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 “nomadic” types of districts were identified. The study showed that the first two types include spatial-settlement structures that are stable in time with approximately the same level of population vulnerability during the year, while the third type requires a special differentiated approach to the development of measures to protect the population from natural and man-made emergencies. Calculations have shown that “nomadic” type of districts concentrate on average from 2.2 million people in the summer season to 3 million people in the winter season, that is, a very significant share of the entire population of the capital.