The PBF (Protocolbuffer Binary Format) is a compact, binary file format used to store OpenStreetMap (OSM) data. It is an alternative to the older XML-based `.osm` format, offering significantly smaller file sizes and faster processing. PBF uses Google’s Protocol Buffers for efficient data serialization, making it ideal for applications that need to download, parse, or process large-scale map data quickly. It supports compression and Homeing, which enhances performance for tools and services working with geographic data, such as map rendering, routing, and data analysis.
Converting OSM PBF to a GIS-ready format is not overly complex, but it does require appropriate tools and some understanding of GIS data structures. Tools like osm2pgsql , ogr2ogr (GDAL) , and OSMConvert can extract and transform PBF data into formats like Shapefile , GeoPackage , or load it into PostGIS . However, due to the raw nature of OSM data (with tags, nested relations, etc.), you often need to:
* Filter relevant features (e.g., roads, buildings).
* Interpret OSM tags into GIS attribute schemas.
* Reconstruct geometries from nodes and ways.
For basic tasks, it's manageable. For advanced uses, especially involving relations (like multipolygons), it can become complex without the right tooling.This repository serves as a centralized hub for all PBF (Protocolbuffer Binary Format) country datasets that have been fully converted into GIS-ready GeoPackage (.gpkg) format. The data transformation pipeline has been meticulously customized and engineered to efficiently extract, preprocess, and reformat OpenStreetMap (OSM) PBF files to support advanced GIS-based spatial analysis and cartographic visualization workflows. The processing architecture includes automated routines for data normalization, topology validation, feature classification, and schema harmonization to ensure consistency across geospatial layers. These .gpkg files are optimized for seamless integration with common GIS platforms such as QGIS, ArcGIS, and PostGIS, making them suitable not only for analytical tasks but also as high-performance vector basemap layers. This setup significantly reduces the overhead of raw PBF handling, offering ready-to-use datasets that empower spatial modeling, infrastructure planning, land use analysis, and other geospatial intelligence applications.