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| Web URL(s): | https://scisoc.confex.com/scisoc/2021am/meetingapp.cgi/Paper/133214
Last checked: 03/31/2022
Requires: JavaScript |
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| Publication Type:
| Report |
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| Content Type: | Abstract or Summary only |
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| Author(s): | Wilber, Amy L.;
Czarnecki, Joby;
McCurdy, James D. |
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| Author Affiliation: | Wilber and Czarnecki: Mississippi State University, Mississippi State, MS; McCurdy: Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS |
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| Title: | Drone to data: Extracting vegetation indices from aerial imagery |
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| Section: | Turfgrass science oral II
Other records with the "Turfgrass science oral II" Section
C05 turfgrass science
Other records with the "C05 turfgrass science" Section
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| Meeting Info.: | Salt Lake City, Utah: November 7-10, 2021 |
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| Source: | ASA, CSSA and SSSA International Annual Meetings. 2021, p. 133214. |
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| Publishing Information: | [Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America] |
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| # of Pages: | 1 |
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| Abstract/Contents: | "Collection of multispectral imagery from an unmanned aircraft system (UAS) -mounted sensor is a means to obtain plot-level vegetation index values; however, post-capture image processing and analysis remains a challenge for small-plot turfgrass researchers. Challenges include how to process imagery and how to extract useful information in a timely and efficient manner. A workflow consisting of two task items was developed with established routines and commands within ArcGIS Pro to extract plot-level vegetation index values (e.g., Normalized Difference Vegetation Index, Ratio Vegetation Index, and Chlorophyll Index-Red Edge) from aerial multispectral imagery of small-plot turfgrass research experiments. Users can access and download the task item(s) from the ArcGIS Online platform. The workflow and procedures standardize the processing of aerial imagery to ensure repeatability between sampling dates and across site locations. A guided workflow saves the user time with the assigned commands, ultimately allowing them to obtain a table with plot descriptions and vegetation index values within a .csv file for further statistical analysis." |
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| Language: | English |
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| References: | 0 |
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| Note: | This item is an abstract only!
"367-6" |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Wilber, A. L., J. Czarnecki, and J. D. McCurdy. 2021. Drone to data: Extracting vegetation indices from aerial imagery. Agron. Abr. p. 133214. |
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| Web URL(s):
https://scisoc.confex.com/scisoc/2021am/meetingapp.cgi/Paper/133214
Last checked: 03/31/2022
Requires: JavaScript |
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