Impact of varying light and dew on ground cover estimates from active NDVI, RGB and LiDAR
Data supporting the research paper published in Plant Phenomics Journal: https://doi.org/10.34133/2021/9842178 D. M. Deery, D. J. Smith, R. Davy, J. A. Jimenez-Berni, G. J. Rebetzke, and R. A. James, “Impact of varying light and dew on ground cover estimates from active ndvi, rgb, and lidar,” Plant...
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creator | Deery, David Smith, David J Davy, Robert Rebetzke, Greg James, Richard Jimenez-Berni, Jose |
description | Data supporting the research paper published in Plant Phenomics Journal: https://doi.org/10.34133/2021/9842178
D. M. Deery, D. J. Smith, R. Davy, J. A. Jimenez-Berni, G. J. Rebetzke, and R. A. James,
“Impact of varying light and dew on ground cover estimates from active ndvi, rgb, and lidar,” Plant Phenomics, vol. 2021, pp. 1–14, May 2021. doi: 10.34133/2021/9842178.
A field experiment was conducted in 2017 at the Managed Environment Facility (MEF), Yanco Agricultural Institute, Australia, on chromosol soil with a clay-loam texture. The experiment was sown on May 29th after a pea crop, managed with appropriate nutrition, and pest/disease control measures. It involved 192 plots (6 m long, 7 rows, 25 cm spacing, 200 seeds/m²) of 99 wheat genotypes varying in canopy traits. Genotypes were sown in a partial-replicate design with an average replication of 1.9.
Meteorological data were sourced from a nearby weather station, while solar radiation was measured 60 km away in Griffith, NSW. Phenotypic data were collected using Phenomobile Lite™, a portable terrestrial phenotyping platform equipped with LiDAR, an NDVI GreenSeeker® sensor, and a digital camera. Data were geocoded and collected during two events (August 1-2 and August 17-18, 2017), capturing hourly measurements from 12:00 to 18:00 and 07:00 to 12:00 across both days.
The collected data included LiDAR-derived canopy coverage (green cover, GC), NDVI values, and RGB images. LiDAR data were processed using a custom pipeline, geocoded, segmented into plots, and analyzed to extract GC. RGB images were analyzed for green pixel content, and NDVI data were averaged across plots. |
doi_str_mv | 10.25919/0xke-d287 |
format | Dataset |
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D. M. Deery, D. J. Smith, R. Davy, J. A. Jimenez-Berni, G. J. Rebetzke, and R. A. James,
“Impact of varying light and dew on ground cover estimates from active ndvi, rgb, and lidar,” Plant Phenomics, vol. 2021, pp. 1–14, May 2021. doi: 10.34133/2021/9842178.
A field experiment was conducted in 2017 at the Managed Environment Facility (MEF), Yanco Agricultural Institute, Australia, on chromosol soil with a clay-loam texture. The experiment was sown on May 29th after a pea crop, managed with appropriate nutrition, and pest/disease control measures. It involved 192 plots (6 m long, 7 rows, 25 cm spacing, 200 seeds/m²) of 99 wheat genotypes varying in canopy traits. Genotypes were sown in a partial-replicate design with an average replication of 1.9.
Meteorological data were sourced from a nearby weather station, while solar radiation was measured 60 km away in Griffith, NSW. Phenotypic data were collected using Phenomobile Lite™, a portable terrestrial phenotyping platform equipped with LiDAR, an NDVI GreenSeeker® sensor, and a digital camera. Data were geocoded and collected during two events (August 1-2 and August 17-18, 2017), capturing hourly measurements from 12:00 to 18:00 and 07:00 to 12:00 across both days.
The collected data included LiDAR-derived canopy coverage (green cover, GC), NDVI values, and RGB images. LiDAR data were processed using a custom pipeline, geocoded, segmented into plots, and analyzed to extract GC. RGB images were analyzed for green pixel content, and NDVI data were averaged across plots.</description><identifier>DOI: 10.25919/0xke-d287</identifier><language>eng</language><publisher>CSIRO</publisher><subject>Agricultural systems analysis and modelling ; Agronomy ; Crop and pasture biochemistry and physiology</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0001-8193-8516 ; 0000-0002-4881-2572 ; 0000-0001-7404-0046 ; 0000-0001-5486-6625</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,1894</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.25919/0xke-d287$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Deery, David</creatorcontrib><creatorcontrib>Smith, David J</creatorcontrib><creatorcontrib>Davy, Robert</creatorcontrib><creatorcontrib>Rebetzke, Greg</creatorcontrib><creatorcontrib>James, Richard</creatorcontrib><creatorcontrib>Jimenez-Berni, Jose</creatorcontrib><title>Impact of varying light and dew on ground cover estimates from active NDVI, RGB and LiDAR</title><description>Data supporting the research paper published in Plant Phenomics Journal: https://doi.org/10.34133/2021/9842178
D. M. Deery, D. J. Smith, R. Davy, J. A. Jimenez-Berni, G. J. Rebetzke, and R. A. James,
“Impact of varying light and dew on ground cover estimates from active ndvi, rgb, and lidar,” Plant Phenomics, vol. 2021, pp. 1–14, May 2021. doi: 10.34133/2021/9842178.
A field experiment was conducted in 2017 at the Managed Environment Facility (MEF), Yanco Agricultural Institute, Australia, on chromosol soil with a clay-loam texture. The experiment was sown on May 29th after a pea crop, managed with appropriate nutrition, and pest/disease control measures. It involved 192 plots (6 m long, 7 rows, 25 cm spacing, 200 seeds/m²) of 99 wheat genotypes varying in canopy traits. Genotypes were sown in a partial-replicate design with an average replication of 1.9.
Meteorological data were sourced from a nearby weather station, while solar radiation was measured 60 km away in Griffith, NSW. Phenotypic data were collected using Phenomobile Lite™, a portable terrestrial phenotyping platform equipped with LiDAR, an NDVI GreenSeeker® sensor, and a digital camera. Data were geocoded and collected during two events (August 1-2 and August 17-18, 2017), capturing hourly measurements from 12:00 to 18:00 and 07:00 to 12:00 across both days.
The collected data included LiDAR-derived canopy coverage (green cover, GC), NDVI values, and RGB images. LiDAR data were processed using a custom pipeline, geocoded, segmented into plots, and analyzed to extract GC. RGB images were analyzed for green pixel content, and NDVI data were averaged across plots.</description><subject>Agricultural systems analysis and modelling</subject><subject>Agronomy</subject><subject>Crop and pasture biochemistry and physiology</subject><fulltext>true</fulltext><rsrctype>dataset</rsrctype><creationdate>2021</creationdate><recordtype>dataset</recordtype><sourceid>PQ8</sourceid><recordid>eNpjYBAyNNAzMrU0tNQ3qMhO1U0xsjDnZIj0zC1ITC5RyE9TKEssqszMS1fIyUzPKFFIzEtRSEktV8jPU0gvyi8F8pLzy1KLFFKLSzJzE0tSixXSivJzFYB6M8tSFfxcwjx1FILcncD6fDJdHIN4GFjTEnOKU3mhNDeDlptriLOHbkpiSWJyZklqfEER0KSiynhDg3iwu-JB7ooHucuYJMUAEgxESQ</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Deery, David</creator><creator>Smith, David J</creator><creator>Davy, Robert</creator><creator>Rebetzke, Greg</creator><creator>James, Richard</creator><creator>Jimenez-Berni, Jose</creator><general>CSIRO</general><scope>DYCCY</scope><scope>PQ8</scope><orcidid>https://orcid.org/0000-0001-8193-8516</orcidid><orcidid>https://orcid.org/0000-0002-4881-2572</orcidid><orcidid>https://orcid.org/0000-0001-7404-0046</orcidid><orcidid>https://orcid.org/0000-0001-5486-6625</orcidid></search><sort><creationdate>2021</creationdate><title>Impact of varying light and dew on ground cover estimates from active NDVI, RGB and LiDAR</title><author>Deery, David ; Smith, David J ; Davy, Robert ; Rebetzke, Greg ; James, Richard ; Jimenez-Berni, Jose</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-datacite_primary_10_25919_0xke_d2873</frbrgroupid><rsrctype>datasets</rsrctype><prefilter>datasets</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Agricultural systems analysis and modelling</topic><topic>Agronomy</topic><topic>Crop and pasture biochemistry and physiology</topic><toplevel>online_resources</toplevel><creatorcontrib>Deery, David</creatorcontrib><creatorcontrib>Smith, David J</creatorcontrib><creatorcontrib>Davy, Robert</creatorcontrib><creatorcontrib>Rebetzke, Greg</creatorcontrib><creatorcontrib>James, Richard</creatorcontrib><creatorcontrib>Jimenez-Berni, Jose</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Deery, David</au><au>Smith, David J</au><au>Davy, Robert</au><au>Rebetzke, Greg</au><au>James, Richard</au><au>Jimenez-Berni, Jose</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>Impact of varying light and dew on ground cover estimates from active NDVI, RGB and LiDAR</title><date>2021</date><risdate>2021</risdate><abstract>Data supporting the research paper published in Plant Phenomics Journal: https://doi.org/10.34133/2021/9842178
D. M. Deery, D. J. Smith, R. Davy, J. A. Jimenez-Berni, G. J. Rebetzke, and R. A. James,
“Impact of varying light and dew on ground cover estimates from active ndvi, rgb, and lidar,” Plant Phenomics, vol. 2021, pp. 1–14, May 2021. doi: 10.34133/2021/9842178.
A field experiment was conducted in 2017 at the Managed Environment Facility (MEF), Yanco Agricultural Institute, Australia, on chromosol soil with a clay-loam texture. The experiment was sown on May 29th after a pea crop, managed with appropriate nutrition, and pest/disease control measures. It involved 192 plots (6 m long, 7 rows, 25 cm spacing, 200 seeds/m²) of 99 wheat genotypes varying in canopy traits. Genotypes were sown in a partial-replicate design with an average replication of 1.9.
Meteorological data were sourced from a nearby weather station, while solar radiation was measured 60 km away in Griffith, NSW. Phenotypic data were collected using Phenomobile Lite™, a portable terrestrial phenotyping platform equipped with LiDAR, an NDVI GreenSeeker® sensor, and a digital camera. Data were geocoded and collected during two events (August 1-2 and August 17-18, 2017), capturing hourly measurements from 12:00 to 18:00 and 07:00 to 12:00 across both days.
The collected data included LiDAR-derived canopy coverage (green cover, GC), NDVI values, and RGB images. LiDAR data were processed using a custom pipeline, geocoded, segmented into plots, and analyzed to extract GC. RGB images were analyzed for green pixel content, and NDVI data were averaged across plots.</abstract><pub>CSIRO</pub><doi>10.25919/0xke-d287</doi><orcidid>https://orcid.org/0000-0001-8193-8516</orcidid><orcidid>https://orcid.org/0000-0002-4881-2572</orcidid><orcidid>https://orcid.org/0000-0001-7404-0046</orcidid><orcidid>https://orcid.org/0000-0001-5486-6625</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural systems analysis and modelling Agronomy Crop and pasture biochemistry and physiology |
title | Impact of varying light and dew on ground cover estimates from active NDVI, RGB and LiDAR |
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