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Using airborne bathymetric lidar to detect bottom type variation in shallow waters [An article from: Remote Sensing of Environment]
Book Details
Author(s)C.K. Wang, W.D. Philpot
PublisherElsevier
ISBN / ASINB000PDSCAM
ISBN-13978B000PDSCA2
AvailabilityAvailable for download now
Sales Rank9,803,085
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Remote Sensing of Environment, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
The shape and amplitude of the bathymetric lidar waveforms (the recorded time history of the reflected lidar pulses) contain information about the attenuation of the water and the bottom reflectivity in the survey area. This study considers the factors that affect the amplitude of the bottom return and examines the use of the amplitude of the bottom return to distinguishing between different bottom types. The amplitude of the bottom return was corrected for pulse stretching and retro-reflectance due to the bottom slope based on a simple lidar radiative transfer model before the examination. Within-flightline and between-flightline variations of the bottom return were considered, both of which are related to the attenuation of water, surface wave condition, and bottom reflectivity. The major concern of within-flightline variation is the effect of surface waves on the reliability of bottom return. Between-flightline variation concerns the effect of change in viewing orientation on the bottom return from the same bottom type. A data set of Egmont Key, Florida, assuming homogeneous water clarity, was chosen to investigate the latter two effects on the bottom return signals. The result shows that the presence of surface waves is the most impeding factor that complicates the use of bottom return signal, as it can exaggerate the value (not prominent in our data) and variance of the amplitude of bottom return. A map of sand, continuous seagrass, and discontinuous seagrass ranging from the depth of 0.8 to 4.3 m was produced correctly from a single lidar flightline with limited in-situ information, in this case, a nadir viewing videotape concurrent with lidar survey mission. Finally, suggestions are proposed for ways to improve the production of a bottom map using the lidar waveform data.
Description:
The shape and amplitude of the bathymetric lidar waveforms (the recorded time history of the reflected lidar pulses) contain information about the attenuation of the water and the bottom reflectivity in the survey area. This study considers the factors that affect the amplitude of the bottom return and examines the use of the amplitude of the bottom return to distinguishing between different bottom types. The amplitude of the bottom return was corrected for pulse stretching and retro-reflectance due to the bottom slope based on a simple lidar radiative transfer model before the examination. Within-flightline and between-flightline variations of the bottom return were considered, both of which are related to the attenuation of water, surface wave condition, and bottom reflectivity. The major concern of within-flightline variation is the effect of surface waves on the reliability of bottom return. Between-flightline variation concerns the effect of change in viewing orientation on the bottom return from the same bottom type. A data set of Egmont Key, Florida, assuming homogeneous water clarity, was chosen to investigate the latter two effects on the bottom return signals. The result shows that the presence of surface waves is the most impeding factor that complicates the use of bottom return signal, as it can exaggerate the value (not prominent in our data) and variance of the amplitude of bottom return. A map of sand, continuous seagrass, and discontinuous seagrass ranging from the depth of 0.8 to 4.3 m was produced correctly from a single lidar flightline with limited in-situ information, in this case, a nadir viewing videotape concurrent with lidar survey mission. Finally, suggestions are proposed for ways to improve the production of a bottom map using the lidar waveform data.
