1 00:00:03,840 --> 00:00:08,520 Thank you so much, Nick. Happy to be here today. So I. 2 00:00:08,520 --> 00:00:12,900 My name is Suzy Birdzell. I work for a consulting firm in Boston, Massachusetts. 3 00:00:12,900 --> 00:00:17,780 In the US called Dustin Tigard. And we focus on sustainable transportation planning. 4 00:00:17,780 --> 00:00:23,160 And I am here today to talk about mapping towards equitable solutions in public transit planning 5 00:00:23,160 --> 00:00:32,560 and how cartography and clear data analysis can be used to forward equity and in transit. 6 00:00:32,560 --> 00:00:39,490 So the best trend is services are equitable, effective and productive. 7 00:00:39,490 --> 00:00:45,230 And they really are best suited to meet varying needs of varying communities. 8 00:00:45,230 --> 00:00:50,170 Often productivity and equity are seen as a Trade-Off. 9 00:00:50,170 --> 00:00:57,010 But actually better serving transit critical populations by examining how the needs of those populations differ from the 10 00:00:57,010 --> 00:01:05,110 needs of the general populations or those in power can increase the number of people who ride transit and its effectiveness. 11 00:01:05,110 --> 00:01:10,630 Most major cities in the United States have transit systems that reflect the needs of people in power, 12 00:01:10,630 --> 00:01:16,610 and they best serve white, wealthy men who work white collar jobs in dense downtowns. 13 00:01:16,610 --> 00:01:20,230 The travel needs of women, people of colour, low income communities, 14 00:01:20,230 --> 00:01:26,380 and those working low wage jobs or essential jobs must be examined directly to create 15 00:01:26,380 --> 00:01:33,970 equitable transit systems rather than assuming that their needs reflect those in power. 16 00:01:33,970 --> 00:01:41,610 So today I'll be talking about different ways to really. Examine those differences from that. 17 00:01:41,610 --> 00:01:50,160 Different communities have from those in power, rather than just assuming that they have the same needs through both a geographic and temporal lens. 18 00:01:50,160 --> 00:01:56,190 So one of the first strategies we have for looking at geographic equity is identifying 19 00:01:56,190 --> 00:02:02,820 concentrations of transit dependent populations in an area and identifying there. 20 00:02:02,820 --> 00:02:06,090 How reliant on transit they are. 21 00:02:06,090 --> 00:02:11,940 There's a lot of people when looking at transit need who just will make a ton of maps, the different types of population. 22 00:02:11,940 --> 00:02:22,680 One map of race, one map of low income, et cetera. But that doesn't reflect the fact that different groups take transit a lot more than others. 23 00:02:22,680 --> 00:02:26,970 So if you look at this table here, it shows the rates. 24 00:02:26,970 --> 00:02:34,260 This is Fort Worth, Texas. Of how much more or less likely different groups are to take transit. 25 00:02:34,260 --> 00:02:38,820 Black residents in the city are, you know, over three times more likely than average to take it. 26 00:02:38,820 --> 00:02:45,510 And those without a vehicle are overall 11 times more likely to take transit than the general population. 27 00:02:45,510 --> 00:02:52,750 So if we. Wait. The entire population by all of these metrics, we get this map here, 28 00:02:52,750 --> 00:02:58,240 which shows overall how much more likely different populations are different area. 29 00:02:58,240 --> 00:03:03,630 Populations of different areas are to take transit. 30 00:03:03,630 --> 00:03:14,700 So if you apply that rate directly to the population density and you can see in these little boxes here how much more these areas pop, 31 00:03:14,700 --> 00:03:17,490 once you apply that weight, 32 00:03:17,490 --> 00:03:26,310 it's clear that need is much higher in some of these areas based on who lives there than just looking at the density of people alone. 33 00:03:26,310 --> 00:03:36,630 This is really important because density is one of the main ways that we assess transit demand is kind of the bread and butter and the groundwork. 34 00:03:36,630 --> 00:03:42,870 But it's not enough. And you really need to understand the differences in those populations to understand where 35 00:03:42,870 --> 00:03:50,710 transit demand is higher than others and make sure you're providing more service there. 36 00:03:50,710 --> 00:04:00,160 So how could we use something, a measure like that, to directly compare it to how high quality transit access it is? 37 00:04:00,160 --> 00:04:07,960 This is a map of the Boston area showing that same demand map that I've just showed with the socioeconomic characteristics, 38 00:04:07,960 --> 00:04:12,580 Big Ten, compared to the number of jobs accessible by transit. 39 00:04:12,580 --> 00:04:21,490 So this is a matrix map. Any of those red and kind of bright purple areas have high demand, but low access. 40 00:04:21,490 --> 00:04:30,730 And it's not a surprise, although it is unfortunate that all of these areas are majority communities of colour and low income. 41 00:04:30,730 --> 00:04:44,950 So this is a really easy way to use cartography and data analysis to focus on where your efforts should be most prioritised. 42 00:04:44,950 --> 00:04:54,010 So something of a pandemic has really made clear is that trenda equity is not just about where, it's about when Koban 19, 43 00:04:54,010 --> 00:04:59,080 has illuminated that a central workers and transit dependent riders do not exhibit 44 00:04:59,080 --> 00:05:08,160 those sharp peaks that exist when white collar downtown workers are are riding transit. 45 00:05:08,160 --> 00:05:14,380 So, yeah, this is pretty pandemic. We have those really high peaks, but this is during Cobbett at the same time. 46 00:05:14,380 --> 00:05:25,540 And we see that that demand is really more spread out over the day. However, this reflects the needs of the most transit dependent populations. 47 00:05:25,540 --> 00:05:34,400 But peak level services, almost always of higher quality and more frequent. 48 00:05:34,400 --> 00:05:40,640 And when we really dive into that, it's not just that certain types of workers travel at different times, 49 00:05:40,640 --> 00:05:47,060 but that pattern itself is really geographically cluster. 50 00:05:47,060 --> 00:05:57,000 So this is a map of the Chicago area. And if any of you know anything about Chicago, the South and west sides are largely black. 51 00:05:57,000 --> 00:06:02,160 And as well as Hispanic and the southwest, the southwest and the northwest sides. 52 00:06:02,160 --> 00:06:07,670 And the north side is predominantly white, high income and very dense. 53 00:06:07,670 --> 00:06:15,580 This map shows the likelihood of people leaving for work during the traditional like 9:00 a.m. 54 00:06:15,580 --> 00:06:19,490 Keep in that white area. It's close to 100 percent. 55 00:06:19,490 --> 00:06:24,620 Very, very, very high in these blue areas, which are mostly people of colour. 56 00:06:24,620 --> 00:06:33,200 It's, you know, in a lot of places, less than 20 percent. However, when you look at how transit is provided to those areas. 57 00:06:33,200 --> 00:06:39,110 This is the number of bus routes that come every 10 minutes or more often during the peak period. 58 00:06:39,110 --> 00:06:45,440 And this is the number of bus trips that come to that same level during the midday. 59 00:06:45,440 --> 00:06:53,420 Those, you know, all over transit quality drops much less frequently, most, but much less service. 60 00:06:53,420 --> 00:07:00,530 But there's absolutely no correlation between when people are travelling and when transit services provided. 61 00:07:00,530 --> 00:07:07,040 Look at that huge drop between service and the south side between peak and midday. 62 00:07:07,040 --> 00:07:16,730 And when we really examine that, we see that where bus ridership is really falling off the most is in those areas where there's not 63 00:07:16,730 --> 00:07:25,880 a correlation between when people are travelling and when bus service or transit services come in. 64 00:07:25,880 --> 00:07:31,880 This also has a large gender implications. Women are much more likely to work part time. 65 00:07:31,880 --> 00:07:38,600 So even if they did leave during that traditional and peak, probably that p.m. peak, is it appropriate for their travel needs? 66 00:07:38,600 --> 00:07:45,350 And they're not getting the highest quality transit service. Women are also much more likely to trip change. 67 00:07:45,350 --> 00:07:54,680 Meaning that on the way to work, they're much more likely to drop a child off at school or at day-care, much more likely to get groceries after work. 68 00:07:54,680 --> 00:07:58,340 Much more likely to help take family members to the hospital. 69 00:07:58,340 --> 00:08:05,330 And because of this midday service and frequent service, all day is much more important for women. 70 00:08:05,330 --> 00:08:15,930 It's not just about commuting during a traditional commuting pattern, which is what a lot of the transit service is oriented around. 71 00:08:15,930 --> 00:08:24,840 Another thing to examine is where transit access is highest and then compare it to transit need directly. 72 00:08:24,840 --> 00:08:31,560 So this is a map showing the number of jobs that can be reached within a 45 minute transit ride. 73 00:08:31,560 --> 00:08:33,960 Again, in that Chicago area. 74 00:08:33,960 --> 00:08:41,880 And to backtrack on what I just said, being able to access jobs via transit is not just being able to access a place you can work. 75 00:08:41,880 --> 00:08:49,080 It also means being able to access hospitals, restaurants, grocery stores anywhere where someone works. 76 00:08:49,080 --> 00:08:55,230 So this is a really good way to think about economic integration overall. 77 00:08:55,230 --> 00:08:56,280 So when we look at this, 78 00:08:56,280 --> 00:09:08,190 it's that those red areas are where transit access is very high and it drops off extremely quickly outside of the rail network in Chicago. 79 00:09:08,190 --> 00:09:15,120 So I use that blew out that big blue outline here to indicate where that access really draws up, falls off. 80 00:09:15,120 --> 00:09:28,410 And I'll be talking using that again later. So using that same access map and then comparing it to where vehicle ownership is very low. 81 00:09:28,410 --> 00:09:33,480 Similar to that map I showed earlier, this is a matrix map. 82 00:09:33,480 --> 00:09:41,880 We can see that there are some areas where transit access is very low, but vehicle ownership is also very low. 83 00:09:41,880 --> 00:09:46,350 So all of those areas are these bright red. 84 00:09:46,350 --> 00:09:51,470 And again, that's in majority black communities. 85 00:09:51,470 --> 00:09:55,980 And, you know, there's areas up in the north side where vehicle ownership is low as well. 86 00:09:55,980 --> 00:10:00,510 But they are really good transit access. That's not a mobility issue. 87 00:10:00,510 --> 00:10:08,520 When we look at these areas where people have no cars and no transit, it's not surprising that unemployment is very high in these areas. 88 00:10:08,520 --> 00:10:17,970 That's indicated by these yellow outlines. So that's another really important way to prioritise where we should put investments, 89 00:10:17,970 --> 00:10:29,520 because this is incredibly impacting people's ability to find work and also access any type of service. 90 00:10:29,520 --> 00:10:36,390 However, we need to continue to examine the fact that. 91 00:10:36,390 --> 00:10:44,050 Poor transit access to reach areas where white. 92 00:10:44,050 --> 00:10:51,370 Wealthy men need to go is not necessarily helpful for other communities. 93 00:10:51,370 --> 00:10:56,170 So this map is displaying large travel clothes with low transit use and all the 94 00:10:56,170 --> 00:11:01,780 purple areas are those where the minority population is higher than 50 percent. 95 00:11:01,780 --> 00:11:05,320 None of these flows follow the rail network. 96 00:11:05,320 --> 00:11:15,790 And even when people of colour do live right along rail network, they're much more likely to be taking the bus than their white counterparts. 97 00:11:15,790 --> 00:11:23,290 What this means is that just it's extending or making rail service that goes into downtown Chicago better for us 98 00:11:23,290 --> 00:11:30,430 in communities of colour isn't necessarily increasing their access because it's not going where they need to go. 99 00:11:30,430 --> 00:11:43,770 All of these flows are best served by bus service. And when we look at the bus service that serves those areas, many of them are very low quality. 100 00:11:43,770 --> 00:11:52,850 There's not very many of them. And. The midday service, how frequently that's happening. 101 00:11:52,850 --> 00:11:59,000 Is under. Mostly under 15 percent. 102 00:11:59,000 --> 00:12:06,620 So, you know, even if there is bus service serving these areas and these are very dense urban areas, 103 00:12:06,620 --> 00:12:09,230 the likelihood that they're coming frequently during the midday, 104 00:12:09,230 --> 00:12:17,270 again, which is going to benefit women, people of colour, low wage workers, the most that that quality that need. 105 00:12:17,270 --> 00:12:31,970 It's not meeting the needs of those people who really are more transit dependent than their white, wealthy male counterparts. 106 00:12:31,970 --> 00:12:37,090 Another way to continue to make sure that we're. 107 00:12:37,090 --> 00:12:44,190 Focussing on interrogating the idea that just. 108 00:12:44,190 --> 00:12:55,980 Expanding transit transit service that benefits white wealthy men is to overlap where transit demand is very high. 109 00:12:55,980 --> 00:13:01,680 So all of these areas that are coloured in have very high transit demand for service. 110 00:13:01,680 --> 00:13:10,010 You know, 10 minutes or more frequently compared to how often people there are actually using transit. 111 00:13:10,010 --> 00:13:15,480 So the blue is very high transit use. 112 00:13:15,480 --> 00:13:19,350 Yellow is. More average for this area. 113 00:13:19,350 --> 00:13:28,230 And then red is low. So coming back to that blue outline I said before of high transit access everywhere 114 00:13:28,230 --> 00:13:37,660 that's red inside that high access is an area that's majority Hispanic residents. 115 00:13:37,660 --> 00:13:49,740 And so why might that be? When we look at the number of people of different racial and ethnic groups that work in downtown Chicago, 116 00:13:49,740 --> 00:13:59,220 where all the transit services oriented to Hispanic residents are by far the least likely to work in downtown Chicago. 117 00:13:59,220 --> 00:14:05,250 So even though they have high access, theoretically they're not. 118 00:14:05,250 --> 00:14:09,540 That that network does not respond to their needs. 119 00:14:09,540 --> 00:14:22,920 So they're not taking transit, even though Hispanic residents tend to be lower income and really benefit from transit. 120 00:14:22,920 --> 00:14:29,190 So what does all of this mean? How how can we take this forward? 121 00:14:29,190 --> 00:14:35,520 Understand what? How to plan best for different communities? 122 00:14:35,520 --> 00:14:39,810 What we know for sure is that planning for the average will always leave people out. 123 00:14:39,810 --> 00:14:45,780 Equable planning doesn't mean looking for the same solutions for everyone. 124 00:14:45,780 --> 00:14:50,130 It's about target. Target solutions based on difference. 125 00:14:50,130 --> 00:14:59,490 Because usually when we think about the dominant need that's based on people in power and other communities needs really different from that. 126 00:14:59,490 --> 00:15:04,620 And by analysing and telling stories with data and cartography, 127 00:15:04,620 --> 00:15:12,810 maps can help target solutions directly and make, you know, very compelling arguments for city officials. 128 00:15:12,810 --> 00:15:20,190 You know, people who are just going to glance at something, be able to understand where to prioritise until really clear stories. 129 00:15:20,190 --> 00:15:25,480 Thanks so much for the time today. Thank you, Susie. 130 00:15:25,480 --> 00:15:32,650 That was absolutely fantastic. We've got quite a few questions and not enough time really to go through them all. 131 00:15:32,650 --> 00:15:42,730 So first one, is this an American phenomenon or do things tend to play out, say, in other cities across the world? 132 00:15:42,730 --> 00:15:53,850 I don't know Transat as well in other countries, but I do know that historically. 133 00:15:53,850 --> 00:16:05,020 In the U.K., for sure. Any sort of like rail line that is centred around a rail network that brings people into downtown is mostly with, 134 00:16:05,020 --> 00:16:09,270 you know, commuting men in mind and was built around that. 135 00:16:09,270 --> 00:16:14,870 But, yeah, I can't I'm not I'm not going to speak to one of them under shirt. 136 00:16:14,870 --> 00:16:18,510 But I'm that's a reasonable comment, something. 137 00:16:18,510 --> 00:16:22,830 But this civil suit is coming to this is really powerful work. 138 00:16:22,830 --> 00:16:26,820 Has it impacted decisions that future investments. Yeah. 139 00:16:26,820 --> 00:16:36,360 And I think something that really inspired my talk today was the Black Lives Matter movement, which obviously has been going on for many years, 140 00:16:36,360 --> 00:16:44,130 but was very in the spotlight last summer, made, you know, transit agencies usually say they focus on equity, 141 00:16:44,130 --> 00:16:52,020 but I think it's put a really big push to focus on what equity actually means and how a lot of 142 00:16:52,020 --> 00:16:58,950 places in the United States re-examine their racist histories and think about how redlining, 143 00:16:58,950 --> 00:17:05,610 which was, you know, intentionally displacing people of colour and lowering the values of the land that they lived 144 00:17:05,610 --> 00:17:11,370 on and not prioritising transportation investments in those communities needs to be righted. 145 00:17:11,370 --> 00:17:17,430 So a lot of at the beginning I said, you know, equity and productivity, 146 00:17:17,430 --> 00:17:25,950 like getting people on the bus are they're seen as separate, but really they go hand-in-hand. 147 00:17:25,950 --> 00:17:34,230 So there's a lot of really good push right now to use equity to make things better. 148 00:17:34,230 --> 00:17:42,720 But I will say that, you know, there's still tons of transit investment in the United States that does promote gentrification and displacing people. 149 00:17:42,720 --> 00:17:46,140 So it's you know, it's not as easy as like transit is good. 150 00:17:46,140 --> 00:17:49,980 You know, there's there's a lot going into it that we have to examine. OK. 151 00:17:49,980 --> 00:17:54,710 And building on from that, Susie, and trying to merge a couple of questions together, 152 00:17:54,710 --> 00:17:59,420 putting public transport where needed according to the data you have. 153 00:17:59,420 --> 00:18:04,200 Could that reinforce or dissolve the inequalities in different groups? 154 00:18:04,200 --> 00:18:12,740 And can you encourage certain behaviour, sir, for example, reducing car use amongst the wealthy mobile population? 155 00:18:12,740 --> 00:18:17,470 Yeah, I think. There for. 156 00:18:17,470 --> 00:18:25,380 For anybody to use transit. It needs to be high quality and allow you to get where you need to go. 157 00:18:25,380 --> 00:18:30,490 And I know you know, especially there's a an example in the Boston region where there's a low income unit, 158 00:18:30,490 --> 00:18:36,310 low income community right north of downtown that has really poor transit access. 159 00:18:36,310 --> 00:18:42,760 Even though they're really geographically close to a lot of jobs and car ownership is actually a lot higher there than you might expect. 160 00:18:42,760 --> 00:18:49,570 But that's because people there have no other choice if they want to be able to have jobs, to have any sort of mobility. 161 00:18:49,570 --> 00:18:57,940 So especially targeting those areas where, you know, allowing people to put their money towards something else that is in transportation, 162 00:18:57,940 --> 00:19:06,560 which often can be up to 30 percent of what people spend their money on this trip in transportation can allow for, you know. 163 00:19:06,560 --> 00:19:13,880 Money is to be used for many other things that could advance those populations, you know, education, just food, general things. 164 00:19:13,880 --> 00:19:21,470 So I think it is a huge, like poverty alleviation measure to provide good transit, especially to those who need it most. 165 00:19:21,470 --> 00:19:29,840 And yes, we certainly also are not. We also focus on making transit quality good for everybody. 166 00:19:29,840 --> 00:19:32,520 We're not like excluding wealthy populations. 167 00:19:32,520 --> 00:19:41,000 But essentially, my argument is that in major cities in the US, transit is already created best for wealthy people. 168 00:19:41,000 --> 00:19:48,860 So our investment focus should be on low income communities, people of colour and women. 169 00:19:48,860 --> 00:19:57,505 And that's a really comprehensive answer. Thanks ever so much. So, see, that's a really illuminating presentation.