Voices Harvey Miller === Harvey Miller: [00:00:00] Some of the people who grew up in Poindexter Village, when they put those goggles on and saw it like it used to exist, some people got really emotional, and I mean, in a happy way, they, they couldn't believe what they were seeing. It convinced us that VR is a very, very powerful way of experiencing these models. Jen Farmer: From the heart of the Ohio State University on the Oval, this is Voices of Excellence from the College of Arts and Sciences, with your host, David Staley. Voices focuses on the innovative work of Arts and Sciences faculty and staff. With departments as wide ranging as art, astronomy, chemistry and biochemistry, physics, emergent materials and mathematics, and languages, among many others, the college always has something exciting happening. Join us to find out what's new, now. David Staley: I am delighted to be joined today by Harvey Miller, the Bob and Mary Reusche Chair in Geographic Information Science, Professor of Geography and Director of the Center for Urban and Regional Analysis at the Ohio State [00:01:00] University College of the Arts and Sciences. His research and teaching interests include sustainable mobility, resilient communities, and the relationships between human mobility, environmental justice, and wellness. He is a recipient of the Community Engaged Scholar Award from the Ohio State University and an Elected Fellow of both the American Association for the Advancement of Science and the American Association of Geographers. Dr. Miller, welcome back to Voices. Harvey Miller: Thank you, David. Thanks for that kind introduction. David Staley: 2018, I think was the first time you and I spoke here. So, delighted for your return. Harvey Miller: About time you had me back. David Staley: Well, and, we wanted to talk about your upcoming Science Sunday talk, which is titled "The Ghost Neighborhoods of Columbus", which is a pretty extensive project. And, why don't we begin, first of all, by having you tell us, what is "The Ghost Neighborhoods of Columbus Project"? Harvey Miller: Sure. In "Ghost Neighborhoods of Columbus", what we're doing is using AI and GIS to leverage the incredibly rich amount of information that's in [00:02:00] historic fire insurance maps. They're called Sanborn Maps, they were created by a company called Sanborn. They were written, they were developed, I should say, for fire insurance purposes and assessing fire risk, and they are building by building maps of cities. They date from the 1880s to the 1960s, and these are now increasingly available in, you know, they're coming out of copyrights that are available as you know, public, in the public domain. The Library of Congress is digitizing the sheets, scanning them and making them available at their website in high resolution, full color scans. So, what we're doing is using these techniques to pull the data off these historical maps and create 3D virtual worlds of what neighborhoods used to look like in the past. David Staley: Hmm. Harvey Miller: And there's really two parts of this project. One is the science: how do we pull data off the maps and build these worlds as realistically and authentically and as quickly as possible? That's the scientific part of it, but the humanities and outreach and engagement is that we're doing [00:03:00] this for neighborhoods in Columbus as well, and specifically we're doing it for historically Black neighborhoods in Columbus that were altered by Urban Highway Construction, urban renewal, redlining, and other types of practices that led to their decline, and we wanna show what some of these neighborhoods looked like in the past. As part of that, we're working with the Ohio History Connection. The Ohio History Connection is opening a museum at one of our study sites, which is Poindexter Village, one of our study sites is Poindexter Village in 1940, when it opened the first public housing community in Columbus. David Staley: From the east side of Columbus, I think. Harvey Miller: That's, that's correct. That's between Long and Mount Vernon Avenue, out by Champion, and two of the buildings still exist, and the Ohio History Connection is creating a Poindexter Village African American History Museum highlighting the experiences and stories and histories of historically Black neighborhoods in Columbus. And we're working with them, we're partnering with them to include these 3D models, these experiences [00:04:00] is part of the museum experience, both on the web and also on site. David Staley: Hmm. Well, so, I wanna start first with the science. Harvey Miller: Mm-hmm. David Staley: You talked about the process of pulling the data from these Sanborn maps. Tell us, tell us about that process. Harvey Miller: Sure. Let me talk a little bit about the Sanborn maps first, if you don't mind. David Staley: Yep. Harvey Miller: They were created again for fire insurance underwriting purposes, and they are literally building by building maps of a city, and they exist for 12,000 cities and towns around the country from the 1880s to 1960s. A building by building map where you could see the parcels, the addresses, the building footprints. You could see information coded on the map showing like how many stories each building was, where the firewalls were, what the roofs were constructed from, what their usage worth, was it retail, dwelling apartments, garages, you know, it was coated with that. So, these were really incredible. You know, number of windows per floor is another thing that's featured, you know, so they're [00:05:00] incredibly rich maps that were created, you know, for fire insurance purposes, and what's happened is that now that they're in digital form and not just in printed form, we can process them using computers. So I, I have a bit of a history of these maps, I'd like to tell you about it. Back when I was a Master's student at Kent State University, I... David Staley: Many, many years ago, I'm guessing. Harvey Miller: Many, many years ago, and I'll describe, you'll see why in just a second, because I did, I did my Master's thesis on Youngstown, Ohio, looking at changes in the downtown over a 25 year period using Sanborn Maps. But in order to do this, back in the eighties, I had to drive to Youngstown with sheets, you know, for mapping and with drafting material and hand copy the data off the maps over many, many visits over weeks and weeks and weeks. So I, I've known a lot about these maps for a long time in this incredible amount of detail and rich historical, you know, information that's available. But, when we saw that they were [00:06:00] being made available by the Library of Congress and also other libraries like OSU Library, Columbus Metropolitan Library, other universities and local cities maintain, you know, these digital Sanborn maps as they come out of copyright and into the public domain. So, when we, discovered that, we decided, first of all, let's try to geo-reference the maps. In other words, place them on a modern map of the city and look at the differences. And then, we thought, well, you know, there's all this advances now in AI for automatically reading maps and pulling the data off the maps, and there's also been advances in 3D GIS, geographic information systems. So, putting these two together, I said to my crew at CURA, let's try to pull the data off the maps and see if we can build 3D models of these neighborhoods in the past, and we tried it. It took us a while to get it working. It took us, took us quite some time. David Staley: Why, was the, what was the issue? Harvey Miller: Well, we have to basically develop and train a machine learning technique to do this, and what machine learning is, is basically just a computer simulation [00:07:00] acceleration of human learning. So, like when you're riding a bike, for example, if you're going correctly, you, you can go forward, you're not hitting the ground, but if you make a mistake, you know, you may fall down as a kid. Then you get up and you try again, and you eventually learn through reinforcement. What are the proper things to do and what are the improper things to do? That's how machine learning works. Basically, what we do is we take some data, like a Sanborn map, and we hand identify some features that we know about, like this is this color, this symbol means this, this means that, and then we train the machine a computer algorithm on that, and it basically has a procedure where when it gets it right, we're like, yay, good job, and when it gets it wrong, we give it a dope slap and say, no, wrong, fix it, and there is a procedure for it to learn from its mistakes. And the beauty of machine learning is that if you have enough data with all the computer power that we have nowadays, we can just throw data at it and these algorithms can learn things really quickly and in detail. So, we first had to get that technique working, and [00:08:00] it took a while to make sure it was accurate, you know, that it was reproducing what we knew about the maps. Then, once we did that, then the project took off and we started applying that to some neighborhoods in Columbus. David Staley: Hmm. Harvey Miller: And also, the GIS software, we use a software called City Engine, and this is new software from a company called Esri, ESRI, they're the biggest software vendor for GIS software in the world. They've developed new software for building 3D models of buildings and entire neighborhoods, and they're doing this a lot for current applications. No one's done this historically, like we are. What they're doing right now is doing it to say like, okay, there's proposed building here, what will be the impact on like shadows and light and what will it look like? So, we're taking our data, putting into the software instead of modeling the current environment or a future possible environment: we're going back to historic environments. David Staley: So, I wanna be clear, the Sanborn maps are really descriptions, it has, you know, this many floors, windows, that sort of thing, and these are being, what, converted, turned [00:09:00] into images or 3D models? Harvey Miller: Right. I mean, directly what the libraries are doing is scanning it and making it available as JPEGs, but as JPEGs, they're just, it's unstructured data. It's what we call soft urban data. David Staley: Okay. Harvey Miller: And what we have to do is somehow make sense of that unstructured data on the map and identify it and structure it and put into a database, and that's what we're doing with these techniques. This is part of a more general trend we're seeing right now. You, you're familiar with digital humanities, of course. There's this new trend we're seeing, new activity around soft urban data, data that's stored in documents, deeds, newspapers, maps, other types of historical documents. For many years, these historical documents were just stored away in boxes and files and forgotten about, but increasingly, like the Sanborn maps, these historical documents are being scanned and made available as JPEGs or PDFs, for archival purposes, but also research purposes. Once we get them [00:10:00] into digital form, we can then try to process them using a computer to pull the information off and create databases. And there's several groups around the country that are doing similar things. The University of Minnesota has a mapping prejudice project, we're looking for racial covenants in real estate deeds, and then mapping them over time to see how this evolved in the Twin Cities. Also, last year I was invited to a workshop at the Philadelphia Federal Reserve Bank. They have a new center called the Center for the Restoration of Economic Data or CRED, and they had a workshop to celebrate their one year anniversary. And what they're doing, these are a bunch of machine learning economists, they call themselves, they're taking these old scanned digital archives and they're pulling the data off and building databases and applying traditional economic analysis to it. And, they're doing some incredible things here, so there's a lot of breakthroughs in this field. David Staley: Yeah. Harvey Miller: Because of digital documents and applying machine learning to make sense of the [00:11:00] data. David Staley: So, you are connecting, in a sense, machine learning, AI machine learning, and this 3D GIS. How's that interface been working? And you're pioneering this, I'm understanding. Harvey Miller: To a large extent, we are, we're trying to automate the process as much as possible. There is existing software to take like a Sanborn map or something like that and hand pull the data off, but that's very tedious and time consuming and prone to mistakes. We're developing methods to allow this to be done automatically at scale, meaning many buildings at a time, not just one building at a time. So, this can be applied much more widely. We can generate entire neighborhoods and cities much quicker than you could if you did the whole process by hand. So, what happens is that with the machine learning algorithms, we basically pull the data off the map and we put it into a GIS database, and then once we import it into a GIS, we then have to take the classified image and create objects, like these color pixels mean it's a brick building, or these color pixels mean it's a wood [00:12:00] building, or this color pixels mean it's a concrete building. And we also pull the attributes, like how many stories, how many windows per floor, things like that, and also put into the database. And once we have that, we then use the GIS to say, okay, well this collection of pixels is a building. And that takes a little bit of processing just to clean up the data and convert it into geo-referenced objects. Once we have that, we then pipe it into the 3D City Engine modeling software. And the way that works is that they have a language called computer generated architecture or CGA, and it's a modeling language for creating 3D buildings. And, basically, right now it's still mostly a manual process. We have students, undergraduate, graduate, research associates. They take the data that we pulled off the maps and applying rules and code. They actually built the buildings based on the information in the map. So, a lot of that's still a manual process. We can pull the data off the maps automatically, we're still building the 3D models building by [00:13:00] building, one building at a time. But, our current research and development is to try to accelerate that by automatically generating batches of buildings. And we just had got an award from the National Science Foundation to accelerate our techniques and to try to speed up our process by automating that building construction part in the GIS software. So my goal, I've said that what I wanna do is try to increase our development speed by tenfold, by an order of magnitude, which is a very lofty goal, but we have some really good ideas of how to do it. So, I think a couple years from now we'll have a lot of success in really, you know, being able to create entire neighborhoods very quickly. David Staley: Right. And to be clear, these buildings no longer exist. They were torn down. Harvey Miller: Some buildings still exist, some buildings do not exist. David Staley: So do you rely in this process, do you rely on say, photographs of these buildings? Harvey Miller: Oh, we do, and some other data called lidar data, which is basically aerial scan laser imaging. This happens all the time, like doing, for example, tree canopy Modeling. You can fly this over a neighborhood [00:14:00] and its laser sweeps the scene and creates a 3D point cloud, which you then can convert into information about the buildings. David Staley: Just like a drone, or...? Harvey Miller: Often it's a manned flight, actually. David Staley: Oh, Okay. Harvey Miller: Some ways, yeah. Yeah. This is very common for cities to collect building information and to collect information on tree canopy. So, yeah, and we use photographs. One of the challenges we face with the Sanborn maps is that, you know, these were created for fire insurance purposes and we know what the roof was made of, but we don't know the shape of it. David Staley: Okay. Harvey Miller: Because that didn't make a difference to a firefighter. They cared whether it was shingles or not, they didn't care the geometry of it. So, one of the things we're doing is using the lidar data to get roof geometry from the buildings that still exist in order to determine what the similar geometry would be in buildings that we're there historically, but don't exist. And then in some cases, we're actually creating the detailed building textures, which means how they appeared. So, one of our study sites is Mount Vernon Avenue on the near east side of Columbus in 1951. [00:15:00] There, we're not just creating the little architectural models of the buildings on Mount Avenue; we actually wanted the storefronts to look realistic as somebody would've seen them in 1951. So, one of the things we did is we hired a PhD student in history a couple years ago, and she worked for us for a year and she did a lot of archival research and dug up city directory information about all the buildings along Mount Vernon Avenue and then went, worked at Columbus Metropolitan Libraries and at Ohio History Connection to find old photos wherever they were. You know, archive photos, cover of a book in one case, advertisements, anything that featured pictures of Mount Vernon Avenue in the 1950s, and used that to construct the appearance of the buildings from the outside. David Staley: So, this is a 3D recreation; as a viewer, how am I going to experience this? What am I, what am I gonna see? What am I going to feel, I guess? Harvey Miller: Oh, and there's lots of ways we can experience it. The easiest way is something people can experience right now, if you go to cura.osu.edu, click on [00:16:00] Ghost Neighborhoods, there's a link to the models, and you can see them online. You can explore them, you can rotate them, you can zoom in, zoom out, scroll through, explore the models on your own. We have three study areas, three models we've built so far. One is Hanford Village in 1961 before I 70 came through, we have, I just mentioned Mount Vernon Avenue in 1951 when it was at its commercial height when there was a lot of activity and businesses there, and then we also, Poindexter Village in 1940, the first public housing community in Ohio, we built a model of it as it existed in 1940. So you can go online right now and actually see that, but we've actually worked working with some other ways of delivering it. One thing we're doing is creating story maps. David Staley: Mm-hmm. Harvey Miller: And story maps, we're basically embedding these models in a map-based story where you can scroll through it online and read about these neighborhoods and then actually tour our models, and also hear stories about the lives and memories and things that happened in these buildings. So, as part [00:17:00] of our project, we've been interviewing elders in the neighborhood who lived there before urban highways and these renewal projects, people who lived in Poindexter Village. We also worked with a PhD seminar in folklore and they did some of their own interviews, which we have, and we're incorporating these memories, these stories in various forms, photograph, text, videos of people describing what it was like in these neighborhoods. So, that's a way we're incorporating these 3D models with stories about the lives and experiences in the neighborhoods. David Staley: Mm-hmm. Harvey Miller: A third way, which we're playing with right now is virtual reality. David Staley: I wondered if we were heading in that direction. Harvey Miller: Oh, we are, we are heading in that direction. Last year, in December, 2024, we were at a community launch for the Poindexter Village Museum in the Union Grove Baptist Church, which is next to the two buildings that still exist on the near east side of Columbus that actually predates Poindexter Village. So, we went there and we, and we decided, let's [00:18:00] put one of our models in the VR and see how people like it, and we took it to the event and the reaction was unbelievable. Some of the people who grew up in Poindexter Village, when they put those goggles on and saw it like it used to exist, some people got really emotional, and I mean, in a happy way, they, they couldn't believe what they were seeing. It convinced us that VR is a very, very powerful way of experiencing these models. So, we now have VR versions of the other two models, and we're also working on trying to create other similar experiences like that, like we might put one in a VR cave at some point where you can walk in and actually... David Staley: Don't need the goggles. Harvey Miller: Yeah. Don't need the goggles. Right now the trouble with VR is that the goggles require a lot of energy. David Staley: Mm-hmm. Harvey Miller: So, they have big batteries that wear out and they'll like run out pretty quickly. But, that's gonna change. I mean, five years from now, maybe not even five years from now, they're gonna be like simple glasses like you might wear. David Staley: Mm-hmm. Harvey Miller: Like sunglasses. David Staley: They used to have a lag problem, which at least gave me a little bit of motion sickness, and my sense is that it's getting better and better. Harvey Miller: It's [00:19:00] getting better. One thing we avoid in these VR experiences is having people walk and tour the model because that disconnect between walking and what you're seeing, that creates motion sickness. So, we have people can basically can float above the models and then fly to different scenes, both in the air and at the street level. And again, it's really incredible. It's really incredible when you see it for the first time. We've had a lot of people in CURA come in and they've never experienced VR before and we show 'em this and they're always like, whoa. Our city council president Shannon Hardin was at an event at the Union a couple weeks ago, and we showed them the VR Mount Vernon, and he just said, are you kidding me? Are you kidding me? Are you kidding me? I didn't edit that. He didn't swear or anything, but you can imagine he, you know, the reaction's been always very powerful. So, we're gonna continue developing that. There's also the possibility of printing out some of these models. David Staley: Like, 3D printing? Harvey Miller: 3D printing. Yes. David Staley: Mm-hmm. Harvey Miller: The models we have are detailed enough that we need to get a large format printer and we can actually print [00:20:00] out, like, for example, Poind exter Village. That's a possibility, again, we're working with Ohio History Connection to talk about all these different ways of experiencing these models. They're interested in heads up immersive displays, if you've ever been to Ohio History Connection, they have a heads up immersive display of Native American earthworks. So, it's like 180 and you stand there and you can look around and see the entire scene. So, it's not like VR, but it gives a 3D appearance to it, you know. So that's... David Staley: Like a, like a panorama or...? Harvey Miller: Yeah, exactly. Exactly. And you know, having iPads and tablets or a desktop display, that's something else we looked at, like having a desktop, kind of like huge iPad like display and being able to zoom in and click on buildings and have information come up. So, these are the options that we're exploring with the Ohio History Connection for delivering these models. The museum's opening in 2028, so we have some time. The groundbreaking is gonna be this May. So yeah, we're, we're exploring all the different ways you can experience these models. David Staley: Well, you said on the one hand this project is as much about the [00:21:00] science and the technology, and that's super impressive, but you also say that what you're exploring are historical issues like redlining. Say, say a little more about, well, first of all, what redlining means and how this project is exploring that. Harvey Miller: Okay, well, it's mostly focused on urban highways and urban renewal. Redlining is part of the story, but, what happened in a lot of historically Black neighborhoods in the United States is that they develop maps where basically put red lines or colored certain neighborhoods as being risky for loans. And that led to, you know, disinvestment over time, people couldn't become homeowners. It harmed intergenerational wealth transfer, and that's the way a lot lot of people historically in American history have become more affluent, or more middle class at least, is through home ownership. So that was denied of some of these neighborhoods in the United States. What also happened is that when urban highways came through in the sixties and seventies, they tended to go through these neighborhoods. Sometimes it was because, well, the land was cheap. David Staley: Mm-hmm. Harvey Miller: You know, because there's [00:22:00] been disinvestment. Sometimes it was because they cleared them to be slums, and decided this to be a good way to clear out these slums. So, a lot of these neighborhoods were harmed by constructing urban highways, you know, I 70 in Columbus went through Hanford Village. Hanford Village is now what we call driving park on the east side of Columbus. But, it used to be a separate town called Hanford Village, it was incorporated in 1909 and it became majority African American, they had a Black mayor you know, city leadership. Eventually got absorbed into the city of Columbus in 1955, and then in late 1960s, I 70 came through and bisected it in half and also went through something called the George Washington Carver Edition. That is on the east side of Hanford Village along Alum Creek. So, if you're going down I 70 and right when you're about to hit Elm Creek and Bexley, you notice I 70 curves to the South, they were trying to avoid, this is the story, at least I don't have direct evidence of it, [00:23:00] but they wanted to avoid going right through Bexley, so they curved to the south and they took out part of the George Washington Carver Edition. That was an undeveloped stretch of land in Hanford Village. In 1946, they developed a neighborhood of Cape Cod homes for returning Black veterans from World War II, including Tuskegee Airmen, who were stationed at after World War II, was then Lock Born Army Air Base. David Staley: Mm-hmm. Harvey Miller: And some of these veterans moved in, they owned homes, they were able to take advantage of the GI Bill, which only provided financial support for buying new homes, nonexisting homes. And then within some cases, within five, six years, they were told you have to get out, the highway's coming through. And in our model, we created that part of it in detail, and you could see the Cape Cod homes, you can see the trees, and you could see some homes, the homes that are colored red in our model are ones that were taken out for I 70 and also Alum Creek Drive and the freeway interchange there. [00:24:00] Now, the reason why I'm telling that story is that that's the kind of stories they're trying to tell. David Staley: Mm-hmm. Harvey Miller: We want people to realize that there were, you know, some of these neighborhoods and these communities were thriving. The stories we hear about Poindexter Village is that, you think of public housing now and you think it's dysfunctional and not good for people :that's not the stories we hear about Poindexter Village. David Staley: It was a village. Not big high rises, it was a village. Harvey Miller: It was a village with 33 buildings. It had its own high school, daycare center, administration building. People looked out for each other. We've heard nothing but warm stories about Poindexter Village and nearby Mount Vernon Avenue, which was the main kind of strip for that commercial strip. So, this is what these neighborhoods looked like before all of these, you know, decades of disinvestment and then urban highways, and eventually urban renewal. Mount Vernon Avenue, our study site, the north side of it, was bulldozed in 1978 as part of a model cities program. They not only tore down all the existing [00:25:00] buildings, but they actually erased several streets as well. Now, Mount Vernon Plaza is there, that's what's, that's what's there nowadays. And when we go to events, we've done a lot of events actually on Mount Vernon Avenue, like we've gone to the Juneteenth Jubilee celebration on Mountford and Avenue, which is right at the site where we built our model, and some of the people, especially younger people, look at our depictions, you know, on the computer and on the iPads, and they say, that was here? David Staley: Mm-hmm. Harvey Miller: And we're like, yes, that's what this neighborhood was like in 1951. So, people don't have a sense of history. They look at like how things are now, like urban highways as they're inevitable, they've always been there. No, they haven't always been there. These cities were very different, you know, Columbus was a very different place 70 years ago, and we just wanna not only highlight some of the the harms that were done to these historically Black neighborhoods, but we also wanna highlight what they had, the rich, you know, lifetime, you know, lifestyles, culture, activities. Mount Vernon Avenue was a happening place, you know, [00:26:00] there were, there were theaters, bowling alleys, you know, restaurants, bars, closed stores. A green grocer, you know, it was pharmacies, it was a very, very lively place, and you wouldn't know that if you went there now. So, part of what we're trying to do here is get people to think about that, to think about, how does this knowledge of the past help us think about where this neighborhood should go next? How do we, how do we make repairs? How do we build back the neighborhood and reverse some of these harm that happened to it? David Staley: Hmm. I'm interested to know, this has been a big project for CURA, I understand. What's next for CURA? What sort of research projects should we expect to see next from CURA? Harvey Miller: You know, CURA's mission is using GIS and Geospatial Technologies to foster more sustainable, resilient, equitable, and healthy cities. So we're, our big mission's around urban sustainability. So, we generally work with community partners to look at how we can use this type of data and technologies to [00:27:00] really make our community a better place, in short. So, we have several projects going on right now. We're working with eviction data right now. As we know, Columbus is one of the eviction hotspots. Oh yeah, we have as many evictions in Columbus as Chicago and Chicago is three times the size. David Staley: Hmm. Harvey Miller: And there's a number of reasons for that. We probably don't have to go down that rabbit hole as to why that's happening, but one of the things we're trying to understand now is that we're working with a group in the Moritz College of Law, the Justice Tech program, which is a combination of lawyers and computer scientists. And we've been given access to the eviction court records, and what we're doing is trying to look at how to explain the different, understand the different eviction experiences that occur and what happens to people, and can we monitor what will happen if we do policy changes or interventions that can make things better? Basically, set up a system where we can measure the impacts of new policies and how that's affecting the eviction experiences. That's one project we have going on. We have another project [00:28:00] where we're working with COTA to understand bus delays in Columbus. You know, that's one that... David Staley: They'll give you a Nobel Prize if you figure that one out. Harvey Miller: Well, one of the solutions, which is what, what we're looking at here in Columbus is dedicated bus lanes, you know, for the "Link Us" Bus Rapid Transit. David Staley: Right. Harvey Miller: And they have experience with that in Minnesota, and we're working with one of my former PhD students, Dr. Ying Song, who's a Professor at U niversity of Minnesota, and she's constructed a very detailed elaborate model that predicts what factors lead to bus delays in in Minneapolis, and we're gonna reproduce that research here to try to help COTA make a case for why we need dedicated bus lanes as part of the "Link Us" initiative. We're also working with MORPC, it's one of our biggest partners, the Middle Ohio Regional Planning Commission. That's our local metropolitan planning organization that covers the 15th county region centered on Columbus. They're responsible for long-term transportation planning in central Ohio, and we've worked with them quite a bit over the years, but our latest project is that we're [00:29:00] trying to figure out better ways of representing walking, biking, and public transit when we look at access to community resources such as green spaces in Columbus. Right now, we mostly consider driving 'cause there's easy data on the road network and, but getting data on buses, you know, on public transit and on the sidewalk network and biking, traditionally has been difficult, but now there's more of that data available. So, we're trying to build like a very detailed multim mold network where we can model different ways that people can get to places like parks without having to drive, and looking at social differences in that as well, to see if there's differences among different neighborhoods in Columbus and how easy it is to access things like healthcare and green space, groceries and things like that. David Staley: Will this rely on 3D GIS? Can you see this being modeled? Harvey Miller: Not like that. You know, the visualization of the built environment's not the important thing here, and the important thing is connectivity, how connected different neighborhoods are by different ways of [00:30:00] traveling, and also moving among different ways of traveling, because when you ride the bus, you have to walk to the bus and then walk from the bus, and that's something that's been hard to model when we look at travel and accessibility in a city like Columbus, but now it's become easier and we're working with them to try to come up with these representations. But, mostly those will be in map form, just showing who has good access, like heat maps, you know what heat maps are. David Staley: Mm-hmm. Harvey Miller: Where you show like, where people have good access and bad access. We'll be able to say that at a very detailed level, and also because of the data we have, we can not just compute averages, which are kind of meaningless, we could say like on a Wednesday at nine in the morning, how long will it take you to get to a park in Columbus versus Saturday at three in the afternoon? 'Cause we have very detailed, we've worked with the Central Ohio Transit Authority for many years and we have access to their scheduled data, route data, bus stop data, and their real time bus data, you know, the locations of buses, so, we can actually say things at that level of detail, like how quick can you get to a grocery store [00:31:00] by bus at this date and time? That's where we're at nowadays, that's how detailed. You know, this is part of what's going on right now in my field is this major revolution in urban science. There's just so much data available now. Back when I started, you know, as a young Assistant Professor in the nineties, we didn't have much data and we had to do a lot of theorizing. Now, we have incredibly rich detail about cities and how they behave in the processes and dynamics of a city, and it's totally changed my field. David Staley: So you had to, you had to change your orientation, even after your PhD. You really had to change your orientation, yes? Harvey Miller: Well, that's one of the beauties of being professor, you're just basically paid to be a student your whole life, you know? So yeah, I've just been a student my whole life and just learning as these things evolve and it's been very rewarding, you know, it's really rewarding connecting this new urban science with all its possibilities, with community issues and problems and trying to work to make, you know, a city like Columbus and really cities [00:32:00] everywhere, you know, better places for people. David Staley: Well, we're looking forward to your Science Sunday talk. Harvey Miller. Thank you. Harvey Miller: Thank you, David. Jen Farmer: Voices of Excellence is produced and recorded at The Ohio State University College of Arts and Sciences Marketing and Communications Studio. More information about the podcast and our guests can be found at go.osu.edu/voices. Voices of Excellence is produced by Doug Dangler. I'm Jen Farmer.