2min chapter

The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography cover image

Aerial Imagery: The State Of The Art

The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography

CHAPTER

A New Approach to Vector Maps as a Service?

For 15 years we've had imagery as a service customers, whether they're viewing it in our map browser tool and using it directly there. And then we've got API users on the imagery as well who kind of pull into their own custom applications. There's two, three years ago now that we launched the near map AI as a product. That was in response to customers saying, hey, can you help us recognize things in the imagery? So people have sort of vector maps as a service almost. For every pixel of RGB imagery, we're producing actually a Zoom 21 in Web Macata,. Then we run that through a big post processing engine. We make that available behind an API.

00:00
Speaker 2
Okay, so we've got this new camera, hyper camera three, it's capturing better, stronger, faster data, also another channel, infrared or near infrared. Your model is improving, you're being able to identify and segment more features. This is great. This is amazing. What is the business model of this? I guess there's some kind of imagery as a service
Speaker 1
and there's some kind of vector maps as a service. What am I on the right path here? Yeah, absolutely. So there's for a long time, for 15 years we've had imagery as a service customers, whether they're viewing it in our map browser tool and using it directly there. And you don't need any geospatial skills to do that. More software skills, you just, in a browser, looking at pictures. And then we've got API users on the imagery as well who kind of pull into their own custom applications. There's two, three years ago now that we launched the near map AI as a product. That was in response to customers saying, hey, can you help us recognize things in the imagery? So people have sort of vector maps as a service almost. For every pixel of RGB imagery, we're producing actually a Zoom 21 in Web Macata, set of 78 pixel probabilities for each of the 78 classes. Then we run that through a big post processing engine. And then we make that available behind an API. So you can basically, we've got this feature API thing where you can ask for a one square kilometer up to a one square kilometer polygon of data and it'll give you the map. That's kind of the core of where we were maybe a year ago. The new thing that we've done alongside Gen 5 is actually go beyond that. As it turns out, geospatial things are pretty complicated. And I don't think I need to highlight that further to your listeners. But this idea that a data scientist or a software engineer can just grab this payload of GeoJSON and other metadata and integrate into their application, it works for the more sophisticated users who have that sort of capability in the house. But now we're building things on top of that to basically make that information more accessible. So there's a whole stack of things that we're building on top of Gen 5 as really a product platform, which is still a product in its own right. But we're going that extra mile for customers who want a more direct end solution.

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