The service filters thousands of online news sources of the last 24 hours mentioning occurred wildfires. We are using a web mercator projection using a grid size being optimized for geographic visualization. Each grid cell has a count attribute representing the number of news article related to locations of the corresponding grid cell.
The service uses the impressive data source provided by the Global Database of Events, Language and Tone (GDELT) Project (https://www.gdeltproject.org/).
Ready to use
The geofires API offer ready-to-use geospatial features representing broadcasted news related to wildfires. You can use these geospatial features to build various mapping and geospatial applications. The underlying serverless cloud-backend analyses raw geospatial locations of news articles provided by the Global Database of Events, Language and Tone (GDELT) Project (https://www.gdeltproject.org/).
Every geospatial result support the GeoJSON and Esri FeatureSet format out of the box. All endpoints support a date parameter for filtering the geospatial features. For best sustainability, the serverless cloud-backend queries the articles from the knowledge graph and calculates the geospatial features on-the-fly.
Aggregate broadcasted news
Aggregates the broadcasted news related to wildfires using a spatial grid and returns the features as hexagonal bins. These features represent the coarse grained geographical view of the broadcasted news.
Query source articles
Returns a list of broadcasted articles related to wildfires. The extracted locations of these news articles define the source for the calculation of the geospatial aggregations.
Query named locations
Returns the location features related to wildfires. A location feature represents the extracted and geocoded named location occurred in many news articles.
Specific Python client libraries
An easy-to-use client library implemented using Python.