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| DOI: | 10.4148/2378-5977.7766 |
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| Web URL(s): | https://newprairiepress.org/kaesrr/vol5/iss5/2/
Last checked: 12/22/2020
https://newprairiepress.org/cgi/viewcontent.cgi?article=7766&context=kaesrr
Last checked: 12/22/2020
Requires: PDF Reader |
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| Publication Type:
| Report |
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| Author(s): | Hong, Mu;
Bremer, Dale J.;
van der Merwe, Deon |
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| Author Affiliation: | Hong and Bremer: Kansas State University; and van der Merwe: GD Animal Health, Deventer, The Netherlands |
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| Title: | Thermal imaging detects early drought stress in turfgrass utilizing small unmanned aircraft systems |
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| Source: | 2017 Turfgrass Research: Research Reports [Kansas State University]. Vol. 5, No. 5, 2019, p. [1-6]. |
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| Publishing Information: | Manhattan, Kansas: Kansas State University Agricultural Experiment Station and Cooperative Extension Service |
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| # of Pages: | 6 |
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| Keywords: | TIC Keywords: Agrostis stolonifera; Comparisons; Drought stress; Equipment evaluation; Identification; Remote sensing; Thermal infrared imagery; Unmanned aerial vehicle
Author-Supplied Keywords: Drought stress; Drone; Thermal imaging; Creeping bentgrass fairway; Spectral reflectance
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| Cultivar Names: | Declaration |
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| Abstract/Contents: | "Plots of fairway-height creeping bentgrass were watered differently to create a gradient of drought stress from severe deficit irrigation to well-watered, under an automatic rainout shelter in Manhattan, KS. Canopy temperature (Tc) measured by a small unmanned aerial system (sUAS) predicted drought stress approximately 5 days or more before drought symptoms were evident in either turfgrass visual quality (VQ) or percentage green cover (PGC). The ability of Tc to predict drought stress was comparable to the best spectral parameters acquired by sUAS on companion flights [i.e., near infrared (NIR) and GreenBlue VI], and slightly better than with spectral data obtained from handheld sensors. Better drought-prediction ability combined with faster data collection using sUAS indicates significant potential for sUAS-based compared with ground-based drought stress monitoring methods." |
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| Language: | English |
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| References: | 1 |
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| 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, "Evaluating small unmanned aerial systems for detecting drought stress on turfgrass" in Turfgrass and Environmental Research Program: 2018 Research Summaries, p. 206-212, R=304998. R=304998
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 |
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| Note: | "Article 2"
Pictures, color
Tables |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Hong, M., D. J. Bremer, and D. van der Merwe. 2019. Thermal imaging detects early drought stress in turfgrass utilizing small unmanned aircraft systems. K-State Turfgrass Res. 5(5):p. [1-6]. |
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| DOI: 10.4148/2378-5977.7766 |
| Web URL(s):
https://newprairiepress.org/kaesrr/vol5/iss5/2/
Last checked: 12/22/2020
https://newprairiepress.org/cgi/viewcontent.cgi?article=7766&context=kaesrr
Last checked: 12/22/2020
Requires: PDF Reader |
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MSU catalog number: b4866211 |
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