Everything is Connected: Exploring the Online M.S. in GIS and Spatial Analysis Program

If you ask Director of the Online Master’s Program in GIS and Spatial Analysis, Michael Harman, he’d tell you that GIS is everywhere. He explains that “At its core, GIS is about understanding relationships in physical space, patterns, boundaries, connections, and using that understanding to make better decisions more quickly” and as things become increasingly closely connected, there’s never been a more relevant field of study. With the support of the Geography and Geology department at WVU’s Eberly College of Arts and Sciences, Harman has helped build a top ten nationally recognized online program that has one focus: student outcomes.

We recently connected with Dr. Michael Harman about this program, the successes that have resulted from it, and why he cares so much about the work he does.

Can you give me some background on the M.S. in Geospatial Analysis program at WVU?

The Geographic Information Systems and Spatial Analysis, M.S. (GIS) program has been underway for a while. Some of the existing faculty in the department had wanted to do this for some time, but it's not always easy to get things like that moving through the University. After lots of work and effort, we got the program launched. I joined WVU to spearhead the program, but I can’t overstate the role the rest of the faculty in the department played in getting this up and running. The faculty here are incredibly diverse, experienced, and student focused. They designed the program. I just helped build it. They were the architects; I was the contractor.

One of the big milestones is that it’s the first online program of its kind in West Virginia. It was designed to train students in spatial analysis, geospatial technologies, remote sensing, programming, and data science. We have a strong emphasis on real-world problem solving. In the GIS community, masters students tend to make up the core of the workforce and look into new solutions to problems that don’t come with instructions. That’s hard to do with just a couple of undergraduate classes.

Most people who end up working in GIS come from backgrounds like natural sciences, geography, geology, or resource management, and they’ve had some exposure. But to become the kind of employee who can handle new, undefined problems, that’s really where master’s students come in.

Is that because it’s more research-based?

Not exactly. It’s more about exposure and repetition. More techniques, more hands-on practice, and a deeper understanding of the theories behind what you’re doing, developed through application. That’s what gets you to the point where, when someone says, “This is what we need to do, and we don’t know how,” your brain starts turning. You can think through options, test ideas, reject what doesn’t work, and eventually figure out a solution.

That mindset develops through repeated practice. I often describe learning GIS as a “sink or swim” type of thing. The process is intentionally iterative. A student will encounter difficulty, reflect on what went wrong, and try again. In the same way, GIS education requires students to engage with unfamiliar problems, not just step-by-step instruction.

That’s kind of what we do in GIS. We show you things, tell you things, and make you try them. If you don’t fully understand how something works, the best thing you can do is try it anyway even if you get it wrong. It’s important to learn why it didn’t work, and that’s incredibly powerful. You have to get past the fear of doing something incorrectly, because in the real world there’s not always a prescribed playbook or way to solve every problem. You’re going to try things, and it’s very unlikely you’ll get everything right the first time. What matters is understanding why something didn’t work and knowing how to pivot.

For someone new or unfamiliar with the field, what is GIS?

In my opinion, this is really the easiest way to understand what GIS is and take a practical route to get there. At its core, GIS works with two basic data types: raster and vector. Raster is the simpler one to picture. It’s just a grid. All raster data is the world explained in tiny little squares.

The way I usually describe working with raster data is it is like a stack of pancakes. Each pancake is one layer of information. One layer might be land cover, another might be elevation, and another might be zoning or ownership. If you stack up the layers, can do some amazing things

When we build models in GIS, all we’re really doing is stacking layers of information and doing math between them. We might add layers together, subtract them, multiply them or even sometimes divide them. But the idea is simple: we take multiple pieces of information, combine them, and create a brand-new information that didn’t exist before. And the values in that new layer aren’t just land cover or elevation anymore, they’re the result of all those things interacting.

One of the first concepts I teach students is something called a suitability model. And I start there because if you understand suitability modeling, you can model almost anything in GIS. We introduce it using a real example: the Northern West Virginia flying squirrel. It’s a threatened species that only lives in very specific conditions, like high elevations, certain forest types, limited human presence. And in a state like West Virginia, that combination doesn’t leave a lot of room.

The first layer we look at is land cover. Across the entire state, data exists that classifies every three-by-three-meter square (about nine square meters) by what’s on the ground there. Urban areas, forests, wetlands, shrubland, different forest types. There are about twenty categories in total, all derived from satellite imagery and remote sensing.

Once we have that layer, GIS lets us actually do something with it. We go through those land cover types and decide: Does this work for a flying squirrel habitat, or does it not? The simplest models are binary. One means yes, zero means no. You can’t have flying squirrel habitat in a city or a lake. That’s a hard line. We reclassify that land cover layer into a new one that’s just ones and zeros. One if it’s a forest type the squirrels prefer, zero if it isn’t.

The second layer is elevation. These flying squirrels are almost exclusively found above 900 meters. That means we have to take the elevation data for the state and apply a simple rule: if elevation is greater than or equal to 900 meters, it’s a one. Everything else is a zero.

Now here’s where the math matters. If you multiply those two layers together, only places where both conditions are met, it’s the proper elevation and the right forest type, the layer will remain a one. Everything else becomes zero. That doesn’t mean flying squirrels are there. It means the conditions exist for them to be there.

What you end up with is a new layer: a habitat suitability model. Potential habitat, or not.

From there, you can ask bigger questions. Which counties have the most suitable habitat? How much land does that represent? The software simply counts how many of those three-by-three-meter squares are ones instead of zeros, adds them up, and converts that area into something meaningful like acres, square miles, or whatever you need.

And if you take that same idea and apply it more broadly, you can use GIS to answer almost any spatial question. If a problem has a “where” component, this and similar modeling approaches work.

What are your thoughts on the future of the field?

I think GIS is becoming infrastructure. It’s becoming foundational in science, business, and physical infrastructure projects. Almost every problem you can imagine has some spatial component. At its core, GIS is about understanding relationships in physical space, patterns, boundaries, connections, and using that understanding to make better decisions more quickly.

You see this everywhere. Geopolitical borders, for example, moving an artificially constructed line can radically affect people who never moved at all. Gerrymandering is another case. Whether you’re trying to do it, prevent it, or fairly redistrict; GIS is the most efficient way to analyze and design those boundaries. Early oil prospectors used aircraft to look for large landscape features, a very intuitive form of GIS.

Even molecular biology has spatial components. With AI, researchers look at the shapes of molecules and how they interact, then design new molecules based on those patterns. Years ago, just for fun, I modeled a DNA double helix in a 3D GIS environment. These tools can reach into a lot of unexpected places.

What I find most exciting going forward is AI and machine learning. For years, we talked about these ideas theoretically, but they weren’t practical. Now, with cloud computing and modern GPUs, they are. I tried running a machine-learning model recently on a laptop without the right processor, it took over 11 hours. With the proper setup, it would’ve taken about 40 minutes. That’s the difference. The “one day” people talked about is here.

What really fascinates me, though, is voice interaction. If a system can understand what I’m saying and execute models based on that, then I don’t need to learn every piece of software, I need to understand the theory behind what I’m trying to do. That’s a massive shift. It reminds me of an old Star Trek movie where Scotty tries to talk to a computer and gets frustrated because it won’t respond to voice commands. I honestly don’t think we’re that far from that reality anymore.

There’s a concept in agronomy that a plant can only grow to its limiting nutrient. Technology is the same way. Some areas advance far beyond what we can use, while others lag behind. But when those lagging areas catch up, suddenly things that were impractical become routine. Machine learning has been discussed for decades, but until recently, almost no one had the computing power to actually use it. Now, it’s becoming commonplace.

What hard skills and technical tools will students learn in the program?

Students learn core geospatial theory, things like Tobler’s First Law of Geography, which says that everything is related, but things closer together are more related than things farther apart. That idea underpins spatial modeling, pattern analysis, and predictive work. We also teach programming, but not in the old “Hello World” sense. I can’t make someone fluent in a programming language in a semester, but I can teach them how it works and how to collaborate effectively with AI tools. Most GIS professionals don’t code every day, it’s more like few times a year.

In my classes we focus on prompt engineering, troubleshooting, and understanding why something works or doesn’t. On top of that, students learn data analysis and professional communication, like how to present results clearly and professionally.

How does the online format shape the student experience in this program?

The online format actually works really well for GIS. It’s like oil painting, you improve through practice, and it’s often solitary. Even in a classroom, students are focused on their screens. Online, students learn to solve problems independently, use resources effectively, and reach out when needed. In many ways, that accelerates skill development, doubling down on that “sink or swim” approach I described earlier. By the end of the program, students will have completed somewhere between 50 and 100 hands-on lab activities. Everything we do has a practical component. You cannot finish this program without developing the ability to actually do GIS. That’s something I’m incredibly proud of. There’s no way someone finishes this program and walks away without marketable skills. 

I’ve heard rumors about a project where students use what they’ve learned in class to try to find Bigfoot, can you tell me about that?

Yeah, this is actually a great story. When I was a faculty member at Northern Virginia Community College, I had a student who worked at a big federal agency. One of his coworkers sat in the cube next to him and was deeply obsessed with Bigfoot. So, the student comes to me and says, “This guy I work with is convinced Bigfoot is real.” And I said, “Well… are you sure he’s not?” And he goes, “Not you too.”

What he wanted to do, purely out of curiosity, was build a model that asked: If Bigfoot is real, where would he actually be? Because nobody’s shot one during hunting season, nobody’s hit one with a car, and nobody’s gotten a clear photo that can’t be discredited. So, if Bigfoot exists, he must be somewhere those things don’t happen.

He built a spatial model for California with some pretty specific criteria:

• Bigfoot has to be near water, everything needs water.
• It has to be in heavily forested areas, or we’d see it more often.
• There has to be wildlife for food.
• It can’t be near roads, or someone would’ve hit one by now.
• It can’t be in areas under constant development pressure, or there’d be human–wildlife conflict.

When you layer all of that together, you end up with a very small set of places where Bigfoot could exist (if he even exists at all). That project was never about proving Bigfoot is real. It was about learning how to build and defend a spatial model.

I’ve had other students do similarly whimsical projects. One group mapped UFO sightings in West Virginia. Another mapped Elvis sightings in West Virginia. Then they looked for correlations.

Now, important lesson here, correlation does not mean causation. You can map piracy rates and global warming and conclude, incorrectly, that pirates cause climate change. So I can’t confirm that Elvis is hanging out with aliens. It may just be that the same people who report UFO sightings are also prone to seeing Elvis. I don’t know.

But the point is, these projects can be hard. If a student can make it fun or a little absurd, that keeps them engaged, and they’re still learning the same core skills.

What kind of jobs will graduates of the program qualify for?

In my experience, the most common path is analyst. Entry-level positions are usually technician roles, doing the same task repeatedly. If our students take those jobs, it’s usually to get their foot in the door and move up to analyst roles, where they’re working on more complex problems.

From there, you can specialize, developers building tools, instructors and trainers, managers, consultants, planners. Initially, I even ran this through an AI and it gave me a list of seven different analyst titles. But at the root of it, you’re an analyst. You’re doing the same job, just with different data and for different purposes.

That’s one of the coolest things about GIS. It’s not a standalone industry. It’s a toolbox that every other industry uses. Sometimes people are experts in a field and learn GIS to support that work. Other times, people are GIS experts who apply their skills across many fields.

Most often, GIS is someone’s second core skill, or the field they work in becomes their second core skill. If you have a biology degree and GIS training, you’ll likely do biology-related GIS work. Not everyone is qualified for every job, but anyone with good GIS skills can do the work with the right subject-matter context.

What industries are most in need of GIS expertise right now?

Pretty much all of them! Government, utilities, natural resources, public safety, defense, healthcare, construction, agriculture, everything.

One of my favorite examples comes from the pandemic. Some people made a lot of money using remote sensing. They knew that companies that missed delivery deadlines would see their stock prices drop, so they looked at companies dependent on supply chains from China. They studied parking lots at manufacturing facilities using satellite imagery. If a factory claimed it was running at capacity, but the parking lot had two cars in it. That company wasn’t telling the truth, so they sold the stock.

The same thing happens in agriculture. If you understand agronomy, you can use remote sensing to estimate moisture levels, pollination success, and yield potential months before harvest. That lets people hedge risks and make smarter decisions.

How do you see demand for GIS professionals evolving in the next 5-10 years? What kinds of real-world problems are GIS professionals solving?

Demand over the next five to ten years is only going to increase. Spatial data is becoming central to decision-making. AI and automation amplify that. Even public-facing uses, school redistricting, utilities, infrastructure, are all GIS-driven. Take Loudoun County, Virginia. They start planning school assignments a year in advance. They look at demographics, ages, parcel-level data to make these assignments. One key thing, however, is they try to avoid redrawing boundaries, if possible, because every time you redraw a line, parents get upset. They use GIS to move resources instead of disrupting communities whenever they can. That work never stops. As soon as one school year starts, they’re already planning the next one.

Do you have any student success stories that stand out to you?

The program is still young, but I can tell you a few stories. I have a student at the National Geospatial-Intelligence Agency who told me that he learned more GIS in a handful of classes here than in 20 years of professional development there. Our first graduate works at the FBI. I have another student at Oak Ridge National Lab whose employer is paying for his degree. Cost wasn’t the deciding factor; he chose us because the curriculum fit his needs.

He takes one class a semester. It’ll take him over three years, and that’s fine. He’s learning exactly what he needs without disrupting his life. That flexibility matters.

What advice would you give to prospective students considering this program?

Pace yourself! The right pace is the one where you can actually learn. Don’t let calendars dictate your life. The difference between finishing in 18 months and finishing in three years, in the grand scheme of life, is nothing.

The right time is when it’s right for you. This program is affordable, flexible, and designed to fit into real lives, not force you to reshape your life around it.

We’ve had students from all over the country! About a year and a half into my role here at WVU, I found a ranking that listed us as the number 10 online GIS master’s program in the country. We didn’t pay for it. We weren’t notified. We just showed up on the list, ahead of programs like Penn State. I don’t know every metric they use, but I know this: they looked at the program, the University, and what we’re doing here. They thought it mattered and wanted to recognize us. It’s cool to say we’re a top ten online GIS program in the country. What’s even cooler is that it’s a faculty of one - me.

I’m confident saying this: even though the program is relatively new and even though we don’t yet have decades of job placement data, but we’re ranked among the best online GIS programs in the country. In both instances where we were ranked, they never reached out to me. I didn’t sell them anything. They didn’t ask me to buy anything. They just made the list, and we were on it. That says something about the work I’ve done, but just as importantly, it also reflects well on the work the faculty did before I ever got here. They built the program. They made sure the curriculum made sense. They gave me course materials and syllabi to work from. That foundation is what made this possible. Without that, none of this was possible.

"The right time is when it’s right for you. This program is affordable, flexible, and designed to fit into real lives, not force you to reshape your life around it." Dr. Michael Harman, Director of the Online Master’s Program in GIS and Spatial Analysis

Do you have any parting thoughts to share with our readers?

The part of this whole thing we’ve built that I am the proudest of is how we’re giving people opportunities that wouldn’t exist otherwise. That’s life changing. It affects careers, lifestyles, families. That’s a big responsibility, but it’s also a gift, because it gives meaning to what I do. I already care a lot about the University but knowing I can help people like that means everything.

A lot of us are first-generation. A lot of us didn’t come from academic families. That gives you a very different perspective. I know what it’s like to be on the other side of opportunity. I had to quit college after my first year. I worked a job I didn’t love and couldn’t quit because I had to pay for the truck that I had just bought. Eventually, I found out the factory that I had worked at was going to close. When it did, I used a federal retraining program to go back to school. I went fishing for two months, then started summer classes. That path is why I care about this.

At the end of the day, GIS is more than just a tool, it’s a craft. It’s about taking information that has a location, where something is, and combining layers to create new information that didn’t exist before, crafting knowledge! Whether that’s flying squirrel habitat, sewer lines under Morgantown, a coffee shop location, or something much bigger, it’s the same logic, the same processes, the same basic fundamental of geoscience every time. If there’s a spatial component to a problem, GIS can help solve it more efficiently and more accurately. That’s the power of it.

Learn More

Thank you again to Michael for sharing his passion about the program. If you’re interested in the Geographic Information Systems and Spatial Analysis, M.S. degree, you can learn more on our website or reach out to Michael Harman if you have any other questions!