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| DOI: | 10.2135/cropsci2019.04.0212 |
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| Web URL(s): | https://acsess.onlinelibrary.wiley.com/doi/10.2135/cropsci2019.04.0212
Last checked: 01/22/2020
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https://acsess.onlinelibrary.wiley.com/doi/epdf/10.2135/cropsci2019.04.0212
Last checked: 01/22/2020
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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: | Using small unmanned aircraft systems for early detection of drought stress in turfgrass |
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| Section: | Turfgrass science
Other records with the "Turfgrass science" Section
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| Source: | Crop Science. Vol. 59, No. 6, November/December 2019, p. 2829-2844. |
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| Publishing Information: | Madison, Wisconsin: Crop Science Society of America |
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| # of Pages: | 16 |
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| Related Web URL: | https://acsess.onlinelibrary.wiley.com/doi/abs/10.2135/cropsci2019.04.0212
Last checked: 01/22/2020
Notes: Abstract only |
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| Keywords: | TIC Keywords: Aerial infrared photography; Agrostis stolonifera; Drought stress; Equipment evaluation; Ground cover; Normalized Difference Vegetation Index; Remote sensing; Soil temperature; Stress monitors; Turfgrass quality; Unmanned aerial vehicles; Volumetric water content
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| Abstract/Contents: | "Recent advances in small unmanned aircraft systems (sUAS) and sensors may improve accuracy and efficiency in turfgrass research and management compared with conventional methods. We evaluated the ability of sUAS combined with ultra-high spatial resolution remote sensing to detect early drought stress. Results were compared with ground-based techniques in creeping bentgrass (Agrostis stolonifera L.) irrigated at different levels from well-watered to severe deficit (100 to 15% evapotranspiration [ET] replacement). Small UAS-based measurements with a modified digital camera included three reflectance bands (near infrared [NIR, 680-780 nm] and overlapping green [G] and blue [B] bands [400-580 nm]) and eight derived vegetation indices (VIs). Ground-based measurements included soil volumetric water content (VWC), turfgrass quality (TQ), green cover (GC), soil temperature (Tsoil), and reflectance with handheld optical sensors. Declines in VWC in deficit-irrigation treatments were detected with NIR and six of eight VIs from sUAS, and the normalized difference vegetation index (NDVI) and red band reflectance from a handheld sensor, before symptoms appeared in TQ and GC. The most consistently sensitive parameters of sUAS throughout the 3-yr study were NIR and GreenBlue VI [(G - B)/(G + B)], which detected drought stress >5 d before decreases in TQ. Results indicate that ultra-high spatial resolution remote sensing with sUAS detected drought stress before it was visible to a human observer and could be valuable for improving irrigation management in turfgrass." |
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| Language: | English |
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| References: | 42 |
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| See Also: | See also interpretive summary "Using small unmanned aircraft systems for early detection of turfgrass drought stress" CSA News, 64(12) December 2019, p. 10, R=310497. R=310497 |
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| Note: | Figures
Tables
Graphs |
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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. Using small unmanned aircraft systems for early detection of drought stress in turfgrass. Crop Sci. 59(6):p. 2829-2844. |
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| DOI: 10.2135/cropsci2019.04.0212 |
| Web URL(s):
https://acsess.onlinelibrary.wiley.com/doi/10.2135/cropsci2019.04.0212
Last checked: 01/22/2020
Access conditions: Item is within a limited-access website
https://acsess.onlinelibrary.wiley.com/doi/epdf/10.2135/cropsci2019.04.0212
Last checked: 01/22/2020
Requires: JavaScript; PDF Reader
Access conditions: Item is within a limited-access website |
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MSU catalog number: b2211522a |
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