Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR
Canopy ground cover (GC) is an important agronomic measure for evaluating crop establishment and early growth. This study evaluates the reliability of GC estimates, in the presence of varying light and dew on leaves, from three different ground-based sensors: (1) normalized difference vegetation ind...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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American Association for the Advancement of Science (AAAS)
2021-01-01
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| Series: | Plant Phenomics |
| Online Access: | http://dx.doi.org/10.34133/2021/9842178 |
| _version_ | 1798016804998610944 |
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| author | David M. Deery David J. Smith Robert Davy Jose A. Jimenez-Berni Greg J. Rebetzke Richard A. James |
| author_facet | David M. Deery David J. Smith Robert Davy Jose A. Jimenez-Berni Greg J. Rebetzke Richard A. James |
| author_sort | David M. Deery |
| collection | DOAJ |
| description | Canopy ground cover (GC) is an important agronomic measure for evaluating crop establishment and early growth. This study evaluates the reliability of GC estimates, in the presence of varying light and dew on leaves, from three different ground-based sensors: (1) normalized difference vegetation index (NDVI) from the commercially available GreenSeeker®; (2) RGB images from a digital camera, where GC was determined as the portion of pixels from each image meeting a greenness criterion (i.e., Green−Red/Green+Red>0); and (3) LiDAR using two separate approaches: (a) GC from LiDAR red reflectance (whereby red reflectance less than five was classified as vegetation) and (b) GC from LiDAR height (whereby height greater than 10 cm was classified as vegetation). Hourly measurements were made early in the season at two different growth stages (tillering and stem elongation), among wheat genotypes highly diverse for canopy characteristics. The active NDVI showed the least variation through time and was particularly stable, regardless of the available light or the presence of dew. In addition, between-sample-time Pearson correlations for NDVI were consistently high and significant (P<0.0001), ranging from 0.89 to 0.98. In comparison, GC from LiDAR and RGB showed greater variation across sampling times, and LiDAR red reflectance was strongly influenced by the presence of dew. Excluding times when the light was exceedingly low, correlations between GC from RGB and NDVI were consistently high (ranging from 0.79 to 0.92). The high reliability of the active NDVI sensor potentially affords a high degree of flexibility for users by enabling sampling across a broad range of acceptable light conditions. |
| first_indexed | 2024-04-11T15:56:32Z |
| format | Article |
| id | doaj.art-1cff9450086f48d69f35fb6a22fa2f5a |
| institution | Directory Open Access Journal |
| issn | 2643-6515 |
| language | English |
| last_indexed | 2024-04-11T15:56:32Z |
| publishDate | 2021-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Plant Phenomics |
| spelling | doaj.art-1cff9450086f48d69f35fb6a22fa2f5a2022-12-22T04:15:08ZengAmerican Association for the Advancement of Science (AAAS)Plant Phenomics2643-65152021-01-01202110.34133/2021/9842178Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDARDavid M. Deery0David J. Smith1Robert Davy2Jose A. Jimenez-Berni3Greg J. Rebetzke4Richard A. James5CSIRO Agriculture and Food, Canberra, ACT, AustraliaCSIRO Agriculture and Food, Yanco, NSW, AustraliaCSIRO Information Management and Technology, Canberra, ACT, AustraliaCSIRO Agriculture and Food, Canberra, ACT, Australia; Instituto Agricultura Sostenible, Consejo Superior de Investigaciones Cientificas, Cordoba, SpainCSIRO Agriculture and Food, Canberra, ACT, AustraliaCSIRO Agriculture and Food, Canberra, ACT, AustraliaCanopy ground cover (GC) is an important agronomic measure for evaluating crop establishment and early growth. This study evaluates the reliability of GC estimates, in the presence of varying light and dew on leaves, from three different ground-based sensors: (1) normalized difference vegetation index (NDVI) from the commercially available GreenSeeker®; (2) RGB images from a digital camera, where GC was determined as the portion of pixels from each image meeting a greenness criterion (i.e., Green−Red/Green+Red>0); and (3) LiDAR using two separate approaches: (a) GC from LiDAR red reflectance (whereby red reflectance less than five was classified as vegetation) and (b) GC from LiDAR height (whereby height greater than 10 cm was classified as vegetation). Hourly measurements were made early in the season at two different growth stages (tillering and stem elongation), among wheat genotypes highly diverse for canopy characteristics. The active NDVI showed the least variation through time and was particularly stable, regardless of the available light or the presence of dew. In addition, between-sample-time Pearson correlations for NDVI were consistently high and significant (P<0.0001), ranging from 0.89 to 0.98. In comparison, GC from LiDAR and RGB showed greater variation across sampling times, and LiDAR red reflectance was strongly influenced by the presence of dew. Excluding times when the light was exceedingly low, correlations between GC from RGB and NDVI were consistently high (ranging from 0.79 to 0.92). The high reliability of the active NDVI sensor potentially affords a high degree of flexibility for users by enabling sampling across a broad range of acceptable light conditions.http://dx.doi.org/10.34133/2021/9842178 |
| spellingShingle | David M. Deery David J. Smith Robert Davy Jose A. Jimenez-Berni Greg J. Rebetzke Richard A. James Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR Plant Phenomics |
| title | Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR |
| title_full | Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR |
| title_fullStr | Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR |
| title_full_unstemmed | Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR |
| title_short | Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR |
| title_sort | impact of varying light and dew on ground cover estimates from active ndvi rgb and lidar |
| url | http://dx.doi.org/10.34133/2021/9842178 |
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