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Office: SL 020
Phone: 317-274-7491
Email:
klrandol@iupui.edu
Departmental Mailing Address
Background
M.S. Geography, IUPUI, 2007
B.S. Environmental Management, IU Bloomington, 2002
Specialties
Remote Sensing
My research focuses
on the use of hyperspectral remote sensing for estimating algal
abundance and composition to monitor water quality. My Research
Interests Include: understanding the optical and mathematical
principles and limitations of semi-empirical and bio-optical
models, applying bio-optical modeling to remote sensing of case
II waters (e.g., lakes, estuaries and coastal water bodies) to assess
water quality parameters (e.g., productivity using chlorophyll a
and phycocyanin, suspended sediment, colored dissolved organic
matter, and pollutants), and
utilizing remotely sensed data to better understand global
changes in aquatic ecosystems on both spatial and temporal
scales. |
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Projects |
Research
Program |
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The water quality remote sensing
research project began in 2005, when blooms of potentially harmful
blue-green algae began to occur in the drinking water and
recreational reservoirs in Indiana. Remote sensing techniques,
which utilize the optical properties of blue-green algal pigments
(chlorophyll a and phycocyanin), were modified and applied to
both field and airborne hyperspectral remote sensing data collected
for Indiana reservoirs to provide rapid assessment of the spatial
distribution and relative concentration of blue-green algae.
Coupled with physical and chemical data from lakes, remote sensing
provides an efficient method for tracking blue-green algal
occurrence over time and relative to long term management
strategies. The 2006 field
season focused on assessing the robustness of semi-empirical
algorithms tested in 2005 for estimating phycocyanin concentration
over a wide range of reservoir conditions and seasons. The
results of our 2006 dataset suggest that productivity in central
Indiana reservoirs is highly variable both spatially and temporally
based on chlorophyll a and phycocyanin distribution.
We are working with the 2006 dataset to identify compositions of
optically active constituents for which the algorithm accuracy is
reduced.
The 2007 research seeks to further
improve upon the semi-empirical algorithms and to work toward a
bio-optical modeling approach by measuring inherent and apparent
optical properties and concentrations of constituents including
chlorophyll a, colored dissolved organic matter, and
suspended matter. Bio-optical and semi-empirical modeling
techniques will be extended to Hyperion imagery.
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The purpose of the water quality
remote sensing research is to evaluate the utility of spectroscopy
as a real-time cyanobacteria bloom assessment method for inland,
productive systems and to establish remote sensing algorithms for
these systems that can be extendable to airborne and eventually
space-borne systems.
.jpg)
This study was designed to
determine the relationship between spectral response and
in-vitro phytoplankton pigment concentrations and
blue-green algal biovolume.
Analytically
measured phycocyanin concentration (left) and semi-empirical
algorithm estimated phycocyanin concentration from field
spectral response measurements (right) at Morse Reservoir,
Indianapolis.
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Recent Publications |
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Randolph, K., and Wilson, J. (2007).
Remote sensing of cyanobacteria in case II waters using
optically active pigments, chlorophyll a and phycocyanin.
Master's Thesis 128pp.
Randolph K., Wilson, J., Tedesco,
L., Li, L. In Review. Hyperspectral Remote Sensing
of cyanobacteria in turbid productive water using optically
active pigments, chlorophyll a and phycocyanin. Remote
Sensing of Environment Special Issue Monitoring Freshwater
Systems.
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 IUPUI Department
of Earth Sciences
723 West Michigan
Street, SL118
Indianapolis, Indiana 46202
317.274.7484
(fax)
317.274.7966
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