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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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Satellite Constellations for Environmental Monitoring

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The Disaster Monitoring Constellation

The Disaster Monitoring Constellation (DMC) consists of several similar satellites orbiting in a configuration that enables a daily revisit for most points on the Earth’s surface. If a historical record going back farther than 2002 is important, DMC has it covered: the DMC spatial resolution and placement of its three spectral bands were designed to match up well with Landsat TM. The satellites were built by Surrey Satellite Technology Ltd (SSTL), and are currently operated for various international governments by DMC International Imaging. The constellation currently includes AISAT-1 (Algeria), BilSAT (Turkey), NigeriaSAT-1 (Nigeria), UK-DMC (United Kingdom), Beijing-1 (China), UK-DMC2 (United Kingdom), Deimos-1 (Spanish commercial), NigeriaSAT-2 (Nigeria), and NigeriaSAT-X (Nigeria).

This NigeriaSat-1 image of New Orleans, USA in 2005 shows an area affected by Hurricane Katrina. New Orleans is visible in the centre. Dark areas in the city indicate flooding, and at full detail (not shown here) it is possible to see which streets are submerged.

Data from DMC sensors have been used to monitor the effects of the Indian Ocean Tsunami in December 2004 and Hurricane Katrina August 2005, in addition to many other disasters. The RapidEye constellation consists of five satellites which, like the DMC constellation, were designed and implemented by SSTL (this time subcontracted to MacDonald Dettwiler and Associates ). Each satellite carries an identical sensor, designed and implemented by Jena Optronik, which measures five visible and near infrared bands at 5 m spatial resolution. The sensors include a unique red edge band that make RapidEye data appropriate for monitoring changes in chlorophyll content. Consequently, RapidEye data can be used to monitor vegetation health, distinguish different species of vegetation, and monitor protein and nitrogen content in vegetation.

NigeriaSat-1Image of Katrina aftermath

RapidEye imagery before and after alumina plant accident in Hungary
Natural-color RapidEye imagery of Kolontár, Hungary, before and after an alumina plant accident in which a dam holding back a reservoir of caustic sludge failed catastrophically, resulting in flooding of nearby towns and villages. Source: RapidEye.

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