://demoscope.ru/weekly/2015/0641/demoscope641.pdf [Accessed 20 Apr. 2022] (in Russian). Nelson K.S., Abkowitz M.D., Camp J.V. (2015). A method for creating high resolution maps of social vulnerability in the context of environmental hazards. Applied Geography, 63, 89-100. Osipov V.I., Burova V.N., Zaikanov V.G. et al. (2011). Map of large-scale (detailed) engineeringgeological zoning of the territory of Moscow. Geoecology, 4, 306-318. (in Russian). Petrov N.V. (1986). Spatial and temporal analysis in social geography: Main achievements and directions of research. Swedish. shk. [T. Hegerstrand]. Moscow: VINITI (in Russian). Siagian T.H., Purhadi P., Suhartono S., Ritonga H. (2014). Social vulnerability to natural hazards in Indonesia: driving factors and policy implications. Natural hazards, 70(2), 1603-1617. Sorokin P.A. and Merton R.K. (1937). Social Time: a methodological and functional analysis. The American Journal of Sociology, 42(5), 615-629. Spielman S.E., Tuccillo J., Folch D.C., Schweikert A., Davies R., Wood N., Tate E. (2020). Evaluating social vulnerability indicators: criteria and their application to the Social Vulnerability Index. Natural Hazards, 100(1), 417-436. United Nations, Department of Economic and Social Affairs, Population Division (2019). World Urbanization Prospects: The 2018 Revision (ST/ESA/SER.A/420). New York: United Nations. Ward P.S. and Shively G.E. (2017). Disaster risk, social vulnerability, and economic development. Disasters, 41(2), 324-351. Zemlyansky D.Y. (2011). An indicative approach to assessing the seasonal dynamics of population placement in Russia. Regional studies, 3, 83-92 (in Russian). Zhang, Z., Tian, H., Cazelles, B., Kausrud, K. L., Bräuning, A., Guo, F., Stenseth, N. C. (2010). Periodic climate cooling enhanced natural disasters and wars in China during AD 10–1900. Proceedings of the Royal Society B: Biological Sciences, 277(1701), 3745-3753. Zhongrui W., Feng S., Maocang T.A. (2003). Relationship between solar activity and frequency of natural disasters in China. Advances in Atmospheric Sciences, 20 (6), 934-939. https://ges.rgo.ru/jour/article/view/2718 doi:10.24057/2071-9388-2022-116 Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).The information and opinions presented in the Journal reflect the views of the authors and not of the Journal or its Editorial Board or the Publisher. The GES Journal has used its best endeavors to ensure that the information is correct and current at the time of publication but takes no responsibility for any error, omission, or defect therein. Авторы, публикующие в данном журнале, соглашаются со следующим:Авторы сохраняют за собой авторские права на работу и предоставляют журналу право первой публикации работы на условиях лицензии Creative Commons Attribution License, которая позволяет другим распространять данную работу с обязательным сохранением ссылок на авторов оригинальной работы и оригинальную публикацию в этом журнале.Авторы сохраняют право заключать отдельные контрактные договорённости, касающиеся не-эксклюзивного распространения версии работы в опубликованном здесь виде (например, размещение ее в институтском хранилище, публикацию в книге), со ссылкой на ее оригинальную публикацию в этом журнале.Авторы имеют право размещать их работу CC-BY GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY; Vol 15, No 4 (2022); 90-101 2542-1565 2071-9388 time-geography vulnerability of the urban population dynamic clustering typology of urban districts Moscow intracity population mobility social time info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2023 ftjges https://doi.org/10.24057/2071-9388-2022-116 2023-01-24T17:49:42Z The relevance of the study lies in the need for a scientific search for the possibilities of using new types of Big data in studies of the population vulnerability to solve practical problems of improving the safety of urban spaces from natural and man-made hazards. The object of the study is the administrative districts of Moscow; the subject is the temporal patterns of vulnerability of their population to potential natural and man-made hazards. The research question of the study is to develop a typology of Moscow districts and further assess this sustainability in terms of the population vulnerability to natural and man-made hazards. To achieve this research question, a set of tasks was solved: 1. Processing of the mobile operators’ data array and further construction of a continuous graph of the Moscow population dynamics in 2019 (with a time cycle of 30 minutes, over 36 million measurements in more than 7 thousand time slices); 2. Empirical justification of natural temporal boundaries of daily, weekly, seasonal cycles of population dynamics in Moscow districts; 3. Justification of key factors and parameters of urban population vulnerability; 4. Development and approbation of the dynamic clustering method of Moscow districts using selected variables and periods. The study is based on the impersonal mobile operators’ data on the locations of subscribers for 2019, provided by the Department of Information Technologies of the Moscow city. The method of dynamic cluster analysis is used. Four particular clusterings were obtained that characterize the “behavior” of the settlement system in the main intervals of social time (weekdays and weekends of the cold and warm seasons). Сluster stability matrix allows to identify which of the districts retain their properties during the period under review, and which are characterized by instability of considered indicators of population vulnerability. Depending on the stability of the position of the districts in a particular cluster, “stable”, “conditionally stable” and ... Article in Journal/Newspaper Arctic Geography, Environment, Sustainability (E-Journal) GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 15 4 90 101