ENVI Deep Learning at Work
The ENVI Deep Learning module is offered as an extension to ENVI for desktop applications and is built on the ENVI Task framework. This means that classifiers can be built once and run in any environment, whether that’s your desktop computer, on-premises servers or in the cloud. To demonstrate how you can use this technology, here are a few real-world examples of customer problems that have been solved using the module.
The ENVI Deep Learning module makes it easy to assess the environment. The module was used to generate the landcover classification image below. When another image was generated the following year, traditional change detection workflows in ENVI were used to approximate the human impact on the environment and detect things like new buildings and well pads.
Using the ENVI Deep Learning module, the locations of current, and past, lava flows in Hawaii were identified. This information was used in ENVI to understand the environmental impact that the volcanic gasses had on local crops, which gave farmers insights for insurance claims and an ability to understand if crops are safe for human consumption.
When disasters strike, response time is very important. The ENVI Deep Learning module has been tuned so you don’t need thousands of samples to create models for finding features. After a recent hurricane, the module was used to quickly characterize different types of damage to buildings throughout the region ranging from partial to full destruction. First, a handful of small areas were labeled according to the extent of the damage. When the model was applied to the scene, the damaged buildings were automatically classified according to the extent of the damage they sustained.