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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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Dynamic Plots Using an Equation String

Anonym

The PLOT function's new Equation argument adds flexibility to the creation of plots in IDL, allowing you to create dynamic, interactive output.

The Equation argument on the PLOT function allows you to specify either a string containing an equation with variable X, or the name of an IDL function that accepts X as an input argument. The result of the equation (or the function) should be a one-dimensional array of Y coordinates to be plotted.

  • If Equation is an expression, then the EXECUTE function is called once with the X array. Note that in certain circumstances (such as the IDL Virtual Machine), you may not be able to use the EXECUTE function.
  • If Equation is a function name, then CALL_FUNCTION is called once, with the X array as an input argument. The function should return a one-dimensional result array.

Once IDL creates the plot output, if you then interactively adjust the plot range, IDL will automatically recompute the equation to cover the new range.

We'll use the BESELJ function in IDL to show how to use a Function String in the Equation Argument:

 

; Plot J Bessel Functions

pj0 = PLOT('BESELJ(X, 0)', XRANGE=[0.0, 50],  $

  XTITLE='X', YTITLE='$J_n(x)$ or $Y_n(x)$', $

  TITLE='J Bessel Function')

pj1 = PLOT('BESELJ(X, 1)', 'r2', XRANGE=[0.0, 50], /OVERPLOT)

pj2 = PLOT('BESELJ(X, 2)', 'b2', XRANGE=[0.0, 50], /OVERPLOT)

; Annotate the plot.

xcoords = [1, 1.66, 3]

ycoords = [.8, .62,.52]

labels = '$\it' + ['J_0','J_1','J_2'] + '$'

  t = TEXT(xcoords, ycoords, labels, /DATA)

 

If you run the code above, it should generate a graphic like this:

Once IDL creates the plot, test out its dynamic capabilities:

  • Try clicking with the middle mouse button on the graphic and panning around.
  • You can also use the mouse wheel to zoom in or out, or hold down the <Shift> key and draw a zoom box.
  • Change the plot range programatically at the IDL command line:

pj0.xrange=[0.0, 150]

As you change the plot range, IDL recomputes the equation with new X values that span the new range.

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