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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!



New ENVI Agent, IDL Agent, and GeoAgent Quick Guides

New ENVI Agent, IDL Agent, and GeoAgent Quick Guides

6/9/2026

The recent release of ENVI® Agent, IDL® Agent, and GeoAgent™ revolutionize how users interact with geospatial software. These agentic AI applications act as partners to plan, simplify, and execute complex workflows. Knowing where to start can be challenging for new users. To this end, we developed three new quick guides to... Read More >

Introducing NISAR Data Support

Introducing NISAR Data Support

6/5/2026

The release of ENVI® SARscape 6.3 in April 2026 includes preliminary support for NASA-ISRO SAR (NISAR) data. The NISAR mission is a joint Earth-observing satellite project between NASA and the Indian Space Research Organization designed to monitor changes in the planet’s land and ice surfaces using advanced radar imaging. It... Read More >

Monitoring Illegal Mining in the Amazon: Turning Persistent Data Into Actionable Insight

Monitoring Illegal Mining in the Amazon: Turning Persistent Data Into Actionable Insight

5/28/2026

Illegal mining over decades has constituted one of the most persistent and complex socio-environmental problems in the Brazilian Amazon. In recent years, with the increasingly intensive use of mechanized extraction, the associated environmental impacts—such as deforestation, intense soil disturbance, river siltation, and mercury... Read More >

From Answers to Action: Why ENVI and IDL Agents Go Beyond General AI

From Answers to Action: Why ENVI and IDL Agents Go Beyond General AI

4/20/2026

As generative AI tools like Claude and Gemini continue to gain traction, many organizations are asking the same question: Can general purpose AI actually support real geospatial workflows, or does it stop at surface-level answers? That question was front and center in our recent webinar, Meet Your New Partners in Science: ENVI... Read More >

Mapping Earthquake Deformation in Taiwan With ENVI

Mapping Earthquake Deformation in Taiwan With ENVI

12/15/2025

Unlocking Critical Insights With ENVI® Tools Taiwan sits at the junction of major tectonic plates and regularly experiences powerful earthquakes. Understanding how the ground moves during these events is essential for disaster preparedness, public safety, and building community resilience. But traditional approaches like field... 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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