1. Remote Sensing Analysis of Urban Sprawl in Birmingham, Alabama: 1988-2004. Introduction In the realm of urban studies, urban sprawl is a topic drawing a lot of interest. Push factors of the average American inner-city such as the perception of high crime rates, poverty, low quality schools, and pollution have driven the more affluent of the urban society to seek new opportunities on the fringe of the urban landscape. As more citizens leave the densely constructed city center for the more spacious suburban life, rural lands are built- up at an accelerated rate. The metropolitan area of Birmingham, Alabama is no exception to this trend. Birmingham is experiencing a constant decline of the inner-city and expansion of suburban areas into the surrounding rural landscape. One can see evidence of urban expansion by driving along roadways in the Birmingham suburbs or observing census data for the communities and counties surrounding the city center. According to the U. S. Census Bureau, the population in Jefferson and Shelby Counties increased by 10.4% between 1990 and 2005. Of the two counties, the most rapid growth in that fifteen year period took place in Shelby County, which experienced a population increase of about 73% (Table 1). Table 1. Population by County 2005 2000 1990 Jefferson County 657,229 662,047 651,525 Shelby County 171,465 143,293 99,358 Source: U.S. Census Bureau, 2005 Population Estimates, Census 2000, 1990 Census Unfortunately, census data lack the capability to provide researchers with a detailed landscape scale analysis of the urban expansion taking place and the areas effected. Satellite imagery, however, provides a bird’s eye view of the physical landscape of the area of interest. Using remote sensing and change detection methods, the transition of areas surrounding Birmingham from rural to urban can be seen in great detail as the growing man- made environment creeps its way across the mostly forested rural landscape. Satellite remote sensing is a relatively new source for data acquisition. The first “land sensing satellite”, Landsat 1, was launched into orbit in the summer of 1972 (Saunders et al., 2003). Since then, the Landsat Program has archived imagery nearly twice per month for public use. The USGS currently maintains and collects data from Landsat 5 and Landsat 7 (Saunders et al., 2003). For landscape scale studies using such data is cost efficient and combined with frequent data collection it is a powerful tool for spatial analysis (Ryznar and Wagner, 2001). Remotely sensed data coupled with powerful Geographic Information Systems (GIS) provides a tool that enables urban growth to be monitored (Sultana and Marzen, 2004). Results and AnalysisData and Methods For this project, two cloud free Landsat 5 TM images of Jefferson and Shelby Counties were analyzed using change detection procedures (figure 1). For the change detection aspect of the project, the images selected were created 16 years apart, one from October 13th, 1988, and the other from November 10th, 2004. The two images were examined in tandem in order to monitor the expansion of the urban area over the 16 year period. Both images were classified using an ISODATA unsupervised classification procedure. The Landsat images were initially classified into 100 classes, each of which was designated as either built-up (urban impervious surfaces) or not built-up (vegetation, water, bare land) (figure 2). Next, the two images were recoded, creating an image for each year showing the land cover as having either a built-up or not built-up classification. Once recoded, a post-classification matrix process was used to produce a final map merging and comparing the two recoded images, allowing for analysis of from-and-to land cover changes over the 16 year period (figure 3). Figure 1. Landsat 5 Images of Jefferson and Shelby Counties, Years 1988 and 2004 Figure 2. Recoded Images for 1988 and 2004 Table 2. Analysis Results by Class Classes Area (Square Miles) Percent (%) of Total Landscape 1. Built-up (unchanged) 103.973 5.7 2. Built-up to not built-up 117.324 6.4 3. Not built-up (unchanged) 1470.55 80.5 4. Not built-up to built-up 134.511 7.4 Total 1826.36 100 The results show there was a substantial amount urban expansion, especially to the south and east of Birmingham along the major highways. This analysis indicates that remote sensing can be a powerful tool in studying urban sprawl. However, for a more complete analysis, future studies should not rule out field work. In addition, other remote sensing tools such as aerial photography could prove to be useful. References Ryznar, R. M. and Wagner, T. W. 2001. Using Remotely Sensed Imagery to Detect Urban Change: Viewing Detroit from Space. Journal of the American Planning Association, 67 (3): 327-33 Sultana, S. and Marzen, L. 2004. Quantifying Urban Encroachment in Dhaka, Bangladesh from 1989-2000. Theodore, S., Feuquay, J., Kelmelis, J. 2003. The U. S. Geological Survey Land Remote Sensing Program. Cartography and Geographic Information Science. 30.2 (April 2003): p211(5). U. S. Census Bureau, 2006. Website: www.census.govwww.census.gov Figure 3. Post-Classification Land Cover Comparison