Mining Spot Detection with Google Earth Engine and TensorFlow
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This short course, taught by Cesar Diniz and Luiz Cortinhas, will focus on theoretical and practical aspects essential to the appropriate use of satellite data, how to access the proper information domain, and how to execute two sets of algorithms to perform mining-related pattern identification on Landsat data.
Cesar Diniz is a post-doctoral fellow at Harvard T.H. Chan School of Public Health. He is trained in oceanography, with a master's degree and PhD in geology from the Federal University of Pará - UFPA, Brazil. His background involves identifying numerical patterns in satellite images, primarily concerning the identification of land use and cover changes in Earth's surface.
Luiz Cortinhas is a Google developer specialist. He is a trained computer engineer who holds a master's degree in applied computing with an emphasis on computational intelligence from UFPA.
Cesar and Luiz are the founder and co-founder of a tech startup called Solved. Solved leads the development of artificial intelligence algorithms used, among other tasks, for recognizing industrial and "Garimpo" patterns in the Amazon as part of the MapBiomas Initiative.
Students must have experience using any programming language. Questions? Please contact Cesar Diniz at: cesargdiniz @ gmail.com.
