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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!



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 >

NV5 at ESA’s Living Planet Symposium 2025

NV5 at ESA’s Living Planet Symposium 2025

9/16/2025

We recently presented three cutting-edge research posters at the ESA Living Planet Symposium 2025 in Vienna, showcasing how NV5 technology and the ENVI® Ecosystem support innovation across ocean monitoring, mineral exploration, and disaster management. Explore each topic below and access the full posters to learn... Read More >

Monitor, Measure & Mitigate: Integrated Solutions for Geohazard Risk

Monitor, Measure & Mitigate: Integrated Solutions for Geohazard Risk

9/8/2025

Geohazards such as slope instability, erosion, settlement, or seepage pose ongoing risks to critical infrastructure. Roads, railways, pipelines, and utility corridors are especially vulnerable to these natural and human-influenced processes, which can evolve silently until sudden failure occurs. Traditional ground surveys provide only periodic... Read More >

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Don’t forget to Stretch! Using ENVI’s stretch tools to see things our eyes can’t.

Anonym

Living in Boulder, we mountain people out here like to do a lot of physical activities whether it’s hiking, skiing, or yoga. Everyone knows the first thing you have to do before any physical activity is STRETCH! This also applies in ENVI as well! Over the past few months I have worked on various projects where, had I applied one of our stretches in ENVI first, I would have saved a lot of time for myself. This example today was a dataset of a large grass field in which the user was looking for an invasive species weed within this field.

You can see from the figure above that EVERYTHING LOOKS GREEN! How can you pick out a weed when everything looks like grass? With a little help from the customer, we were able to get access to a shapefile they provided that showed us areas in the scene that actually were the weed we were looking for. Still, even with these shapefiles everything looks the same color. This is where, before you start any of your preprocessing or classification workflows, you stretch!

ENVI has some really great stretch tools to choose from, but seeing them isn’t actually helping you know what they mean. For this example we used a few different linear percent stretches to help accentuate some of our features. What these percent stretches do is trim the X% of extreme values at the beginning and end of the histogram.

So for example, if you look at our three images with the histogram stretch plot shown, you can see in the first image with no stretch that our pixel values are 0-255 which is standard. If we look at our Linear 2% and 5% stretched images respectively you see the pixel values get trimmed on each end of each color band.

From here we were easily able to identify the invasive weed in our scene and compare it to the shapefiles provided for us so that we could run a classification workflow and extract the features that we wanted. Our shapefiles, not shown here, were all around the areas in the scene above that were a very dark green. These stretches allowed us to make more accurate ROIs  (Regions of Interest) for our classification which in turn gave us a more accurate result.

So remember, DON’T FORGET TO STRETCH!

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