An assessment of two methods for identifying undocumented levees using remotely sensed data

Christiana R. Czuba; Byron K. Williams; Jack Westman; Keith LeClaire

doi:10.3133/sir20155009

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An assessment of two methods for identifying undocumented levees using remotely sensed data

Christiana R. Czuba·Byron K. Williams·Jack Westman·Keith LeClaire

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Abstract

Many undocumented and commonly unmaintained levees exist in the landscape complicating flood forecasting, risk management, and emergency response. This report describes a pilot study completed by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers to assess two methods to identify undocumented levees by using remotely sensed, high-resolution topographic data. For the first method, the U.S. Army Corps of Engineers examined hillshades computed from a digital elevation model that was derived from light detection and ranging (lidar) to visually identify potential levees and then used detailed site visits to assess the validity of the identifications. For the second method, the U.S. Geological Survey applied a wavelet transform to a lidar-derived digital elevation model to identify potential levees. The hillshade method was applied to Delano, Minnesota, and the wavelet-transform method was applied to Delano and Springfield, Minnesota. Both methods were successful in identifying levees but also identified other features that required interpretation to differentiate from levees such as constructed barriers, high banks, and bluffs. Both methods are complementary to each other, and a potential conjunctive method for testing in the future includes (1) use of the wavelet-transform method to rapidly identify slope-break features in high-resolution topographic data, (2) further examination of topographic data using hillshades and aerial photographs to classify features and map potential levees, and (3) a verification check of each identified potential levee with local officials and field visits.

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Source-reported bounding extent: 44.2075577272807° to 45.06782265048428° latitude; -95.01251220703125° to -93.75646591186523° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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Christiana R. Czuba, Byron K. Williams, Jack Westman, Keith LeClaire. 2015. An assessment of two methods for identifying undocumented levees using remotely sensed data. https://doi.org/10.3133/sir20155009

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