How to catch a wave

Thursday, December 6, 2012
by Diane Boudreau


The air around you right now is full of waves. The sun emits light waves and other objects reflect them. Radio waves cruise by on their way to the nearest stereo. If you’re outside, ultraviolet waves might be giving you a sun tan. In kitchens around town, microwaves are heating up leftovers from last night’s dinner.

All of these waves are part of the electromagnetic (EM) spectrum. The waves along this spectrum range from the size of an atomic nucleus (gamma rays) to the length of a football field (radio waves) and beyond. The only waves you can see are light waves, which fall in the middle of the spectrum. If you look at a rainbow, the colors appear in order from the longest wavelengths (red) to the shortest (violet).

Scientists can use EM waves that are emitted or reflected by objects to get information. For example, cameras capture visible light to make pictures. Radar bounces sound waves off objects to find out where they are and how fast they are moving. Infrared thermometers can detect temperatures from a distance using infrared (heat) radiation.

All of these techniques are forms of remote sensing, a way of getting information about an object without touching it. Scientists working on the UVCC study at Arizona State University (ASU) are using remote sensing to find out how land is being used throughout the Phoenix area and how that affects temperature.

“When you talk about a city the size of Phoenix, going out on the ground and mapping objects is extremely time intensive. Remote sensing allows us to do this in a more efficient manner. Using a satellite or a plane, we can get a snapshot of data,” explains William Stefanov, a contractor scientist with the NASA Johnson Space Center in Houston, Texas.

Stefanov is a geologist who specializes in remote sensing. He helped them set up an airplane flight over Phoenix using a NASA instrument called the MODIS/ASTER (MASTER) simulator.

MASTER’s sensor measures 50 different wavelengths, ranging from blue light to infrared. The infrared data is particularly useful for determining surface temperatures.

A photo and infrared image of Phoenix
These two images show part of Phoenix from the air. The top image is a photograph. The bottom one shows surface temperatures (infrared data) for the same area at night. You can see how the roads and rooftops are hotter than other areas.

The MASTER sensor was mounted on an airplane. The plane flew over Phoenix four times in July 2011— twice during the day and twice at night. It flew back and forth across the sky the way you might push a lawn mower back and forth across a lawn in rows, so you don’t miss any spots.

“The data give a good indication of what parts of the city are really hot and what parts are cool,” Stefanov says. This information is especially useful when you compare it with census data about people living in the neighborhoods.

“When you start putting the social information on top, it’s clear that people with the lowest socioeconomic status also tend to live in the most uncomfortable environmental conditions,” says Stefanov.

Why would low-SES neighborhoods be hotter? Most likely because they have different land cover than other neighborhoods. Juan Declet-Barreto is using remote sensing data to find out exactly what kinds of land cover exist in different neighborhoods in Phoenix. Declet-Barreto is a Ph.D. student in environmental social science at ASU.

He has been using aerial images from the U.S. Department of Agriculture. The images were taken by airplane in 2007. They provide data on red, green, blue and infrared wavelengths. Declet-Barreto says the infrared information is especially useful for locating plants.

Declet-Barreto takes the data and pulls it into remote sensing software. The software turns all the measurements into pictures. The pictures don’t have the full range of colors you’d see in a normal photograph. But it’s still pretty easy to make out the shapes of roads, trees, houses and swimming pools.

Declet-Barreto has been programming software to tease out the different kinds of land cover in different neighborhoods. He is “teaching” the computer to recognize features like roads, grass or trees. When Stefanov has finished processing the MASTER data, Declet-Barreto will use it to help the computer do an even better job at recognizing what’s on the ground.

But if Declet-Barreto can see these features with his own eyes, why does he need the computer to do it for him? For one thing, picking out every object by sight in 45 different neighborhoods would be terribly tedious.

“Land use/land cover classifications are done over large areas, usually on a regional scale,” he says. “These are really time-consuming, menial tasks. If you can have them automated, then you can get to the really interesting questions.”

The computer can also make calculations about what’s in the pictures. For example, it can figure out what percentage of land in a neighborhood is covered by grass. It can also compare that neighborhood to others.

Declet-Barreto pulls up images of two neighborhoods. “Look at the percentage of grass in this Historic Anglo Phoenix neighborhood—it’s 21 percent of the study area. Then you look at this Black Canyon Freeway neighborhood—it’s only 1.7 percent. The difference is really staggering.” He notes that the two neighborhoods are only about four or five miles apart.

Graphs compare green space in two neighborhoods
These graphs show the percentage of green space in two different Phoenix-area neighborhoods.

He adds: “For me the interesting question isn't knowing the percentage of trees in a particular neighborhood. For me the interesting question is figuring out why. Environmental benefits like those provided by trees and surface water are just an indicator of socioeconomic differences in the city.”

Stefanov, who received his Ph.D. in geology from ASU before moving to Houston, says this research lets the scientists take their work a step beyond the usual research about urban heat islands.

“We know there’s an urban heat island in Phoenix. That’s well established. Can we find where people are most vulnerable in the city to the heat island and to extreme heat events?” he asks. “This study is a really nice example of the kind of work that scientists who come from a different range of disciplines can do when they sit down and talk to each other. We can all get together and compare our world-views and see how they interact with each other.”

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