Mapping Urban Expansion Across North America Using Multi-Temporal Landsat and Nighttime Lights Data

Thursday, 18 December 2014
Cristina Milesi1, Christopher Small2, Uttam Kumar1, Kumar Raja3, Andrew Michaelis4, Gong Zhang1, Sangram Ganguly1, Petr Votava5, Weile Wang6, Forrest S Melton5, Jennifer L Dungan1, Susan E. Alexander5 and Ramakrishna R Nemani1, (1)NASA Ames Research Center, Moffett Field, CA, United States, (2)Lamont Doherty Earth Obs., Palisades, NY, United States, (3)EADS Innovation Works, Airbus Engineering Centre India, Bangalore, India, (4)University Corporation at Monterey Bay, Seaside, CA, United States, (5)California State University Monterey Bay, Seaside, CA, United States, (6)CSUMB & NASA/AMES, Seaside, CA, United States
Urban expansion and the associated changes in land cover have important climatic, hydrologic, biophysical and ecologic and socio-economic impacts on the environment. Yet, despite today’s abundance of remote sensing data, an automated characterization of large-scale historical changes in urban spatial extent remains a challenge due to the inherent complexity and variability of the urban environment, the lack of a spectral signature unique to urban land cover, and the absence of an unambiguous definition of what is urban versus non-urban.

Here we present a consistent, robust, scalable, physically- based methodology for characterization of urban expansion using Landsat observations. We use atmospherically corrected Landsat Global Land Survey time series, Web-enabled Landsat data time series, DMSP-OLS and NPP-VIIRS nighttime lights, for mapping the built-up and vegetated components of urban settlements at 30m resolution through multi- temporal standardized spectral mixture analysis. The methodology is tested and validated over the North American continent where it provides a first quantification of urban expansion and vegetation abundance changes from 1990 to 2010.