overture2hdx 0.0.6

Lib to convert Overture data in GIS formats and upload it to HDX

Overture Map Data 2 HDX

This project is designed to export geographic data from Overture Maps and upload it to the Humanitarian Data Exchange (HDX). The data is processed using DuckDB and can be exported in various formats such as GeoJSON, GPKG, and ESRI Shapefile.

Features

• Export geographic data from Overture Maps.
• Upload data to HDX.
• Support for multiple output formats.
• Configurable via YAML and environment variables.
• Logging setup using environment variables or parameters.

Installation

pip install overture2hdx

Configuration

The application is configured using a YAML file and environment variables.

YAML Configuration

Example config.yaml:

iso3: npl
geom: '{"type": "FeatureCollection", "features": [{"type": "Feature", "properties": {}, "geometry": {"coordinates": [[]], "type": "Polygon"}}]}'
key: osgeonepal_pkr
subnational: true
frequency: yearly
categories:
- Roads:
    select:
        - id
        - names.primary as name
        - class as class
        - subclass as subclass
        - UNNEST(JSON_EXTRACT(road_surface, '$[*].value')) as road_surface
        - UNNEST(JSON_EXTRACT(sources, '$[*].dataset')) AS source
    hdx:
        title: Roads of Pokhara
        notes: Overturemaps Export for Pokhara. Data might have errors but has gone through validation checks.
        tags:
        - geodata
        - transportation
        - roads
    theme:
        - transportation
    feature_type:
        - segment
    formats:
        - gpkg
        - shp

Code Overview

Config: Class to handle configuration. OvertureMapExporter: Class to handle the export process. setup_logging: Function to set up logging.

Default export config

Following is the default yaml used

Category	Description	License	Overture Theme Docs	Attributes	File Formats
Hospitals	Health POIs like hospitals and clinics, from Meta and Microsoft open data	CDLA Permissive 2.0	Places	id, names.primary, names.common.en, categories.primary	gpkg, shp
Schools	Education POIs like schools, colleges, universities from Meta and Microsoft	CDLA Permissive 2.0	Places	id, names.primary, names.common.en, categories.primary	gpkg, shp
Rivers	Water bodies (rivers, lakes, etc.) from OpenStreetMap via the Base theme	ODbL 1.0	Base	id, names.primary, names.common.en, subtype, class	gpkg, shp
Land Use	Land use polygons (farmland, forest, etc.) based on OSM landuse tags	ODbL 1.0	Base	id, names.primary, names.common.en, subtype, class	gpkg, shp
Transportation Hubs	Airports, stations, terminals from Meta & Microsoft	CDLA Permissive 2.0	Places	id, names.primary, names.common.en, categories.primary	gpkg, shp
Settlements	Populated places like cities, towns, and villages from OSM, geoBoundaries, and Esri	ODbL 1.0	Divisions	id, names.primary, names.common.en, population, country	gpkg, shp
Roads	Road network (highways, local roads, etc.) from OSM and TomTom	ODbL 1.0	Transportation	id, names.primary, names.common.en, class, subclass, road_surface, source	gpkg, shp
Buildings	Building footprints from OSM, Microsoft, Google, and Esri	ODbL 1.0	Buildings	id, names.primary, names.common.en, class, subtype, height, level, num_floors, source	gpkg, shp

Default python example

For default yaml example python implementation , follow here

How it works?

Author and License

Kshitij Raj Sharma , License : GNU GENERAL PUBLIC LICENSE V3