Dr. Anna Klene, a Professor of Geography at the University of Montana, has a long history with data visualization tools. She’s putting that history to work in the classroom, using Surfer and Grapher to train the next generation of geoscientists. And with both software available, her master’s students have what they need to process and visualize vital permafrost data that’s helping modelers, engineers, and communities alike make informed decisions for the future.

When Dr. Klene was hired at the University of Montana, she was excited to learn that her department already had access to Surfer and Grapher, as she had used both tools since her master’s student days. In fact, upon getting hired, she discovered that the University of Montana shared a unique, long-standing connection with Golden Software. 

“Pat Madison was a co-founder of Golden Software, and his dad worked in the university’s old Journalism Building (now Stone Hall) running the printing press,” Dr. Klene explained. “When the school built a new Journalism building, the geography department moved into the old one, but the printing press stayed there because they couldn’t get it out without taking it apart. So there are deep roots of Golden Software being in this building and on campus.”

It’s this long tradition that has given Dr. Klene the opportunity to introduce Surfer and Grapher to her master’s students so they have real-world experience using tools that will help them process and visualize data effectively.

The data that Dr. Klene and her students work with is complex and critical to science and engineering. Their research focuses on permafrost in northern Alaska, specifically the active layer, which is the upper part of the ground that freezes and thaws annually above the permanently frozen permafrost.

To get the necessary data, the measurement process is straightforward: insert a metal rod into the ground until it hits the hard frozen permafrost table. At their research sites, the permafrost table can be quite shallow, sometimes just 30 centimeters, or it can reach two meters or more under shallow lakes. The main challenge, however, is the high spatial variability of the active layer. It can vary by more than 100% within just 2 meters due to differences in soil thermodynamics, vegetation, and the thermal insulation provided by the thick moss layer and snow accumulation.

Because of this complexity, Dr. Klene and her students often use transects or grids when collecting data for processing in Surfer. On the coastal plain, the variability is more predictable, which makes gridding a reasonable approach. But in the southern part of the study area, Dr. Klene and her students know they are interpolating from a sampling of points to make their estimates due to the extremely complicated local-scale conditions.

While complex, Dr. Klene and her students’ research is a piece of a larger and necessary mission. Dr. Klene is one of five Principal Investigators on the Circumpolar Active Layer Monitoring (CALM) NSF grant, and she and her students are part of a collaborative team that includes professors, researchers, and students at George Washington University, Northern Michigan, and the University of Alaska Fairbanks. The grant supports the team’s research in northern Alaska as well as coordinating the international CALM network, which archives standardized data from over 250 sites in more than 15 countries around the world, including the data gathered by students at the University of Montana and other institutions. All sites use consistent sampling methods, which ensure data quality for the international user base. Additionally, this standardized, publicly available data is held in a central archive with other permafrost records for worldwide use as part of the Global Terrestrial Network for Permafrost. 

Funded since the mid-1990s, CALM provides a crucial, long-term record, and maintaining it demands annual updates. Dr. Klene and her students focus on measuring the maximum thaw depth, which generally occurs in August each year at their sites. Doing the measurements requires an annual trip to the field every summer, which offers valuable opportunities for her students to gain hands-on experience collecting data in the Arctic. The primary users of this CALM data are atmospheric and ecosystem modelers who pull the long-term records. However, due to the high spatial variability, modelers often use the mean values for their coarser-scale simulations.

In addition, the CALM data also has significant real-world applications for the following:

• Engineers: The data provides critical parameters for construction, which is why organizations, including oil and gas companies, rely on it.
• Communities: Arctic communities use the data to monitor and ensure the stability of their buildings as the permafrost thaws.

Together, Dr. Klene and her students, as well as their national and international collaborators, all work to gather data to update and maintain the archive, so it continues to be useful in empowering informed decision-making.

For geoscientists and hydrologists, identifying and mapping sinkholes is a critical step in a wide range of projects, from managing natural hazards to protecting sensitive cave environments. Paul Burger, Regional Hydrologist for the National Park Service in Alaska, knows this better than most. For years, he has relied on Surfer to perform rapid assessments of sinkholes, leveraging its peaks and depressions map type to quickly visualize the landscape and determine what deserves a more in-depth review.

Paul’s journey with Surfer began decades ago, during his graduate school days. His initial use of the software was for his thesis work in Central Colorado, a region known for its extensive cave and karst systems. In the early days, with only coarse DEM data available, the peaks and depressions map type equipped him to take a stab at identifying areas with many sinkholes. 

Today, with the growing availability of high-resolution LiDAR data, identifying sinkholes is significantly easier. There are some project areas in Alaska where Paul can rely on available LiDAR, equipping him to create sharp and precise visualizations. However, even when LiDAR data isn’t available in certain areas in Alaska, Paul still finds that he can create a peaks and depression map that delivers a good look at the landscape—and do it very quickly.

“The thing I like about Surfer is that it has a really easy workflow,” Paul said. “You basically push one button, and it gives you the peaks and depressions. For identifying sinkholes, Surfer is super quick at picking those out.”

To illustrate the ease and efficiency of Surfer, Paul shared a peaks and depressions map he created of an area in Colorado. The map showed major and minor depressions of the terrain, but the minor ones had more to do with the glacial topography than actual caves and karst. In glacial areas, it’s common for chunks of ice to sit on the landscape, leading to small depressions and a kettle-type terrain. That said, Paul didn’t pay the minor depressions much attention. Instead, his focus was on quickly assessing the major depressions. 

“By looking at this map, you can see that Surfer does a really good job of picking out the major features,” Paul explained. “All of these major features are truly sinkholes, some of which have caves in them. Surfer is really nice at doing this rapid assessment work.”

This rapid assessment is invaluable for projects requiring a quick overview. Paul recounted a time when he created a peaks and depressions map in Surfer to help a national agency. The organization was planning a logging operation and needed to identify sensitive areas to create buffer zones. 

“The one thing you don’t want to do is major clear-cutting around the edges of sinkholes because it leads to increased erosion and sediment going into the system, which can harm the caves and the cave environment,” Paul said. “So, the agency wanted to create buffer zones around some of these features, and I worked with them on this.”

With the peaks and depressions map type in Surfer, Paul provided a visualization that delivered a high-level overview of the project area. This gave the agency quick insight into where sinkholes were located. However, to provide an even more detailed analysis, Paul used another software to highlight the sinkholes’ depths by color. That way, stakeholders knew which ones truly needed buffer zones. 

“With my workflow, I take the data and create a snapshot of what things look like using Surfer. Then, I use a bigger software package to provide that more detailed look at things,” Paul explained. “So, usually, it starts with Surfer—and then I do the detailed analysis on another platform.”

This is especially true when Paul is handling a large dataset and needs to perform a quick analysis. On other platforms, he has to go through an extensive, multi-step process to achieve the same result that Surfer provides in a single click. 

“In bigger packages, you’re doing all that data processing with each step,” Paul said. “Then, you have to subtract layers and do things to create a map that shows the depressions’ depths. It’s a multi-step process that’s way more cumbersome in other platforms versus one click in Surfer that gives me a pretty quick answer that I can analyze closer in the bigger package. As far as a quick, cost-effective analysis, Surfer definitely beats the bigger package hands down, so it’s great to start in Surfer and then use the other tool for the few remaining steps.”

Environmental projects depend on more than collecting accurate data; they depend on communicating it clearly. Whether you’re mapping subsurface contamination, modeling terrain, or tracking changes over time, the datasets behind these efforts are often large, layered, and complex, making them difficult to effectively convey to stakeholders.

For years, 2D maps have been the standard way to communicate that data, but these visuals often fall flat. Traditional maps force stakeholders to imagine depth, volume, and movement instead of seeing them realistically, making it harder to understand risks or opportunities with confidence. Fortunately, 3D visualization changes that reality.

By turning complex environmental data into realistic, spatially accurate visuals, 3D helps stakeholders clearly see what’s happening both above and below the surface. This ensures a better understanding of site conditions and stronger project outcomes for stakeholders. In fact, here are just some of the most impactful ways 3D visualization enhances clarity to ensure stakeholders get good results.

If you own a geoscience firm, chances are you didn’t get into this line of work just for the paycheck. You’re probably here because you care about the work—you enjoy solving difficult environmental problems, being outside, working with data, and, most of all, making a meaningful impact. Your projects help clean up polluted sites, reduce future risk, and shape better decision-making for clients. That’s real value.

But that value isn’t always easy to communicate when your client is staring at another cost estimate for additional analysis. You might be confident that running another survey or drilling another well is necessary to solve the problem, but your clients may be thinking: “What’s the point? Isn’t what we have already enough?” Here’s the truth: If you believe more analysis is needed to do the job right, then it’s your responsibility to help decision-makers understand why.

Contamination plumes pose significant challenges for environmental scientists and engineers working on remediation projects. Accurately assessing and managing these plumes is crucial to effective cleanup and protection of groundwater resources. One technique for evaluating the effectiveness of remediation efforts is the Ricker Method®.