Transcript Remote Mapping of River Channel Morphology

Remote Mapping of
River Channel
Morphology
March 9, 2003
Carl J. Legleiter
Geography Department
University of California Santa Barbara
Acknowledgements
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Collaborators
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Dar Roberts and Tom Dunne, UCSB
Mark Fonstad, Southwest Texas State University
Andrew Marcus, University of Oregon
Robert Crabtree and Kerry Halligan, Yellowstone
Ecological Research Center
Annie Toth, Jim Rasmussen, Rob Ahl, Seth
Peterson
Funding agencies
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NASA Earth Observation Commercial
Applications Program - Hyperspectral
NASA Jet Propulsion Laboratory
California Space Institute
American Society for Engineering Education
National Science Foundation
Presentation outline
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Project rationale
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Methodology
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Laboratory spectra / numerical simulation
Hyperspectral image analysis
Radiative transfer modeling
Accuracy assessment / sensitivity analysis
Anticipated results
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Significance of river channel morphology
Role of remote sensing
Flexible model for estimating depth from
imagery
Identify potential and limitations of remote
approach
Broader impacts
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Applications in geomorphology and ecology
Powerful tool for resource management
River channel morphology and
the role of remote sensing
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Channel morphology
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establishes physical habitat
conditions
influences flow processes and
sediment transport
responds sensitively to disturbance
impacts
requires an accurate, quantitative,
and spatially explicit descriptive
framework
Remote sensing
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provides expanded coverage
captures spatial and temporal
variations
allows analysis across a range of
scales
Spectral properties of streams:
measurement and modeling
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Signal recorded by sensor influenced by
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Direct spectral measurements
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water depth
substrate characteristics
suspended sediment
surface turbulence
viewing and illumination geometry
Depth, substrate, image geometry
Numerical simulation
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Suspended sediment, specular reflectance
Hydraulic / hyperspectral analysis
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Data sources
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Theoretical basis
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AVIRIS
hyperspectral
imagery
USGS streamflow
records
Manning’s equation
Q = AR2/3S1/2/n
Radiative transfer
models
Solution technique
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Iteratively adjust
model parameters
to match measured
discharge
Model evaluation
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Accuracy assessment
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Sensitivity analyses to
quantify effects of
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AVIRIS scenes excluded from
model-building
Probe-1 hyperspectral imagery
and field data from Lamar
River, WY
suspended sediment
substrate variability
channel complexity
sensor resolution
Goal: identify appropriate
conditions and define
limitations
Anticipated Results
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Laboratory spectral library
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Radiative transfer model for estimating depth from imagery
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flexible and physically-based
Quantitative analysis of potential and limitations
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depth, substrate, image geometry
critical assessment of the technique
Continuous bathymetric maps
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detailed, spatially extensive representation of channel morphology
Applications and broader impacts
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Fluvial geomorphology
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Stream ecology
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spatial distribution of
habitat within
watersheds
Resource management
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process interactions
across a range of scales
inventory and
monitoring
in-stream flow
requirements
stream restoration
flood hazard
assessment
Preservation efforts
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maintain geomorphic,
biotic, and aesthetic
integrity
Conclusion: Remote mapping of
channel morphology
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Rationale
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Methodology
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lab spectra
hyperspectral/hydraulic analysis
accuracy assessment
Research objectives
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Ecological significance and vulnerability of
streams
Remote sensing offers synoptic perspective
flexible model for estimating depth
document potential and limitations
Applications
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fluvial geomorphology
stream ecology
resource management