Exploring GeoSpatial Techniques and Technologies
Welcome to this episode of UMBC's Mic'd up podcast. My name is Dennise Cardona from the Office of Professional Programs at UMBC. Today we are joined by Dr. Dillon Mahmoudi and Ron Wilson of UMBC's graduate program in geographic information systems. I hope you enjoy this episode. Thanks so much to both of you for being here with me on UMBC's Mic'd up podcast, it is fantastic to have you both here with me. I'm so excited to talk with you about you UMBCs GIS program. And let's first hear from both of you on a little bit about your background just to kind of
orient viewers of this on YouTube or listeners on a favorite podcast channel. What led you to UMBC? To this GIS program here? Me? Well, I started way back when the program first was created in 2009. And I was just brought on to do one class. And then, and that was successful, and I kept doing other classes and I started getting more involved with the director at the time Erwin Villiger.
And we sort of built the program and went into different directions as time went on, just to kind of keep the program modernized and whatnot. But, things were changing in the geography department, they were slowly at the time going in more environmental science and physical sciences. And we just kind of stood out on our own a little bit, but then a number of professors started coming on that were more human geography side. So Irwin, decided to take a job, and he left out.
And they kind of left the program with needing somebody to take over and I was recommended, for which I guess Dillon was instrumental in making that happen, because he, the name was floated. And I kind of took over right when the pandemic started. And I had to manage my classrooms and manage the program. And there wasn't a whole lot to do to figure out everything was online, it was pretty easy to do. And then Dillon started reaching out to me, and we started talking about ideas for the program. And we realized that we were pretty much in sync with the ideas of what it needed to be and where it needed to go. Not that we don't have different visions for everything,
but our ideas, our core ideas there, which allows each one of us to just kind of like, alright, we're going on the same page here. We can just keep plugging along without having to worry about what differences or similarities gonna be. We have the same vision for the program, maybe some differences in classes and ideas about them, but there's just, we built the program up, put it in the new program in front of the Graduate Council for the university. They approved it. And wow, we're now relaunched, and going strong and towards building up our new student body. That's exciting. Awesome. And Dillon, let's hear from you. I know that you just came back from Calgary.
So you're a little jet lagged. That's okay. Let's, let's hear from you and your path to UMBC. How did you get here? What was that path like? Yeah, great. Thanks. So yeah, I just came back from a digital geographies workshop. And one of the core kind of themes was that, was how
digital geography has a lineage and critical GIS. And that's really where my background comes from. I was originally trained as a computer scientist, and worked in tech, got out of tech, to go back to graduate school to do social sciences, but realize that there really was a need for people that could work with datasets have technical skills, but also do some of the social science or apply their technical skills and another realm, whether that be social sciences, or even physical sciences. So I interviewed at UMBC, it was a good fit. And what I occurred about Ron Wilson, this mysterious GIS instructor and in the master's program at the time, and because of COVID, we kind of had some time to think through what we wanted out of that master's program. And that's
really when Ron and I started connecting and thinking through what do we really want this program to do. How can we embed some of the kind of open source philosophies that we both agreed upon? How can we actually make this a program for just futures and just maps and that's really where we get that kind of tagline for the program just maps we have that dual focus on justice and the focus on what a lot of people sometimes skip over but the actual map production itself. Yeah, see, I think that's really great to be able to take a step back like you both did, take a step back and allow some ideas to marinate. And to be able to build this program from the ground up. That sounds like it benefits the students, it benefits the faculty and benefits UMBC. And now you have a program that you both can really get behind, and you're proud of. So that to me is
like just a great synergy. And I'm excited for it. I've been at UMBC since 2007. So I've been with the GIS program, helped market them back then. And I've seen the evolution. And it's just it's really cool to see this. And I think it's really exciting for students. And speaking of students, what do you want most for our graduate students? Yeah, great question. I think that goes back to my previous answer a little bit as well. We say focus on open source, and we set our open source technologies and our curriculum. But it's more than just a focus on open source for any kind
of reasoning. It's because we want to have our students understand the concepts behind what the open source technologies do. There are many open source geospatial technologies out there. And the choice of which technology to use whether it's open source, or proprietary, depends on what is the goal that you want to accomplish? What is the task that's at hand? And so what we've done is we centered those open source technologies, because there's so many of them so that our students can take that step back, like you just said was so important tickets, step back and think about what it is that they're trying to accomplish in their analysis, or in their production, and pick the right technology for the right task. A lot of times as a graduate student, myself, I just well, I just graduated from a UMBC program in May. And one of the things, thank you. And one of the things that I was concerned with, when considering graduate school was okay, am I going to be able to, what am I going to be able to do with this? Is this going to be a value to my life to the field? Is there a need for it? Can you talk a little bit Ron, can you talk a little bit about why study GIS? Like what is it what's in it for the student? Well, what's in it for the students is that we operate daily our daily lives in any geography at the point where we kind of take it for granted and we move through it. But
a lot of that interaction with the world around us, has repercussions back and forth between the way we interact with it the way it affects us back and forth, to which there is no aspect in any discipline out there that doesn't have some spatial aspect to an even seemingly disciplines like mathematics, or even brain imaging sciences that has a spatial component. They use GIS geoprocessing techniques to do overlays in the brain from slices across the brains, where they've done imaging from. We're not really focuses on those kinds of things that Dillon said, we're doing justice. So a lot of our students, particularly in the objective of that, that justice and environmental and social, that we're looking at, deals with a lot of public policy, a lot of solutions that are placed based, not all the time. And it, is even when it's there, it isn't the front and center. So it's important that we get our students to recognize that the
space that they're operating in, has this measurement aspect to it to try to understand the effect back and forth between the people in their environment, people and other people, and vice versa. So we've built our program, to have them gain that recognition and understanding so that they can think about the world more spatially, rather than just them being in it and taking it for granted. Who is the ideal student for this program? So what kind of backgrounds should somebody have when they are considering applying for this program? Good question. We're, we're actually, the program is designed to take anybody with a hard working ethos. There's no necessarily requirement on technical skills, no programming is required.
The first several courses help students get on the same page and build a shared vocabulary around space, geospatial techniques, and technologies. And from that platform, it's a very collaborative extension into the other courses. So right, who do we who's the ideal students? Someone who's gonna get in there work hard and work with other students? Of course, if there are advanced students who already have geospatial experience, GIS experience or programming experience, we can slot them into kind of later on courses and build from there. But from the get-go The course is designed for everybody. So now we have this emergence of AI technology, right? It's the
elephant in the room that we all have to deal with. And I know as an instructional designer, that's my, that's where my graduate studies were. It is becoming a huge component of instructional design. And I, from speaking with other programs, alumni, faculty, instructors, it's becoming, it's starting to build into almost every field out there, I think, every field, how does it go into effect, the field of GIS and is it a benefit? Is it something that people should be concerned about? Or is it something to just embrace and see where it takes us? For the listeners that can't see us, there was a lot of nodding, as Dennise was describing the potential of AI, but we actually we had had this question in one of our open houses, and solid raw ticket. Yeah, I actually put this in my notes at the end, when I was thinking about what to say in here. And yes, Dillon says, we were asked that by students like how would you program
going to make us from not be coming obsolete from AI? And I said, well, that's a great question, and I've got a good answer for it. We get students to embrace using the AI my assignments in my classes, I had them do some assignments with AI. I have used chat GBT to answer a question. And what they realize is that they can't, they can't complete and pass assignments, if they just plug in the questions and put it because they have to put it in the context of what we're studying, the data that we're analyzing, and fit to the requirements of the analysis. And that takes a lot of their own brainpower to make it work. The AI just gives them a lot of material to work with. So they can build coherent answers. And even if they were to let chat GBT, to answer the entire thing that still requires them to tell chat GBT what it is that they have to answer. So they're learning
while they're doing that, too. But one of the things that I also learned about, so that's just an analysis. One of the things I learned recently about programming, because that's become a big one. So I was working on a project where I was looking at the overlaps and gaps in bicycle docks, to see how much bikes were out. bikes were sitting there, and things like this. So this requires actually doing an analysis where you're looking at multiple bikes, in a dock where there's overlapping times. And if you're trying to count the time that a bike dock has at least one bike
in it, or if one if there's no bikes out. This requires getting rid of the overlaps in the time. And it requires getting rid of the gaps in the time as well. So I was typed, programming this in Python. And I had one technique where you take advantage of Python by using its functionality. You don't have to write a lot of code. And so what I did was that I got that working. But what I wanted to check it, I couldn't get it to quite work. So I asked chat GBT to write me a
program. And it did. It wrote me about an 18 line programming code in the old way of doing it loops, and if then else statements and everything like that, when I said that's not right, so I finally figured out the solution. And my solution was only four lines of code. Taking advantage of pythons full functionality. AI can't figure out, AI does not know Python AI does not know R it knows how
to program in R it knows how to program in Python, but it does not understand the language. Our job is to tell students show students how to think to use and know Python and R so that they can make proper use of Woof, that's powerful. I think with chat GPT, I use it a lot now with what I do with instructional design, lesson plans, development and things of that sort. And it's really about the quality of the input determines the quality of the output. And we have to remember that chat GPT I think it goes back to 2021. It starts there. So it doesn't have any reference to between now
and 2021. At least at this point. I'm sure that's due to change. But there anything that's the new in the past year, it will not have an answer for that if it's brand new information. So with coding, I would imagine that is would be problematic if you're relying solely on chat GPT and AI technology to be able to do your job. So that was yeah, it's really interesting. hearing that story about the bike and the bikes and how coding that and how what your variance was with that. And I really enjoyed hearing that you're embracing as instructors, as directors of programs that you are embracing technology that it's it's not something to fear and it's not something to, think it's going to diminish the quality of education because I think a lot of people were fearful of that in the beginning. And it's really about educating students and learners, that you can use it as a, I personally use it as a an idea generator, it helps to brainstorm ideas, and then I can build upon those, I would never take something black and white right from it, because you need to have that human element. And if we want to be able to coexist with AI in
the future, we need to really make sure that we are holding dear to our human aspect, our human capacity, in addition to AI capabilities. Yeah. And both of those examples that both gave really reflect how AI is good at solving problems that it has encountered in the past. But new problems like the scooter problem that Ron was describing, it doesn't know how to do that. And part of that is because AI does not think, does not think critically about what the data represents, behind the scenes. And that's one of the things that ends up being core to our curriculum is a book that I just grabbed when Ron was describing that this book called All Data Are Local: Thinking Critically in a Data-Driven Society, right? So it's data is everywhere. And we're more than just data and well, data scientists, if you dare, what we want to two as you want to think about, or we want to think about that spatial data, and critical ways that perhaps AI has not been exposed to in the past. So again, we want to build with AI. But AI cannot replace us, if you will. Yeah.
And I've started to build up questions that have sparked a bunch of materials that I've been putting into advertising to that point out, because I think this is a real fear for students. And we want to show them like no, you can marshal that power and make it work for you and make you more productive, and gain more opportunities for insights that you otherwise wouldn't have seen. Yes. Oh, I love that spirit. Yes. So, let's move on to that. My next question for you both, is what makes UMBCs graduate program in GIS stand apart from similar institutions, or similar programs, I should say at other institutions? Who wants to attack that? Go for that one. Start with that when
I'll follow up. Sure. That sounds great. Yeah, so I mentioned a little bit before about the using sentry open source technologies. But it's more than that it's actually several different things in combination. Yes, it's open source, but it's also the purpose behind why we met. And so we are focused on tackling difficult or interesting questions in ways that have not been tackled before. So taking a kind of holistic and rigorous view of geospatial issues or geospatial questions. And we, part of that is the just, again, the focus on just maps are gonna focus on
making maps themselves, but also making maps for a more just future, for a better future. So it's incorporating those things together. And then what we've done is we've connected our our instructors in the program are just phenomenal. They are all throughout the kind of GIS industry, from local planners to like Ron's work in the federal government. So they have this huge kind of span,
to be able to expose students to a variety of different issues that present themselves in really interesting and unique ways. So what we can, what we add is the DMV is such an interesting place, because there's a lot going on. And so what we've been able to do is call instructors from those different places to, to bring them in and expose our students to different ways of thinking. Yeah, and so to capitalize on that, there's a number of GIS programs out there and to the point where if you look on Reddit to there's concern about the saturation of the market, but that's where our program stands apart. A lot of the programs have similar classes to ours. But what I've come to realize about a lot of these programs, even in programs not around this particular region.
They'll teach spatial statistics. They'll teach cartography. They'll teach spatial databases, and things of that nature. But what our program does is say, All right, we're going to provide the meaning behind all that. The book that Dillon mentioned there is one that I've had to and I know
one of our other instructors, Eli Pousson, uses it as well, to try to connect students to the local real world around us to show how this impact gets back to that idea that I mentioned about people being in space all the time working through their geographies. Things like that. So it gets them to think about their place in all of that, and the data that is around them and understanding how to measure that and how to think about that. But when it gets to the classroom level, our classes are designed to get students to not just do the techniques, learn how to use the software, how to select library or whatever technique they're going to use, they have to understand what choosing the making those decisions has on their analysis in two ways, one of which is that there's, when it comes to geographic analysis, it's a lot more complex than a lot of other analysis is because there's multiple dimensions, and there's multiple dimensions in time. So we have to, we get them in one of my classes, for example, I teach students about the various clustering techniques out there to identify where things are clustering and talk about their shapes or patterns and everything. But there's so many things that affect that, I put them through that, where I have the measure, like if you set these parameters, this is what you get, if you pick this technique, this is what you get, if you use this geography, this is what you get. And they get kind of like, oh, really, this is a lot of work. But by the end of it, I can, we go through
the results and say, see what happens when you set this parameter and use this technique? Or you use this geography? You lose this, you gain this. So at the end, the assignment has them assessing which technique did the best under what geography under what settings to make the analysis understand. And so they learn right there is examples like you can't get AI to do that. So they have to go through that. And they understand. So our other classes are very similar, where they're shown a bunch of other libraries, because these are some of these classic geography problems that you can't escape. And so where my class will teach them about those things, a class like, like building spatial datasets, or geoprocessing, will have them saying, alright, how do we set this up, this data up or process this data, so that classes and the analytical or the more advanced technical, can make use of solving those particular problems? Sounds like there's a scaffolding element to the course curriculum design, which is a really great way for learners to be able to learn and apply that knowledge as they continue to gather new knowledge and be able to grow in that field. So that sounds really great. Being able to make meaning
of what you're learning is imperative to being able to be effective and successful out there in the real world. It's not just theory, it sounds like it's really applied knowledge. Yeah, the students grumble about the work, but in the end, they're like, yeah, I am glad I guess I did that. Alright, I'll admit it. Or, the other one that I hear is, oh, that makes that explains so much about why scooters are where they are, or something like that, or, oh, now I understand why the city is so, or has so many houses, in this particular neighborhood, but not this neighborhood. And it's like, oh, yeah, well, we we can kind of spatially
look at how the trajectory of that place. Can you talk about the course curriculum? How does this program prepare students to go out there in the real world and have a successful career? The core curriculum is designed to provide a deep level of rigor that is founded in methodological thinking. Where students learn to process their analysis in a systematic and planned way. All the while framework, by this ability to bring subjectivity to their analysis, that passion, those ideas, what interests them, but temper that subjectivity with objectivity, so that they have rigor and sound thinking behind it so that their, their results don't become biased or become open to attack from critics or people who have disagreeing ideas. Excellent. Dillon's like "Yes!" Well stated. Absolutely. In what ways is the GIS program innovative? And how does it instill that innovation in its students? One of the ways that the UMBC GIS program, just baps incorporates innovation and is always I think one step ahead in terms of innovation is through its instructors, our instructors are exposed to so many different, unique problems on a day to day basis. So what we do is we bring those problems into the classroom and expose students to these tricky problems that we've all run into and real world examples. So, what that does is that gives students a way to
say oh, well, hey, this problem that I heard in the classroom, or that I had an assignment on I know to apply that in my own work or in my own unique way, and that can take place and, or that can take shape and in different ways, right? It could be a novel dataset, it'd be a novel method that a student applies. Or it could be something completely different and saying, okay, well, we actually don't have that kind of data, we need to go out and collect a new type of data that does not yet exist, or we don't have access to that so that we can analyze it in traditional or ways. Ron, how has your experiences, like job or even personal, shaped the way this program has been created? Oh, quite a lot. For the first 12 years of my career, I was in a research center at the Department of Justice for which I ended up taking over which was originally called the Crime Mapping Research Center but it became the Mapping and Analysis for Public Safety Program, and our job was to originally get crime analysis, spatial analysis tools into police departments.
But then once that we did that I took over because the previous director moved on to bigger and better things, I think she wanted something more. And she did, she went on to do great things. That was Nancy Levine. She's now, well she's the director of the National Institute of Justice. She, so she left it to me. And so I've started well, where are we gonna go with, so I started bringing the geography to it. And I started bringing sort of the environmental psychology into it, which is good, because I spent a lot of time in the psychology literature, and I'm like, this is where we have to go. Because that's where police departments are really sort of focusing on these places. And sort of it's not just going there and dealing with crime, it's trying
to understand what are the root causes and the interactions with the environment that are going on to this. So I started building research agendas that looked at that, building that understanding so that not only researchers, but practitioners would be able to take this information and do a geospatial analysis that allowed them to solve the problems and under, understand the underlying mechanisms under them. So the idea was to bring not just the police departments together, but to bring them together with the county executives, local community organizations, and everything, to try to get them to work together to solve this problem simultaneously and get the root cause. Just not what they used to call seven cops to the dots and stuff like that it was
just was never completely about that. So I was at the time still trying to bring geography to that. But then I went to HUD, and I was one of the main researchers evaluating Public Housing Choice Voucher Program, trying to help people who would get housing vouchers to move to a better neighborhood, give them the tools and the understanding of where they're, where their choices might be, as well as evaluating, is the program succeeding? Where is it failing? And how much change has occurred? And things like that, but I was also a bit of a gatekeeper, I won't go too deep into this story. But there was one instance where sometimes you run into people. And it doesn't matter if it's the federal government or academia or the private industry, who just don't have this sort of connection or concern to the constituents that they're serving. And there was a decision going to be made about running this big program that I was like,
you can't do that. There's just too much geography there, there's too much interaction, you're not going to be able to do this and succeed and get any results that are going to matter. And the kind of the end of it was like, well, we should just do the program and see what happens. I'm like, no! Here's the geographic reasons why you can't do this. And so I had, I wrote up a big sort of rebuttal, to try to, like, to try to like mitigate this potential of this program being designed in a bad way that, that can, that could harm or set people back, because the constituents were often trying to help, particularly in Housing and Urban Development. They said at one time,
in an interview that sort of backed up my ideas is like, we run these programs. And we get these people to participate, who don't have many resources, they're at a huge disadvantage. And if you don't get it, right, they've lost time, that they don't have, and they can't recover. And so we got to make sure this right, this is what we try to bring into our
programs to understand that your work will in fact, impact people and you've got to connect with that. Oh, wow, that is very powerful, and who doesn't want to make a difference in this world? So, there you have it, viewers, listeners, if you're looking for a career where you can make a difference. Think about GIS. Seriously, that you just really brought it home. For those listening in, myself included because I didn't realize the level of impact that you can make in this field using geography, GIS, to be able to make really important decisions that affect many people's lives. So, wow, thank you for shedding light on that. And we just did with with that story is described the importance of spatial thinking. And I'll just add very quickly that
there's kind of a running joke in geography, that the economists just discovered space. This is true. Yeah. In fact, Paul Krugman won a very prestigious economics prize for the incorporating space into economic analysis. Well, the thing is, we've been doing it for decades, and we have a lot of insight into how and when best to apply those kinds of spatial thinking. And so yes, I think that if there is a way to make positive change in the world, a GIS degree Just Maps, our program, is a good place to start. So here is your here's your chance to say one
last thing here that you think that listeners or viewers of this video need to hear about GIS, about our program, about anything that you think would be of value to somebody tuning in here, what would that sound like? What would that be? I'm gonna let Dillon finish it up. But I'm going to start with just saying that don't look at the GIS program, as a technical degree, look it, as a social science degree with a technological foundation, because you're going to get all the benefits of social science, understanding research analysis, with the tools and technology to be able to make use of it. So that's my finish. I'll add to that. A lot of problems that we see today are, in fact have or do, in fact, have a social route to them. So problems that may appear to be, for example, natural science, or just purely sustainability oriented, are in fact, social problems or have a social component to them. Everything happens in space. So how can we use spatial thinking, to tackle the issues that we
face today? Thank you so much, both of you for sharing your insights today. It to me it was an eye opening conversation, and one that I derived a lot of value from and I'm positive that our viewers and listeners will do the same, will have that same experience. So thank you for being here, sharing those insights, really excited to be part of this helping just being seeing the growth and the eventual pathways that will grow from this and the impacts that students will make in the world as a result of studying here at UMBC. Thank you, Denise. That was a lot of fun. Yes.
Thanks so much for listening to this episode of UMBC's Mic'd up podcast. I hope you enjoyed this episode. If you'd like to learn more about our offerings, do a quick search for UMBC graduate program in geographic information systems, or simply click the link in the description.