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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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Water, Water Everywhere

But never where you need it.

Anonym

For some reason, water has been a big theme for me lately. Two weeks ago, it was a snow storm causing problems for a class I was teaching in Virginia and delaying my flight home to Colorado. Then I got a bunch of followup work for the arctic coastal erosion and bathymetric projects I’ve been working on. The Winter Olympics started, and brought the usual concerns about snow quantities. Now, I’m back in the DC area again this week to teach another class, and sure enough another snow storm is forecast to make a mess of roads and air traffic.

Precipitation, like most of nature, has a habit of following its own rules and systems which are at best loosely coupled to what we’d like to see. We get too much in some places, and not enough in others. But one project I get to work on in a small way promises to help us work with the water we have a lot more effectively. The first step in understanding an earth system is getting a decent map of it, and that’s not particularly easy. There have been some great earlier missions to develop and test the technology, like TRMM. The new missions, SMAP and GPM, however, will give us frequent global maps of where precipitation is falling, and where that water goes when it hits the ground. My little contribution is to make sure we can help get that data on screen in the ways scientists and end users want. When I get some more of the code finished, I’ll post it as a blog on making use of global data systems through HDF5 and map routines in IDL. But for now, here’s a sneak peek of where I’m at:

 

 

 

There aren’t many geospatial fields that don’t have a heavy dependency on precipitation and water. How will you use the new data from precipitation and soil moisture missions?

 

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