Urban Landscape Metrics for Climate and Sustainability Assessments

Abstract:

To test metrics for rapid identification of urban classes and sustainable urban forms, we examine the configuration of urban landscapes using satellite remote sensing data. We adopt principles from landscape ecology and urban planning to evaluate urban heterogeneity and design themes that may constitute more sustainable urban forms, including compactness (connectivity), density, mixed land uses, diversity, and greening. Using 2-D wavelet and multi-resolution analysis, landscape metrics, and satellite-derived indices of vegetation fraction and impervious surface, the spatial variability of Landsat and MODIS data from metropolitan areas of Manaus and São Paulo, Brazil are investigated. Landscape metrics for density, connectivity, and diversity, like the Shannon Diversity Index, are used to assess the diversity of urban buildings, geographic extent, and connectedness. Rapid detection of urban classes for low density, medium density, high density, and tall building district at the 1-km scale are needed for use in climate models. If the complexity of finer-scale urban characteristics can be related to the neighborhood scale both climate and sustainability assessments may be more attainable across urban areas.