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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!



NV5 at ESA’s Living Planet Symposium 2025

NV5 at ESA’s Living Planet Symposium 2025

9/16/2025

We recently presented three cutting-edge research posters at the ESA Living Planet Symposium 2025 in Vienna, showcasing how NV5 technology and the ENVI® Ecosystem support innovation across ocean monitoring, mineral exploration, and disaster management. Explore each topic below and access the full posters to learn... Read More >

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 >

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IDL's Lambda Function Examples

Anonym

The Lamba function concept was introduced in IDL 8.4. I found that using a Lambda function can result in fewer lines of code and save coding time. However, IDL's Lambda function does not create the most optimal code. Although in my experience, the same is also true for other languages. While the syntax can look very short and concise, the execution time and memory use is not optimal.

Here are some examples of using a Lambda function in conjunction with Map, Filter, Reduce, as well as the FOR loop versions for comparison.

First create some data to use for the remainder of the examples.

 ;Create some test data in a string array of 1400 lines

 ;containing various comma separated numbers

 str = strjoin(strtrim(fix(bindgen(8,1400)),2),',')

This is an example of splitting all the strings on the commas using Map.

 ;split on comma and place the result in another array

 a = str.map(lambda(x:x.split(',')))

 

 ;exactly the same result using a loop

 b = strarr(8,1400)

 for j=0,1399 do b[0,j] = str[j].split(',')

 

The next example is using Filter to return only strings that have a '10' in the 3rd column:

 ;Filter to only keep lines with '10' in 3rd column

 c = str.filter(lambda(x:(x.split(','))[2] eq '10'))

 

 ;Use For and list

 d = list()

 for j=0,1399 do if (str[j].split(','))[2] eq '10' then d.Add, str[j]

 d = d.ToArray()

The final example uses Reduce to return the maximum of the individual totals for each string:

 ;Use Reduce to find the maximum total

 m = str.reduce(lambda(x,y:isa(x,/string)?total(long(x.split(',')))>total(long(y.split(','))):x>total(long(y.split(',')))))

 

 ;Using for loop

 maxtot = -999

 for j=0,999 do begin

   tot = total(long(str[j].split(',')))

   if tot gt maxtot then maxtot = tot

  endfor

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