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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!



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 >

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 >

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Creating timestamps with sub-second accuracy

Anonym

The TIMESTAMP function in IDL is good when you need to write log files and chronologically sort entries from multiple files. However, a common problem is that the number of digits is not enough when code runs quickly. This alternative routine shows how to improve timestamps into fractions of seconds. On Windows,"systime" is normally limited to about 1ms. But on Linux the accuracy can be closer to 1 microsecond.

 

Here is a comparison of the standard TIMESTAMP function and the output from the improved accuracy TIMESTAMP2 function.

ENVI> print,(t=timestamp()) & for i=0, 299 do if t ne timestamp() then print, (t=timestamp())

2014-08-27T21:31:30.00004827976228Z

ENVI> print,(t=timestamp2()) & for i=0, 299 do if t ne timestamp2() then print, (t=timestamp2())

2014-08-27T21:31:41.808

2014-08-27T21:31:41.809

2014-08-27T21:31:41.810

2014-08-27T21:31:41.811

2014-08-27T21:31:41.812

2014-08-27T21:31:41.813

2014-08-27T21:31:41.814

2014-08-27T21:31:41.815

2014-08-27T21:31:41.816

2014-08-27T21:31:41.817

 

For TIMESTAMP2 the update rate is about 1ms running on a Windows 7 OS in this case. The following is a listing of the source code for the TIMESTAMP2 function:

function timestamp2

 compile_opt idl2,logical_predicate

 t = systime(1)

 str = systime(0, floor(t), /utc)

 td = 0d

 reads, str, td, format='(c())'

 td += (t-floor(t))/(24*3600d)

 tstr = string(td, format='(c(cyi4.4,"-",cmoi2.2,"-",cdi2.2,"T",cHi2.2,":",cmi2.2,":",csf06.3))')

 return, tstr

end

 

 

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