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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!



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 >

Geo Sessions 2025: Geospatial Vision Beyond the Map

Geo Sessions 2025: Geospatial Vision Beyond the Map

8/5/2025

Lidar, SAR, and Spectral: Geospatial Innovation on the Horizon Last year, Geo Sessions brought together over 5,300 registrants from 159 countries, with attendees representing education, government agencies, consulting, and top geospatial companies like Esri, NOAA, Airbus, Planet, and USGS. At this year's Geo Sessions, NV5 is... Read More >

Not All Supernovae Are Created Equal: Rethinking the Universe’s Measuring Tools

Not All Supernovae Are Created Equal: Rethinking the Universe’s Measuring Tools

6/3/2025

Rethinking the Reliability of Type 1a Supernovae   How do astronomers measure the universe? It all starts with distance. From gauging the size of a galaxy to calculating how fast the universe is expanding, measuring cosmic distances is essential to understanding everything in the sky. For nearby stars, astronomers use... Read More >

Using LLMs To Research Remote Sensing Software: Helpful, but Incomplete

Using LLMs To Research Remote Sensing Software: Helpful, but Incomplete

5/26/2025

Whether you’re new to remote sensing or a seasoned expert, there is no doubt that large language models (LLMs) like OpenAI’s ChatGPT or Google’s Gemini can be incredibly useful in many aspects of research. From exploring the electromagnetic spectrum to creating object detection models using the latest deep learning... Read More >

From Image to Insight: How GEOINT Automation Is Changing the Speed of Decision-Making

From Image to Insight: How GEOINT Automation Is Changing the Speed of Decision-Making

4/28/2025

When every second counts, the ability to process geospatial data rapidly and accurately isn’t just helpful, it’s critical. Geospatial Intelligence (GEOINT) has always played a pivotal role in defense, security, and disaster response. But in high-tempo operations, traditional workflows are no longer fast enough. Analysts are... Read More >

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Testing parameters with N_ELEMENTS and !null

Anonym

The N_ELEMENTS function is typically used to test whether an input parameter has data. For example, here's a program that doubles a number:

function double_it, x
   compile_opt idl2
   on_error, 2

   if n_elements(x) eq 0 then $
      message, 'Need input number to double.'

   return, x*2
end

N_ELEMENTS is used to test whether the user actually passed anything when calling DOUBLE_IT. If not, an error message is thrown:

IDL> a = double_it(4)
IDL> print, a
           8
IDL> b = double_it()
% DOUBLE_IT: Need input number to double.
% Execution halted at: $MAIN$

In IDL 8, we have the option of instead comparing parameters with the null variable!null. In DOUBLE_IT, this looks like:

function double_it, x
   compile_opt idl2
   on_error, 2

   if x eq !null then $
      message, 'Need input number to double.'

   return, x*2
end

Now, which is faster: using N_ELEMENTS or !null? Here's a simple test program:

pro test_nullparameter, param
   compile_opt idl2

   n_iter = 1e7

   t0 = systime(/seconds)
   for i=1, n_iter do a = n_elements(param) eq 0
   t1 = systime(/seconds)
   print, 'N_ELEMENTS:', t1-t0, format='(a15,f12.8,1x,"s")'

   t0 = systime(/seconds)
   for i=1, n_iter do a = param eq !null
   t1 = systime(/seconds)
   print, '!null:', t1-t0, format='(a15,f12.8,1x,"s")'
end

and here's a sample result from my laptop:

IDL> test_nullparameter
    N_ELEMENTS:  1.07800007 s
         !null:  0.84400010 s

It turns out that it's more efficient to compare against !null. The syntax is more compact, too. (Thanks to Jim Pendleton, who initially pointed out this to me.)

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