NV5 GEOSPATIAL SOFTWARE

Automate Analytics With Deep Learning For Faster, More Accurate Results

ENVI^® Deep Learning Software

NV5 Geospatial has developed commercial off-the-shelf deep learning technology that is specifically designed to work with remotely sensed imagery to solve geospatial problems. The ENVI Deep Learning module removes the barriers to performing deep learning with geospatial data and is currently being used to solve problems in defense, disaster response, urban development, transportation and other industries.

No Programming Required

Not everyone is a deep learning expert and ENVI Deep Learning software was developed with this in mind. The module has intuitive tools and workflows that don’t require programming and enable users to easily label data and generate models with the click of a button.

Additionally, it is simple for seasoned imagery experts to fuse information layers such as spectral indices, elevation data or data transforms to create more robust classifiers.

Accuracy Counts

Leverage the power of Geospatial Deep Learning

ENVI is the leading image analysis software on the market and its science-based analytics are accurate and reliable for extracting meaningful information from all types of geospatial imagery and data. ENVI’s preprocessing tools such as calibration, atmospheric correction and color space transforms create consistent input data for deep learning models. With geospatial deep learning technology built on TensorFlow, a leading open-source library, you can create reliable models for image classification.

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ENVI Deep Learning Software 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 or network, whether that’s your desktop computer, on-premises servers or in the cloud. Here are a few real-world deep learning applications that customers have used to solve problems with ENVI Deep Learning Software.

Urban Growth

The ENVI geospatial deep learning technology makes it easy to assess the environment. The module was used to generate the landcover classification image above. 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 objects like new buildings and well pads.

Agriculture

Using ENVI Deep Learning software, 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.

Disaster Response

When disasters strike, response time is very important. ENVI Deep Learning analytics have been fine-tuned so you don’t need thousands of samples to create models for finding features. After a recent hurricane, the deep learning technology 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.