Abstract
In the summertime, many Moscow residents move to second homes in the countryside, which causes strong seasonal fluxes in the population size of the Russian capital, its surroundings, and more remote rural areas. To better understand the spatial scale and patterns of seasonal suburbanization, we tracked the changes in average monthly nighttime light radiance between August and October 2018 at 1 km resolution. Our results revealed a significant, 1.5 times increase of the summer nighttime lighting in the surroundings of Moscow and a more than 2 times increase in the rural areas to the West and North of the capital. This study illustrates the seasonal character of suburbanization in the Moscow agglomeration and raises the question of its effects on both urban and rural development of the area.
Moscow is one of the largest and fastest-growing cities on the European continent. Since the early 2000s, the city's population size has grown by more than a quarter from 9.9 to 12.7 million people. Moscow attracts people from all over Russia but especially from the rapidly depopulating neighboring regions (Nefedova and Treivish, 2020). At the same time, the city population is subject to serious seasonal fluctuations: in the summertime, many urban dwellers move to second homes in the countryside, called dachas (Treivish, 2014). According to 2019 cell phone data, the maximum variation in Moscow population size, between winter weekdays and May holidays, when dacha season starts, reaches 5 million people (Makhrova et al., 2021). Since official statistics do not cover the phenomenon of second homes, other data sources are needed to shed light on the scale and spatial patterns of summer suburbanization.
Here, we use nighttime lights (NTL) satellite imagery produced by NASA (Román et al., 2018). We suggest that significant changes in population density affect nighttime lighting in the countryside surrounding Moscow. By tracking the seasonal changes of NTL radiance, we can identify the areas that attract summer residents (Sheludkov and Starikova, 2021).
Figure 1 shows the difference in average monthly NTL radiance between August and October 2018 aggregated at 1 km spatial resolution in Moscow and its surroundings. The selected time steps provided the best data available for the area. To remove background noise and to avoid the “blooming” effect (de Miguel et al., 2020) of large cities, the image was masked with a Global Human Settlement Layer (GHSL) built-up layer (Corbane et al., 2018).

The nighttime lights (NTL) radiance in August 2018 as a percentage of October 2018.
While Moscow and the built-up areas along the major routes toward other large cities remain steadily lit, we observe an August increase in the NTL radiance in the areas between the routes and, most prominently, in the countryside to the West and North of Moscow. The scatter in the growth values ranges from 1.5 times in the vicinity 50–70 km from Moscow up to 2 or more times in more remote rural areas. The spatial pattern of the NTL dynamics pronounces the differences between the more industrialized and densely populated lowlands of the Southeast and less anthropogenically disturbed upland landscapes of the Northwest. The examples of areas around Tver, Rzhev, Gagarin, and Vyazma show that the summer suburbanization expands beyond the Moscow Region.
This study illustrates the seasonal character of suburbanization in the Moscow urban agglomeration and raises the question of its effects on both urban and rural development in the area.
Footnotes
Acknowledgment
The authors are grateful to Brett Hankerson for helpful comments and suggestions.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was carried out within the framework of the state-ordered research theme of the Institute of Geography of the Russian Academy of Sciences АААА-А19-119022190170-1 (FMGE-2019-0008).
