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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

12/15/2025

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 >

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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Burn Severity Analysis of the Chelaslie River Forest Fire

Anonym

In my previous blog post back in January of this year I discussed "Using SWIR and LWIR Imagery to Analyze Forest Fires" which involved using Landsat 8 OLI/TIR data to analyze the Chelaslie River forest fire in British Columbia last summer (2014). In the earlier blog post I describe utilization of ENVI's Spectral Indices tool to compute the Normalized Burn Ratio (NBR) index for a scene that was acquired while the fire was still actively burning. As I mentioned in this previous blog post "the real power of the Normalized Burn Ratio spectral index is exhibited when you create pre-fire and post-fire NBR images then subtract the post-fire NBR raster from the pre-fire NBR raster to create a Differenced Normalized Burn Ratio (DNBR) image that indicates burn severity". However, at that time I was unable to find a good post-fire Landsat scene as most had either clouds or snow obscuring the burned areas.

Now that several months of summer 2015 have passed it occurred to me that it's worth another search of the Landsat archive available on USGS EarthExplorer to see if a new scene is available that provides a good post-fire capture of the Chelaslie River forest fire area. As luck would have it Landsat 8 acquired a nice cloud-free (at least over the fire area) scene just in the past month on 05 July 2015 that happens to be the same exact path/row as a pre-fire Landsat 7 scene acquired on 09 July 2002. The DNBR index can be calculated using a series of simple processing steps followed by the PreFireNBR - PostFireNBR equation which can easily be executed using the Band Math tool within the ENVI software.

Here's a quick high-level synopsis of the processing steps:

  • Open both pre-fire and post-fire Landsat datasets
  • Run the Radiometric Calibration tool
  • Calibrate both datasets into top-of-atmosphere (TOA) at-sensor reflectance
  • Run the Spectral Indices tool
  • Calculate the Normalized Burn Ratio index for both datasets
  • Run the Band Math tool
  • Enter simple "b1 - b2" subtraction expression
  • Map pre-fire NBR to "b1" and post-fire NBR to "b2"
  • Apply a raster color slice to the output DNBR raster
  • Convert the raster color slice to a classification image with specific class names & colors

Below is a screenshot of the DNBR classification overlaid on top of the post-fire Landsat image with class names based on the "FIREMON BR Cheat Sheet V4 (June 2004)" document.

Image data downloaded from USGS EarthExplorer

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