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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!



New ENVI Agent, IDL Agent, and GeoAgent Quick Guides

New ENVI Agent, IDL Agent, and GeoAgent Quick Guides

6/9/2026

The recent release of ENVI® Agent, IDL® Agent, and GeoAgent™ revolutionize how users interact with geospatial software. These agentic AI applications act as partners to plan, simplify, and execute complex workflows. Knowing where to start can be challenging for new users. To this end, we developed three new quick guides to... Read More >

Introducing NISAR Data Support

Introducing NISAR Data Support

6/5/2026

The release of ENVI® SARscape 6.3 in April 2026 includes preliminary support for NASA-ISRO SAR (NISAR) data. The NISAR mission is a joint Earth-observing satellite project between NASA and the Indian Space Research Organization designed to monitor changes in the planet’s land and ice surfaces using advanced radar imaging. It... Read More >

Monitoring Illegal Mining in the Amazon: Turning Persistent Data Into Actionable Insight

Monitoring Illegal Mining in the Amazon: Turning Persistent Data Into Actionable Insight

5/28/2026

Illegal mining over decades has constituted one of the most persistent and complex socio-environmental problems in the Brazilian Amazon. In recent years, with the increasingly intensive use of mechanized extraction, the associated environmental impacts—such as deforestation, intense soil disturbance, river siltation, and mercury... Read More >

From Answers to Action: Why ENVI and IDL Agents Go Beyond General AI

From Answers to Action: Why ENVI and IDL Agents Go Beyond General AI

4/20/2026

As generative AI tools like Claude and Gemini continue to gain traction, many organizations are asking the same question: Can general purpose AI actually support real geospatial workflows, or does it stop at surface-level answers? That question was front and center in our recent webinar, Meet Your New Partners in Science: ENVI... Read More >

Mapping Earthquake Deformation in Taiwan With ENVI

Mapping Earthquake Deformation in Taiwan With ENVI

12/15/2025

Unlocking Critical Insights With ENVI® Tools Taiwan sits at the junction of major tectonic plates and regularly experiences powerful earthquakes. Understanding how the ground moves during these events is essential for disaster preparedness, public safety, and building community resilience. But traditional approaches like field... 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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