Park(ing) Day in Seattle

Park(ing)Day took place on Friday, September 19, and was a "one-day, global event centered in San Francisco where artists, activists, and citizens collaborate to temporarily transform metered parking spots into “PARK(ing)” spaces: temporary public parks." The Trust for Public Land hired CORE GIS to create a map of the park locations in Seattle, to hand out to curious passers-by and help people find the various parks.

This photo of one of the parks was taken by Jeanine Anderson.

Sustainable Ballard: Local Food Production and Population

CORE GIS is located right on the edge of the Ballard neighborhood in Seattle. The non-profit Sustainable Ballard has been active in numerous sustainability and environmental issues, and each year at this time they ramp up their "Eat Local" campaign by promoting the 100 mile diet.

This seems like a great idea, for a number of reasons--it supports local farmers and local economies, reduces fossil fuel consumption, builds community, and encourages all of us to think about where and how our food is grown.

I decided to take this idea to its logical extreme--what if everyone in Seattle decided to follow the 100 mile diet? Do we have enough agricultural land to support that many people?

I started with 2000 U.S. Census data, specifically the SF1 100% population count at the block group. Then I used 2001 NLCD land cover data and extracted the two agricultural classes--cultivated crops and hay/pasture. I arbitrarily chose a spot in the middle of Seattle, created 50 mile and 100 mile buffers, then counted up the number of people and the acres of agricultural land within the two distance bands.

As it turns out there is far less acreage in cultivated crops than in hay/pasture, and within 50 miles, each acre of cultivated crops would need to feed 172 people! If we assume that all of the hay/pasture can be converted into cultivated crops, the number of people supported by one acre drops to 22. Moving out to 100 miles improves the situation, with just under 31 people per acre of cultivated crops and just under 7 per acre for all agricultural land. (The cartographic and tabular results are shown in the thumbnail image to the right; if you'd like to download a screen-resolution PDF of the 30"x36" poster, just click here. Please contact me if you'd like a printed version).

However, according to one study, a meat-based diet requires 9 acres per person! A diet that is primarily plant-based (with some milk, cheese, and eggs) requires 3/4 of an acre. Clearly, we still have far too little agricultural land within our 100 mile radius to feed our entire population.

This suggests to me that our region has a lot of thinking to do about our food security and food sovereignty. What happens if there are shortages of fossil fuels, in particular diesel, for transporting food across the vast distances it currently travels? Are there areas within our region that have prime agricultural soils that are not being cultivated? What policies can/should be put in place to ensure that we have the capacity to feed a much larger proportion of our population from local farms? How should our food distribution network change to make it easier and more efficient for local farmers to get their produce to market?

Stemilt Partnership

For the past several months I've been working with the Trust for Public Land on the Stemilt-Squilchuck Community Vision. Our client is Chelan County, and we've been working closely with a large citizen group known as the Stemilt Partnership. This photo was taken just after our most recent Partnership meeting last Wednesday at the Malaga Fire Hall. The project started in response to a proposed land exchange in which the Washington Department of Natural Resources was planning to divest itself of four sections in the upper part of the basin. As it happens, these four sections form the central core of many of the land use and land management activities that affect the entire watershed. The Partnership was formed to help the County determine what should happen with the land in light of all of the stakeholder groups that are using these public lands.

This project has been particularly interesting for me to work on, because it contains all of the elements that I really love about my job--interesting data and modeling challenges, lots of cartography, the opportunity to meet with and learn from a wide range of citizens and agency people (farmers, real estate developers, wildlife biologists, policy wonks, etc), public speaking and lots of travel to the watershed. The timeline is fairly compact for a project of this size and complexity, but I think the fact that so many community members are heavily engaged will help us produce an excellent result.

Chuckanut Mountains Park District Map

I recently completed work on a map for the Chuckanut Mountains Park District. This was a quick, fun project I did for Ken Wilcox and the other folks involved in establishing a more coherent and comprehensive land management approach for this unique region. The Chuckanut Mountains are the only place where the Cascade foothills come all the way to salt water.

The map shows 2006 NRCS NAIP 1 m color orthophotography, major public land owners (derived from the Snohomish and Skagit County parcel databases), as well as all private parcels 10 acres or larger in size.

I wish the CMPD well, and I hope this large poster (40" x 60") is helpful in accomplishing their mission.

Mauritius--A Projection Challenge

Recently, I was asked by one of my clients to project a bunch of data for the island nation of Mauritius in preparation for some wetlands-related field work they will be doing there. They received the data from the national government, and there was no projection information included with the data.

As it turns out, Mauritius has its own grid, which is independent from all other geographic coordinate systems and is not natively supported by ArcMap. According to a map I found on the Government of Mauritius web site, the projection is as follows:

Grid : Mauritius
Projection : Lambert Conical Orthomorphic
Spheroid : Clarke 1880
Unit Of Measurement : Metre
Longitude of origin : 57°31'18.58" East of Greenwich
Latitude of Origin : 20°11'42.25" South
Scale Factor at Origin : Unity
False Co-ordinates of origin : 1,000,000m Easting
1,000,000m Northing

Unfortunately, Lambert Conical Orthomorphic is not available in ArcMap, but through my research I determined that Lambert Conformal Conic is a very close approximation. So, converting the above description into ESRI lingo, it looks something like this:

Projected Coordinate System: Mauritius
Projection: Lambert_Conformal_Conic
False_Easting: 1000000.00000000
False_Northing: 1000000.00000000
Central_Meridian: 57.52183000
Standard_Parallel_1: -20.19507000
Standard_Parallel_2: -20.19507000
Scale_Factor: 1.0
Latitude_Of_Origin: -20.19507000
Linear Unit: Meter

I punted on the Standard Parallels, assuming that the island is small enough for the latitude of origin to suffice for both parallels. This sort of worked, and I placed the GTOPO global DEM in the map frame with the newly projected data, resulting in the first image. Seems close, but a bit hard to tell.

So I downloaded SRTM data for the island, which has much higher resolution than GTOPO, and the result is the second image. Clearly, pretty far off. At this point, I was getting in over my head with respect to creating custom datum/spheroid combinations, so I called the good folks at ESRI and after an hour on the phone, they helped me to build a very solid projection and transformation for Mauritius (this is the actual PRJ file, please feel free to use it, just remove the carriage returns after each comma before saving as a PRJ):

PROJCS["Mauritius_lambert",
GEOGCS["Mauritius",
DATUM["",
SPHEROID["Clarke_1880_RGS",6378249.145,293.465]],
PRIMEM["Greenwich",0.0],
UNIT["Degree",0.0174532925199433]],
PROJECTION["Lambert_Conformal_Conic"],
PARAMETER["False_Easting",1000000.0],
PARAMETER["False_Northing",1000000.0],
PARAMETER["Central_Meridian",57.52182777777779],
PARAMETER["Standard_Parallel_1",-20.19506944444445],
PARAMETER["Standard_Parallel_2",-20.19506944444445],
PARAMETER["Latitude_Of_Origin",-20.19506944444445],
UNIT["Meter",1.0]]

The custom datum comes from the Le_Pouce_1934_TO_WGS_1984 transformation ESRI helped me to create, which is here (again, remove CR after commas, save as a gtf file):

GEOGTRAN["Le_Pouce_1934_TO_WGS_1984",
GEOGCS["Mauritius",DATUM["",
SPHEROID["Clarke_1880_RGS",6378249.145,293.465]],
PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],
GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",
SPHEROID["WGS_1984",6378137.0,298.257223563]],
PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],
METHOD["Geocentric_Translation"],
PARAMETER["X_Axis_Translation",-770.1],
PARAMETER["Y_Axis_Translation",158.4],
PARAMETER["Z_Axis_Translation",-498.2]]

The result is a very nice agreement between the red coastline vector and the SRTM topography, shown in the third image.