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| DOI: | 10.2134/age2019.04.0028 |
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| Publication Type:
| Refereed |
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| Author(s): | Hong, Mu;
Bremer, Dale J.;
van der Merwe, Deon |
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| Author Affiliation: | Hong and Bremer: Horticulture and Natural Resources Dep., Kansas State Univ., Manhattan, KS; 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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| Section: | Agrosystems
Other records with the "Agrosystems" Section
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| Source: | Agrosystems, Geosciences & Environment. Vol. 2, No. 1, 2019, p. 190028 [1-9]. |
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| Publishing Information: | Madison, Wisconsin: American Society of Agronomy and Crop Science Society of America |
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| # of Pages: | 9 |
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| Abstract/Contents: | "Recent advances in aerial platforms and thermal imaging provide opportunities to improve water management in turfgrass, but research on this topic is limited. Our objectives were to: (i) evaluate the ability of canopy temperature (Tc) imaging from small unmanned aircraft systems (sUAS) to detect drought stress early in turfgrass; (ii) compare early drought-stress detection ability of Tc measurements with that of sUAS-mounted and handheld optical sensors; and (iii) evaluate thermal data's relationship to spectral reflectance from sUAS-mounted and handheld sensors, soil volumetric water content (VWC), soil temperature, turfgrass visual quality (VQ), and percentage green cover (PGC). The study was conducted during summer 2017 on creeping bentgrass (Agrostis stolonifera L.) irrigated with 15 to 100% evapotranspiration (ET) replacements to impose a gradient of drought stress. Airborne spectral reflectance measurements included three bands (near infrared [NIR, 680-780 nm], green and blue bands [overlapped, 400-580 nm]) and eight derived vegetation indices. Results indicated Tc measurements via the sUAS detected rises of Tc in 15 and 30% compared with 100% ET plots, corresponding with declines in VWC, before drought stress became visible. This was comparable to the best spectral parameters on companion flights, and Tc was closely correlated with spectral data from sUAS-mounted (r = 0.52-0.69) and handheld sensors (r = 0.75-0.82). Thermal data were more strongly correlated with turfgrass VQ (r = -0.60 to -0.77) and PGC (r = -0.58 to -0.78) than with VWC (r = -0.43 to -0.63) and soil temperature (r = 0.27-0.41)." |
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| Language: | English |
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| References: | 22 |
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| See Also: | 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 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: | "Contribution no. 19-295-J from the Kansas Agricultural Experiment Station"
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. Agrosyst. Geosci. Environ. 2(1):p. 190028 [1-9]. |
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| DOI: 10.2134/age2019.04.0028 |
| Web URL(s):
https://acsess.onlinelibrary.wiley.com/doi/10.2134/age2019.04.0028
Last checked: 03/23/2023
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