Boston, New York City, Denver, Cambridge and other cities have created solar potential maps to help their residents understand that solar photovoltaic systems are viable in dense urban areas, and to demonstrate the potential that exists on rooftops.
Of course, I had to try this myself.
Minnesota produces LiDAR data, which is basically micro-scale elevation data produced by flying a plane back and forth in a grid and shooting the ground with lasers a bajillion times. Skilled/obsessive GIS users can clean from this data information that can be used to make a fairly accurate model of everything on the ground (buildings, trees, etc). GIS software also makes it easy to produce daily, monthly or annual solar insolation maps. By taking the position of the buildings and trees, knowing the latitude, and projecting how the sun moves across the sky throughout the year, the software calculates a total amount of solar radiation that will hit a point after shading, angle and other factors are taken into account.
Solar insolation in January
After much tinkering, the Kingfield Solar Energy Potential map was born. The extreme density of the LiDAR data limits how large an area I could process (there were 4.9 million individual data points in this one small section of Minneapolis), but you get the idea. This map shows the area of each roof that might be appropriate for solar, how many panels could fit in that area, and an estimate of the annual production from those panels.
The Kingfield Solar Map
Some roofs are wholly inappropriate for solar, whether due to tree or building shading, orientation or size. But there is significant potential. If solar was installed on every appropriate piece of roof in this one-quarter square mile area, it would produce an estimated 2.2 megawatt hours of electricity each year, and avoid 2.9 million pounds of carbon dioxide emissions.
Minnpost has taken my concept of mapping Nice Ride data to new heights. They’ve produced an animation of a 24-hour period showing where bikes navigated. I haven’t figured out how to embed the animation, so you’ll have to click on over.
For the mapping nerds: they used Routino, which I never figured out how to use, rather than ArcGIS with Network Analyst.
Nice Ride has released their data on rentals from 2011. After seeing these maps of “route fluxes” from bike sharing systems around the world by Oliver O’Brien at the Suprageography blog, I just had to figure out how to make them myself.
I didn’t use Routino as Oliver did, but instead figured out a way to make ArcGIS Network Analyst do what I wanted (after a fair amount of data wrangling and lots of loading time). I’ll probably post more on that later.
Trip counts on each segment vary between 4 and 29,000. I restricted bike routes to roads with a speed limit under 40 mph. One drawback is that my road network did not include off-street trails (greenway, etc).
Google has a pretty cool labs project called Fusion Tables, which I think most people don’t know about. One great feature is the ability to create a web map from georeferenced data quickly and easily. Great news, it’s getting even easier. From Steven Vance, news that you can now upload shapefiles (through a third-party site).
It is now possible to upload a shapefile (and its companion files SHX, PRJ, and DBF) to Google Fusion Tables (GFT).
Before we go any further, keep in mind that the application that does this will only process 100,000 rows. Additionally, GFT only gives each user 200 MB of storage (and they don’t tell you your current status, that I can see).
- Login to your Google account (at Gmail, or at GFT).
- Prepare your data. Ensure it has fewer than 100,000 rows.
- ZIP up your dataX.shp, dataX.shx, dataX.prj, and dataX.dbf. Use WinZip for Windows, or for Mac, right-click the selection of files and select “Compress 4 items”.
- Visit the Shape to Fusion website. You will have to authorize the web application to “grant access” to your GFT tables. It needs this access so that after the web application processes your data, it can insert it into GFT.
- If you want a Centroid Geometry column or a Simplified Geometry column added, click “Advanced Options” and check their checkboxes – see notes below for an explanation.
- Choose the file to upload and click Upload.
- Leave the window open until it says it has processed all of the rows. It will report “Processed Y rows and inserted Y rows”. You will be given a link to the GFT the web application created.
Here is a web map I made
of Minneapolis bike count
figures over time, the old fashioned way (geocoding by hand). You could also get this to work before by exporting KML from ArcGIS an importing it into Fusion Tables, but that was clunky and had inconsistent results. Google should incorporate this quickly, if they want to keep up with what you can do with ArcGIS Online
On-street bike parking at the Birchwood Cafe in Seward
New American Community Survey data is out, which gives us the first look at Census Tract-level data since 2000. I pulled out some transportation data for the Twin Cities metro, and previously looked at trip-to-work mode share changes for the region. Cycling and telecommuting showed gains, carpooling and driving alone showed losses.
These small changes don’t seem that interesting, until you start to dive into the data. Since cycling gained mode share, it’s worth exploring in more detail where these gains are happening. Are the gains happening uniformly across the metro, or in specific areas? What places have the highest bicycle mode share? What do the changes mean for infrastructure and transportation planning? Attempts at answers are after the break. Continue reading
New 5-year estimates from the American Community Survey are out, which give everyone the first update of Census tract-level data since the 2000 Census. If you haven’t explored the New York Times Mapping America tool for some of the broader trends (race, income, housing and education), make sure to check it out.
I pulled out some journey to work data (mode and travel time) for the seven county Twin Cities area since the New York Times didn’t include any transportation information and I was curious. I’ll be sharing some interesting things I find over the next week. You can download my raw data set here.
The first thing I looked at was simply the change in mode share for travel to work for the metro as a whole. Mode share increased for working at home (which could be telecommuting) and bicycling. Mode share for telecommuting rose almost 3/4 of a percent, while bicycling was up a little less than 1/2 of a percent. However, if you look at change in total commuters for each mode, the number of cycling commuters increased over 90% since 2000, while the number of telecommuters increased 25%. Driving alone, carpooling and walking all lost mode share, noticeably, carpooling was down over 1 percentage point. Transit stayed nearly static.
Next time I’ll dive a little deeper into these changes in bike and telecommuting mode share and map how changes are happening across the metro.
Where can Twin Cities residents with kids in child care commute actively?
One of the easier ways to incorporate more physical activity into your daily life is switching from an auto-powered commute to a foot-powered commute. This might mean walking to transit or biking to work. Although many people’s commutes are bikeable, if you have kids, the availability of child care near you can mean the bike stays in the garage.
In the first post of this series I proposed that child care needed to be within 1/4 mile of your home in order to make an active commute feasible. So how accessible is child care in the Twin Cities? Where are the best and worst neighborhoods for parents who want an “active” commute? I think I have some answers below the break.