Mapflow.ai — New Buildings Model and Kepler.gl Implementation

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Last month we released Mapflow — our new app to work with Geoalert Platform Mapflow.ai. Hopefully you’ve had a chance to try it. If you haven’t, let me convince you to try some new cool features we’ve just implemented into Mapflow:

1. “High-density housing” AI-mapping Model 

A new “high-density housing” AI-mapping model is available. It improves the automatic mapping of buildings in areas with terraced and other similar densely standing buildings, such as in the Middle East and in Africa.

While this new model is still in experimental beta, the credit cost for its use is very low. So you can test it. In case you do “urban mapping” and see this model applicable to your area of interest — we’ll be happy to learn from your experiments and to share the results of ours. 

A densely built-up area in Morocco.  Image: GeoAlert.
A densely built-up area in Morocco. Image: GeoAlert.

Improved Mapflow Visualization Capabilities

We’ve improved Mapflow visualization capabilities through the implementation of Kepler.gl which is open-sourced by Uber. It is a simple but powerful tool for data scientists to explore and analyse geospatial datasets. 

In particular, you can change visualization parameters such as fill, opacity, etc. (the user guide for Kepler.gl can be found here)

Moreover, you can visualize buildings in 3D if you have enabled the “building_height” option for your processing.

3D building visualisation using Kepler.gl. Image: GeoAlert.
3D building visualisation using Kepler.gl. Image: GeoAlert.

Playing around with Kepler I visualized an extract from “Urban Mapping” — our building footprints product with population counts. For example, you can use “Hexbin” or “Grid” map types to sum population in adjustable grid and visualize it — even in 3D.

Population data for Moscow city and Moscow region visualized in Kepler.gl.  Image: GeoAlert.
Population data for Moscow city and Moscow region visualized in Kepler.gl. Image: GeoAlert.

However, you should be aware that all the data is rendered on the client’s side which can be a challenge for your PC performance. 

There are also other ways to preview and visualize data in Mapflow.ai before you download it for importing into any specialized GIS software — you can head over to our embedded map viewer or to geojson.io which enables small datasets conversion to the other geospatial data types. But be aware that geojson.io may hang your browser for good if you have more than a few tens of megabytes of data.

Stay tuned for more updates! Tell us what you think if you have any questions / suggestions regarding Mapflow.ai or other GeoAlert products.

This article was republished with permission from GeoAlert. See the original article.

About GeoAlert

At GeoAlert we love maps and data science. We apply machine learning for automated detection and mapping over global Earth observation data. You can find links and contacts below:

Mapflow Platform | Mapflow documentation | Facebook page | Linkedin page | Telegram | Github page | Contacts


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