EarthDefine deploys state of the art machine learning algorithms to extract different ground cover classes from aerial imagery or Lidar data. Typically, we use one or more Deep Convolutional Neural Networks for each ground object that we are trying to classify. These models are iteratively trained over large training datasets to create robust AI models. The final products are further be refined using morphological filtering and rule based modeling.