The Catalog serves as the index of all geospatial data managed by an OpenOrthoMap instance. It’s structured to function as a set of static files, enabling it to be served from virtually any web server setup - even something as lightweight as a Raspberry Pi. This approach, implemented in the initial proof-of-concept cloud service, maximizes flexibility for both cloud-based and local deployments.

Core of the Catalog: S2 Index

At the heart of the Catalog lies the S2 Geometry index, chosen for its efficient subdivisibility and spatial locality. Unlike hexagonal grids, which don’t nest cleanly, the S2 index subdivides cells in a way that’s both hierarchical and precise. Additionally, it leverages a Hilbert curve to ensure spatially close cells are stored close together in the index, improving data locality.

Introducing OpenOrthoMap: A New Approach to Organizing Geospatial Data

With OpenOrthoMap (OOM), I’m setting out to create something different in the world of geospatial software—a versatile tool focused not on hosting a massive repository of data, but on helping users organize and manage their own. Unlike OpenAerialMap (OAM) and OpenStreetMap (OSM), which provide comprehensive repositories of open data, OpenOrthoMap’s mission is simpler: to be a lightweight, deployable solution for organizing geospatial data wherever it’s needed.

Welcome to OpenOrthoMap! I created this service to keep track of orthophoto maps that I’ve been making of Yakushima Island. I’ve been taking individual photos and using OpenDroneMap to create orthophoto maps and point clouds – it’s fun – but I want to do something more with those GeoTIFF files.

That’s where this project comes in. I want OpenOrthoMap to be a repository of orthophoto maps taken not only by drones, but airplanes and satellites, allowing free use of the data with attribution. Think OpenStreetMap but instead of vector data, OpenOrthoMap is a repository of raster data.