Quantification of chlorophyll in small reservoirs using airborne video imagery.
| dc.contributor.advisor | Canter, Larry, | en_US |
| dc.contributor.author | Avard, Margaret Marie. | en_US |
| dc.date.accessioned | 2013-08-16T12:30:04Z | |
| dc.date.available | 2013-08-16T12:30:04Z | |
| dc.date.issued | 1998 | en_US |
| dc.description.abstract | The primary objective of this study was to develop a rapid, economic method of assessing water quality and productivity in surface impoundments. Airborne video cameras equipped with narrow band filters were used to assess chlorophyll-a concentration in flood retention reservoirs of the Little Washita River Watershed in central Oklahoma. The video data was calibrated by converting raw data (digital numbers) into radiance values $\rm (uW/cm\sp2/sr)$ and further processed into reflectance values by the incorporation of solar irradiance data. Results indicate that chlorophyll-a concentration in reservoirs may be approximated using airborne video imagery and that this relationship is best described by the model $\rm y = a\sb0(1$-$e\sp{\rm -x/40}).$ Studies utilizing aerial videography may be performed more quickly and are less expensive than traditional field-based studies. | en_US |
| dc.format.extent | ix, 175 leaves : | en_US |
| dc.identifier.uri | http://hdl.handle.net/11244/5654 | |
| dc.note | Adviser: Larry Canter. | en_US |
| dc.note | Source: Dissertation Abstracts International, Volume: 59-07, Section: B, page: 3315. | en_US |
| dc.subject | Water quality Measurement. | en_US |
| dc.subject | Engineering, Environmental. | en_US |
| dc.subject | Aerial photography. | en_US |
| dc.subject | Biology, Ecology. | en_US |
| dc.subject | Environmental Sciences. | en_US |
| dc.subject | Suspended sediments. | en_US |
| dc.subject | Chlorophyll. | en_US |
| dc.subject | Remote Sensing. | en_US |
| dc.thesis.degree | Ph.D. | en_US |
| dc.thesis.degreeDiscipline | School of Civil Engineering and Environmental Science | en_US |
| dc.title | Quantification of chlorophyll in small reservoirs using airborne video imagery. | en_US |
| dc.type | Thesis | en_US |
| ou.group | College of Engineering::School of Civil Engineering and Environmental Science | |
| ou.identifier | (UMI)AAI9839788 | en_US |
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