Multi-Scale Spatial Indexing Approach for OSM- Based Urban Data Representation in Yangon Disaster Management
Year: 2026
Type: conference-paper
Abstract: Urban disaster management requires fast, structured, and scale-aware spatial data representation. Emergency response operations in Yangon require accurate information about hospitals, schools, buildings, roads, waterways, administrative areas, and other important urban features. OpenStreetMap provides the open-source source of volunteer geographic information for these applications, but raw OSM data is difficult to use directly in disaster management systems due to heterogeneous geometry, inconsistent semantic tags, and spatial detail. This paper proposes a multi-scale spatial indexing approach for OSM-based urban data representation in Yangon disaster management. The proposed framework systematically collects OpenStreetMap nodes, paths and relationships specifically sourced from the Yangon area. Critical attributes are identified through the utilization of OSM tags, further refined via spatial preprocessing techniques, and subsequently transformed into multi-tiered spatial tokens employing H3 indexing at resolutions 6, 8, and 10. The fine-resolution index supports tactical field units, the medium-resolution index supports township emergency operation centres, and the coarse-resolution index supports regional command centres. A scale-aware risk aggregation method is then applied to compute cumulative risk weights for emergency map visualisation. The proposed approach improves the effectiveness of spatial inquiries, supports decision-making at different scales and creates a solid framework for key activities such as disaster management, flood surveillance, evacuation strategies and urban risk assessment. Keywords— OpenStreetMap, OSM, spatial indexing, H3, disaster management, Yangon, urban data representation, emergency response, geospatial information system
Authors: Ye Myat Han, Nyein Nyein Oo, Sai Myo Htet
Institution: Yangon Technological University
Language: English
Subfield: Geography, Planning and Development
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7203892300