HR: 1330h
AN: U52A-0022    [PDF]
TI: Urban Growth as a Component of Global Change
AU: * Schneider, A
EM: anmarie@bu.edu
AF: Boston University Department of Geography and Center for Remote Sensing, 675 Commonwealth Avenue, Boston, MA 02215 United States
AU: Friedl, M A
AF: Boston University Department of Geography and Center for Remote Sensing, 675 Commonwealth Avenue, Boston, MA 02215 United States
AU: Woodcock, C E
AF: Boston University Department of Geography and Center for Remote Sensing, 675 Commonwealth Avenue, Boston, MA 02215 United States
AB: Urban populations have exploded in the last three decades, with nearly 50 percent (3 billion) of the Earth's inhabitants currently living in cities (UN 2000). Further, while urban land cover accounts for less than two percent of the Earth's land area, this proportion is growing rapidly as more cities expand into natural ecosystems and agricultural areas. The amount and rate of this land conversion affects local and regional ecosystems, climate, biogeochemistry, as well as food production. While monitoring and understanding of land use/cover change has improved dramatically in the arenas of forests, grasslands, and agriculture, more attention must be paid to the form and extent of urbanization as a key land transformation process. To address this issue, this research involves two objectives: 1) to map and monitor urban areas globally using coarse resolution data, and 2) to understand urban growth and its drivers during the last decade at regional to local scales, in a cross section of global cities. The first objective is to improve understanding of the methodological requirements for mapping urban land cover over large areas from coarse resolution remotely sensed data. Circulation models will soon include urban information in their parameterization of global land cover (G. Bonan, pers. comm.), however, no complete, updated map of global cities exists. Of the commonly used surrogate data sources, the Digital Chart of the World urban data (Danko 1992) is outdated, while the nighttime lights data (Elvidge et al. 1999) overestimates cities due to ``blooming'' effects. To meet this need, a technique called boosting is used to improve supervised classification accuracy and provides a means to integrate Moderate Resolution Imaging Spectroradiometer (MODIS) data with prior information derived from ancillary sources. Results indicate that fusion of data types improves urban classification results by resolving confusion between urban and other classes that occurs when any of the data sets are used by themselves. The second objective is to understand the rates, patterns, and drivers of urban expansion in cities around the globe. Urban areas have typically been studied at the local scale on a case by case basis, with little or no comparison performed among studies. A global comparison of cities is critical if we are to understand and mitigate the effects of rapid urban growth, as well as determine efficient use and sustainability of land and resources. The approach involves change detection in a sample of cities using Landsat imagery, and statistical analysis combining land cover data with socioeconomic data. Preliminary results reveal the emergence of several city ``types,'' based on commonalities in spatial patterns, rates and mechanisms of growth. \\ {\begin{bf}{References:}\end{bf}} \\ Danko, D.~M., 1992. The Digital Chart of the World project. {\em Photogrammetric Engineering and Remote Sensing\/}~{\em 58}, 1125--1128. \\ Elvidge, C.~D., Baugh, K.~E, Dietz, J.~B., Sutton, P.~C., and Kroehl, H.~W., 1999. Radiance calibration of DMSP-OLS low light imaging data of human settlements. {\em Remote Sensing of Environment\/}~{\em 68}, 77--88. \\ United Nations, 2000. {\em Demographic Yearbook, Department of Economic and Social Affairs, Statistical Office\/}, United Nations, New York, New York, 674 p.
UR: http://cers28.bu.edu/urban
DE: 0315 Biosphere/atmosphere interactions
DE: 0345 Pollution--urban and regional (0305)
DE: 1610 Atmosphere (0315, 0325)
DE: 1630 Impact phenomena
DE: 1655 Water cycles (1836)
SC: U
MN: 2003 Fall Meeting