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NV5 Geospatial Blog

Each month, NV5 Geospatial posts new blog content across a variety of categories. Browse our latest posts below to learn about important geospatial information or use the search bar to find a specific topic or author. Stay informed of the latest blog posts, events, and technologies by joining our email list!



Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

12/3/2025

Large commercial SAR satellite constellations have opened a new era for persistent Earth monitoring, giving analysts the ability to move beyond simple two-image comparisons into robust time series analysis. By acquiring SAR data with near-identical geometry every 24 hours, Ground Track Repeat (GTR) missions minimize geometric decorrelation,... Read More >

Empowering D&I Analysts to Maximize the Value of SAR

Empowering D&I Analysts to Maximize the Value of SAR

12/1/2025

Defense and intelligence (D&I) analysts rely on high-resolution imagery with frequent revisit times to effectively monitor operational areas. While optical imagery is valuable, it faces limitations from cloud cover, smoke, and in some cases, infrequent revisit times. These challenges can hinder timely and accurate data collection and... Read More >

Easily Share Workflows With the Analytics Repository

Easily Share Workflows With the Analytics Repository

10/27/2025

With the recent release of ENVI® 6.2 and the Analytics Repository, it’s now easier than ever to create and share image processing workflows across your organization. With that in mind, we wrote this blog to: Introduce the Analytics Repository Describe how you can use ENVI’s interactive workflows to... Read More >

Deploy, Share, Repeat: AI Meets the Analytics Repository

Deploy, Share, Repeat: AI Meets the Analytics Repository

10/13/2025

The upcoming release of ENVI® Deep Learning 4.0 makes it easier than ever to import, deploy, and share AI models, including industry-standard ONNX models, using the integrated Analytics Repository. Whether you're building deep learning models in PyTorch, TensorFlow, or using ENVI’s native model creation tools, ENVI... Read More >

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

10/13/2025

On July 24, 2025, a unique international partnership of SaraniaSat, NV5 Geospatial Software, BruhnBruhn Innovation (BBI), Netnod, and Hewlett Packard Enterprise (HPE) achieved something unprecedented: a true demonstration of cloud-native computing onboard the International Space Station (ISS) (Fig. 1). Figure 1. Hewlett... Read More >

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The Perks of Being a Beta Tester

Anonym

As part of the Commercial Services Group here at NV5 Geospatial (formerly Harris), I have a unique opportunity of using our latest and greatest tech, often before it even goes public. (Making me a bit of a beta tester sometimes.) Over the past couple months, I’ve had the pleasure of getting to work with some of our newest tech, and it’s very exciting. The two pieces of technology I’ve had my hands on are our Geospatial Services Framework (GSF), and our machine learning tool known as MEGA.

The Geospatial Framework has given me a lot of power in setting up large amounts of processing either locally, or on a server. It allows for clustering, many different processing engines, and even lets you hook it into custom websites. From what I’ve seen, it’s very flexible and powerful tech.

MEGA, which I’m also extremely excited about, is a new way to tackle feature extraction problems. Though I don’t understand the underlying development of artificial intelligence, I have had hands on experience training this deep learning system. While the code is complex, the idea is not – first, feed the system examples of what you are looking for in imagery. Once the system is trained, the software will tell you locations and confidences for where those objects of interest are.

Image: http://stats.stackexchange.com/questions/tagged/deep-learning

Using these two technologies together, I’ve been classifying large amounts of image data quickly through a deep learning system, and the sky really is the limit. With GSF, the ability to scale up just depends on how much hardware you can allocate to a task.

The more I use and learn about these technologies, the more excited I become about them. The best part is that they are very new, so they have room to become more and more powerful and robust. Can’t wait!!

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