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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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What the *bleep* is IDL doing? Creating variables

Anonym

The IDL language has many features which allow for quick and simple programming.  For example, say you have an INT array and you need to append a value to it:

intarray = [intarray,42]

 

Quick.  Simple.  However, just because you can do this doesn't mean you should.  Let's examine what is happening in the statement:

intarray = [intarray,42]

 

First, IDL has to create a temporary array to hold intarray and the new value.  Then, IDL copies intarray into the temporary and adds 42 to the end of it.  Finally, it has to free the old intarray variable.  Creating a temporary variable is an expensive operation.  As such, you should always be mindful when operations will create temporary variables.  Take for example creating an integer array of fixed length with some initial value using array appending.

print, 'Creating array by appending'

tic

length=100000l

a=[]

for i=0l,length-1 do a=[a,42]

toc

 

Which completes in:

% Time elapsed: 1.4720001 seconds.

While the append functionality gives the flexibility to add an element to an array, the time to create the temporary makes this approach extremely impractical.  However, if we need a dynamic array which elements and be added and removed as needed, consider using LIST. 

print, 'Creating array by list'

tic

length=100000l

l=list()

for i=0l, length-1 do l.add, 42

a=l.toarray()

toc

 

Which completes in:

% Time elapsed: 0.15200019 seconds.

LIST's avoid duplicating the entire array every time you add an element.  This is especially important when you are dealing with dynamic data.  However, if we know how long our array should be we can use IDL's array creation functions to drastically increase performance. 

print, 'Creating array by preallocate'

tic

length=100000l

a=intarr(length,/nozero)

for i=0l, length-1 do a[i]=42

toc

 

Which completes in:

% Time elapsed: 0.0060000420 seconds.

In this case we can speed up our processing even more.  Since we are initializing each element of our array to the same value, we can improve our performance even more by using the MAKE_ARRAY function.

print, 'Creating array by vectorized solution'

tic

length=100000l

a=make_array(length,value=42)

toc

 

Which completes in:

% Time elapsed: 0.00000000 seconds.

There are many way to accomplish any given task in IDL.  However, each method has its unique advantages and disadvantages.  By understanding what you are trying to accomplish and what IDL has to do under the hood to perform an operation, you can dramatically decrease the time it takes your code to run.

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