Fastlink to record 304998
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| Full TGIF Record # 304998 Item 1 of 1 |
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| Web URL(s): | http://archive.lib.msu.edu/tic/ressum/2018/2018.pdf#page=214 Last checked: 05/02/2019 Requires: PDF Reader Notes: Item is within a single large file |
| Publication Type: | Report |
| Author(s): | Hong, Mu; Bremer, Dale J.; van der Merwe, Deon |
| Author Affiliation: | Hong and Bremer: Horticulture and Natural Resources Dept., Kansas State University; van der Merwe: Dept. of Farm Animal Health, University of Utrecht |
| Title: | Evaluating small unmanned aerial systems for detecting drought stress on turfgrass |
| Section: | Integrated turfgrass management Other records with the "Integrated turfgrass management" Section Ecophysiology: Water Other records with the "Ecophysiology: Water" Section |
| Source: | Turfgrass and Environmental Research Program: 2018 Research Summaries. 2018, p. 206-212. |
| Publishing Information: | [New York, New York]: The United States Golf Association Green Section |
| # of Pages: | 7 |
| Keywords: | TIC Keywords: Drought stress; Problem diagnosis; Product evaluation; Remote sensing; Unmanned aerial vehicles |
| Language: | English |
| References: | 0 |
| See Also: | See also related article, "Thermal imaging detects early drought stress in turfgrass utilizing small unmanned aircraft systems" in Agrosystems, Geosciences & Environment, 2(1) 2019, p. 190028 [1-9], R=326451.R=326451 See also related article, "Thermal imaging detects early drought stress in turfgrass utilizing small unmanned aircraft systems" in 2017 Turfgrass Research: Research Reports [Kansas State University], 5(5) 2019, p. [1-6], R=311517.R=311517 See also related abstract, "Evaluating small unmanned aerial systems for detecting drought stress on turfgrass" in ASA, CSSA and SSSA International Annual Meetings, p. 113668, R=302080.R=302080 |
| See Also: | Other Reports from this USGA research project: 2015-16-531 |
| Note: | Thermal images Tables Graphs |
| USGA Summary Points: | Declines in VWC in irrigation-deficit treatments were consistently detected by the NIR band and six VIs from sUAS, and NDVI and the red band from the handheld device with an active optical sensor, before drought stress was evident in VQ and PGC These bands and indices predicted drought stress at least one week before symptoms appeared in VQ and PGC in 2016 and 2017. The NIR band and GreenBlue VI from sUAS were the most sensitive and the only ones to consistently detect drought stress early during the three years compared to other bands or VIs The one year of Tc measurements acquired by sUAS were comparable to the best spectral parameters in predicting drought stress before drought symptoms appeared. Using ultra-high resolution remote sensing with sUAS can detect drought stress as well as or better than handheld devices before it is visible to the human eye and may prove viable for irrigation management on turfgrass. Results from this research have been widely presented at multiple international conferences, statewide turfgrass conferences and field days, university departmental seminars, and published or discussed in research reports, abstracts, a newsletter, and interviews in a trade journal (Golfdom) and an online webinar. |
| ASA/CSSA/SSSA Citation (Crop Science-like – may be incomplete): | Hong, M., D. J. Bremer, and D. van der Merwe. 2018. Evaluating small unmanned aerial systems for detecting drought stress on turfgrass. USGA Turfgrass Environ. Res. Summ. p. 206-212. |
| Fastlink to access this record outside TGIF: | http://tic.msu.edu/tgif/flink/RECNO/304998 |
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| Web URL(s) : | http://archive.lib.msu.edu/tic/ressum/2018/2018.pdf#page=214 Last checked: 05/02/2019 Requires: PDF Reader Notes: Item is within a single large file |
| MSU catalog number: | b3609415 |
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