Satellite Image-based objects detection
Availability of high-quality hyperspectral satellite imagery data unveils a new way of observing and monitoring the Earth. As part of our company’s social responsibility activities, we developed an en-vironmental monitoring solution based on satellite imagery analysis. The technology is based on an award-winning solution recognized by IEEE society. It allows us to identify objects on satellite imag-es with very high accuracy. Detected objects can include but are not limited to: trees, cars, trains, buildings and identify coastal and sea debris, oil spillage, and other human activities results.
Detection of small (relative to the distance from where it was captured) objects on the Earth from an orbit with the help of Deep Learning is a non-trivial task. Environmental monitoring and object detection by humans using images of Earth from satellites is hardly achievable in the area of thousands of kilometers. In addition to that, some substances like methane leakage or oil spills might be invisible to a human eye which is sensitive only to three channels of the visual spectrum: red, green, and blue.
Solution by AI Superior
We developed a Deep Learning solution that employs all channels provided by hyperspectral imagery and is able to recognize objects with a very low-resolution, e.g., 10 x 8 pixels. The approach demonstrates state-of-the-art performance in detecting various objects: residential and commercial buildings, cars, trains, roads, highways, railways, etc.
Outcome and Implications
The developed technology has a high potential to be applied in a wide variety of scenarios, namely:
- Ecology control and pollution monitoring: detection of coastal and marine plastic debris, oil spillage detection, methane leakage, detection, and severity analysis
- Building Control Authority: detection of unauthorized building, construction site monitoring, illegal tree removal
- Roads and railways quality monitoring, detection of road coverage by sand or snow, parking lots monitoring
- Analysis of human activity on oil fields, in industrial zones, logistics monitoring