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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!



Mapping Earthquake Deformation in Taiwan With ENVI

Mapping Earthquake Deformation in Taiwan With ENVI

12/4/2025

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 >

Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

12/3/2025

Large commercial SAR satellite constellations have opened a new era for persistent Earth monitoring, giving analysts the ability to move beyond simple two-image comparisons into robust time series analysis. By acquiring SAR data with near-identical geometry every 24 hours, Ground Track Repeat (GTR) missions minimize geometric decorrelation,... Read More >

Empowering D&I Analysts to Maximize the Value of SAR

Empowering D&I Analysts to Maximize the Value of SAR

12/1/2025

Defense and intelligence (D&I) analysts rely on high-resolution imagery with frequent revisit times to effectively monitor operational areas. While optical imagery is valuable, it faces limitations from cloud cover, smoke, and in some cases, infrequent revisit times. These challenges can hinder timely and accurate data collection and... Read More >

Easily Share Workflows With the Analytics Repository

Easily Share Workflows With the Analytics Repository

10/27/2025

With the recent release of ENVI® 6.2 and the Analytics Repository, it’s now easier than ever to create and share image processing workflows across your organization. With that in mind, we wrote this blog to: Introduce the Analytics Repository Describe how you can use ENVI’s interactive workflows to... Read More >

Deploy, Share, Repeat: AI Meets the Analytics Repository

Deploy, Share, Repeat: AI Meets the Analytics Repository

10/13/2025

The upcoming release of ENVI® Deep Learning 4.0 makes it easier than ever to import, deploy, and share AI models, including industry-standard ONNX models, using the integrated Analytics Repository. Whether you're building deep learning models in PyTorch, TensorFlow, or using ENVI’s native model creation tools, ENVI... Read More >

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A column sort routine

Anonym

In spreadsheet programs like Excel or LibreOffice, you can apply a sort on a column to every other column in the spreadsheet. IDL's SORT function doesn't provide this functionality, but with a little code, we can make it so. The function COLSORT (get the source code here) accepts a 2D array and the zero-based index of the column to sort on. By default, values are sorted in ascending order; a keyword can be set to sort in descending order. Here's an example of how the routine works. Start with a 4 x 5 array of numbers:

IDL> a = round(randomu(seed, 4, 5) * 20.0)
IDL> print, 'Original array:', a, format='(a,/,4(i))'
Original array:
           8           6          14          10
           4           9          18           5
           1          11          13          18
           8           9          11           9
           3          19           4          16

Use COLSORT to perform a reverse sort on column index 1 (the second column) and extend the sort to the other columns in the array:

IDL> sort_index = 1
IDL> b = colsort(a, sort_index, /reverse_sort)

Check the result:

IDL> print, 'Sorted (descending) array:', b, format='(a,/,4(i))'
Sorted (descending) array:
           3          19           4          16
           1          11          13          18
           8           9          11           9
           4           9          18           5
           8           6          14          10

This program could be extended to apply to rows and to arrays of higher dimensionality.

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