Comparative assessment of applicability of spatial data analysis tools for assessing and predicting the state of environmental factors

Introduction: Geographic information systems (GIS) are widely used in assessing sanitary and epidemiological well-being, planning control and supervisory activities, and organizing monitoring owing to a set of spatial analysis tools that allows prediction of the magnitude and distribution of values of a factor within the study area based on limited initial data. GIS development has led to the emergence of many variations of such tools while the variety of methods at their core complicates the choice, potentially leading to erroneous results.

Objective: To analyze tools of spatial data analysis implemented in geographic information systems from the standpoint of their applicability to the tasks of assessing and forecasting environmental conditions.

Materials and methods: We used the results of ambient air quality monitoring in St. Petersburg in 2022–2023; drinking water and ambient air quality and morbidity data collected in the Arkhangelsk, Murmansk, and Vologda regions in 2018–2023, and the results of summary calculations of ambient air pollution in the city of Petrovsk-Zabaikalsky as of 2023. Methods of visualization of distribution of spatially referenced data using spatial analysis and data grouping tools were analyzed using the ArcMap 9.3 geographic information system as an example.

Results: Our findings showed the importance of taking into account characteristics of the samples of analyzed data, the type and nature of the data themselves when choosing certain tools for grouping (classifying) data or performing geostatistical analysis. Practical examples illustrate the significance of choosing a certain spatial analysis method for the result of forecasting value distribution of an indicator.

Discussion: Traditional GIS remain relevant in the analysis of environmental factors, incidence and prevalence rates, and the results of public health monitoring, which require the use of specialized tools for data grouping and geostatistics. To obtain objective results, it is essential to take into account properties of the data array when choosing an analysis tool.

Conclusion: Recommendations for selecting the optimal spatial analysis tools for the tasks of assessing and forecasting the sanitary and epidemiological situation given the type of data, their sample characteristics, and the goals set are suggested.

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