Watching the familiar, rural landscapes of our youth give way to suburban sameness has become as much a part of modern American life as portable electronics, instant food, and wasted time in front of the television. Nearly all of us have had the disappointing experience of returning to what used to be the woods near our childhood homes and finding a new subdivision. Or we have been shocked to see that some corporate entity has erected aluminum-sided duplexes and an outlet mall in the middle of our favorite vacation spot.

Like it or not, throughout this century, the United States has undergone a steady process of urbanization as a larger and larger percentage of the population has moved towards the cities. While increasing urbanization may have some positive impacts on our environment, such as the lower birth rates that come with a city lifestyle, scientists are becoming more concerned about the negative long-term effects. Unlike rural communities, urban sprawl completely transforms the landscape and the soil and alters the surrounding ecosystem and the climate.

Marc Imhoff, a biologist at NASA’s Goddard Space Flight Center, is one of these concerned scientists. For the past six years, he and a team of researchers have been looking for ways to measure the effects of urbanization on the biological productivity in the U. S. and other countries around the world. They created a method of mapping urbanization on a countrywide scale by using satellite images of the light cities generate at night. With the resulting city lights maps, they are now zeroing in on the impacts urban sprawl has on the food we eat, the air we breathe, and the ecosystem within which we live.

 Seeing the Light

The data used in this study are available in one or more of NASA's Earth Science Data Centers.

Urbanization in any country generally begins when large-scale commerce takes root and most new jobs are to be found in the factories and financial centers in cities. In the United States, urbanization began to occur roughly around the turn of the last century. Since then, the percentage of people living in the United States in urban areas has risen from 39 percent to more than 73 percent (U.S. Census Bureau, 1995). From decade to decade the amount of rural land that has been consumed by urbanization is enormous. Between 1982 and 1992, for instance, 19,000 square miles of otherwise rural cropland and wilderness were developed in the U.S. This would be the equivalent of covering half of Ohio into one big subdivision in a ten-year period (World Resources Institute, 1996).

Urbanization is not just an issue in the United States. Right now researchers estimate that worldwide movement towards cities is growing at three times the rate of population expansion worldwide. Only a third of the planet’s population lived in urban areas ten years ago. Now that number is up to 50 percent and in ten more years roughly two thirds of humanity will live in the cities (World Resources Institute, 1996).

Imhoff says that while working at Stanford University as a post-doctorate, he initially became intrigued by the biological implications of urbanization after he saw how urban sprawl appeared on the Earth’s surface when viewed from orbit. "I spent a number of years looking at the Earth from space, and I found it remarkable how human development of land looked a lot like biological growth. Like mold on an orange," he says.
 

He wanted to know how urban sprawl was changing the landscape on a global scale, and whether this increased development was affecting food supplies, local ecosystems, and even the global climate. Early on, he realized that the best way to do such a study would be to construct a map of urbanization using remote-sensing data from satellites. "Satellite data would give us a synoptic view of the globe from which we could get an explicit idea of where the human-dominated surface features are – especially with respect to cities. We could also merge that information with soil maps and biosphere data from other satellites to assess the impact of urbanization on ecosystems," he says.

To construct such a map Imhoff needed a satellite instrument that would give him a snapshot of the urbanization on an entire continent all at once. When he began this research, he had access to data from a number of remote-sensing satellites, such as Landsat 5 and NOAA’s operational satellites, that record the reflected sunlight and heat emissions from the surface of the Earth. But demarcating urban sprawl with the instruments on these satellites would require the researchers to retrieve close-up images of cities and separate each individual, urbanized area from the surrounding farms, parks, and wilderness. Doing so for an entire continent would have been labor intensive and tedious.
 

Imhoff found a solution in an unlikely place. He recounts a weekly astronomy club meeting he attended in 1996. "The people at the meeting were talking about how light pollution was a problem. They pulled out a satellite-generated city lights map. They were looking at it and saying, ‘Look at all that awful light pollution.’ And I’m there thinking, ‘This is exactly what I need. There’s my global map of where human beings are,’" he recalls.

The images were taken by a Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System (OLS). This network of satellites was originally designed to pick up on lunar illumination reflecting off of clouds at night in order to aid nighttime aircraft navigation. What the Air Force discovered is that on evenings when there was a new moon, the satellites were sensitive enough to record the illumination from city lights. Over a period of several new moons, the data the satellites retrieved could be pieced together to produce a global image of city lights.

Imhoff explains that in the past census researchers have tried to use the city lights images to estimate the number of people in urban areas. In general they could only get a rough count simply because there was no way to tell, by looking at the lights alone, whether a very densely populated city such as Seattle had more people per square mile than a sprawling city such as St. Louis. However, Imhoff and his team were not interested in population counts. They wanted to measure the spatial extent of urbanization. For this purpose, he reasoned, the maps would be perfect.

 Toning It Down
 Bright Lights, Big City

Upon receiving the satellite data, Imhoff realized there was one big problem they’d have to overcome." The raw image overestimates urbanized areas by as much as seven or eight times," he says. The problem came mostly from the effects of the relatively bright city lights on the satellites’ sensor array. The sensors on these satellites are made up of photoelectric cells organized into in a grid-like pattern, like pixels on a computer monitor. When light emanating from the Earth’s surface hits one pixel on the array, it is registered in the satellite data as a 2.7-km by 2.7-km square area of well-lit land surface.

Yet sometimes, bright lights trigger the initial pixel and inadvertently set off neighboring pixels in the array as well. If this happens, then an area the size of a city block will appear to be the size of three or four square blocks on the raw satellite image. It’s somewhat similar to what happens when a flash photo is taken of a mirror. Though the flashbulb itself may not be more than a couple of inches across, the light from the flash reflecting off the mirror would likely cover an area the size of a person’s head on the photograph.

To correct for this "blooming" effect, the Goddard team zoomed in on the lights emanating from individual cities, effectively isolating them from the larger, continental image. Using computers, they then lowered the overall brightness levels of the city image. The blob of lights representative of the given metropolis would begin to shrink on the outside in a manner similar to an evaporating puddle of water." We scale back on the brightness levels of the imaging data, until the perimeter stops shrinking on the outside and the interior lights of the city begin to break up," Imhoff says. "At that point we stop."

The researchers classified the lights left on the image, after this dimming process, as urban area. The previously lit areas on the image that shrank back were classified as peri-urban (low-density suburban areas or farmland). Any areas that had no lights to begin with were labeled as non-urban. They compared these classifications to the boundaries on the actual urban areas of the city and found there was a close match. Imhoff and his team now had a set of numbers (threshold values), which told them to what extent the lights from any portion of the United States should be dimmed to get an accurate and spatially explicit representation of urbanization.

Using the threshold values, Imhoff’s group categorized the entire continental United States into urban, peri-urban, and non-urban areas. To make sure the classifications were correct on a nationwide basis, they checked each state on their map against the 1990 U.S. Census population statistics. Imhoff explains the Census Bureau doesn’t map urban areas. However, it does classify urban areas as any region where there are 1000 people or more per square mile, and it takes a tally of who lives in these areas. By merging the city urban map with the Census data, the researchers could calculate population density for the urban, peri-urban, and non-urban lands. They found that the number of people per square mile on his map measured up to the Census’s definition of an urban area (1000 people and up per square mile). "After the thresholding we had an almost perfect match, which is amazing since we didn’t use any Census data to create the satellite map," Imhoff said. "We thought this is good; this is working."

For peri-urban areas Imhoff found there were roughly 100 people per square mile, and in non-urban areas, roughly 10 people per square mile. While the Goddard team’s map still couldn’t give them the exact density of the population for these classifications, it presented them with a picture of where the landscape had been transformed to the point where it no longer resembled the natural ecosystem. The researchers could be fairly certain that any area classified as urban on their maps had at least a few subdivisions, strip malls, and parking lots.

Imhoff and his group could now overlay this map of the United States with other maps showing where the best soils are, where fragile ecosystems exist, and where plant life is the most robust. With such comparisons, the NASA scientists could determine exactly how urbanization is affecting our planet, our natural resources, and even our climate. By repeating the entire process for other countries, they could get an idea of what was happening all over the world.

In the coming weeks in the Earth Observatory, we will be bringing you the results Imhoff and his team obtained by comparing his urbanization map of the United States with a map of the most fertile soils in the nation. We will follow this with an article on how urban sprawl may be contributing to the greenhouse effect in the Northern Hemisphere.

References
U.S. Census Bureau, 1995: Urban and Rural Population 1900-1990, Suitland, MD.

World Resources Institute, 1996: World Resources 1996-97, Washington, DC.

 Seeing the Light