Some of the usecases for elevation data I've worked on or have seen
• Raster data for flood modelling
• Point queries comparing elevation to flood models
• Using elevation to improve accuracy of hyper-local weather modelling
• Elevation profiles of activities: like strava but for various different niches
• Flight planning for various aerial activities: drones, general aviation, hang gliding, paragliding, normal gliding
Compared to self hosting, APIs add latency and remove control. But people seem to use them to avoid dealing with multi-TB datasets, abstract away a lot of the geospatial complexity with projections and tiling and geoids, and to avoid dealing with lots of different datasets from different sources.
And with the Google Maps API in particular, people struggle with the high cost of course, but also the lack of providence about the data used, and the accuracy reduction of batch queries.
• Raster data for flood modelling
• Point queries comparing elevation to flood models
• Using elevation to improve accuracy of hyper-local weather modelling
• Elevation profiles of activities: like strava but for various different niches
• Flight planning for various aerial activities: drones, general aviation, hang gliding, paragliding, normal gliding
Compared to self hosting, APIs add latency and remove control. But people seem to use them to avoid dealing with multi-TB datasets, abstract away a lot of the geospatial complexity with projections and tiling and geoids, and to avoid dealing with lots of different datasets from different sources.
And with the Google Maps API in particular, people struggle with the high cost of course, but also the lack of providence about the data used, and the accuracy reduction of batch queries.