Geospatially-intelligent three-dimensional multivariate methods for multiscale dasymetric mapping of urban population: Application and performance in the Minneapolis-St. Paul metropolitan area

The wide availability of remote sensing data, the development of computer technology, and the accessibility of census data in the digital form created new opportunities for highly accurate population estimates. Of particular scientific interest is the method of dasymetric mapping, which can significantly improve the spatial accuracy of mapping socio-demographic processes. In addition to population density, the method has considerable potential in mapping the distribution of other social, economic and demographic variables, such as income level, crime, ethnicity, etc. Another significant gap in the existing studies is the development of three-dimensional dasymetric mapping methods. This study is focused on developing intelligent dasymetric mapping methods to create algorithms for near real-time display demographic and other socio-economic parameters and assess their accuracy and their potential for geovisual analytics. The study is developed and tested in Minneapolis-Saint Paul area, Minnesota, USA as a key study site given the relative diversity of urban areas and the accessibility for field surveys. The goal of this study is to develop and test an effective geospatially-intelligent method and GIS algorithm for the creation of multivariable three-dimensional dasymetric (3DM) geographic visualizations for the Twin Cities Metropolitan area. 2D and 3D binary dasymetric mapping methods, as well as floor fraction and intelligent dasymetric mapping method were used to identify the best performing method in terms of accuracy. The 3D dasymetric mapping method yielded the best accuracy in estimation of population counts in conditions of the given study area. 3D dasymetric mapping method proved to improve the accuracy of population mapping in an urban environment compared to 2D methods. The improvement is more significant at a smaller scale of analysis that reflects a more heterogeneous residential building infrastructure. Finally, the additional socio-economic variables, such as aggregated income and three different types of spending (for food, household supplies, and apparel) were mapped. The study faced the limitations of the inability to obtain data, perfectly synchronized in time between all the spatial layers, non-straightforward nature of the selection of residential/non-residential buildings and low height variance in the study area. The future directions of the study are to integrate the developed methods with the existing web mapping platform, test the dasymetric mapping approach on the extended set of socioeconomic variables and explore the usefulness of the dasymetric mapping approach on the smaller scales of the enumeration units and dasymetric mapping polygons

Regional geographies and public health lessons of the COVID-19 pandemic in the Arctic

Objectives: This study examines the COVID-19 pandemic’s spatiotemporal dynamics in 52 sub-regions in eight Arctic states. This study further investigates the potential impact of early vaccination coverage on subsequent COVID-19 outcomes within these regions, potentially revealing public health insights of global significance. Methods: We assessed the outcomes of the COVID-19 pandemic in Arctic sub-regions using three key epidemiological variables: confirmed cases, confirmed deaths, and case fatality ratio (CFR), along with vaccination rates to evaluate the effectiveness of the early vaccination campaign on the later dynamics of COVID-19 outcomes in these regions. Results: From February 2020 to February 2023, the Arctic experienced five distinct waves of COVID-19 infections and fatalities. However, most Arctic regions consistently maintained Case Fatality Ratios (CFRs) below their respective national levels throughout these waves. Further, the regression analysis indicated that the impact of initial vaccination coverage on subsequent cumulative mortality rates and Case Fatality Ratio (CFR) was inverse and statistically significant. A common trend was the delayed onset of the pandemic in the Arctic due to its remoteness. A few regions, including Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway, experienced isolated spikes in cases at the beginning of the pandemic with minimal or no fatalities. In contrast, Alaska, Northern Sweden, and Russia had generally high death rates, with surges in cases and fatalities. Conclusion: Analyzing COVID-19 data from 52 Arctic subregions shows significant spatial and temporal variations in the pandemic’s severity. Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway exemplify successful pandemic management models characterized by low cases and deaths. These outcomes can be attributed to successful vaccination campaigns, and proactive public health initiatives along the delayed onset of the pandemic, which reduced the impact of COVID-19, given structural and population vulnerabilities. Thus, the Arctic experience of COVID-19 informs preparedness for future pandemic-like public health emergencies in remote regions and marginalized communities worldwide that share similar contexts

Incorporating Resilience When Assessing Pandemic Risk in the Arctic: A Case Study of Alaska

The discourse on vulnerability to COVID-19 or any other pandemic is about the susceptibility to the effects of disease outbreaks. Over time, vulnerability has been assessed through various indices calculated using a confluence of societal factors. However, categorising Arctic communities, without considering their socioeconomic, cultural and demographic uniqueness, into the high and low continuum of vulnerability using universal indicators will undoubtedly result in the underestimation of the communities\u27 capacity to withstand and recover from pandemic exposure. By recognising vulnerability and resilience as two separate but interrelated dimensions, this study reviews the Arctic communities\u27 ability to cope with pandemic risks. In particular, we have developed a pandemic vulnerability-resilience framework for Alaska to examine the potential community-level risks of COVID-19 or future pandemics. Based on the combined assessment of the vulnerability and resilience indices, we found that not all highly vulnerable census areas and boroughs had experienced COVID-19 epidemiological outcomes with similar severity. The more resilient a census area or borough is, the lower the cumulative death per 100 000 and case fatality ratio in that area. The insight that pandemic risks are the result of the interaction between vulnerability and resilience could help public officials and concerned parties to accurately identify the populations and communities at most risk or with the greatest need, which, in turn, helps in the efficient allocation of resources and services before, during and after a pandemic. A resilience-vulnerability-focused approach described in this paper can be applied to assess the potential effect of COVID-19 and similar future health crises in remote regions or regions with large Indigenous populations in other parts of the world

THE OXYGEN REGIME OF A SHALLOW LAKE

The year-round measurement data of water temperature and dissolved oxygen content in a small boreal Lake Vendyurskoe in 2007–2013 were used to explore the hydrophysical prerequisits of anoxia and accumulation and emission of greenhouse gases. Typically, anoxia appears in the bottom layers of lakes in mid-winter and during the summer  stagnation. The thickness of the benthic anaerobic zone (dissolved oxygen concentration <2 mg·l–1) reached one meter in the end of the winter and at the peak of the summer stratification, except for the extremely hot summer of 2010, when it reached five meters. Synoptic conditions had a crucial influence on the formation and destruction of the benthic anaerobic zones in summer. The most favorable oxygen dynamics was observed during the cold summers of 2008, 2009, and 2012, when the repeated full mixings of the water column occurred under conditions of the cyclonic weather. In the winter periods, the early dates of ice season resulted in the most pronounced deficiency of oxygen

The “second wave” of the COVID-19 pandemic in the Arctic: regional and temporal dynamics

This article focuses on the “second wave” of the COVID-19 pandemic in the Arctic and examines spatiotemporal patterns between July 2020 and January 2021. We analyse available COVID-19 data at the regional (subnational) level to elucidate patterns and typology of Arctic regions with respect to the COVID-19 pandemic. This article builds upon our previous research that examined the early phase of the COVID-19 pandemic between February and July 2020. The pandemic’s “second wave” observed in the Arctic between September 2020 and January 2021 was severe in terms of COVID-19 infections and fatalities, having particularly strong impacts in Alaska, Northern Russia and Northern Sweden. Based on the spatiotemporal patterns of the “second wave” dynamics, we identified 5 types of the pandemic across regions: Shockwaves (Iceland, Faroe Islands, Northern Norway, and Northern Finland), Protracted Waves (Northern Sweden), Tidal Waves (Northern Russia), Tsunami Waves (Alaska), and Isolated Splashes (Northern Canada and Greenland). Although data limitations and gaps persist, monitoring of COVID-19 is critical for developing a proper understanding of the pandemic in order to develop informed and effective responses to the current crisis and possible future pandemics in the Arctic. Data used in this paper are available at https://arctic.uni.edu/arctic-covid-19

The second year of pandemic in the Arctic: examining spatiotemporal dynamics of the COVID-19 “Delta wave” in Arctic regions in 2021

The second year of the COVID-19 pandemic in the Arctic was dominated by the Delta wave that primarily lasted between July and December 2021 with varied epidemiological outcomes. An analysis of the Arctic’s subnational COVID-19 data revealed a massive increase in cases and deaths across all its jurisdictions but at varying time periods. However, the case fatality ratio (CFR) in most Arctic regions did not rise dramatically and was below national levels (except in Northern Russia). Based on the spatiotemporal patterns of the Delta outbreak, we identified four types of pandemic waves across Arctic regions: Tsunami (Greenland, Iceland, Faroe Islands, Northern Norway, Northern Finland, and Northern Canada), Superstorm (Alaska), Tidal wave (Northern Russia), and Protracted Wave (Northern Sweden). These regionally varied COVID-19 epidemiological dynamics are likely attributable to the inconsistency in implementing public health prevention measures, geographical isolation, and varying vaccination rates. A lesson remote and Indigenous communities can learn from the Arctic is that the three-prong (delay-prepare-respond) approach could be a tool in curtailing the impact of COVID-19 or future pandemics. This article is motivated by previous research that examined the first and second waves of the pandemic in the Arctic. Data are available at https://arctic.uni.edu/arctic-covid-19

OPTICAL PROPERTIES OF LAKE VENDYURSKOE

We conducted a field study on light conditions in a small boreal Karelian Lake Vendyurskoe over two years. Albedo of ice-covered lake varied from 0.9 to 0.1, and the euphotic zone depth exceeded 3.5 m during the melting stage. The Secchi disc depth changed from 2.5 m after ice-break to 3.7 m at the stage of early summer. The vertical distribution of the photosynthetically active solar radiation (PAR) attenuation coefficient for water Kw was characterized by high spatial (vertical) and temporal (seasonal and interannual) variabilitywhich can be connected with the dynamics of plankton cells. The highest values of Kw  eached 2–2.8 m–1 in the upper 0.5 m layer of a water column, and decreased to 0.5–1.5 m–1 with increasing depth. The highest values of Kw were marked in the end of ice-covered period