Remote measurement of turf water stress and turf biomass
| dc.contributor.advisor | Kopec, David M. | en_US |
| dc.contributor.advisor | Mancino, Charles F. | en_US |
| dc.contributor.author | Kelly, Harold Lorain Jr., 1958- | |
| dc.creator | Kelly, Harold Lorain Jr., 1958- | en_US |
| dc.date.accessioned | 2013-03-28T10:24:59Z | en |
| dc.date.available | 2013-03-28T10:24:59Z | en |
| dc.date.issued | 1989 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/276995 | en |
| dc.description.abstract | Increasing irrigation efficiency on turfgrass could help reduce water consumption on large turf facilities. Two experiments were conducted using perennial ryegrass (Lolium perenne (L.) Derby) to evaluate the potential of using remote sensing to estimate turf water status, predict daily evapotranspiration (ET), and estimate turf biomass. In the first experiment a crop water stress index, utilizing remotely sensed canopy temperature, were used to schedule irrigations on 6 of 10 drainage lysimeters. Three of the remaining lysimeters were irrigated used on meteorological estimates of ET calculated using a modified Penman equation. The results of this experiment were inconclusive due to inconsistent lysimeter drainage characteristics. The second experiment was conducted on a turf green with multiple heights to evaluate the potential for using canopy radiance to estimate turf biomass. These results showed that turf biomass could be estimated from a vegetative index (Red Ratio = Near Infrared/Red radiance) obtained through measurements of canopy radiance (r2 = 0.91). | |
| dc.language.iso | en_US | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en_US |
| dc.subject | Soil moisture -- Measurement -- Instruments. | en_US |
| dc.subject | Lysimeter. | en_US |
| dc.subject | Turf management -- Arizona. | en_US |
| dc.subject | Irrigation -- Management. | en_US |
| dc.title | Remote measurement of turf water stress and turf biomass | en_US |
| dc.type | text | en_US |
| dc.type | Thesis-Reproduction (electronic) | en_US |
| dc.identifier.oclc | 22918675 | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | masters | en_US |
| dc.identifier.proquest | 1336697 | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.discipline | Plant Sciences | en_US |
| thesis.degree.name | M.S. | en_US |
| dc.identifier.bibrecord | .b17534562 | en_US |
| refterms.dateFOA | 2018-09-04T03:37:13Z | |
| html.description.abstract | Increasing irrigation efficiency on turfgrass could help reduce water consumption on large turf facilities. Two experiments were conducted using perennial ryegrass (Lolium perenne (L.) Derby) to evaluate the potential of using remote sensing to estimate turf water status, predict daily evapotranspiration (ET), and estimate turf biomass. In the first experiment a crop water stress index, utilizing remotely sensed canopy temperature, were used to schedule irrigations on 6 of 10 drainage lysimeters. Three of the remaining lysimeters were irrigated used on meteorological estimates of ET calculated using a modified Penman equation. The results of this experiment were inconclusive due to inconsistent lysimeter drainage characteristics. The second experiment was conducted on a turf green with multiple heights to evaluate the potential for using canopy radiance to estimate turf biomass. These results showed that turf biomass could be estimated from a vegetative index (Red Ratio = Near Infrared/Red radiance) obtained through measurements of canopy radiance (r2 = 0.91). |
