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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!



Thermal Infrared Echoes: Illuminating the Last Gasp of a Dying Star

Thermal Infrared Echoes: Illuminating the Last Gasp of a Dying Star

4/24/2025

This blog was written by Eli Dwek, Emeritus, NASA Goddard Space flight Center, Greenbelt, MD and Research Fellow, Center for Astrophysics, Harvard & Smithsonian, Cambridge, MA. It is the fifth blog in a series showcasing our IDL® Fellows program which supports passionate retired IDL users who may need support to continue their work... Read More >

A New Era of Hyperspectral Imaging with ENVI® and Wyvern’s Open Data Program

A New Era of Hyperspectral Imaging with ENVI® and Wyvern’s Open Data Program

2/25/2025

This blog was written in collaboration with Adam O’Connor from Wyvern.   As hyperspectral imaging (HSI) continues to grow in importance, access to high-quality satellite data is key to unlocking new insights in environmental monitoring, agriculture, forestry, mining, security, energy infrastructure management, and more.... Read More >

Ensure Mission Success With the Deployable Tactical Analytics Kit (DTAK)

Ensure Mission Success With the Deployable Tactical Analytics Kit (DTAK)

2/11/2025

In today’s fast-evolving world, operational success hinges on real-time geospatial intelligence and data-driven decisions. Whether it’s responding to natural disasters, securing borders, or executing military operations, having the right tools to integrate and analyze data can mean the difference between success and failure.... Read More >

How the COVID-19 Lockdown Improved Air Quality in Ecuador: A Deep Dive Using Satellite Data and ENVI® Software

How the COVID-19 Lockdown Improved Air Quality in Ecuador: A Deep Dive Using Satellite Data and ENVI® Software

1/21/2025

The COVID-19 pandemic drastically altered daily life, leading to unexpected environmental changes, particularly in air quality. Ecuador, like many other countries, experienced significant shifts in pollutant concentrations due to lockdown measures. In collaboration with Geospace Solutions and Universidad de las Fuerzas Armadas ESPE,... Read More >

Rapid Wildfire Mapping in Los Angeles County

Rapid Wildfire Mapping in Los Angeles County

1/14/2025

On January 8, WorldView-3 shortwave infrared (SWIR) imagery captured the ongoing devastation of the wildfires in Los Angeles County. The data revealed the extent of the burned areas at the time of the capture, offering critical insights for rapid response and recovery. To analyze the affected region, we utilized a random forest... Read More >

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Dynamic Plots Using an Equation Function

Anonym

This blog post continues to explore the Dynamic Visualizations available using the Equation argument on the PLOT function. In this example, we explore the use of a function name rather than an equation string. See Dynamic Plots Using an Equation String for the first article in this series.

Using an equation string has some limitations:

  • You can only have a single statement
  • You cannot easily change the equation unless you set a new string
  • You cannot pass parameters into your equation

As a different approach, create an IDL function containing your equation and then pass the function name to the Equation argument. This method allows you a bit more flexibility in your input equations.

For example, in the first line of the code above, we could have simply written:

p1= PLOT('LambertW', '2', DIMENSIONS=[400,400],$

  NAME='Upperbranch', $

  TITLE='LambertW Function', XRANGE=[-0.4, 2])

 

Notice that we no longer have an X variable in our equation, we just have the name of the function. We can also create our own routine which accepts our X vector and some optional user data.

First, create a new IDL routine called ex_plot_function and save it in a file ex_plot_function.pro on IDL's path:

FUNCTIONex_plot_function, x, k

COMPILE_OPTIDL2

RETURN,LAMBERTW(DCOMPLEX(x), k)

END

 

Next, we create our plot visualization, passing in the name of our equation along with our user data containing the "branch" parameter k:

 

p1= PLOT('ex_plot_function', '2', DIMENSIONS=[400,400],$

 

NAME='k= 0', EQN_USERDATA=0, $

TITLE='$\Re${LambertW}',XRANGE=[-1, 2])

p2r= PLOT('ex_plot_function', '2r', /OVERPLOT, $

NAME='k= -1', EQN_USERDATA=-1)

p3r= PLOT('ex_plot_function', '2g', /OVERPLOT, $

NAME='k= 1', EQN_USERDATA=1)

p4r= PLOT('ex_plot_function', '2b', /OVERPLOT, $

NAME='k= 2', EQN_USERDATA=2)

lg= LEGEND(/DATA, POSITION=[1.9, -4], LINESTYLE=6, SHADOW=0)

 

Our plot should now look like the following:

Again, we can pan and zoom around the plot, and IDL will automatically update the equations.

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