Long-Term Application of Remote Sensing Chlorophyll Detection Models: Jordanelle Reservoir Case Study
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Affiliation(s)
1Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, USA.
2Department of Civil and Environmental Engineering, Brigham Young University, Provo, USA.
2Department of Civil and Environmental Engineering, Brigham Young University, Provo, USA.
ABSTRACT
Algae
blooms pose a threat to water quality by depleting oxygen during
decomposition and also cause other issues with water quality and water
use. Algae biomass is traditional monitored through field samples
analyzed for chlorophyll-a, a pigment present in all algae. Field
sampling can be time- and cost-intensive, especially in areas that are
difficult to access and provides only limited spatial coverage.
Estimations of algal biomass based on remote sensing data have been
explored over the past two decades as a supplement to information
obtained from limited field samples. We use Landsat data to develop and
demonstrate seasonal remote sensing models, a relatively recent method,
to evaluate spatial and temporal algae distributions for the Jordanelle
Reservoir, located in north-central Utah. Remote sensing of chlorophyll
as a monitoring and analysis method can provide a more spatially
complete representation of algae distribution and biomass; information
that is difficult to obtain using point samples.
Cite this paper
References
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Sensing Chlorophyll Detection Models: Jordanelle Reservoir Case Study. Natural Resources, 6, 123-129. doi: 10.4236/nr.2015.62011.
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