ABSTRACT
Area Map .......................................................................................... 131 7.5 Results and Discussion ................................................................................. 132
7.5.1 Built-Up Area Map ........................................................................... 132 7.5.2 Accuracy Assessment ....................................................................... 133 7.5.3 Agreement with Existing Built-Up Area Maps ................................ 134
7.6 Experimental Release of the Global Built-Up Area Map with Web-Mapping System .......................................................................... 136
7.7 Conclusions and Future Perspectives............................................................ 138 Acknowledgments .................................................................................................. 139 References .............................................................................................................. 139
Urbanization is a major issue in regional and global environmental changes [1] and socioeconomic problems [2]. Global urban area maps are used in various types of studies to assess the impacts of urbanization on the natural and human environments and to evaluate the critical aspects of urbanization such as the size, scale, and form of cities [3]. Remote sensing plays an important role in monitoring such geographic aspects of urbanization. Several global urban area maps and global land cover maps have been developed at coarse resolutions ranging from 300 to 1000 m using coarse-resolution satellite images (e.g., Advanced Very High Resolution Radiometer [AVHRR] [4,5], VEGETATION [6], Moderate Resolution Imaging Spectroradiometer [MODIS] [7-9], Defense Meteorological Satellite Program Operational Linescan System [DMSP-OLS] [10,11], and Medium Resolution Imaging Spectrometer [MERIS] [12]). These global land cover maps provide valuable information on urbanization for grid-based population estimates [13,14], studying food problems [15], predicting epidemics [16,17], estimating ecological footprints [18], estimating tsunami mortality [19], and assessing damage from rising sea levels [20], especially for less documented regions.
