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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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Making movies with IDL, part I

Anonym

Over the years there have been many ways to make movies with IDL, but none of them have been great. I think we now have a robust solution: the IDLffVideoWrite class, introduced in IDL 8.1, wraps FFmpeg, which can create a movie in just about any format. This week, I’ll show an example of using IDLffVideoWrite with Direct Graphics (DG). Next week, I’ll show how to make a similar movie with (New) Graphics (NG). This example is written as a procedure. Start the program by declaring some test data and setting up the IDLffVideoWrite object:

pro dg_movie_ex
   compile_opt idl2

   data = dist(30)

   video_file = 'dg_movie_ex.mp4'
   video = idlffvideowrite(video_file)
   framerate = 10
   framedims = [640,512]
   stream = video.addvideostream(framedims[0], framedims[1], framerate)

The variable video is an object, an instance of IDLffVideoWrite. I chose to make an MPEG-4 video file; see the IDL Help for other supported formats. We configure the dimensions and frame rate of the single video stream that this file holds (files can hold multiple video and audio streams) with the AddVideoStream method. Next, switch to the DG Z buffer device and configure it:

   loadct, 1
   set_plot, 'z', /copy
   device, set_resolution=framedims, set_pixel_depth=24, decomposed=0

We’ll need the Z buffer for hidden line removal in the visualization, but it’s also convenient because it allows us to render the frames of the movie offscreen. The next step is where we make and load frames into the movie file:

   nframes = 50
   for i=0, nframes-1 do begin
      shade_surf, data, charsize=2.0, az=(15 + i), /save
      contour, data, nlevels=10, /t3d, zval=i/float(nframes), /overplot
      xyouts, 0.5, 0.9, 'IDL Movie Example - DG', align=0.5, charsize=2, /normal
      timestamp = video.put(stream, tvrd(true=1))
   endfor

There’s quite a bit going on in this code block. On each iteration of the loop:

  1. SHADE_SURF displays data as a shaded surface and rotates the surface one degree about its z axis.
  2. CONTOUR visualizes data as a planar contour plot in the 3D coordinate system set up by SHADE_SURF. The contour plot is moved upward by a fraction of the total height of the surface.
  3. XYOUTS adds the title at the top of the visualization.
  4. TVRD takes a picture of the Z buffer. The picture is a pixel-interleaved RGB image, with dimensions 3 x 640 x 512.
  5. The Put method of IDLffVideoWrite loads this picture as a frame into the video stream.

End the program by closing the Z buffer, returning to the windowing device and destroying the video object:

   device, /close
   set_plot, strlowcase(!version.os_family) eq 'windows' ? 'win' : 'x'
   video.cleanup
   print, 'File "' + video_file + '" written to current directory.'
end

Click below to see the resulting video on the VIS YouTube channel. [youtube http://www.youtube.com/watch?v=e1zSoZWBx6E] Sweet! Update: Here's the second example.  

1 comments on article "Making movies with IDL, part I"

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Patrick Essien

This is very usefull

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