HR: 1400h
AN: OS23E-07    [Abstracts]
TI: Improved Beach Zone Segmentation From Airborne Lidar Measurements Using Intensity Measures
AU: * Starek, M J
EM: mstarek@ufl.edu
AF: Department of Civil and Coastal Engineering University of Florida, PO Box 116130, Gainesville, FL 32611, United States
AU: Vemula, R K
EM: vraghav@ufl.edu
AF: Department of Civil and Coastal Engineering University of Florida, PO Box 116130, Gainesville, FL 32611, United States
AU: Slatton, C
EM: slatton@ece.ufl.edu
AF: Department of Civil and Coastal Engineering University of Florida, PO Box 116130, Gainesville, FL 32611, United States
AU: Slatton, C
EM: slatton@ece.ufl.edu
AF: Department of Electrical and Computer Engineering University of Florida, PO Box 116130, Gainesville, FL 32611, United States
AU: Shrestha, R L
EM: rshre@ce.ufl.edu
AF: Department of Civil and Coastal Engineering University of Florida, PO Box 116130, Gainesville, FL 32611, United States
AU: Carter, W E
EM:
AF: Department of Civil and Coastal Engineering University of Florida, PO Box 116130, Gainesville, FL 32611, United States
AB: In an effort to monitor beach zone stability along the St. Augustine Beach region of Florida, high-resolution airborne laser swath mapping (ALSM) data are routinely acquired by the University of Florida's Geosensing and Engineering Mapping (GEM) Center. ALSM, often referred to as Light Detection and Ranging (LiDAR), systems enable sub-meter sampling of the near-shore coastal topography and the subsequent creation of digital elevation images with rms errors of less than 10cm over minimally-vegetated surfaces, such as beaches. Currently, there are seven collection dates spanning August 2003 to February 2007. This high spatial resolution coupled with the multiple acquisitions through time provided several results: two separate beach nourishment efforts were captured in the data allowing sediment spreading rate to be modeled and volume loss quantified, shoreline change rates were estimated for temporal scales ranging from a few months to over two years at various spatial frequencies from < 5m to > 300m, storm and seasonal wave climate induced shoreline response were modeled, and novel approaches to morphological feature extraction and identification of localized erosional hot- spots were developed. All previous analyses are based on range measurements; however, the ALSM system also records the intensity (peak voltage from the APD) for each return. Intensity has traditionally been under utilized as a feature for image classification because it does not represent true terrain radiance. We show that in areas with minimal topographic relief, such as beaches, intensity measures have great potential for improved beach zone segmentation. Segmentation of the beach zone is important for several factors including identification of the wet-dry line for traditional shoreline comparison and change-detection, and removal of water points to allow analysis of beach-only zones. Several intensity-based features are extracted from ALSM training data collected along the St. Augustine beach and partitioned into three classes, wet beach, dry beach, and water to detect the water line. Class-conditional probability density functions are estimated for each feature to assess which are most informative and their separability is ranked. Results indicate significant class separation using centroidal features, such as mean and median, suggesting robust segmentation of the beach using intensity measures is possible. The method presented provides a novel geometric feature extraction and a systematic feature selection procedure for high-resolution ALSM intensity data.
DE: 4262 Ocean observing systems
DE: 4294 Instruments and techniques
DE: 4546 Nearshore processes
DE: 9805 Instruments useful in three or more fields
SC: Ocean Sciences [OS]
MN: 2007 Joint Assembly