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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!



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 >

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 >

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On Demand Geospatial Image Dissemination

Anonym

Geospatial imagery provides current information that defense and intelligence personnel, first responders, and other tactical users need to make mission-critical decisions. The challenge is getting this data to them quickly and easily. These end users frequently operate in environments where bandwidth is limited and networks are slow.  They don’t have the time to wait for data ‘bricks’ to be shipped to the field or for large image libraries to be downloaded to forward-deployed servers.  By the time these resources arrive, they are often out of date.  Tactical users need the most recently collected imagery in order to attain the latest situational awareness to help guide decision making.

One solution to the geospatial image delivery problem is to deploy high-performance, secure image delivery and management systems that incorporate JPEG 2000 technology.  JPEG 2000 is an ISO standard (ISO/IEC 15444) for image compression and coding.  JPIP is the protocol used for browsing JPEG 2000 images.  With this technology, only selected regions of an image have to be moved from the server to the client for the end user to gain critical information and save valuable time.  Repeated requests from the client to the server and progressive rendering of the image provide more data as the user zooms and pans in the image, yet only a small amount of the total image size is typically required to deliver actionable intelligence to the field. The movement of the image data from the server to the client is referred to as JPIP streaming.

For example, let’s suppose I’m trying to determine if a bridge in Nashville is still standing after the Cumberland River has reached the high water stage. The latest image of the area on a server I can access is 4 hours old. It’s been compressed from 2.2 GB to 400 MB with JPEG2000.  I’m in the field using a laptop with a poor connection where it will take two hours to download the compressed image.  My server is JPIP-enabled, and I have a JPIP-enabled client, so I access the image on the server and request that it be JPIP streamed to my client.  I have an overview in less than 1 minute, and with two more requests, initiated by moving and clicking my pointing device, I’m zoomed in on the bridge in question and can see that it is still standing and operational.  My original view downloaded 0.45% of the overall image, or 1.7 MB, and with a couple of zooms and pans, I’ve downloaded only 1.35% of the image, or 5.2 MB of data. With JPIP tools available, I’ve been able to determine, in less than 5 minutes, that my planned route to deliver emergency supplies is feasible, and I’m ready to head out on my mission.  Now that’s timely actionable intelligence!

Nashville Cumberland River JPIP

Figure 1 – Image of Nashville and the Cumberland River loaded into a JPIP viewer at 1:32 resolution (1.7 MB of 400 MB). The blue lines are highway feature data overlaid on the image.

Nashville Cumberland River JPIP Zoom

Figure 2 - Zoomed in to 1:1 resolution on a bridge in upper left of image (4.8 MB of 400 MB). I’ve determined that the bridge is still operational with less than 5 MB of image data downloaded to my local system.

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