A multi-scale framework for mapping and analysis of the spatial and temporal pattern of urban growth

In the past, remote sensing has shown an ability to detect and describe urban growth patterns at different spatial scales. With new remote sensing devices (e.g. IKONOS, MODIS), with innovative image processing techniques and with further development of decision support tools (e.g. GIS and urban land use change models), remote sensing has new opportunities to provide useful information in support of sustainable development and "smart growth" for urban areas. Given that urban dynamics impact many spatial scales, we present a framework for the mapping and analysis of predictable patterns of urban at different spatial scales in order to analyze the urbanization process. We discuss problems of urban area mapping at the super-regional/global scale, and more directly address issues of spatial and spectral sensor requirements for urban mapping on the local and regional scale. We conduct urban growth analysis using spatial measurements of changes in the urban environment on the regional scale, and urban land cover structure on the local scale, in the Santa Barbara, CA area. Results show how the new era of remote sensing data and superior methods allow for a better mapping, understanding, modeling, and prediction of the spatial and temporal dynamics of urban growth at each of the different scales.