AI and machine learning are revolutionizing the field of remote sensing. The ability of machine learning algorithms to automatically detect and identify objects in satellite images has enhanced our abilities to monitor deforestation, identify illegal fishing, track wildlife, and more quickly implement disaster response.
Thanks to AI it is now also possible to see who owns a Tesla car in San Francisco. Bluesight.ai has released a new interactive map to demonstrate how objects can be identified in aerial imagery of San Francisco. Using natural language searches it is possible to explore the Blue Explorer map for things like Tesla cars, dry patches, boats, and tennis courts. Just type your search criteria into the Blue Explorer search box and the AI will automatically search the aerial imagery of San Francisco and show the results highlighted on the interactive map.
Some other recent examples of machine learning being used to search aerial imagery include OneSoil (which uses AI to detect where different the types of crops are being grown), Земляна проказа (identifying illegal amber mines) and Curio Canopy (identifying tree canopy cover in European cities).
Robin Wilson also recently released an impressive Aerial Image Search Demo which allows you to explore an AI image search of aerial imagery in the UK port town of Southampton. Clay Explore is another impressive interactive AI map demo, allowing you to search aerial imagery of Southern California, Seoul and Puerto Rico using machine learning.
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