It started in the garden. That’s what 39-year-old Kevin Bell will tell you was the genesis of the idea that led him to use 3-D mapping technology to quantify the solar energy and food-growing potentials for every square foot in Salt Lake City.

Bell is a IT guy specializing in mapping and GPS (Global Positioning System) systems for the City of Salt Lake, and he’s also an urban farmer. He and his wife, Celia, are something like rock stars in the local urban farming scene (if there could be such a thing). They work a 1.5-acre patch in Glendale. From this land they produce the lion’s share of their food needs. They use advanced techniques for irrigation, planting and season extension to accomplish this, and everyone from hobbyists to community garden activists, agricultural professors to conservation students, consults with them on how to make things grow in the SLC.

Bell himself is an iconoclastic personality who defies pigeonholing. His lean frame, Nazarene beard and long, red hair all scream Rocky Mountain hippie-snowboarder, but he’s a gun-owner and loves riding dual-sport motorcycles around the deserts and mountains of Utah. (He also rips up the backcountry on his split-board.) His interests in self-sufficient living intersect unexpectedly with his skills at data analysis. By day he’s a techie wunderkind, and by night he’s a back-to-the-land crusader committed to living as simply as possible. And, if you know Bell, you know all that works.  


Three years ago, Bell was playing around with a data gift from the FBI. In preparation for security measures for the 2002 Winter Olympics, the bureau performed a 3-D mapping flyover of the city using LIDAR (Light Detection and Ranging, basically RADAR with a laser instead of radio waves). The FBI uses this data to figure out places snipers or other such bad guys could conduct their nefarious business. After the sniper-free Olympics were complete, they gave the mapping data to the city.
Just for kicks, Bell used this LIDAR data to map his own farming plot and determine which portions received the most sunlight for each day of the year.

“I took home the data on my plot, looked up the sun angles for different times of year and, using the 3-D model, generated my own tool for looking at sun patterns on my yard,” he says. “I could simulate the sunlight, find the hottest places and coldest places. I had a high-resolution analysis of the shadow patterns, and I laid out the pathways and structures in the areas that were least-optimal for growing.”

With this personal project in his back pocket, Bell was brought into a city project that sought to create a solar map of Salt Lake as part of the Solar City program. “Since we had all of this 3-D data, I suggested that we incorporate the actual model of the city and estimate solar potential that accounted for every shape, tree, building, chimney and surface in the city.”

So Bell created a number-crunching program that used the LIDAR data to take into account shadows cast by other buildings, trees, etc. The result was a city website to determine sun intensity.

“It’s a visual map,” Bell says. “You can see your house’s solar potential and estimate your energy savings if you were to install a solar device.”

No sense in putting expensive photovoltaic panels on your roof if it’s in the shade most of the time, right?

“We’ll see the most action with the site as the price for panels starts to drop,” he says. “But it’s also useful for investigating other passive solar devices like solar water heaters, which are relatively inexpensive.


Armed with the techniques for mapping solar energy potential, Bell once again stumbled upon a novel use for the LIDAR data, after a meeting kicking off a community food assessment. The assessment, which is still in progress, is an effort to evaluate the availability of food and food-growing potential around the county.

“So, we had quantified the ‘sun-shed,’ and we know how much sunlight falls on every square foot of land in SLC,” he says. “We had this great idea. Why not evaluate how much food could be grown with that sunlight? Why not quantify the food shed?”

So Bell divided up the city, subtracted the hardscape (like driveways), structures and the tree canopy to come up with the total amount of arable land. University of Utah students helped out by using data from bio-intensive gardening guru John Jeavons, who has calculated calorie potential in the city by square foot. This combo allows users of the soon-to-be-completed website to calculate how much food they could grow on their property.

“Now, is everybody going to raze their yard and plant every square inch, like me?” Bell asks. “Well, no, but it’s a starting point. You can see how much food you can grow if you use, say, 25 percent of your yard.”


Bell’s use of the 3-D mapping data has many more applications, especially when combined with other data sets. For example, he has combined the LIDAR, sun angle and vehicle accident data to determine what intersections are more dangerous at different times of day because of sun glare.

“Mapping traffic accident hot spots was something a transportation manager in the 1950s could only dream of,” he says. “Back then you’d have paper accident reports and no way of making any sense of them, but now that we have all this in databases, we can use it in so many ways.”

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