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Summary of Proposal HYD2148

TitleLevee characterization with TerraSAR-X imagery combined with geophysical and geotechnical data
Investigator Dabbiru, Lalitha - Mississippi State University, Geosystems Research Institute
Team Member
Associate Research P Aanstoos, James - Mississippi State University, Electrical and Computer Engineering
Hasan, Khaled - University of Mississippi, MMRI
SummaryMan-made large dams and levees are expected to be more sustainable if they are in harmony with their surrounding environment. 3 levee sites in US, Netherlands and Bangladesh will be studied to determine their stability with respect to their environmental setting and conditions under which they become vulnerable.Investigation of vulnerability will be done primarily by using SAR imagery, measurement of subsurface conditions, and ground data on surface cover. Failure of levee and dams can produce disastrous consequences on life and property as evidenced in the aftermath of Hurricane Katrina, Hurricane Ike and flood events that occur regularly across the globe. This project will develop tools and methods based on combined use of SAR, subsurface, and surface data for rapid and efficient screening of levee reaches. SAR's all weather capability to map surface and near surface properties and ability to detect surface displacements via interferometry will be tasked to detect changes in levees that may signal impending failure. The pre-emptive screening using SAR images will identify levee sections that exhibit signs that make the reach vulnerable to failure under flood loading. Vulnerability under changed loading possible due to future climate change scenario will also be simulated and tested. This will lead to more detailed examination or repairs of these higher-priority sections. We are proposing to use airborne NASA UAVSAR, a polarimetric L-band SAR and satellite based TerraSAR-X imagery for this task. The primary objectives of this research are to: (1) Develop algorithms to utilize TerraSAR-X data to screen levees for vulnerabilities, and (2) Investigate the relationship between subsurface properties of levee segments to SAR backscatter over them. We will analyze polarimetric and interferometric SAR data, and test and refine the feature detection algorithms we have developed in our earlier research.Deformation, soil moisture and vegetation pattern information derived from SAR data combined with subsurface information will allow us to detect features indicative of weakness in the levee segment. DEM, optical data and ground truth will be used to assist information extraction from the images. The analysis will investigate existing approaches and develop new algorithms and a study will be performed to determine which is preferred, based on required input,skill of the end-user, and quality of output. The ability of different sensors to detect different features will be utilized by combining the outputs from the analysis of TerraSAR and UAVSAR imagery in a decision fusion to determine the final classes. Knowledge -based expert system will be employed to incorporate soil type, elevation, volumetric water content and surface roughness as ancillary data for SAR image classification. The primary data for this research will be the high resolution polarimetric SAR data from TerraSAR-X at 1-3 m resolution to detect slides, sand boils and high soil moisture content indicative of levee weakness. To support the SAR analysis we will also use optical imagery and field measurements (surface and subsurface) to match with image data acquisition. Similarly, data on climate, hydrology, soils, geology,topography and landuse-landcover will be integrated in the analysis. The primary deliverables are the prototyped algorithm for Levee Segment Classification. Results will be published in appropriate scientific journals and conferences. Technical report will be submitted to DLR as required. The current project is funded by US National Science Foundation under their Partnerships for International Research and Education (PIRE) Program. At commercial price we can buy very limited number of TerraSAR image, limiting the scope of the study.If approved for scientific pricing adequate number of images can be acquired to make the research comprehensive allowing a vigorous evaluation/validation of TerraSAR imagery.

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