Run AI-Mapping in QGIS over high-resolution satellite imagery

QGIS — Mapflow: the example of “Building Detection”

What is AI-Mapping?

This term may refer to “AI-assisted Mapping”. There is a growing number of deep learning approaches for Earth Observation data analysis and feature extraction. These can be used instead of or in combination with the traditional digitizing tools used by cartographers. GIS software vendors like ESRI or SuperMap have started implementing deep learning tools into their products.

Satellite imagery connections — Maxar SecureWatch

We also integrated our plugin with a key source of high-resolution satellite imagery, — Maxar SecureWatch. SecureWatch provides access to imagery basemaps and various OGC services (WMS, TMS, WFS), and the plugin smoothly integrates them all together to enable the user to run Mapflow AI-Mapping over SecureWatch imagery.

Trust us — it works much smoothly than search for imagery using WFS and WMS in QGIS

How to work with the Mapflow-QGIS plugin

The plugin’s made out of three tabs. The Processing ⏺ tab is the mission control center: here, you select what to detect (AI model ), where to detect (an area of processing , which can be a polygon feature created in QGIS), and what imagery ⏯ to use. These three components make up a processing.

  • Buildings
  • Construction sites
  • Forest vegetation (optionally, with heights)
  • Roads
  • Agriculture fields — New❗
Mapflow-QGIS — Processing tab

What’s next?

We’re constantly working on the plugin to add more functionality as one more way to use which is supposed to be closer to cartographic and spatial analysis work. Mapflow API is out there for anyone who’d like to integrate “AI-Mapping” into their product or workflow. We will share the best practices provided by our partners.



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We apply Machine learning to automated analysis over Earth observation data