Mapping the population density of a rarely populated region (the example of the Irkutsk region)

Abstract

The principles and methodology of mapping the population density of a sparsely populated area has been developed using the example of the Irkutsk region. For the most part of the Irkutsk region is not characterized by a continuous area settlement, but linear and focal with an extremely rare network of permanent settlements, except for its southern part along the Trans-Siberian railway. Of the three possible types of population density maps there are contours, choropleths and quantitative areas for a rarely inhabited and little populated region, and only the latter type is suitable. The borders of the inhabited territory are carried out in a formal way. To draw the boundaries of the area populated area by the method of spots we need the radius of the buffer 3 km. Inhabited zones, formed by chains of settlements along the transport routs, adjoin the entirely populated territory. A quantitative map of the density by areas of the rural and urban population was constructed. The map helps you visualize the quantitative differentiation of the populated areas seeing population density and distinguish the unsettled territories. A map of inhabited areas can be the basis for mapping demographic, ethnographic, ecological and socio-economic characteristics of the population.

Estimation and Mapping of the Settlement Field Potential Basing on Real Transportation Connections Between Settlements

“…The first one ambiguity is the variability of SFP essence and availability of different computational formulas in publications of different authors (Kushnyr, 2015;Sozdaev, Teslenok, 2019;Vorobiev, 2019;Mandyt, 2021;Dong et al, 2022). At least three most popular formulas can be easily found in scientific publications, while SFP values estimated using any of the found can differ by an order of magnitude.…”

“…Geographic science in whole and human geography in particular operate wide range of computational facilities and techniques to ensure quantitative description, analysis, estimation and forecasting of discovered object of interest. Over the time, new technologies like fractal computations (Yanguang, 2009), remote sensing (Kubanek et al, 2014), machine learning (Guzman et al, 2022), and other are involved in human geography studies, while the application of automated computation, modelling and mapping (Bashirov, 2017;Sidorina et al, 2019;Vorobiev, 2019;Sumping et al, 2021) in geographic information systems appears to be classical approach applied to study social processes. Analysis elaborated in geographic information systems (GISs) assumes generally a quantitative description of explored phenomenon and its spatial characteristics, like coordinates, areas and lengths (distances).…”

Fires on Ice: Emerging Permafrost Peatlands Fire Regimes in Russia’s Subarctic Taiga

“…This paper focuses on the Siberian taiga near the villages of Tokma and Vershina Khandy in the Irkutsk region of Russia (Figure 1). These study areas are characterized by harsh (and changing) climatic conditions, discontinuous permafrost, the prevalence of conif-erous vegetation, and susceptibility to wildfires [35][36][37]. The region has been historically settled by Evenki, Indigenous Tungus-speaking people who have traditionally subsisted on hunting, fishing, and gathering Siberian pine nuts, berries, and herbs.…”