Direct Estimation of Impervious Surface

References:
Imagine Subpixel Classifier Version 8.4: Software Review. 2001. Flanagan and Civco.

Subpixel Impervious Surface Mapping. 2001. Flanagan and Civco.

Impervious surface mapping for the state of Connecticut. 1997. Civco and Hurd.

Temporal characterization of impervious surfaces for the state of Connecticut. 2004. Hurd and Civco.

 

 

 

 

 

A completely different line of research from the use of impervious surface coefficients is our work on modeling impervious surface using “subpixel” analysis of Landsat data. The ERDAS Imagine SubPixel ClassifierTM, engineered by Applied Analysis Inc., is a supervised classifier that enables the detection of materials of interest (MOIs) as whole or fractional pixel composition, with a minimum detectable threshold of 20 percent and in increments of 10 percent (i.e., 20-30%, 30-40%, …90-100%).

Exploratory work conducted in Massachusetts showed promising results on the accuracy of the subpixel estimates. An impervious surface layer for the entire state of Connecticut has been produced from spring 1995 Landsat TM. A close-up of this data layer for the town of Simsbury CT is shown here. During 2004, CLEAR researchers will be using this technique to chart the changes in IS coverage in the Connecticut and New York areas of the Long Island Sound drainage basin, for the period 1985 to 2002. For more information please see our reference papers.


A close-up of imperviousness in Simsbury, Connecticut as derived from sub-pixel analysis of Landsat satellite imagery.

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