Tag Archives: maps

How far will public transit take you in 15 minutes?

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Mapnificent answers this question by drawing travel-sheds for trip lengths you select.  They dynamic slider to change trip travel time is really cool.  You can also change the settings to include biking to/from stations (rather than walking) and you can compute the intersection between two or more travel sheds.

I’d love to see them add bike and car travel sheds to this map.  Presumably the data could be pulled from Google in the same way as transit information.  Pairing this information with NAICS data could provide a really powerful accessibility map.

One drawback (at least for the Twin Cities), they don’t appear to have any data for opt-out transit services (Southwest, MVTA, etc).

Explore The Twin Cities LEED ND Maps

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View Full Screen

For a while I’ve been looking for a better way to display the maps I made for the LEED ND and Regional Planning series.  After some experimentation with the Google Maps API, I’ve got something functional.  There have been a few times when I’ve been presenting this topic and wished I had a way to pan around the metro and zoom in on specific areas.  This works well.

I haven’t quite figured out how to do a legend yet, so here’s the key: red areas are those place that are likely eligible for LEED ND based on the Smart Location and Linkage prerequisites. Areas in yellow may be eligible if the local comprehensive plan guiding (and accompanying zoning) were changed to allow density consistent with LEED ND requirements. View the map full screen.

For the full run-down on how I developed these maps, check out the whole LEED ND and Regional Planning series.

What locations in the Twin Cities are eligible for LEED ND: Part 1

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In a previous post, I talked about the news that HUD will begin scoring grant applications based on location efficiency, and using the LEED ND rating system to do so.  While it is not yet clear what exactly HUD means by this, we can do our own exercise to look at the ND system, compare it to the existing built environment and see what locations in the Twin Cities might be eligible.

This isn’t just about HUD and their projects, it is a way of determining what the best locations are for new development that would ensure compact, contiguous development that makes the most efficient use of infrastructure and has multiple transportation options.  Or in other words, it’s a method to begin planning a more sustainable region.

Before the analysis, a little background on LEED ND is appropriate:

The rating system is divided into five topic areas:

  • Smart Location and Linkage
  • Neighborhood Pattern and Design
  • Green Infrastructure and Buildings
  • Innovation and Design Process
  • Regional Priority Credit

The first three topic areas have prerequisites, or requirements that a project must meet in order to be eligible.  All the topic areas have credits, from which a project proposer can choose to achieve to meet the various certification levels (Certified: 40, Silver: 50, Gold: 60, Platinum: 80).

While the LEED ND system is long and complex, there is really one topic area of the five in the rating system that deals with location and what land is off-limits versus eligible: Smart Location and Linkage (SLL).  In this topic, there are five prerequisites and nine credits.  For the purposes of this exercise, we’re going to be looking at just the prerequisites for LEED ND SLL, because once you get into credits, you have to start making lots of assumptions about how the project will be designed and what features it will contain.  In addition, the other four topic areas deal primarily with the design of the project, or what is inside the project boundary, something we can’t know until a project is proposed.  We want to know just what locations are at minimum eligible, and that means focusing on prerequisites in SLL.

Read on for the details of Smart Location and Linkage and the results.

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CNT Maps show what we should already know: addressing climate change is about land use

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cntco2map

The Center for Neighborhood Technology has added some great maps to their Housing and Transportation Affordability Index series that show, side by side, the difference between CO2 emissions per acre and per household from auto use.  Minneapolis/St. Paul is part of the series.

The message? Urban living produces up to 70% less transportation-related CO2 than suburban living, according to the press release.

“Cities are more location-efficient – meaning key destinations are closer to where people live and work,” said Scott Bernstein, CNT’s President. “They require less time, money, fuel and greenhouse gas emissions for residents to meet their everyday travel needs. People can walk, bike, car-share, take public transit. So residents of cities and compact communities generate less CO2 per household than people who live in more dispersed communities, like many suburbs and outlying areas.

I know, you say, that transportation is a big deal, but what about all those other factors like heating and cooling and waste?  We need to be looking at transportation in context and looking for complete solutions, you say.  So, what difference does location make as a percentage of total household emissions, between a household in Minneapolis (a community with the lowest auto-related emissions per household) versus one in say, Lino Lakes, Ramsey or Prior Lake (communities with the highest)? If it’s minuscule, let’s focus on other strategies to reduce emissions first, if it’s big, let’s admit that land use and transportation planning can play a big role in mitigating climate change and get to work.

The map says the difference is roughly 5.3 metric tons of CO2 from auto transportation.  According to the US EPA emissions calculator, the average emissions for a household of three people, in total, is 62,250 pounds or 28 metric tons.  This means that if you choose an urban location over a very suburban one, you can cut your total household emissions by nearly 20%.  Some portions of Minneapolis, near downtown and in northeast, are between zero and 3.3 metric tons per household, meaning the difference could be up to 30%.