  The spread of the Red Palm Weevil has dramatically affected date growers,
homeowners and governments, forcing them to deal with a constant threat to
their palm trees. Early detection of palm tree infestation has been proven to
be critical in order to allow treatment that may save trees from irreversible
damage, and is most commonly performed by local physical access for individual
tree monitoring. Here, we present a novel method for surveillance of Red Palm
Weevil infested palm trees utilizing state-of-the-art deep learning algorithms,
with aerial and street-level imagery data. To detect infested palm trees we
analyzed over 100,000 aerial and street-images, mapping the location of palm
trees in urban areas. Using this procedure, we discovered and verified infested
palm trees at various locations.
