Join us in this training to learn about some of the latest and greatest features in ERDAS IMAGINE!  With the exponentially increasing amount of data being collected in the world today, customized repeatable, batchable workflows are needed to extract as much valuable information from raw data as possible.  

The Spatial Modeler is the key to setting up these types of workflows.  The creation of spatial models and the use of AI, machine learning and deep learning allow more data to be processed, classified, and utilized.    

In 2020 Update 2, a new DSM extractor was added.  Hexagon's own SGM algorithm is used in photogrammetric processing to extract high resolution point clouds from satellite, aerial and UAV imagery.   

In 2022, ERDAS IMAGINE has added automatic Co-registration as a spatial model operator to seamlessly integrate misaligned datasets into more complex change detection and mosaicked workflows.   

Another feature to continue advancing deep learning methods added was Semantic Segmentation.  This is a pixel by pixel application to categorize each pixel belonging to one of the trained classes.  This achieves pixel level precision and most reflects the traditional remote sensing supervised classification results, but using deep learning technicques.  The spatial modeler workflow allows the analyst to train once but classify many times.