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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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Shining a Little Light on Vegetation Indices

Anonym

Vegetation interacts with solar radiation in a different way than other natural materials. The vegetation spectrum typically absorbs in the red and blue wavelengths, reflects in the green wavelength, strongly reflects in the near infrared wavelength (NIR), and displays strong absorption properties in wavelengths where atmospheric moisture is present. The unique properties of vegetation have allowed spectral scientists to develop a number of vegetation indices (VIs) to aid in monitoring the health of vegetation. VIs are combinations of surface reflectance at two or more wavelengths designed to extract useful information about vegetation. More than 150 unique VIs have been developed and published in scientific literature over the past several decades. Many VIs are currently unknown or under-used in commercial, government and scientific communities.

Vegetation Spectrum, ENVI

Perhaps the most common, and most often used VI, is the Normalized Difference Vegetation Index (NDVI). The NDVI is a simple, but effective VI for quantifying vegetation. The NDVI normalizes green leaf scattering in the near-infrared wavelength and chlorophyll absorption in the red wavelength. The NDVI is defined by the following equation:

NDVI = (NIR – RED) / (NIR + RED)

NDVI values range from -1 to 1, with the common range for green vegetation falling between values of 0.2 and 0.8.  While the NDVI is likely the most common VI, there are a number of other VIs that are worth exploring when using satellite imagery to monitor vegetation. When choosing the appropriate VI to use, it is important to consider what you are interested in getting out of your data. For instance, if you are interested in performing a fire fuel analysis, there are a number of VIs that have been specifically designed to provide an estimate of the amount of carbon in dry states of lignin and cellulose.  Dry carbon molecules are present in large amounts in woody materials and senescent, dead, or dormant vegetation.  These materials are highly flammable when dry. Dry or senescent carbon VIs use reflectance measurements in the shortwave infrared range to take advantage of known absorption features of cellulose and lignin. One such example of a VI that takes advantage of these features is the Cellulose Absorption Index (CAI). The CAI is useful for identifying exposed surfaces containing dry plant material. CAI is defined by the following equation:

CAI = 0.5(2000nm +2200nm) - 2100nm

The value range of this index ranges from -3 to more than 4, with the common range for green vegetation falling between values of -2 to 4. If you are interested in learning more about VIs and how you can use them to get the information you need from your data, you just might be in luck. I have been working with a colleague to put together a whitepaper that outlines 27 of the most commonly-used VIs and will share it soon!

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