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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!



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 >

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

10/13/2025

On July 24, 2025, a unique international partnership of SaraniaSat, NV5 Geospatial Software, BruhnBruhn Innovation (BBI), Netnod, and Hewlett Packard Enterprise (HPE) achieved something unprecedented: a true demonstration of cloud-native computing onboard the International Space Station (ISS) (Fig. 1). Figure 1. Hewlett... Read More >

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Nesting a hash within itself

Anonym

Lists and hashes have always been one of my favorite tools in IDL due to their versatile nature. A cool trick is that a hash can be stored recursively within itself. For example:

 

h = hash()
h['myself'] = h

 

With only level, this may not be particularly useful. However, this trick can be powerful for creating loops of information. Take days of the week, for instance. For fun, I'll use a DICTIONARY instead of a traditional hash, which has the convenience of the dot syntax for access.

 

Monday = dictionary('today', 'Monday')
Tuesday = dictionary('today', 'Tuesday')
Wednesday = dictionary('today', 'Wednesday')
Thursday = dictionary('today', 'Thursday')
Friday = dictionary('today', 'Friday')
Saturday = dictionary('today', 'Saturday')
Sunday = dictionary('today', 'Sunday')

 

Now define each day's tomorrow:

 

 

Monday.tomorrow = Tuesday
Tuesday.tomorrow = Wednesday
Wednesday.tomorrow = Thursday
Thursday.tomorrow = Friday
Friday.tomorrow = Saturday
Saturday.tomorrow = Sunday
Sunday.tomorrow = Monday

 

 

We can now loop through these days indefinitely. If we take Monday and request "tomorrow" seven times, we get Monday back again:

 

Next_Monday = Monday.tomorrow.tomorrow.tomorrow.tomorrow.tomorrow.tomorrow.tomorrow

 

We can store additional information in each of these hashes/dictionaries, such as a schedule for each day. 

 

Monday.Morning = 'Math 251, 9:00-10:00, Room 304'
Tuesday.Morning = 'Writing 301, 10:00-11:30, Room 211'

etc.

If today = Monday, then we can get today's morning schedule calling today.Morning. At the end of the day on Monday, we can say today = today.tomorrow, and tomorrow is the new today. Likewise, if we want today's morning schedule, we call today.Morning

Loops, routines, and cycles, are very common in the world as well as in scientific data. This method of information storage can be used for displaying radar data loops, with each frame stored in a hash that contains a "previous" and "next" frame. Additionally, it could be used for modeling states of pendulum or circular motion. It can be used for storing geographic information, such as time zones containing UTC offsets. There are probably many additional use cases.

As always, use caution with recursion. It is always unfortunate to find yourself killing code because it is stuck in an infinite loop. That said, be aware that JSON_SERIALIZE will not work in the examples above. Fortunately, given this use-case, there is no significant need to serialize the hashes' information into a string.

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