An automated approach to flood mapping

Weihua Sun; Donald M. Mckeown; David W. Messinger

doi:10.1117/12.970662

25 October 2012 An automated approach to flood mapping

Weihua Sun, Donald M. Mckeown, David W. Messinger

Proceedings Volume 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III; 853811 (2012) https://doi.org/10.1117/12.970662
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

Heavy rain from Tropical Storm Lee resulted in a major flood event for the southern tier of New York State in early September 2011 causing evacuation of approximately 20,000 people in and around the city of Binghamton. In support of the New York State Office of Emergency Management, a high resolution multispectral airborne sensor (WASP) developed by RIT was deployed over the flooded area to collect aerial images. One of the key benefits of these images is their provision for flood inundation area mapping. However, these images require a significant amount of storage space and the inundation mapping process is conventionally carried out using manual digitization. In this paper, we design an automated approach for flood inundation mapping from the WASP airborne images. This method employs Spectral Angle Mapper (SAM) for color RGB or multispectral aerial images to extract the flood binary map; then it uses a set of morphological processing and a boundary vectorization technique to convert the binary map into a shapefile. This technique is relatively fast and only requires the operator to select one pixel on the image. The generated shapefile is much smaller than the original image and can be imported to most GIS software packages. This enables critical flood information to be shared with and by disaster response managers very rapidly, even over cellular phone networks.

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Weihua Sun, Donald M. Mckeown, and David W. Messinger "An automated approach to flood mapping", Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 853811 (25 October 2012); https://doi.org/10.1117/12.970662

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KEYWORDS

Floods

Image processing

Binary data

Geographic information systems

MATLAB

RGB color model

Sensors

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