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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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Disable window updates to improve (New) Graphics performance

Anonym
When making a visualization with many graphic elements in NG, you can improve the render speed by disabling updates to the window. For example, this program displays a 3-by-5 grid of sample plots and prints to the console the time taken in doing so:
pro grid3by5
   compile_opt idl2

   n_rows = 5
   n_cols = 3

   start_time = systime(/seconds)

   w = window(dimensions=[500,700])
   ;w.refresh, /disable
   for i=1, n_rows*n_cols do $
      !null = plot(/test, layout=[n_cols, n_rows, i], color=!color.(i), /current)
   ;w.refresh

   end_time = systime(/seconds)
   print, 'Time elapsed (s): ', end_time – start_time
end
Here’s the console output from running this program on my laptop:
IDL> grid3by5
Time elapsed (s):        6.6850002
Note that you can also see the individual plots being rendered to the window, one after another. (I find this a little distracting.) Now uncomment the calls to disable and re-enable the NG Refresh method in GRID3BY5. This turns off intermediate updates to the window. After recompiling, here’s the console output from running the program:
IDL> grid3by5
Time elapsed (s):        3.4670000
That’s faster! Plus, you don’t see the individual plots being rendered to the window. Depending on what and how many graphic elements are in your visualization, you may see more or less of a performance boost, but speedups of a factor of two are not uncommon.
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