Dynamic Impervious Surface Cover Observations


Cities and related urban and sub-urban agglomerations are among Earth's rarest, but fastest growing land use types. Urban impervious surfaces affect hydrological and energy balances, as well as biological composition and functioning of ecosystems. To understand the causes and consequences of urbanization, we have developed an empirical method for retrieving annual, long-term continuous fields of impervious surface cover from the long-term Landsat archive and applied it to retrieve a record of urban growth of the Washington, DC - Baltimore, MD megalopolis from 1984 to 2010. Excluding the year 2009 due to lack of data availability resulting from nearly continual winter snow cover, the resulting dataset is a continuous-field representation of impervious surface coverage at 30-m horizontal and annual temporal resolution from 1984 to 2010. Average error is approximately 6% cover, with outliers due to shadows from large buildings in winter images. The region's impervious surface cover grew from 881.29 to 1,176.46 11.35 km2 over the 27-year span-an average annual rate of approximately 11.35 2.08 km2/yr-with great variability between local municipalities in terms of rate and acceleration of development. The dataset depicts stability, growth, and acceleration of impervious surface development in various places and times across the region. Development patterns, including extensification (i.e., exurban or "sprawl" development), intensification (i.e., "infill development"), as well as fragmentation and isolation of natural areas, were clearly visible in the dataset, although neither impervious surface loss nor deceleration were observed in any city or county over the study span. These results show that retrieval of impervious coverage at the spatial and temporal scale of the Landsat archive is possible, and that long-term records such as this provide an opportunity for analyzing land-use patterns and their underlying causes to improve understanding of socio-economic processes and human-environment interactions.

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