Intensive anthropogenic activity leads to ecosystem degradation, necessitating a shift from conventional management approaches towards proactive environmental risk assessment strategies. This study presents a quantitative methodology for calculating a Comprehensive Environmental Risk Indicator (CERI) based on the analysis of types of permitted use (TPU) of land plots in the Russian Federation. The methodology comprises three stages: determining a base risk weight for each TPU, statistically weighting impact factors using multiple regression analysis (MRA), and synthesizing the final CERI. This research identifies five key impact factors: industrial pollution, biogenic and agrogenic effects, landscape and resource changes, anthropogenic and household load, and specific risks and disasters. The results demonstrate that biogenic and agrogenic effects (weight 0.450) and specific risks and disasters (weight 0.398) are the most significant factors. Industrial pollution and landscape changes were excluded from the model due to multicollinearity. The model’s R2 (0.194) confirms its statistical validity as a foundational framework for macro-level risk evaluation. Further improvements could address limitations related to cadastral data variability and the integration of localized environmental parameters. The developed CERI was integrated into geographic information systems (GIS) to visualize risk gradients across land parcels. This study concludes that the use of statistically substantiated factor weights enables objective territorial zoning, facilitating a transition from subjective expert assessments to management based on actual environmental consequences.
Kovyazin et al. (Thu,) studied this question.
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