A method for developing an information base for planning volunteer rescue units based on open geospatial data

Abstract

The article develops a method for forming an information base for planning volunteer rescue formations using open geospatial data. The relevance of the study is determined by the need to provide decision-support systems with structured, spatially consistent, and analytically suitable data on settlements, road networks, buildings, and infrastructure objects within territorial communities. The study aims to develop a method that enables automated collection, verification, preprocessing, integration, aggregation, and structuring of open geospatial data for further use in planning volunteer rescue formations. The proposed method includes identification of the study area, acquisition of data from an open mapping environment, selection of target spatial objects, data quality checking and cleaning, spatial integration, aggregation of territorial characteristics, and formation of a structured feature matrix with associated metadata. To implement the method, software code was developed in Python in a cloud-based computing environment using specialized libraries for geospatial data processing, tabular data management, and visualization.The method was experimentally tested using a territorial community in Volyn Oblast as a case study. As a result, an information base was formed containing spatially consistent characteristics of settlements, road networks, buildings, and infrastructure objects. Experimental verification confirmed the operability of the proposed method according to spatial, structural, and logical criteria. The practical value of the study lies in creating a reproducible information basis for further assessment and prediction of rescue-service accessibility and for decision support in planning volunteer rescue formations. Further research should focus on integrating additional official and departmental data sources and using the formed information base in models for accessibility prediction and rational location of rescue formations.