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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!



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 >

Not All Supernovae Are Created Equal: Rethinking the Universe’s Measuring Tools

Not All Supernovae Are Created Equal: Rethinking the Universe’s Measuring Tools

6/3/2025

Rethinking the Reliability of Type 1a Supernovae   How do astronomers measure the universe? It all starts with distance. From gauging the size of a galaxy to calculating how fast the universe is expanding, measuring cosmic distances is essential to understanding everything in the sky. For nearby stars, astronomers use... Read More >

Using LLMs To Research Remote Sensing Software: Helpful, but Incomplete

Using LLMs To Research Remote Sensing Software: Helpful, but Incomplete

5/26/2025

Whether you’re new to remote sensing or a seasoned expert, there is no doubt that large language models (LLMs) like OpenAI’s ChatGPT or Google’s Gemini can be incredibly useful in many aspects of research. From exploring the electromagnetic spectrum to creating object detection models using the latest deep learning... Read More >

From Image to Insight: How GEOINT Automation Is Changing the Speed of Decision-Making

From Image to Insight: How GEOINT Automation Is Changing the Speed of Decision-Making

4/28/2025

When every second counts, the ability to process geospatial data rapidly and accurately isn’t just helpful, it’s critical. Geospatial Intelligence (GEOINT) has always played a pivotal role in defense, security, and disaster response. But in high-tempo operations, traditional workflows are no longer fast enough. Analysts are... Read More >

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A cool visualization with (New) Graphics

Anonym

Matt Trawick, an associate professor of physics at the University of Richmond, develops atomic force microscopy techniques for use in studying various nanostructures. He used C++ and IDL 8 to analyze his data and produce, with (New) Graphics, this visualization:

Matt Trawick: aligning scans from an atomic force microscope

Here’s Prof. Trawick’s description:

The blue and yellow surfaces are two different scans of a sample (a thin gold film deposited on mica) made with an atomic force microscope, which operates by physically rastering a sharp tip across a sample surface. All units in the figure are in nanometers. When originally taken, the two scans were distorted (stretched, skewed, and tilted) by about 100 nanometers due to positional drift in the microscope, a common problem caused by, for instance, environmental temperature change during imaging. The two distorted scans were corrected, independently, using a new technique I have developed in my laboratory. The purpose of this graphic is to show the extent to which these corrected images are aligned. The vector annotations show the residual in-plane (black) and perpendicular (red) displacement of the top image for each of the square regions shown. The lengths of the arrows are exaggerated by 40x relative to their respective scales on the graph. All numerical analysis of these corrected scans was performed in IDL.

Thanks, Matt! If you’ve made a cool visualization with IDL that you’d like to share, please let me know and I’ll post it, along with a description.

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