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Impervious Surface Mapping using Multi-Resolution Imagery

Introduction

In the Chesapeake Bay Watershed population has been increasing rapidly since the end of World War II.  This growing population has put an increased strain on the regions natural ecosystems through the expansion of urban centers.  The environmental damage from urbanization and the related effects from non-point source pollution and increased water runoff have been shown to have adverse effects on the Bay.  The need for accurate estimates of urban sprawl and man-made impervious surfaces at the local, city, and regional levels are necessary to assess the environmental impacts of the growing urban population on watershed quality.  This need to monitor urban expansion at various scales has led the Mid-Atlantic RESAC to investigate the usefulness of multi-spectral and hyper-spectral imagery in discerning man-made impervious surfaces. Take a tour of Paint Branch creek, a tributary of the Anacostia river, to see the effect of impervious surfaces on stream channel erosion.

Methods

Previously urban mapping efforts have included the use of historical maps, United States Geological Survey (USGS) topographic maps, aerial photography, and satellite imagery from the Landsat Multi-Spectral Scanner (MSS) and Thematic Mapper (TM).  Manual interpretation of aerial photography and image classification techniques are common methodologies used to discriminate between vegetated surfaces and the built environment.  While some of these methods were sucessful in delineating between urban and non-urban land surfaces many of the techniques are labor intensive and non-repeatable.  The Mid-Atlantic RESAC efforts are focused on the use of Geographic Information Systems (GIS), high-resolution multi-spectral and hyper-spectral imagery from aircraft, as well as satellite-based imagery from the Landsat series of satellites.  We hope to develop methodologies that can be automated and used in a variety of ecologically diverse regions.

High Resolution Imagery

Another aspect of our impervious surface research efforts focuses on the use of high resolution aerial imagery collected from two different sensors.  The Airborne Data Aquisition and Registration (ADAR) system flown by Positive Systems Inc. is a four band TM-like sensor that is capable of collecting submeter multispectral imagery and the Airborne Imaging Spectroradiometer for Applications (AISA) system flown by 3DI is a submeter tunable hyperspectral instrument.  Each system captures views of the land surface that complement the Landsat TM imagery and extend the possibilities of impervious surface mapping in spatially complex environments.  For more information on either the ADAR or AISA imagery aquired for the Mid-Atlantic RESAC see the above links or visit the respective company's website.

Summary

The ultimate goal of our impervious surface research effort is to evaluate the numerous methodologies used to map urbanization and suburban sprawl.  We hope to provide information about the application of certain methodologies to specific study areas and to highlight the limitations of certain types of data to the user community so that they can best utilize avilable resources to fulfill their needs.  The impacts of urbanization on the environment can best be evaluated by identifying areas that are in the most need of attention and to preserve those that are more pristine. The Mid-Atlantic RESAC is collaborating with partners, including the Nautilus RESAC to improve public and community government awareness of the links between impervious surfaces and water quality.


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The results and data products displayed on these web pages are the intellectual property of the Mid-Atlantic RESAC, consisting of the University of Maryland, Woods Hole Research Center and Shippensburg University. Any use of these products must cite the appropriate publication or, in the case of unpublished materials including maps and data, the Mid-Atlantic RESAC  partners responsible for the work.

Neither the RESAC nor its partners can accept any responsibility for the consequences of use of the information provided.

 
For questions and information, please contact resac@geog.umd.edu
 
Partially updated on 21.AUG.2008