Wind Turbine Detection detects wind turbines locations on SPOT imagery.
Disclaimer: This block version currently uses a BETA version of the algorithm.
This block uses a deep learning model for the classification of wind turbines.
|Input parameters||Tiled imagery in GeoTIFF of any size. Expected ground resolution at 1.20 m. (i.e. WebMercator projection)|
|Output format||A GeoJSON file with each detected turbine as a specific polygon.|
|Training dataset||The algorithm has been trained on a 40,000 object dataset created specifically for this purpose.|
The algorithm is expected to achieve a high level of recall. It is still considered as a Beta version.
There are numerous use cases where it is important to know where wind turbines are located, typically energy production forecast and aircraft traffic regulations. Some databases are available but they do not cover all locations and are not accurate. Extracting their location from satellite imagery enables getting a current and precise view of the location. Revisiting at a later date also enables monitoring the construction of new wind turbines.
For more information about this processing block, please see the provider website
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