ISSN 2786-4561 (printed)
ISSN 2786-457X (online)
Vol.7.1 (2026). pp. 4-11
Crowdsourced open geodata for last-mile delivery risk assessment: a comparative analysis of sources and approaches
Koliada Y.
https://orcid.org/0009-0001-7938-6713
Taras Shevchenko National University, Kyiv, Ukraine
https://doi.org/10.17721/2786-4561.2026.7.1-1/14
Annotation. The article addresses the comparative analysis of crowdsourced open geodata sources and GIS-based methods applicable to spatial risk assessment in last-mile urban logistics. Despite the broad variety of available data platforms and analytical approaches, their systematic comparative evaluation in the context of logistics risk tasks remains fragmented in the literature. Methods. Based on a structured review of scientific literature and open-platform documentation, a search, systematisation, and critical evaluation of seven key geodata sources and five classes of GIS approaches for spatial risk analysis was carried out. Sources are evaluated across five criteria: geographic coverage, data freshness, spatial granularity, risk-group coverage, and licensing terms. Results. No single source was found to provide complete coverage across all spatial risk groups; instead, a clear complementarity between sources was established. Five classes of GIS approaches are classified along a spectrum from static network analysis to predictive machine-learning methods combined with spatial analysis. Conclusions. An integrative multi-source approach within a unified GIS analytical pipeline is argued to be the most promising direction, and a research agenda for subsequent empirical studies is outlined.
Keywords: last-mile delivery, crowdsourced geodata, OpenStreetMap, GIS, spatial risk, urban logistics, network analysis.
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