Machine Learning and Object Detection in Spatial Analysis

There is no question deep learning and artificial intelligence techniques have transformed remote sensing, computer vision, and spatial analysis. Until now, most efforts would have had to code their efforts, segment or semantically segment data, and then also layer and parallelize their code to run on high performance or cloud-based systems. While this may not be a major issue for those with software engineering backgrounds, it was a restriction for those interested in conducting spatial and remote sensing analysis to have these additional skills. A new tool, called Picterra (https://picterra.ch/) which was discussed by Julien Rebetez in a recent Mapscaping podcast, enables a relatively easy to use interface that allows users to upload remote sensing images whereby users can identify and train an automated detector to find and detect objects of interest. This means that Web Map Service (WMS) and other raster data could be used directly for deep learning-based spatial analysis by those with minimal experience in artificial intelligence techniques.